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Shah NP, Willsey MS, Hahn N, Kamdar F, Avansino DT, Fan C, Hochberg LR, Willett FR, Henderson JM. A flexible intracortical brain-computer interface for typing using finger movements. bioRxiv 2024:2024.04.22.590630. [PMID: 38712189 PMCID: PMC11071346 DOI: 10.1101/2024.04.22.590630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Keyboard typing with finger movements is a versatile digital interface for users with diverse skills, needs, and preferences. Currently, such an interface does not exist for people with paralysis. We developed an intracortical brain-computer interface (BCI) for typing with attempted flexion/extension movements of three finger groups on the right hand, or both hands, and demonstrated its flexibility in two dominant typing paradigms. The first paradigm is "point-and-click" typing, where a BCI user selects one key at a time using continuous real-time control, allowing selection of arbitrary sequences of symbols. During cued character selection with this paradigm, a human research participant with paralysis achieved 30-40 selections per minute with nearly 90% accuracy. The second paradigm is "keystroke" typing, where the BCI user selects each character by a discrete movement without real-time feedback, often giving a faster speed for natural language sentences. With 90 cued characters per minute, decoding attempted finger movements and correcting errors using a language model resulted in more than 90% accuracy. Notably, both paradigms matched the state-of-the-art for BCI performance and enabled further flexibility by the simultaneous selection of multiple characters as well as efficient decoder estimation across paradigms. Overall, the high-performance interface is a step towards the wider accessibility of BCI technology by addressing unmet user needs for flexibility.
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Ali YH, Bodkin K, Rigotti-Thompson M, Patel K, Card NS, Bhaduri B, Nason-Tomaszewski SR, Mifsud DM, Hou X, Nicolas C, Allcroft S, Hochberg LR, Au Yong N, Stavisky SD, Miller LE, Brandman DM, Pandarinath C. BRAND: a platform for closed-loop experiments with deep network models. J Neural Eng 2024; 21:026046. [PMID: 38579696 PMCID: PMC11021878 DOI: 10.1088/1741-2552/ad3b3a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 01/27/2024] [Accepted: 04/05/2024] [Indexed: 04/07/2024]
Abstract
Objective.Artificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in existing real-time frameworks. Researchers need a platform that fully supports high-level languages for running ANNs (e.g. Python and Julia) while maintaining support for languages that are critical for low-latency data acquisition and processing (e.g. C and C++).Approach.To address these needs, we introduce the Backend for Realtime Asynchronous Neural Decoding (BRAND). BRAND comprises Linux processes, termednodes, which communicate with each other in agraphvia streams of data. Its asynchronous design allows for acquisition, control, and analysis to be executed in parallel on streams of data that may operate at different timescales. BRAND uses Redis, an in-memory database, to send data between nodes, which enables fast inter-process communication and supports 54 different programming languages. Thus, developers can easily deploy existing ANN models in BRAND with minimal implementation changes.Main results.In our tests, BRAND achieved <600 microsecond latency between processes when sending large quantities of data (1024 channels of 30 kHz neural data in 1 ms chunks). BRAND runs a brain-computer interface with a recurrent neural network (RNN) decoder with less than 8 ms of latency from neural data input to decoder prediction. In a real-world demonstration of the system, participant T11 in the BrainGate2 clinical trial (ClinicalTrials.gov Identifier: NCT00912041) performed a standard cursor control task, in which 30 kHz signal processing, RNN decoding, task control, and graphics were all executed in BRAND. This system also supports real-time inference with complex latent variable models like Latent Factor Analysis via Dynamical Systems.Significance.By providing a framework that is fast, modular, and language-agnostic, BRAND lowers the barriers to integrating the latest tools in neuroscience and machine learning into closed-loop experiments.
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Affiliation(s)
- Yahia H Ali
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Kevin Bodkin
- Department of Neuroscience, Northwestern University, Chicago, IL, United States of America
| | - Mattia Rigotti-Thompson
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Kushant Patel
- Department of Neurological Surgery, University of California, Davis, CA, United States of America
| | - Nicholas S Card
- Department of Neurological Surgery, University of California, Davis, CA, United States of America
| | - Bareesh Bhaduri
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Samuel R Nason-Tomaszewski
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Domenick M Mifsud
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Xianda Hou
- Department of Neurological Surgery, University of California, Davis, CA, United States of America
| | - Claire Nicolas
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, United States of America
| | - Shane Allcroft
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, United States of America
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, United States of America
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, United States of America
- Harvard Medical School, Boston, MA, United States of America
- Veterans Affairs Rehabilitation Research & Development Center for Neurorestoration and Neurotechnology, Providence VA Medical Center, Providence, RI, United States of America
| | - Nicholas Au Yong
- Department of Neurosurgery, Emory University, Atlanta, GA, United States of America
| | - Sergey D Stavisky
- Department of Neurological Surgery, University of California, Davis, CA, United States of America
| | - Lee E Miller
- Department of Neuroscience, Northwestern University, Chicago, IL, United States of America
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, United States of America
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, United States of America
- Shirley Ryan AbilityLab, Chicago, IL, United States of America
| | - David M Brandman
- Department of Neurological Surgery, University of California, Davis, CA, United States of America
| | - Chethan Pandarinath
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
- Department of Neurosurgery, Emory University, Atlanta, GA, United States of America
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Card NS, Wairagkar M, Iacobacci C, Hou X, Singer-Clark T, Willett FR, Kunz EM, Fan C, Vahdati Nia M, Deo DR, Srinivasan A, Choi EY, Glasser MF, Hochberg LR, Henderson JM, Shahlaie K, Brandman DM, Stavisky SD. An accurate and rapidly calibrating speech neuroprosthesis. medRxiv 2024:2023.12.26.23300110. [PMID: 38645254 PMCID: PMC11030484 DOI: 10.1101/2023.12.26.23300110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Brain-computer interfaces can enable rapid, intuitive communication for people with paralysis by transforming the cortical activity associated with attempted speech into text on a computer screen. Despite recent advances, communication with brain-computer interfaces has been restricted by extensive training data requirements and inaccurate word output. A man in his 40's with ALS with tetraparesis and severe dysarthria (ALSFRS-R = 23) was enrolled into the BrainGate2 clinical trial. He underwent surgical implantation of four microelectrode arrays into his left precentral gyrus, which recorded neural activity from 256 intracortical electrodes. We report a speech neuroprosthesis that decoded his neural activity as he attempted to speak in both prompted and unstructured conversational settings. Decoded words were displayed on a screen, then vocalized using text-to-speech software designed to sound like his pre-ALS voice. On the first day of system use, following 30 minutes of attempted speech training data, the neuroprosthesis achieved 99.6% accuracy with a 50-word vocabulary. On the second day, the size of the possible output vocabulary increased to 125,000 words, and, after 1.4 additional hours of training data, the neuroprosthesis achieved 90.2% accuracy. With further training data, the neuroprosthesis sustained 97.5% accuracy beyond eight months after surgical implantation. The participant has used the neuroprosthesis to communicate in self-paced conversations for over 248 hours. In an individual with ALS and severe dysarthria, an intracortical speech neuroprosthesis reached a level of performance suitable to restore naturalistic communication after a brief training period.
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Pun TK, Khoshnevis M, Hosman T, Wilson GH, Kapitonava A, Kamdar F, Henderson JM, Simeral JD, Vargas-Irwin CE, Harrison MT, Hochberg LR. Measuring instability in chronic human intracortical neural recordings towards stable, long-term brain-computer interfaces. bioRxiv 2024:2024.02.29.582733. [PMID: 38496552 PMCID: PMC10942277 DOI: 10.1101/2024.02.29.582733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Intracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive cursor control from movement intentions. To translate to practical use, iBCIs should provide reliable performance for extended periods of time. However, performance begins to degrade as the relationship between kinematic intention and recorded neural activity shifts compared to when the decoder was initially trained. In addition to developing decoders to better handle long-term instability, identifying when to recalibrate will also optimize performance. We propose a method to measure instability in neural data without needing to label user intentions. Longitudinal data were analyzed from two BrainGate2 participants with tetraplegia as they used fixed decoders to control a computer cursor spanning 142 days and 28 days, respectively. We demonstrate a measure of instability that correlates with changes in closed-loop cursor performance solely based on the recorded neural activity (Pearson r = 0.93 and 0.72, respectively). This result suggests a strategy to infer online iBCI performance from neural data alone and to determine when recalibration should take place for practical long-term use.
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Willsey MS, Shah NP, Avansino DT, Hahn NV, Jamiolkowski RM, Kamdar FB, Hochberg LR, Willett FR, Henderson JM. A real-time, high-performance brain-computer interface for finger decoding and quadcopter control. bioRxiv 2024:2024.02.06.578107. [PMID: 38370697 PMCID: PMC10871262 DOI: 10.1101/2024.02.06.578107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
People with paralysis express unmet needs for peer support, leisure activities, and sporting activities. Many within the general population rely on social media and massively multiplayer video games to address these needs. We developed a high-performance finger brain-computer-interface system allowing continuous control of 3 independent finger groups with 2D thumb movements. The system was tested in a human research participant over sequential trials requiring fingers to reach and hold on targets, with an average acquisition rate of 76 targets/minute and completion time of 1.58 ± 0.06 seconds. Performance compared favorably to previous animal studies, despite a 2-fold increase in the decoded degrees-of-freedom (DOF). Finger positions were then used for 4-DOF velocity control of a virtual quadcopter, demonstrating functionality over both fixed and random obstacle courses. This approach shows promise for controlling multiple-DOF end-effectors, such as robotic fingers or digital interfaces for work, entertainment, and socialization.
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Schiff ND, Diringer M, Diserens K, Edlow BL, Gosseries O, Hill NJ, Hochberg LR, Ismail FY, Meyer IA, Mikell CB, Mofakham S, Molteni E, Polizzotto L, Shah SA, Stevens RD, Thengone D. Brain-Computer Interfaces for Communication in Patients with Disorders of Consciousness: A Gap Analysis and Scientific Roadmap. Neurocrit Care 2024:10.1007/s12028-023-01924-w. [PMID: 38286946 DOI: 10.1007/s12028-023-01924-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 12/14/2023] [Indexed: 01/31/2024]
Abstract
BACKGROUND We developed a gap analysis that examines the role of brain-computer interfaces (BCI) in patients with disorders of consciousness (DoC), focusing on their assessment, establishment of communication, and engagement with their environment. METHODS The Curing Coma Campaign convened a Coma Science work group that included 16 clinicians and neuroscientists with expertise in DoC. The work group met online biweekly and performed a gap analysis of the primary question. RESULTS We outline a roadmap for assessing BCI readiness in patients with DoC and for advancing the use of BCI devices in patients with DoC. Additionally, we discuss preliminary studies that inform development of BCI solutions for communication and assessment of readiness for use of BCIs in DoC study participants. Special emphasis is placed on the challenges posed by the complex pathophysiologies caused by heterogeneous brain injuries and their impact on neuronal signaling. The differences between one-way and two-way communication are specifically considered. Possible implanted and noninvasive BCI solutions for acute and chronic DoC in adult and pediatric populations are also addressed. CONCLUSIONS We identify clinical and technical gaps hindering the use of BCI in patients with DoC in each of these contexts and provide a roadmap for research aimed at improving communication for adults and children with DoC, spanning the clinical spectrum from intensive care unit to chronic care.
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Affiliation(s)
- Nicholas D Schiff
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA.
| | - Michael Diringer
- Departments of Neurology and Neurosurgery, Washington University in St. Louis, St. Louis, MO, USA
| | - Karin Diserens
- Neurology and Acute Neurorehabilitation Unit, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness, Centre du Cerveau, University Hospital of Liège, University of Liège & Centre du Cerveau, Liège, Belgium
| | - N Jeremy Hill
- National Center for Adaptive Neurotechnologies, Stratton VA Medical Center, Albany, NY, USA
- Electrical & Computer Engineering Department, State University of New York at Albany, Albany, NY, USA
| | - Leigh R Hochberg
- Veterans Affairs Rehabilitation Research & Development Center for Neurorestoration and Neurotechnology, Rehabilitation Research & Development Service, Providence VA Medical Center, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Fatima Y Ismail
- Department of Pediatrics, United Arab Emirates University, Al Ain, United Arab Emirates
- Department of Neurology, Adjunct Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ivo A Meyer
- Neurology and Acute Neurorehabilitation Unit, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Centre for Advanced Research in Sleep Medicine and Integrated Trauma Centre, Integrated University Health and Social Services Centre (CIUSSS) du Nord-de-L'Île-de-Montréal, Montreal, QC, Canada
| | - Charles B Mikell
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA
| | - Sima Mofakham
- Department of Neurosurgery, Stony Brook University Hospital, Stony Brook, NY, USA
- Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Erika Molteni
- School of Biomedical Engineering and Imaging Sciences, and Centre for Medical Engineering, King's College London, London, UK
| | - Leonard Polizzotto
- Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Sudhin A Shah
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Robert D Stevens
- Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
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Deo DR, Willett FR, Avansino DT, Hochberg LR, Henderson JM, Shenoy KV. Brain control of bimanual movement enabled by recurrent neural networks. Sci Rep 2024; 14:1598. [PMID: 38238386 PMCID: PMC10796685 DOI: 10.1038/s41598-024-51617-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 01/07/2024] [Indexed: 01/22/2024] Open
Abstract
Brain-computer interfaces have so far focused largely on enabling the control of a single effector, for example a single computer cursor or robotic arm. Restoring multi-effector motion could unlock greater functionality for people with paralysis (e.g., bimanual movement). However, it may prove challenging to decode the simultaneous motion of multiple effectors, as we recently found that a compositional neural code links movements across all limbs and that neural tuning changes nonlinearly during dual-effector motion. Here, we demonstrate the feasibility of high-quality bimanual control of two cursors via neural network (NN) decoders. Through simulations, we show that NNs leverage a neural 'laterality' dimension to distinguish between left and right-hand movements as neural tuning to both hands become increasingly correlated. In training recurrent neural networks (RNNs) for two-cursor control, we developed a method that alters the temporal structure of the training data by dilating/compressing it in time and re-ordering it, which we show helps RNNs successfully generalize to the online setting. With this method, we demonstrate that a person with paralysis can control two computer cursors simultaneously. Our results suggest that neural network decoders may be advantageous for multi-effector decoding, provided they are designed to transfer to the online setting.
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Affiliation(s)
- Darrel R Deo
- Department of Neurosurgery, Stanford University, Stanford, CA, USA.
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
| | - Francis R Willett
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
| | - Donald T Avansino
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
| | - Leigh R Hochberg
- School of Engineering, Brown University, Providence, RI, USA
- Carney Institute for Brain Science, Brown University, Providence, RI, USA
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jaimie M Henderson
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Bio-X Institute, Stanford University, Stanford, CA, USA
| | - Krishna V Shenoy
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Bio-X Institute, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
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8
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Verzhbinsky IA, Rubin DB, Kajfez S, Bu Y, Kelemen JN, Kapitonava A, Williams ZM, Hochberg LR, Cash SS, Halgren E. Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans. Proc Natl Acad Sci U S A 2024; 121:e2312204121. [PMID: 38157452 PMCID: PMC10769862 DOI: 10.1073/pnas.2312204121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 11/05/2023] [Indexed: 01/03/2024] Open
Abstract
How the human cortex integrates ("binds") information encoded by spatially distributed neurons remains largely unknown. One hypothesis suggests that synchronous bursts of high-frequency oscillations ("ripples") contribute to binding by facilitating integration of neuronal firing across different cortical locations. While studies have demonstrated that ripples modulate local activity in the cortex, it is not known whether their co-occurrence coordinates neural firing across larger distances. We tested this hypothesis using local field-potentials and single-unit firing from four 96-channel microelectrode arrays in the supragranular cortex of 3 patients. Neurons in co-rippling locations showed increased short-latency co-firing, prediction of each other's firing, and co-participation in neural assemblies. Effects were similar for putative pyramidal and interneurons, during non-rapid eye movement sleep and waking, in temporal and Rolandic cortices, and at distances up to 16 mm (the longest tested). Increased co-prediction during co-ripples was maintained when firing-rate changes were equated, indicating that it was not secondary to non-oscillatory activation. Co-rippling enhanced prediction was strongly modulated by ripple phase, supporting the most common posited mechanism for binding-by-synchrony. Co-ripple enhanced prediction is reciprocal, synergistic with local upstates, and further enhanced when multiple sites co-ripple, supporting re-entrant facilitation. Together, these results support the hypothesis that trans-cortical co-occurring ripples increase the integration of neuronal firing of neurons in different cortical locations and do so in part through phase-modulation rather than unstructured activation.
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Affiliation(s)
- Ilya A. Verzhbinsky
- Neurosciences Graduate Program, University of California San Diego, La Jolla, CA92093
- Medical Scientist Training Program, University of California San Diego, La Jolla, CA92093
| | - Daniel B. Rubin
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
| | - Sophie Kajfez
- Department of Radiology, University of California San Diego, La Jolla, CA92093
| | - Yiting Bu
- Department of Neurosciences, University of California San Diego, La Jolla, CA92093
| | - Jessica N. Kelemen
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
| | - Anastasia Kapitonava
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
| | - Ziv M. Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA02114
| | - Leigh R. Hochberg
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Center for Neurorestoration and Neurotechnology, Department of Veterans Affairs, Providence, RI02908
- Carney Institute for Brain Science and School of Engineering, Brown University, Providence, RI02912
| | - Sydney S. Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
| | - Eric Halgren
- Department of Radiology, University of California San Diego, La Jolla, CA92093
- Department of Neurosciences, University of California San Diego, La Jolla, CA92093
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Coughlin B, Muñoz W, Kfir Y, Young MJ, Meszéna D, Jamali M, Caprara I, Hardstone R, Khanna A, Mustroph ML, Trautmann EM, Windolf C, Varol E, Soper DJ, Stavisky SD, Welkenhuysen M, Dutta B, Shenoy KV, Hochberg LR, Mark Richardson R, Williams ZM, Cash SS, Paulk AC. Modified Neuropixels probes for recording human neurophysiology in the operating room. Nat Protoc 2023; 18:2927-2953. [PMID: 37697108 DOI: 10.1038/s41596-023-00871-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 06/08/2023] [Indexed: 09/13/2023]
Abstract
Neuropixels are silicon-based electrophysiology-recording probes with high channel count and recording-site density. These probes offer a turnkey platform for measuring neural activity with single-cell resolution and at a scale that is beyond the capabilities of current clinically approved devices. Our team demonstrated the first-in-human use of these probes during resection surgery for epilepsy or tumors and deep brain stimulation electrode placement in patients with Parkinson's disease. Here, we provide a better understanding of the capabilities and challenges of using Neuropixels as a research tool to study human neurophysiology, with the hope that this information may inform future efforts toward regulatory approval of Neuropixels probes as research devices. In perioperative procedures, the major concerns are the initial sterility of the device, maintaining a sterile field during surgery, having multiple referencing and grounding schemes available to de-noise recordings (if necessary), protecting the silicon probe from accidental contact before insertion and obtaining high-quality action potential and local field potential recordings. The research team ensures that the device is fully operational while coordinating with the surgical team to remove sources of electrical noise that could otherwise substantially affect the signals recorded by the sensitive hardware. Prior preparation using the equipment and training in human clinical research and working in operating rooms maximize effective communication within and between the teams, ensuring high recording quality and minimizing the time added to the surgery. The perioperative procedure requires ~4 h, and the entire protocol requires multiple weeks.
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Affiliation(s)
- Brian Coughlin
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - William Muñoz
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Yoav Kfir
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Michael J Young
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Domokos Meszéna
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Mohsen Jamali
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Irene Caprara
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Richard Hardstone
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Arjun Khanna
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Martina L Mustroph
- Department of Neurosurgery, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
| | - Eric M Trautmann
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA
- Zuckerman Institute, Columbia University, New York, NY, USA
- Grossman Center for the Statistics of Mind, Columbia University Medical Center, New York, NY, USA
| | - Charlie Windolf
- Department of Statistics, Zuckerman Institute, Columbia University, New York, NY, USA
| | - Erdem Varol
- Department of Statistics, Zuckerman Institute, Columbia University, New York, NY, USA
- Department of Computer Science and Engineering, Zuckerman Institute, Columbia University, New York, NY, USA
| | - Dan J Soper
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Sergey D Stavisky
- Department of Neurological Surgery, University of California Davis, Davis, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
| | | | | | - Krishna V Shenoy
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - R Mark Richardson
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA.
| | - Sydney S Cash
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
| | - Angelique C Paulk
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
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Ali YH, Bodkin K, Rigotti-Thompson M, Patel K, Card NS, Bhaduri B, Nason-Tomaszewski SR, Mifsud DM, Hou X, Nicolas C, Allcroft S, Hochberg LR, Yong NA, Stavisky SD, Miller LE, Brandman DM, Pandarinath C. BRAND: A platform for closed-loop experiments with deep network models. bioRxiv 2023:2023.08.08.552473. [PMID: 37609167 PMCID: PMC10441362 DOI: 10.1101/2023.08.08.552473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Artificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in existing real-time frameworks. Researchers need a platform that fully supports high-level languages for running ANNs (e.g., Python and Julia) while maintaining support for languages that are critical for low-latency data acquisition and processing (e.g., C and C++). To address these needs, we introduce the Backend for Realtime Asynchronous Neural Decoding (BRAND). BRAND comprises Linux processes, termed nodes , which communicate with each other in a graph via streams of data. Its asynchronous design allows for acquisition, control, and analysis to be executed in parallel on streams of data that may operate at different timescales. BRAND uses Redis to send data between nodes, which enables fast inter-process communication and supports 54 different programming languages. Thus, developers can easily deploy existing ANN models in BRAND with minimal implementation changes. In our tests, BRAND achieved <600 microsecond latency between processes when sending large quantities of data (1024 channels of 30 kHz neural data in 1-millisecond chunks). BRAND runs a brain-computer interface with a recurrent neural network (RNN) decoder with less than 8 milliseconds of latency from neural data input to decoder prediction. In a real-world demonstration of the system, participant T11 in the BrainGate2 clinical trial performed a standard cursor control task, in which 30 kHz signal processing, RNN decoding, task control, and graphics were all executed in BRAND. This system also supports real-time inference with complex latent variable models like Latent Factor Analysis via Dynamical Systems. By providing a framework that is fast, modular, and language-agnostic, BRAND lowers the barriers to integrating the latest tools in neuroscience and machine learning into closed-loop experiments.
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Willett FR, Kunz EM, Fan C, Avansino DT, Wilson GH, Choi EY, Kamdar F, Glasser MF, Hochberg LR, Druckmann S, Shenoy KV, Henderson JM. A high-performance speech neuroprosthesis. Nature 2023; 620:1031-1036. [PMID: 37612500 PMCID: PMC10468393 DOI: 10.1038/s41586-023-06377-x] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 06/27/2023] [Indexed: 08/25/2023]
Abstract
Speech brain-computer interfaces (BCIs) have the potential to restore rapid communication to people with paralysis by decoding neural activity evoked by attempted speech into text1,2 or sound3,4. Early demonstrations, although promising, have not yet achieved accuracies sufficiently high for communication of unconstrained sentences from a large vocabulary1-7. Here we demonstrate a speech-to-text BCI that records spiking activity from intracortical microelectrode arrays. Enabled by these high-resolution recordings, our study participant-who can no longer speak intelligibly owing to amyotrophic lateral sclerosis-achieved a 9.1% word error rate on a 50-word vocabulary (2.7 times fewer errors than the previous state-of-the-art speech BCI2) and a 23.8% word error rate on a 125,000-word vocabulary (the first successful demonstration, to our knowledge, of large-vocabulary decoding). Our participant's attempted speech was decoded at 62 words per minute, which is 3.4 times as fast as the previous record8 and begins to approach the speed of natural conversation (160 words per minute9). Finally, we highlight two aspects of the neural code for speech that are encouraging for speech BCIs: spatially intermixed tuning to speech articulators that makes accurate decoding possible from only a small region of cortex, and a detailed articulatory representation of phonemes that persists years after paralysis. These results show a feasible path forward for restoring rapid communication to people with paralysis who can no longer speak.
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Affiliation(s)
- Francis R Willett
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA.
| | - Erin M Kunz
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Chaofei Fan
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Donald T Avansino
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
| | - Guy H Wilson
- Department of Neuroscience, Stanford University, Stanford, CA, USA
| | - Eun Young Choi
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Foram Kamdar
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Matthew F Glasser
- Department of Neuroscience, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Leigh R Hochberg
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Shaul Druckmann
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Krishna V Shenoy
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Bio-X Program, Stanford University, Stanford, CA, USA
| | - Jaimie M Henderson
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
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Lin DJ, Hardstone R, DiCarlo JA, Mckiernan S, Snider SB, Jacobs H, Erler KS, Rishe K, Boyne P, Goldsmith J, Ranford J, Finklestein SP, Schwamm LH, Hochberg LR, Cramer SC. Distinguishing Distinct Neural Systems for Proximal vs Distal Upper Extremity Motor Control After Acute Stroke. Neurology 2023; 101:e347-e357. [PMID: 37268437 PMCID: PMC10435065 DOI: 10.1212/wnl.0000000000207417] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 03/31/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The classic and singular pattern of distal greater than proximal upper extremity motor deficits after acute stroke does not account for the distinct structural and functional organization of circuits for proximal and distal motor control in the healthy CNS. We hypothesized that separate proximal and distal upper extremity clinical syndromes after acute stroke could be distinguished and that patterns of neuroanatomical injury leading to these 2 syndromes would reflect their distinct organization in the intact CNS. METHODS Proximal and distal components of motor impairment (upper extremity Fugl-Meyer score) and strength (Shoulder Abduction Finger Extension score) were assessed in consecutively recruited patients within 7 days of acute stroke. Partial correlation analysis was used to assess the relationship between proximal and distal motor scores. Functional outcomes including the Box and Blocks Test (BBT), Barthel Index (BI), and modified Rankin scale (mRS) were examined in relation to proximal vs distal motor patterns of deficit. Voxel-based lesion-symptom mapping was used to identify regions of injury associated with proximal vs distal upper extremity motor deficits. RESULTS A total of 141 consecutive patients (49% female) were assessed 4.0 ± 1.6 (mean ± SD) days after stroke onset. Separate proximal and distal upper extremity motor components were distinguishable after acute stroke (p = 0.002). A pattern of proximal more than distal injury (i.e., relatively preserved distal motor control) was not rare, observed in 23% of acute stroke patients. Patients with relatively preserved distal motor control, even after controlling for total extent of deficit, had better outcomes in the first week and at 90 days poststroke (BBT, ρ = 0.51, p < 0.001; BI, ρ = 0.41, p < 0.001; mRS, ρ = 0.38, p < 0.001). Deficits in proximal motor control were associated with widespread injury to subcortical white and gray matter, while deficits in distal motor control were associated with injury restricted to the posterior aspect of the precentral gyrus, consistent with the organization of proximal vs distal neural circuits in the healthy CNS. DISCUSSION These results highlight that proximal and distal upper extremity motor systems can be selectively injured by acute stroke, with dissociable deficits and functional consequences. Our findings emphasize how disruption of distinct motor systems can contribute to separable components of poststroke upper extremity hemiparesis.
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Affiliation(s)
- David J Lin
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital.
| | - Richard Hardstone
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Julie A DiCarlo
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Sydney Mckiernan
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Samuel B Snider
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Hannah Jacobs
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Kimberly S Erler
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Kelly Rishe
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Pierce Boyne
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Jeff Goldsmith
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Jessica Ranford
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Seth P Finklestein
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Lee H Schwamm
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Leigh R Hochberg
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
| | - Steven C Cramer
- From the Center for Neurotechnology and Neurorecovery (D.J.L., R.H., J.A.D., S.M., H.J., K.S.E., K.R., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology; Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School; Department of Occupational Therapy (H.J., K.S.E.), MGH Institute of Health Professions, Boston, MA; Department of Rehabilitation (P.B.), Exercise and Nutrition Sciences, University of Cincinnati College of Allied Health Sciences, OH; Department of Biostatistics (J.G.), Columbia University Mailman School of Public Health, New York, NY; Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; School of Engineering (L.R.H.), Brown University, Providence, RI; and Department of Neurology (S.C.C.), University of California, Los Angeles, California Rehabilitation Hospital
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Verzhbinsky IA, Rubin DB, Kajfez S, Bu Y, Kelemen JN, Kapitonava A, Williams ZM, Hochberg LR, Cash SS, Halgren E. Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans. bioRxiv 2023:2023.05.20.541588. [PMID: 37292943 PMCID: PMC10245779 DOI: 10.1101/2023.05.20.541588] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Synchronous bursts of high frequency oscillations ('ripples') are hypothesized to contribute to binding by facilitating integration of neuronal firing across cortical locations. We tested this hypothesis using local field-potentials and single-unit firing from four 96-channel microelectrode arrays in supragranular cortex of 3 patients. Neurons in co-rippling locations showed increased short-latency co-firing, prediction of each-other's firing, and co-participation in neural assemblies. Effects were similar for putative pyramidal and interneurons, during NREM sleep and waking, in temporal and Rolandic cortices, and at distances up to 16mm. Increased co-prediction during co-ripples was maintained when firing-rate changes were equated, and were strongly modulated by ripple phase. Co-ripple enhanced prediction is reciprocal, synergistic with local upstates, and further enhanced when multiple sites co-ripple. Together, these results support the hypothesis that trans-cortical co-ripples increase the integration of neuronal firing of neurons in different cortical locations, and do so in part through phase-modulation rather than unstructured activation.
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Affiliation(s)
- Ilya A. Verzhbinsky
- Neurosciences Graduate Program, University of California San Diego, La Jolla, CA 92093, USA
- Medical Scientist Training Program, University of California San Diego, La Jolla, CA 92093, USA
| | - Daniel B. Rubin
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02114, USA
| | - Sophie Kajfez
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Yiting Bu
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Jessica N. Kelemen
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Anastasia Kapitonava
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Ziv M. Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114
- Program in Neuroscience, Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA 02115
| | - Leigh R. Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02114, USA
- Center for Neurorestoration and Neurotechnology, Department of Veterans Affairs, Providence, RI 02908, USA
- Carney Institute for Brain Science and School of Engineering, Brown University, Providence, RI 02912, USA
| | - Sydney S. Cash
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02114, USA
| | - Eric Halgren
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
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Deo DR, Willett FR, Avansino DT, Hochberg LR, Henderson JM, Shenoy KV. Translating deep learning to neuroprosthetic control. bioRxiv 2023:2023.04.21.537581. [PMID: 37131830 PMCID: PMC10153231 DOI: 10.1101/2023.04.21.537581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Advances in deep learning have given rise to neural network models of the relationship between movement and brain activity that appear to far outperform prior approaches. Brain-computer interfaces (BCIs) that enable people with paralysis to control external devices, such as robotic arms or computer cursors, might stand to benefit greatly from these advances. We tested recurrent neural networks (RNNs) on a challenging nonlinear BCI problem: decoding continuous bimanual movement of two computer cursors. Surprisingly, we found that although RNNs appeared to perform well in offline settings, they did so by overfitting to the temporal structure of the training data and failed to generalize to real-time neuroprosthetic control. In response, we developed a method that alters the temporal structure of the training data by dilating/compressing it in time and re-ordering it, which we show helps RNNs successfully generalize to the online setting. With this method, we demonstrate that a person with paralysis can control two computer cursors simultaneously, far outperforming standard linear methods. Our results provide evidence that preventing models from overfitting to temporal structure in training data may, in principle, aid in translating deep learning advances to the BCI setting, unlocking improved performance for challenging applications.
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15
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Shah NP, Willsey MS, Hahn N, Kamdar F, Avansino DT, Hochberg LR, Shenoy KV, Henderson JM. A brain-computer typing interface using finger movements. Int IEEE EMBS Conf Neural Eng 2023; 2023:10.1109/ner52421.2023.10123912. [PMID: 37465143 PMCID: PMC10353344 DOI: 10.1109/ner52421.2023.10123912] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
Intracortical brain computer interfaces (iBCIs) decode neural activity from the cortex and enable motor and communication prostheses, such as cursor control, handwriting and speech, for people with paralysis. This paper introduces a new iBCI communication prosthesis using a 3D keyboard interface for typing using continuous, closed loop movement of multiple fingers. A participant-specific BCI keyboard prototype was developed for a BrainGate2 clinical trial participant (T5) using neural recordings from the hand-knob area of the left premotor cortex. We assessed the relative decoding accuracy of flexion/extension movements of individual single fingers (5 degrees of freedom (DOF)) vs. three groups of fingers (thumb, index-middle, and ring-small fingers, 3 DOF). Neural decoding using 3 independent DOF was more accurate (95%) than that using 5 DOF (76%). A virtual keyboard was then developed where each finger group moved along a flexion-extension arc to acquire targets that corresponded to English letters and symbols. The locations of these letter/symbols were optimized using natural language statistics, resulting in an approximately a 2× reduction in distance traveled by fingers on average compared to a random keyboard layout. This keyboard was tested using a simple real-time closed loop decoder enabling T5 to type with 31 symbols at 90% accuracy and approximately 2.3 sec/symbol (excluding a 2 second hold time) on average.
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Affiliation(s)
| | | | | | | | | | - Leigh R Hochberg
- Neurol., Mass. Gen. Hosp; Boston, MA; Brown Univ./VA Medical Center, Providence, RI
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16
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Rubin DB, Ajiboye AB, Barefoot L, Bowker M, Cash SS, Chen D, Donoghue JP, Eskandar EN, Friehs G, Grant C, Henderson JM, Kirsch RF, Marujo R, Masood M, Mernoff ST, Miller JP, Mukand JA, Penn RD, Shefner J, Shenoy KV, Simeral JD, Sweet JA, Walter BL, Williams ZM, Hochberg LR. Interim Safety Profile From the Feasibility Study of the BrainGate Neural Interface System. Neurology 2023; 100:e1177-e1192. [PMID: 36639237 PMCID: PMC10074470 DOI: 10.1212/wnl.0000000000201707] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 11/03/2022] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Brain-computer interfaces (BCIs) are being developed to restore mobility, communication, and functional independence to people with paralysis. Though supported by decades of preclinical data, the safety of chronically implanted microelectrode array BCIs in humans is unknown. We report safety results from the prospective, open-label, nonrandomized BrainGate feasibility study (NCT00912041), the largest and longest-running clinical trial of an implanted BCI. METHODS Adults aged 18-75 years with quadriparesis from spinal cord injury, brainstem stroke, or motor neuron disease were enrolled through 7 clinical sites in the United States. Participants underwent surgical implantation of 1 or 2 microelectrode arrays in the motor cortex of the dominant cerebral hemisphere. The primary safety outcome was device-related serious adverse events (SAEs) requiring device explantation or resulting in death or permanently increased disability during the 1-year postimplant evaluation period. The secondary outcomes included the type and frequency of other adverse events and the feasibility of the BrainGate system for controlling a computer or other assistive technologies. RESULTS From 2004 to 2021, 14 adults enrolled in the BrainGate trial had devices surgically implanted. The average duration of device implantation was 872 days, yielding 12,203 days of safety experience. There were 68 device-related adverse events, including 6 device-related SAEs. The most common device-related adverse event was skin irritation around the percutaneous pedestal. There were no safety events that required device explantation, no unanticipated adverse device events, no intracranial infections, and no participant deaths or adverse events resulting in permanently increased disability related to the investigational device. DISCUSSION The BrainGate Neural Interface system has a safety record comparable with other chronically implanted medical devices. Given rapid recent advances in this technology and continued performance gains, these data suggest a favorable risk/benefit ratio in appropriately selected individuals to support ongoing research and development. TRIAL REGISTRATION INFORMATION ClinicalTrials.gov Identifier: NCT00912041. CLASSIFICATION OF EVIDENCE This study provides Class IV evidence that the neurosurgically placed BrainGate Neural Interface system is associated with a low rate of SAEs defined as those requiring device explantation, resulting in death, or resulting in permanently increased disability during the 1-year postimplant period.
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Affiliation(s)
- Daniel B Rubin
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA.
| | - A Bolu Ajiboye
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Laurie Barefoot
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Marguerite Bowker
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Sydney S Cash
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - David Chen
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - John P Donoghue
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Emad N Eskandar
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Gerhard Friehs
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Carol Grant
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Jaimie M Henderson
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Robert F Kirsch
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Rose Marujo
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Maryam Masood
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Stephen T Mernoff
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Jonathan P Miller
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Jon A Mukand
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Richard D Penn
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Jeremy Shefner
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Krishna V Shenoy
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - John D Simeral
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Jennifer A Sweet
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Benjamin L Walter
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Ziv M Williams
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
| | - Leigh R Hochberg
- From the Center for Neurotechnology and Neurorecovery (CNTR) (D.B.R., L.B., S.S.C., C.G., R.M., M.M., L.R.H.), Department of Neurology, and Department of Neurosurgery (Z.M.W.), Massachusetts General Hospital, Boston; Harvard Medical School (D.B.R., S.S.C., L.R.H.), Boston, MA; Department of Biomedical Engineering (A.B.A., R.F.K.), Case Western Reserve University, Cleveland, OH; FES Center of Excellence, Rehab. R&D Service (A.B.A., R.F.K., J.P.M., J.A.S., B.L.W.), Louis Stokes Cleveland Department of Veterans Affairs Medical Center, OH; Center for Neurorestoration and Neurotechnology (CfNN) (M.B., J.P.D., J.D.S., L.R.H.), Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI; Legs and Walking Lab (D.C.), Shirley Ryan AbilityLab, Chicago, IL; Department of Physical Medicine and Rehabilitation (D.C.), Northwestern University Feinberg School of Medicine, Rehabilitation Institute of Chicago, IL; Department of Neuroscience (J.P.D.), Robert J. and Nancy D. Carney Institute for Brain Science (J.P.D., J.D.S., L.R.H.), School of Engineering (J.P.D., J.D.S., L.R.H.), and Department of Rehabilitation Medicine (J.A.M.), Brown University, Providence, RI; Department of Neurological Surgery (E.N.E.), Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY; European University of Cyprus (G.F.), Nicosia, Cyprus; Department of Neurosurgery (J.M.H.), Stanford University School of Medicine, CA; Wu Tsai Neurosciences Institute (J.M.H., K.V.S.), Bio-X Institute (J.M.H., K.V.S.), and Departments of Neurobiology (K.V.S.), Electrical Engineering (K.V.S.), and Bioengineering (K.V.S.), Stanford University, CA; Department of Neurological Surgery (R.F.K., J.P.M., J.A.S.), University Hospitals Case Medical Center, Cleveland, OH; Neurology Section (S.T.M.), VA Providence Health Care System, Providence, RI; Department of Neurology (S.T.M.), Alpert Medical School of Brown University, Providence, RI; Sargent Rehabilitation Center (J.A.M.), Warwick, RI; Section of Neurosurgery (R.D.P.), Department of Surgery, University of Chicago; Department of Neurosurgery (R.D.P.), Rush University Medical Center, Chicago, IL; Department of Neurology (J.S.), Barrow Neurological Institute, Phoenix, AZ; Howard Hughes Medical Institute at Stanford University (K.V.S.); Center for Neurological Restoration (B.L.W.), Cleveland Clinic, OH; and Program in Neuroscience (Z.M.W.), Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, MA
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Wilson GH, Willett FR, Stein EA, Kamdar F, Avansino DT, Hochberg LR, Shenoy KV, Druckmann S, Henderson JM. Long-term unsupervised recalibration of cursor BCIs. bioRxiv 2023:2023.02.03.527022. [PMID: 36778458 PMCID: PMC9915729 DOI: 10.1101/2023.02.03.527022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Intracortical brain-computer interfaces (iBCIs) require frequent recalibration to maintain robust performance due to changes in neural activity that accumulate over time. Compensating for this nonstationarity would enable consistently high performance without the need for supervised recalibration periods, where users cannot engage in free use of their device. Here we introduce a hidden Markov model (HMM) to infer what targets users are moving toward during iBCI use. We then retrain the system using these inferred targets, enabling unsupervised adaptation to changing neural activity. Our approach outperforms the state of the art in large-scale, closed-loop simulations over two months and in closed-loop with a human iBCI user over one month. Leveraging an offline dataset spanning five years of iBCI recordings, we further show how recently proposed data distribution-matching approaches to recalibration fail over long time scales; only target-inference methods appear capable of enabling long-term unsupervised recalibration. Our results demonstrate how task structure can be used to bootstrap a noisy decoder into a highly-performant one, thereby overcoming one of the major barriers to clinically translating BCIs.
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Rubin DB, Hosman T, Kelemen JN, Kapitonava A, Willett FR, Coughlin BF, Halgren E, Kimchi EY, Williams ZM, Simeral JD, Hochberg LR, Cash SS. Learned Motor Patterns Are Replayed in Human Motor Cortex during Sleep. J Neurosci 2022; 42:5007-5020. [PMID: 35589391 PMCID: PMC9233445 DOI: 10.1523/jneurosci.2074-21.2022] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 02/04/2022] [Accepted: 02/28/2022] [Indexed: 11/30/2022] Open
Abstract
Consolidation of memory is believed to involve offline replay of neural activity. While amply demonstrated in rodents, evidence for replay in humans, particularly regarding motor memory, is less compelling. To determine whether replay occurs after motor learning, we sought to record from motor cortex during a novel motor task and subsequent overnight sleep. A 36-year-old man with tetraplegia secondary to cervical spinal cord injury enrolled in the ongoing BrainGate brain-computer interface pilot clinical trial had two 96-channel intracortical microelectrode arrays placed chronically into left precentral gyrus. Single- and multi-unit activity was recorded while he played a color/sound sequence matching memory game. Intended movements were decoded from motor cortical neuronal activity by a real-time steady-state Kalman filter that allowed the participant to control a neurally driven cursor on the screen. Intracortical neural activity from precentral gyrus and 2-lead scalp EEG were recorded overnight as he slept. When decoded using the same steady-state Kalman filter parameters, intracortical neural signals recorded overnight replayed the target sequence from the memory game at intervals throughout at a frequency significantly greater than expected by chance. Replay events occurred at speeds ranging from 1 to 4 times as fast as initial task execution and were most frequently observed during slow-wave sleep. These results demonstrate that recent visuomotor skill acquisition in humans may be accompanied by replay of the corresponding motor cortex neural activity during sleep.SIGNIFICANCE STATEMENT Within cortex, the acquisition of information is often followed by the offline recapitulation of specific sequences of neural firing. Replay of recent activity is enriched during sleep and may support the consolidation of learning and memory. Using an intracortical brain-computer interface, we recorded and decoded activity from motor cortex as a human research participant performed a novel motor task. By decoding neural activity throughout subsequent sleep, we find that neural sequences underlying the recently practiced motor task are repeated throughout the night, providing direct evidence of replay in human motor cortex during sleep. This approach, using an optimized brain-computer interface decoder to characterize neural activity during sleep, provides a framework for future studies exploring replay, learning, and memory.
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Affiliation(s)
- Daniel B Rubin
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, Massachusetts 02114
| | - Tommy Hosman
- Center for Neurorestoration and Neurotechnology, Department of Veterans Affairs, Providence, Rhode Island 02908
- Carney Institute for Brain Science and School of Engineering, Brown University, Providence, Rhode Island 02912
| | - Jessica N Kelemen
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114
| | - Anastasia Kapitonava
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114
| | - Francis R Willett
- Hughes Medical Institute at Stanford University, Palo Alto, California 94305
| | - Brian F Coughlin
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114
| | - Eric Halgren
- Departments of Neurosciences and Radiology, University of California at San Diego, La Jolla, California 92093
| | - Eyal Y Kimchi
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, Massachusetts 02114
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts 02114
- Program in Neuroscience, Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School, Boston, Massachusetts 02115
| | - John D Simeral
- Center for Neurorestoration and Neurotechnology, Department of Veterans Affairs, Providence, Rhode Island 02908
- Carney Institute for Brain Science and School of Engineering, Brown University, Providence, Rhode Island 02912
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, Massachusetts 02114
- Center for Neurorestoration and Neurotechnology, Department of Veterans Affairs, Providence, Rhode Island 02908
- Carney Institute for Brain Science and School of Engineering, Brown University, Providence, Rhode Island 02912
| | - Sydney S Cash
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, Massachusetts 02114
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Erler KS, Wu R, DiCarlo JA, Petrilli MF, Gochyyev P, Hochberg LR, Kautz SA, Schwamm LH, Cramer SC, Finklestein SP, Lin DJ. Association of Modified Rankin Scale With Recovery Phenotypes in Patients With Upper Extremity Weakness After Stroke. Neurology 2022; 98:e1877-e1885. [PMID: 35277444 PMCID: PMC9109148 DOI: 10.1212/wnl.0000000000200154] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 01/18/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Precise measurement of outcomes is essential for stroke trials and clinical care. Prior research has highlighted conceptual differences between global outcome measures such as the Modified Rankin Scale (mRS) and domain-specific measures (e.g. motor, sensory, language or cognitive function). This study related motor phenotypes to the mRS, specifically aiming to (1) determine whether mRS levels distinguish motor impairment and function phenotypes, and (2) compare mRS outcomes to meaningful changes in impairment and function from acute to subacute recovery after stroke. METHODS Patients with upper extremity weakness after ischemic stroke were assessed with a battery of impairment and functional measures within the first week and at 90-days post-stroke. Impairment and functional outcomes were examined in relation to 90-day mRS scores. Clinically meaningful changes in motor impairment, activities of daily living, and mobility were examined in relation to 90-day mRS. RESULTS In this cohort of n = 73 stroke patients, impairment and functional outcomes were associated with 90-day mRS scores but showed substantial variability within individual mRS levels: within mRS level 2, upper extremity impairment ranged from near hemiplegia (with an upper extremity Fugl-Meyer 8) to no deficits (upper extremity Fugl-Meyer 66). Overall, there were few differences in impairment and functional outcomes between adjacent mRS levels. While some outcome measures were significantly different between mRS levels 3 and 4 (Nine-Hole Peg, Leg Motor, Gait Velocity, Timed Up and Go, National Institutes of Health Stroke Scale, and Barthel Index), none of the outcome measures differed between mRS levels 1 and 2. Fugl-Meyer and Grip Strength were not different between any adjacent mRS levels. A substantial number of patients experienced clinically meaningful changes in impairment and function in the first 90 days post-stroke but did not achieve good mRS outcome (mRS ≤ 2). CONCLUSIONS The mRS broadly relates to domain-specific outcomes after stroke confirming its established value in stroke trials, but it does not precisely distinguish differences in impairment and function nor does it sufficiently capture meaningful clinical changes across impairment, ADL status, and mobility. These findings underscore the potential utility of incorporating detailed phenotypic measures alongside the mRS in future stroke trials.
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Affiliation(s)
- Kimberly S Erler
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,School of Health and Rehabilitation Sciences, MGH Institute of Health Professions, Boston, MA, USA.,Department of Occupational Therapy, Massachusetts General Hospital, Boston, MA, USA
| | - Rui Wu
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Julie A DiCarlo
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Marina F Petrilli
- School of Health and Rehabilitation Sciences, MGH Institute of Health Professions, Boston, MA, USA
| | - Perman Gochyyev
- School of Health and Rehabilitation Sciences, MGH Institute of Health Professions, Boston, MA, USA
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,Division of Neurocritical Care, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,Stroke Service, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,VA RR&D Center for Neurorestoration and Neurotechnology, VA Medical Center, Providence, RI, USA.,School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - Steven A Kautz
- Department of Health Sciences and Research, Medical University of South Carolina, Charleston, SC, USA.,Ralph H Johnson VA Medical Center, Charleston, SC, USA
| | - Lee H Schwamm
- Stroke Service, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Steven C Cramer
- Department of Neurology University of California, Los Angeles, CA, USA.,California Rehabilitation Institute, Los Angeles, CA, USA
| | - Seth P Finklestein
- Stroke Service, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - David J Lin
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,School of Health and Rehabilitation Sciences, MGH Institute of Health Professions, Boston, MA, USA.,Division of Neurocritical Care, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,Stroke Service, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,VA RR&D Center for Neurorestoration and Neurotechnology, VA Medical Center, Providence, RI, USA
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20
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Paulk AC, Kfir Y, Khanna AR, Mustroph ML, Trautmann EM, Soper DJ, Stavisky SD, Welkenhuysen M, Dutta B, Shenoy KV, Hochberg LR, Richardson RM, Williams ZM, Cash SS. Large-scale neural recordings with single neuron resolution using Neuropixels probes in human cortex. Nat Neurosci 2022; 25:252-263. [PMID: 35102333 DOI: 10.1038/s41593-021-00997-0] [Citation(s) in RCA: 70] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 12/07/2021] [Indexed: 12/20/2022]
Abstract
Recent advances in multi-electrode array technology have made it possible to monitor large neuronal ensembles at cellular resolution in animal models. In humans, however, current approaches restrict recordings to a few neurons per penetrating electrode or combine the signals of thousands of neurons in local field potential (LFP) recordings. Here we describe a new probe variant and set of techniques that enable simultaneous recording from over 200 well-isolated cortical single units in human participants during intraoperative neurosurgical procedures using silicon Neuropixels probes. We characterized a diversity of extracellular waveforms with eight separable single-unit classes, with differing firing rates, locations along the length of the electrode array, waveform spatial spread and modulation by LFP events such as inter-ictal discharges and burst suppression. Although some challenges remain in creating a turnkey recording system, high-density silicon arrays provide a path for studying human-specific cognitive processes and their dysfunction at unprecedented spatiotemporal resolution.
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Affiliation(s)
- Angelique C Paulk
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
| | - Yoav Kfir
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Arjun R Khanna
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Martina L Mustroph
- Department of Neurosurgery, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
| | - Eric M Trautmann
- Department of Neuroscience, Columbia University Medical Center, New York City, NY, USA
- Zuckerman Institute, Columbia University, New York City, NY, USA
- Grossman Center for the Statistics of Mind, Columbia University Medical Center, New York City, NY, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Columbia University, New York City, NY, USA
| | - Dan J Soper
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Sergey D Stavisky
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Department of Neurological Surgery, University of California at Davis, Davis, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | | | | | - Krishna V Shenoy
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - R Mark Richardson
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA.
| | - Sydney S Cash
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
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21
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Goldberg MA, Hochberg LR, Carpenter D, Walz JM. Development of a Manually Operated Communication System (MOCS) for patients in intensive care units. Augment Altern Commun 2022; 37:261-273. [PMID: 35023431 DOI: 10.1080/07434618.2021.2016958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
Abstract
Nonvocal alert patients in the intensive care unit (ICU) setting often struggle to communicate due to inaccessible or unavailable tools for augmentative and alternative communication. Innovation of a hand-operated non-touchscreen communication system for nonvocal ICU patients was guided by design concepts including speech output, simplicity, and flexibility. A novel communication tool, the Manually Operated Communication System (MOCS), was developed for use in intensive care settings with patients unable to speak. MOCS is a speech-output technology designed for patients with manual dexterity impairments preventing legible writing. MOCS may have the potential to improve communication for nonvocal patients with limited manual dexterity.
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Affiliation(s)
- Miriam A Goldberg
- MD/PhD Program, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Leigh R Hochberg
- Carney Institute for Brain Science and School of Engineering, Brown University, Providence, RI, USA.,Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Cambridge, MA, USA.,Rehabilitation R&D Service, US Department of Veterans Affairs, VA RR&D Center for Neurorestoration and Neurotechnology, Providence, RI, USA
| | - Dawn Carpenter
- Graduate School of Nursing, University of Massachusetts Chan Medical School, Worcester, MA, USA.,Surgical/Trauma Critical Care, Guthrie Robert Packer Hospital, Sayre, PA, USA
| | - J Matthias Walz
- Department of Anesthesiology & Perioperative Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
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22
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Deo DR, Rezaii P, Hochberg LR, M Okamura A, Shenoy KV, Henderson JM. Effects of Peripheral Haptic Feedback on Intracortical Brain-Computer Interface Control and Associated Sensory Responses in Motor Cortex. IEEE Trans Haptics 2021; 14:762-775. [PMID: 33844633 PMCID: PMC8745032 DOI: 10.1109/toh.2021.3072615] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Intracortical brain-computer interfaces (iBCIs) provide people with paralysis a means to control devices with signals decoded from brain activity. Despite recent impressive advances, these devices still cannot approach able-bodied levels of control. To achieve naturalistic control and improved performance of neural prostheses, iBCIs will likely need to include proprioceptive feedback. With the goal of providing proprioceptive feedback via mechanical haptic stimulation, we aim to understand how haptic stimulation affects motor cortical neurons and ultimately, iBCI control. We provided skin shear haptic stimulation as a substitute for proprioception to the back of the neck of a person with tetraplegia. The neck location was determined via assessment of touch sensitivity using a monofilament test kit. The participant was able to correctly report skin shear at the back of the neck in 8 unique directions with 65% accuracy. We found motor cortical units that exhibited sensory responses to shear stimuli, some of which were strongly tuned to the stimuli and well modeled by cosine-shaped functions. In this article, we also demonstrated online iBCI cursor control with continuous skin-shear feedback driven by decoded command signals. Cursor control performance increased slightly but significantly when the participant was given haptic feedback, compared to the purely visual feedback condition.
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23
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Young MJ, Bodien YG, Giacino JT, Fins JJ, Truog RD, Hochberg LR, Edlow BL. The neuroethics of disorders of consciousness: a brief history of evolving ideas. Brain 2021; 144:3291-3310. [PMID: 34347037 DOI: 10.1093/brain/awab290] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 06/11/2021] [Accepted: 07/10/2021] [Indexed: 11/12/2022] Open
Abstract
Neuroethical questions raised by recent advances in the diagnosis and treatment of disorders of consciousness are rapidly expanding, increasingly relevant, and yet underexplored. The aim of this thematic review is to provide a clinically applicable framework for understanding the current taxonomy of disorders of consciousness and to propose an approach to identifying and critically evaluating actionable neuroethical issues that are frequently encountered in research and clinical care for this vulnerable population. Increased awareness of these issues and clarity about opportunities for optimizing ethically-responsible care in this domain are especially timely given recent surges in critically ill patients with unusually prolonged disorders of consciousness associated with coronavirus disease 2019 (COVID-19) around the world. We begin with an overview of the field of neuroethics: what it is, its history and evolution in the context of biomedical ethics at large. We then explore nomenclature used in disorders of consciousness, covering categories proposed by the American Academy of Neurology, the American Congress of Rehabilitation Medicine, and the National Institute on Disability, Independent Living, and Rehabilitation Research, including definitions of terms such as coma, the vegetative state, unresponsive wakefulness syndrome, minimally conscious state, covert consciousness, and the confusional state. We discuss why these definitions matter, and why there has been such evolution in this nosology over the years, from Jennett and Plum in 1972 to the Multi-Society Task Force in 1994, the Aspen Working Group in 2002 and up until the 2018 American and 2020 European Disorders of Consciousness guidelines. We then move to a discussion of clinical aspects of disorders of consciousness, the natural history of recovery, and ethical issues that arise within the context of caring for persons with disorders of consciousness. We conclude with a discussion of key challenges associated with assessing residual consciousness in disorders of consciousness, potential solutions and future directions, including integration of crucial disability rights perspectives.
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Affiliation(s)
- Michael J Young
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114,USA.,Edmond J. Safra Center for Ethics, Harvard University, Cambridge, MA 02138, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114,USA.,Spaulding Rehabilitation Hospital, Charlestown, MA 02129, USA
| | | | - Joseph J Fins
- Division of Medical Ethics, Weill Cornell Medical College, New York, NY 10021, USA
| | - Robert D Truog
- Center for Bioethics, Harvard Medical School, Boston, MA 02115, USA
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114,USA.,School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI 02906, USA.,VA RR&D Center for Neurorestoration and Neurotechnology, Department of Veterans Affairs Medical Center, Providence, RI 02908, USA
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114,USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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24
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Hochberg LR. 4 Brain computer interface for paralysis. J Neurol Psychiatry 2021. [DOI: 10.1136/jnnp-2021-bnpa.4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Intracortically-based Brain-Computer Interfaces (iBCIs) are poised to revolutionize our ability to restore lost neurologic functions. By recording high resolution neural activity from the brain, the intention to move ones hand can be detected and decoded in real- time, potentially providing people with motor neuron disease (ALS), stroke, or spinal cord injury with restored or maintained ability to control communication devices, assistive technologies, and their own limbs. iBCIs also are central to the development of closed-loop neuromodulation systems, with great potential to serve people with neuropsychiatric disorders. A multi-site pilot clinical trial of the investigational BrainGate system is assessing the feasibility of people with tetraplegia controlling a computer cursor and other devices simply by imagining the movement of their own arm or hand. This presentation will review some of the recent progress made in iBCIs, the information that can be decoded from ensembles of cortical or subcortical neurons in real-time, and the challenges and opportunities for restorative neurotechnologies in research and clinical practice.
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25
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Affiliation(s)
- Leigh R Hochberg
- From the Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, and Harvard Medical School, Boston (L.R.H., S.S.C.); and the School of Engineering and Carney Institute for Brain Science, Brown University, and the Department of Veterans Affairs Rehabilitation Research and Development Service Center for Neurorestoration and Neurotechnology - both in Providence, RI (L.R.H.)
| | - Sydney S Cash
- From the Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, and Harvard Medical School, Boston (L.R.H., S.S.C.); and the School of Engineering and Carney Institute for Brain Science, Brown University, and the Department of Veterans Affairs Rehabilitation Research and Development Service Center for Neurorestoration and Neurotechnology - both in Providence, RI (L.R.H.)
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26
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Simeral JD, Hosman T, Saab J, Flesher SN, Vilela M, Franco B, Kelemen J, Brandman DM, Ciancibello JG, Rezaii PG, Eskandar EN, Rosler DM, Shenoy KV, Henderson JM, Nurmikko AV, Hochberg LR. Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia. IEEE Trans Biomed Eng 2021; 68:2313-2325. [PMID: 33784612 PMCID: PMC8218873 DOI: 10.1109/tbme.2021.3069119] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
OBJECTIVE Individuals with neurological disease or injury such as amyotrophic lateral sclerosis, spinal cord injury or stroke may become tetraplegic, unable to speak or even locked-in. For people with these conditions, current assistive technologies are often ineffective. Brain-computer interfaces are being developed to enhance independence and restore communication in the absence of physical movement. Over the past decade, individuals with tetraplegia have achieved rapid on-screen typing and point-and-click control of tablet apps using intracortical brain-computer interfaces (iBCIs) that decode intended arm and hand movements from neural signals recorded by implanted microelectrode arrays. However, cables used to convey neural signals from the brain tether participants to amplifiers and decoding computers and require expert oversight, severely limiting when and where iBCIs could be available for use. Here, we demonstrate the first human use of a wireless broadband iBCI. METHODS Based on a prototype system previously used in pre-clinical research, we replaced the external cables of a 192-electrode iBCI with wireless transmitters and achieved high-resolution recording and decoding of broadband field potentials and spiking activity from people with paralysis. Two participants in an ongoing pilot clinical trial completed on-screen item selection tasks to assess iBCI-enabled cursor control. RESULTS Communication bitrates were equivalent between cabled and wireless configurations. Participants also used the wireless iBCI to control a standard commercial tablet computer to browse the web and use several mobile applications. Within-day comparison of cabled and wireless interfaces evaluated bit error rate, packet loss, and the recovery of spike rates and spike waveforms from the recorded neural signals. In a representative use case, the wireless system recorded intracortical signals from two arrays in one participant continuously through a 24-hour period at home. SIGNIFICANCE Wireless multi-electrode recording of broadband neural signals over extended periods introduces a valuable tool for human neuroscience research and is an important step toward practical deployment of iBCI technology for independent use by individuals with paralysis. On-demand access to high-performance iBCI technology in the home promises to enhance independence and restore communication and mobility for individuals with severe motor impairment.
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Affiliation(s)
| | - Thomas Hosman
- CfNN and the School of Engineering, Brown University
| | - Jad Saab
- CfNN and the School of Engineering, Brown University. He is now with Insight Data Science, New York City, NY
| | - Sharlene N. Flesher
- Department of Electrical Engineering, Department of Neurosurgery, and Howard Hughes Medical Institute, Stanford University. She is now with Apple Inc., Cupertino, CA
| | - Marco Vilela
- School of Engineering, Brown University. He is now with Takeda, Cambridge, MA
| | - Brian Franco
- Department of Neurology, Massachusetts General Hospital, Boston, MA. He is now with NeuroPace Inc., Mountain View, CA
| | - Jessica Kelemen
- Department of Neurology, Massachusetts General Hospital, Boston
| | - David M. Brandman
- School of Engineering, Brown University. He is now with the Department of Neurosurgery, Emory University, Atlanta, GA
| | - John G. Ciancibello
- School of Engineering, Brown University. He is now with the Center for Bioelectronic Medicine at the Feinstein Institute for Medical Research, Manhasset, NY
| | - Paymon G. Rezaii
- Department of Neurosurgery, Stanford University. He is now with the School of Medicine, Tulane University
| | - Emad N. Eskandar
- Department of Neurosurgery, Massachusetts General Hospital. He is now with the Department of Neurosurgery, Albert Einstein College of Medicine, Montefiore Medical Center, NY
| | - David M. Rosler
- CfNN and the School of Engineering and the Robert J. & Nancy D. Carney Institute for Brain Science, Brown University, and also with the Department of Neurology, Massachusetts General Hospital
| | - Krishna V. Shenoy
- Departments of Electrical Engineering, Bioengineering and Neurobiology, Wu Tsai Neurosciences Institute, and the Bio-X Institute, Stanford, and also with the Howard Hughes Medical Institute, Stanford University
| | - Jaimie M. Henderson
- Department of Neurosurgery and Wu Tsai Neurosciences Institute and the Bio-X Institute, Stanford University
| | - Arto V. Nurmikko
- School of Engineering, Department of Physics, and the Robert J. & Nancy D. Carney Institute for Brain Science, Brown University
| | - Leigh R. Hochberg
- CfNN, and the School of Engineering and the Robert J. & Nancy D. Carney Institute for Brain Science, Brown University, and the Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School
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27
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Yang JC, Harid NM, Nascimento FA, Kokkinos V, Shaughnessy A, Lam AD, Westover MB, Leslie-Mazwi TM, Hochberg LR, Rosenthal ES, Cole AJ, Richardson RM, Cash SS. Responsive neurostimulation for focal motor status epilepticus. Ann Clin Transl Neurol 2021; 8:1353-1361. [PMID: 33955717 PMCID: PMC8164849 DOI: 10.1002/acn3.51318] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 01/09/2021] [Accepted: 01/25/2021] [Indexed: 12/12/2022] Open
Abstract
No clear evidence‐based treatment paradigm currently exists for refractory and super‐refractory status epilepticus, which can result in significant mortality and morbidity. While patients are typically treated with antiepileptic drugs and anesthetics, neurosurgical neuromodulation techniques can also be considered. We present a novel case in which responsive neurostimulation was used to effectively treat a patient who had developed super‐refractory status epilepticus, later consistent with epilepsia partialis continua, that was refractory to antiepileptic drugs, immunomodulatory therapies, and transcranial magnetic stimulation. This case demonstrates how regional therapy provided by responsive neurostimulation can be effective in treating super‐refractory status epilepticus through neuromodulation of seizure networks.
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Affiliation(s)
- Jimmy C Yang
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Nitish M Harid
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Fábio A Nascimento
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Vasileios Kokkinos
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Abigail Shaughnessy
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Alice D Lam
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - M Brandon Westover
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Thabele M Leslie-Mazwi
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Leigh R Hochberg
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Eric S Rosenthal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Andrew J Cole
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Robert M Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts, USA
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28
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Dawson J, Liu CY, Francisco GE, Cramer SC, Wolf SL, Dixit A, Alexander J, Ali R, Brown BL, Feng W, DeMark L, Hochberg LR, Kautz SA, Majid A, O'Dell MW, Pierce D, Prudente CN, Redgrave J, Turner DL, Engineer ND, Kimberley TJ. Vagus nerve stimulation paired with rehabilitation for upper limb motor function after ischaemic stroke (VNS-REHAB): a randomised, blinded, pivotal, device trial. Lancet 2021; 397:1545-1553. [PMID: 33894832 PMCID: PMC8862193 DOI: 10.1016/s0140-6736(21)00475-x] [Citation(s) in RCA: 159] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 02/16/2021] [Accepted: 02/19/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Long-term loss of arm function after ischaemic stroke is common and might be improved by vagus nerve stimulation paired with rehabilitation. We aimed to determine whether this strategy is a safe and effective treatment for improving arm function after stroke. METHODS In this pivotal, randomised, triple-blind, sham-controlled trial, done in 19 stroke rehabilitation services in the UK and the USA, participants with moderate-to-severe arm weakness, at least 9 months after ischaemic stroke, were randomly assigned (1:1) to either rehabilitation paired with active vagus nerve stimulation (VNS group) or rehabilitation paired with sham stimulation (control group). Randomisation was done by ResearchPoint Global (Austin, TX, USA) using SAS PROC PLAN (SAS Institute Software, Cary, NC, USA), with stratification by region (USA vs UK), age (≤30 years vs >30 years), and baseline Fugl-Meyer Assessment-Upper Extremity (FMA-UE) score (20-35 vs 36-50). Participants, outcomes assessors, and treating therapists were masked to group assignment. All participants were implanted with a vagus nerve stimulation device. The VNS group received 0·8 mA, 100 μs, 30 Hz stimulation pulses, lasting 0·5 s. The control group received 0 mA pulses. Participants received 6 weeks of in-clinic therapy (three times per week; total of 18 sessions) followed by a home exercise programme. The primary outcome was the change in impairment measured by the FMA-UE score on the first day after completion of in-clinic therapy. FMA-UE response rates were also assessed at 90 days after in-clinic therapy (secondary endpoint). All analyses were by intention to treat. This trial is registered at ClinicalTrials.gov, NCT03131960. FINDINGS Between Oct 2, 2017, and Sept 12, 2019, 108 participants were randomly assigned to treatment (53 to the VNS group and 55 to the control group). 106 completed the study (one patient for each group did not complete the study). On the first day after completion of in-clinic therapy, the mean FMA-UE score increased by 5·0 points (SD 4·4) in the VNS group and by 2·4 points (3·8) in the control group (between group difference 2·6, 95% CI 1·0-4·2, p=0·0014). 90 days after in-clinic therapy, a clinically meaningful response on the FMA-UE score was achieved in 23 (47%) of 53 patients in the VNS group versus 13 (24%) of 55 patients in the control group (between group difference 24%, 6-41; p=0·0098). There was one serious adverse event related to surgery (vocal cord paresis) in the control group. INTERPRETATION Vagus nerve stimulation paired with rehabilitation is a novel potential treatment option for people with long-term moderate-to-severe arm impairment after ischaemic stroke. FUNDING MicroTransponder.
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Affiliation(s)
- Jesse Dawson
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
| | - Charles Y Liu
- USC Neurorestoration Center and Department of Neurological Surgery, USC Keck School of Medicine, Los Angeles, CA, USA; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA
| | - Gerard E Francisco
- Department of Physical Medicine and Rehabilitation, The University of Texas Health Science Center McGovern Medical School, Houston, TX, USA; The Institute for Rehabilitation and Research (TIRR) Memorial Hermann Hospital, Houston, Texas, USA
| | - Steven C Cramer
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; California Rehabilitation Institute, Los Angeles, CA, USA
| | - Steven L Wolf
- Department of Rehabilitation Medicine, Division of Physical Therapy, Emory University School of Medicine, Atlanta, GA, USA
| | - Anand Dixit
- Stroke Service, The Newcastle Upon Tyne Hospitals National Health Service Foundation Trust, Newcastle, UK
| | - Jen Alexander
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Rushna Ali
- Department of Neurosciences, Spectrum Health, Grand Rapids, MI, USA
| | - Benjamin L Brown
- Department of Neurosurgery, Ochsner Neuroscience Institute, Covington, LA, USA
| | - Wuwei Feng
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
| | | | - Leigh R Hochberg
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA; VA RR&D Center for Neurorestoration and Neurotechnology, VA Medical Center, Providence, RI, USA
| | - Steven A Kautz
- Ralph H Johnson VA Medical Center, Charleston, SC, USA; Department of Health Sciences and Research, Medical University of South Carolina, Charleston, SC, USA
| | - Arshad Majid
- Sheffield Institute for Neurological Sciences (SITraN), University of Sheffield, Sheffield, UK; Sheffield Teaching Hospitals National Health Service Foundation Trust, Sheffield, UK
| | - Michael W O'Dell
- Clinical Rehabilitation Medicine, Weill Cornell Medicine, New York City, NY, USA
| | | | | | - Jessica Redgrave
- Sheffield Institute for Neurological Sciences (SITraN), University of Sheffield, Sheffield, UK
| | - Duncan L Turner
- School of Health, Sport and Bioscience, University of East London, London, UK
| | | | - Teresa J Kimberley
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Physical Therapy, MGH Institute of Health Professions, Boston, MA, USA
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Lin DJ, Erler KS, Snider SB, Bonkhoff AK, DiCarlo JA, Lam N, Ranford J, Parlman K, Cohen A, Freeburn J, Finklestein SP, Schwamm LH, Hochberg LR, Cramer SC. Cognitive Demands Influence Upper Extremity Motor Performance During Recovery From Acute Stroke. Neurology 2021; 96:e2576-e2586. [PMID: 33858997 DOI: 10.1212/wnl.0000000000011992] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 02/26/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To test the hypothesis that cognitive demands influence motor performance during recovery from acute stroke, we tested patients with acute stroke on 2 motor tasks with different cognitive demands and related task performance to cognitive impairment and neuroanatomic injury. METHODS We assessed the contralesional and ipsilesional upper extremities of a cohort of 50 patients with weakness after unilateral acute ischemic stroke at 3 time points with 2 tasks: the Box & Blocks Test, a task with greater cognitive demand, and Grip Strength, a simple and ballistic motor task. We compared performance on the 2 tasks, related motor performance to cognitive dysfunction, and used voxel-based lesion symptom mapping to determine neuroanatomic sites associated with motor performance. RESULTS Consistent across contralesional and ipsilesional upper extremities and most pronounced immediately after stroke, Box & Blocks scores were significantly more impaired than Grip Strength scores. The presence of cognitive dysfunction significantly explained up to 33% of variance in Box & Blocks performance but was not associated with Grip Strength performance. While Grip Strength performance was associated with injury largely restricted to sensorimotor regions, Box & Blocks performance was associated with broad injury outside sensorimotor structures, particularly the dorsal anterior insula, a region known to be important for complex cognitive function. CONCLUSIONS Together, these results suggest that cognitive demands influence upper extremity motor performance during recovery from acute stroke. Our findings emphasize the integrated nature of motor and cognitive systems and suggest that it is critical to consider cognitive demands during motor testing and neurorehabilitation after stroke.
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Affiliation(s)
- David J Lin
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles.
| | - Kimberly S Erler
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Samuel B Snider
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Anna K Bonkhoff
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Julie A DiCarlo
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Nicole Lam
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Jessica Ranford
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Kristin Parlman
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Audrey Cohen
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Jennifer Freeburn
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Seth P Finklestein
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Lee H Schwamm
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Leigh R Hochberg
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
| | - Steven C Cramer
- From the Center for Neurotechnology and Neurorecovery (D.J.L., J.A.D., N.L., J.R., K.P., A.C., J.F., L.R.H.), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston; Division of Neurocritical Care (D.J.L., L.R.H.), Department of Neurology, Stroke Service (D.J.L., S.P.F., L.H.S., L.R.H.), Department of Neurology, J. Philip Kistler Stroke Research Center (A.K.B.), Department of Neurology, Department of Occupational Therapy (J.R.), Department of Physical Therapy (K.P.), and Department of Speech, Language, and Swallowing Disorders (A.C., J.F.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurorestoration and Neurotechnology (D.J.L., L.R.H.), Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI; Department of Occupational Therapy (K.S.E., N.L.), MGH Institute of Health Professions, Boston, MA; Division of Neurocritical Care (S.B.S.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; School of Engineering (L.R.H.), Brown University, Providence, RI; Department of Neurology (S.C.C.), University of California, Los Angeles; and California Rehabilitation Hospital (S.C.C.), Los Angeles
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Kline DK, Lin DJ, Cloutier A, Sloane K, Parlman K, Ranford J, Picard-Fraser M, Fox AB, Hochberg LR, Kimberley TJ. Arm Motor Recovery After Ischemic Stroke: A Focus on Clinically Distinct Trajectory Groups. J Neurol Phys Ther 2021; 45:70-78. [PMID: 33707402 DOI: 10.1097/npt.0000000000000350] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND AND PURPOSE Recovery of arm function poststroke is highly variable with some people experiencing rapid recovery but many experiencing slower or limited functional improvement. Current stroke prediction models provide some guidance for clinicians regarding expected motor outcomes poststroke but do not address recovery rates, complicating discharge planning. This study developed a novel approach to defining recovery groups based on arm motor recovery trajectories poststroke. In addition, between-group differences in baseline characteristics and therapy hours were explored. METHODS A retrospective cohort analysis was conducted where 40 participants with arm weakness were assessed 1 week, 6 weeks, 3 months, and 6 months after an ischemic stroke. Arm recovery trajectory groups were defined on the basis of timing of changes in the Fugl-Meyer Assessment Upper Extremity (FMA-UE), at least the minimal clinically important difference (MCID), 1 week to 6 weeks or 6 weeks to 6 months. Three recovery trajectory groups were defined: Fast (n = 19), Extended (n = 12), and Limited (n = 9). Between-group differences in baseline characteristics and therapy hours were assessed. Associations between baseline characteristics and group membership were also determined. RESULTS Three baseline characteristics were associated with trajectory group membership: FMA-UE, NIH Stroke Scale, and Barthel Index. The Fast Recovery group received the least therapy hours 6 weeks to 6 months. No differences in therapy hours were observed between Extended and Limited Recovery groups at any time points. DISCUSSION AND CONCLUSIONS Three clinically relevant recovery trajectory groups were defined using the FMA-UE MCID. Baseline impairment, overall stroke severity, and dependence in activities of daily living were associated with group membership and therapy hours differed between groups. Stratifying individuals by recovery trajectory early poststroke could offer additional guidance to clinicians in discharge planning. (See Supplemental Digital Content 1 for Video Abstract, available at: http://links.lww.com/JNPT/A337.).
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Affiliation(s)
- Danielle K Kline
- Department of Physical Therapy (D.K.K., M.P.-F., T.J.K.) and Center for Interprofessional Studies and Innovation (A.B.F.), MGH Institute of Health Professions, Boston, Massachusetts; Center for Neurotechnology and Neurorecovery, Department of Neurology (D.J.L., A.C., K.S., L.R.H.), Divisions of Neurocritical Care and Stroke, Department of Neurology (D.J.L., L.R.H.), Department of Physical Therapy (K.P.), and Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston; VA RR&D Center for Neurotechnology and Neurorecovery, Providence, Rhode Island (L.R.H.); and School of Engineering, Brown University, Providence, Rhode Island (L.R.H.)
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Abstract
Recent advances in brain-computer interface technology to restore and rehabilitate neurologic function aim to enable persons with disabling neurologic conditions to communicate, interact with the environment, and achieve other key activities of daily living and personal goals. Here we evaluate the principles, benefits, challenges, and future directions of brain-computer interfaces in the context of neurorehabilitation. We then explore the clinical translation of these technologies and propose an approach to facilitate implementation of brain-computer interfaces for persons with neurologic disease.
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Affiliation(s)
- Michael J Young
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - David J Lin
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, Rhode Island
- Department of Veterans Affairs Medical Center, VA RR&D Center for Neurorestoration and Neurotechnology, Providence, Rhode Island
| | - Leigh R Hochberg
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, Rhode Island
- Department of Veterans Affairs Medical Center, VA RR&D Center for Neurorestoration and Neurotechnology, Providence, Rhode Island
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32
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Oxley TJ, Yoo PE, Rind GS, Ronayne SM, Lee CMS, Bird C, Hampshire V, Sharma RP, Morokoff A, Williams DL, MacIsaac C, Howard ME, Irving L, Vrljic I, Williams C, John SE, Weissenborn F, Dazenko M, Balabanski AH, Friedenberg D, Burkitt AN, Wong YT, Drummond KJ, Desmond P, Weber D, Denison T, Hochberg LR, Mathers S, O'Brien TJ, May CN, Mocco J, Grayden DB, Campbell BCV, Mitchell P, Opie NL. Motor neuroprosthesis implanted with neurointerventional surgery improves capacity for activities of daily living tasks in severe paralysis: first in-human experience. J Neurointerv Surg 2021; 13:102-108. [PMID: 33115813 PMCID: PMC7848062 DOI: 10.1136/neurintsurg-2020-016862] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 10/07/2020] [Accepted: 10/09/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND Implantable brain-computer interfaces (BCIs), functioning as motor neuroprostheses, have the potential to restore voluntary motor impulses to control digital devices and improve functional independence in patients with severe paralysis due to brain, spinal cord, peripheral nerve or muscle dysfunction. However, reports to date have had limited clinical translation. METHODS Two participants with amyotrophic lateral sclerosis (ALS) underwent implant in a single-arm, open-label, prospective, early feasibility study. Using a minimally invasive neurointervention procedure, a novel endovascular Stentrode BCI was implanted in the superior sagittal sinus adjacent to primary motor cortex. The participants undertook machine-learning-assisted training to use wirelessly transmitted electrocorticography signal associated with attempted movements to control multiple mouse-click actions, including zoom and left-click. Used in combination with an eye-tracker for cursor navigation, participants achieved Windows 10 operating system control to conduct instrumental activities of daily living (IADL) tasks. RESULTS Unsupervised home use commenced from day 86 onwards for participant 1, and day 71 for participant 2. Participant 1 achieved a typing task average click selection accuracy of 92.63% (100.00%, 87.50%-100.00%) (trial mean (median, Q1-Q3)) at a rate of 13.81 (13.44, 10.96-16.09) correct characters per minute (CCPM) with predictive text disabled. Participant 2 achieved an average click selection accuracy of 93.18% (100.00%, 88.19%-100.00%) at 20.10 (17.73, 12.27-26.50) CCPM. Completion of IADL tasks including text messaging, online shopping and managing finances independently was demonstrated in both participants. CONCLUSION We describe the first-in-human experience of a minimally invasive, fully implanted, wireless, ambulatory motor neuroprosthesis using an endovascular stent-electrode array to transmit electrocorticography signals from the motor cortex for multiple command control of digital devices in two participants with flaccid upper limb paralysis.
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Affiliation(s)
- Thomas J Oxley
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Synchron, Inc, Campbell, California, USA
| | - Peter E Yoo
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Synchron, Inc, Campbell, California, USA
| | - Gil S Rind
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Synchron, Inc, Campbell, California, USA
| | - Stephen M Ronayne
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Synchron, Inc, Campbell, California, USA
| | - C M Sarah Lee
- Neurology, Calvary Health Care Bethlehem, South Caulfield, Victoria, Australia
| | - Christin Bird
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
| | | | - Rahul P Sharma
- Interventional Cardiology, Cardiovascular Medicine Faculty, Stanford University, Stanford, California, USA
| | - Andrew Morokoff
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Neurosurgery, Melbourne Health, Parkville, Victoria, Australia
| | | | | | - Mark E Howard
- Institute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia
| | - Lou Irving
- Respiratory Medicine, Melbourne Health, Parkville, Victoria, Australia
| | - Ivan Vrljic
- Radiology, Melbourne Health, Parkville, Victoria, Australia
| | | | - Sam E John
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Frank Weissenborn
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria, Australia
| | - Madeleine Dazenko
- Neurology, Calvary Health Care Bethlehem, South Caulfield, Victoria, Australia
| | | | | | - Anthony N Burkitt
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Yan T Wong
- Department of Electrical and Computer Systems Engineering, Monash University, Clayton, Victoria, Australia
| | - Katharine J Drummond
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Neurosurgery, Melbourne Health, Parkville, Victoria, Australia
| | - Patricia Desmond
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Radiology, Melbourne Health, Parkville, Victoria, Australia
| | - Douglas Weber
- Department of Mechanical Engineering and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Timothy Denison
- Synchron, Inc, Campbell, California, USA
- Institute of Biomedical Engineering, Oxford University, Oxford, Oxfordshire, UK
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Harvard University, Cambridge, Massachusetts, USA
| | - Susan Mathers
- Neurology, Calvary Health Care Bethlehem, South Caulfield, Victoria, Australia
| | - Terence J O'Brien
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Neurology, Melbourne Health, Parkville, Victoria, Australia
| | - Clive N May
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria, Australia
| | - J Mocco
- Neurosurgery, The Mount Sinai Health System, New York, New York, USA
| | - David B Grayden
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Bruce C V Campbell
- Medicine, University of Melbourne, Parkville, Victoria, Australia
- Neurology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Peter Mitchell
- Radiology, Melbourne Health, Parkville, Victoria, Australia
| | - Nicholas L Opie
- Vascular Bionics Laboratory, Departments of Medicine, Neurology and Surgery, Melbourne Brain Centre at the Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Synchron, Inc, Campbell, California, USA
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Hosman T, Hynes JB, Saab J, Wilcoxen KG, Buchbinder BR, Schmansky N, Cash SS, Eskandar EN, Simeral JD, Franco B, Kelemen J, Vargas-Irwin CE, Hochberg LR. Auditory cues reveal intended movement information in middle frontal gyrus neuronal ensemble activity of a person with tetraplegia. Sci Rep 2021; 11:98. [PMID: 33431994 PMCID: PMC7801741 DOI: 10.1038/s41598-020-77616-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 11/12/2020] [Indexed: 01/29/2023] Open
Abstract
Intracortical brain-computer interfaces (iBCIs) allow people with paralysis to directly control assistive devices using neural activity associated with the intent to move. Realizing the full potential of iBCIs critically depends on continued progress in understanding how different cortical areas contribute to movement control. Here we present the first comparison between neuronal ensemble recordings from the left middle frontal gyrus (MFG) and precentral gyrus (PCG) of a person with tetraplegia using an iBCI. As expected, PCG was more engaged in selecting and generating intended movements than in earlier perceptual stages of action planning. By contrast, MFG displayed movement-related information during the sensorimotor processing steps preceding the appearance of the action plan in PCG, but only when the actions were instructed using auditory cues. These results describe a previously unreported function for neurons in the human left MFG in auditory processing contributing to motor control.
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Affiliation(s)
- Tommy Hosman
- School of Engineering, Brown University, Providence, RI, USA
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Center for Neurorestoration and Neurotechnology, Rehabilitation Research and Development Service, Department of Veterans Affairs Medical Center, Providence, RI, USA
| | - Jacqueline B Hynes
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Department of Neuroscience, Brown University, Providence, RI, USA
| | - Jad Saab
- School of Engineering, Brown University, Providence, RI, USA
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Center for Neurorestoration and Neurotechnology, Rehabilitation Research and Development Service, Department of Veterans Affairs Medical Center, Providence, RI, USA
| | - Kaitlin G Wilcoxen
- Neuroscience Graduate Program, Brown University, Providence, RI, USA
- Center for Neurorestoration and Neurotechnology, Rehabilitation Research and Development Service, Department of Veterans Affairs Medical Center, Providence, RI, USA
| | | | - Nicholas Schmansky
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Sydney S Cash
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Emad N Eskandar
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurosurgery, Albert Einstein College of Medicine, Montefiore Medical Center, New York, NY, USA
| | - John D Simeral
- School of Engineering, Brown University, Providence, RI, USA
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Center for Neurorestoration and Neurotechnology, Rehabilitation Research and Development Service, Department of Veterans Affairs Medical Center, Providence, RI, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Brian Franco
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- NeuroPace, Inc., Mountain View, CA, USA
| | - Jessica Kelemen
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Carlos E Vargas-Irwin
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, USA.
- Department of Neuroscience, Brown University, Providence, RI, USA.
- Center for Neurorestoration and Neurotechnology, Rehabilitation Research and Development Service, Department of Veterans Affairs Medical Center, Providence, RI, USA.
| | - Leigh R Hochberg
- School of Engineering, Brown University, Providence, RI, USA.
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, USA.
- Center for Neurorestoration and Neurotechnology, Rehabilitation Research and Development Service, Department of Veterans Affairs Medical Center, Providence, RI, USA.
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
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Wilson GH, Stavisky SD, Willett FR, Avansino DT, Kelemen JN, Hochberg LR, Henderson JM, Druckmann S, Shenoy KV. Decoding spoken English from intracortical electrode arrays in dorsal precentral gyrus. J Neural Eng 2020; 17:066007. [PMID: 33236720 PMCID: PMC8293867 DOI: 10.1088/1741-2552/abbfef] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
OBJECTIVE To evaluate the potential of intracortical electrode array signals for brain-computer interfaces (BCIs) to restore lost speech, we measured the performance of decoders trained to discriminate a comprehensive basis set of 39 English phonemes and to synthesize speech sounds via a neural pattern matching method. We decoded neural correlates of spoken-out-loud words in the 'hand knob' area of precentral gyrus, a step toward the eventual goal of decoding attempted speech from ventral speech areas in patients who are unable to speak. APPROACH Neural and audio data were recorded while two BrainGate2 pilot clinical trial participants, each with two chronically-implanted 96-electrode arrays, spoke 420 different words that broadly sampled English phonemes. Phoneme onsets were identified from audio recordings, and their identities were then classified from neural features consisting of each electrode's binned action potential counts or high-frequency local field potential power. Speech synthesis was performed using the 'Brain-to-Speech' pattern matching method. We also examined two potential confounds specific to decoding overt speech: acoustic contamination of neural signals and systematic differences in labeling different phonemes' onset times. MAIN RESULTS A linear decoder achieved up to 29.3% classification accuracy (chance = 6%) across 39 phonemes, while an RNN classifier achieved 33.9% accuracy. Parameter sweeps indicated that performance did not saturate when adding more electrodes or more training data, and that accuracy improved when utilizing time-varying structure in the data. Microphonic contamination and phoneme onset differences modestly increased decoding accuracy, but could be mitigated by acoustic artifact subtraction and using a neural speech onset marker, respectively. Speech synthesis achieved r = 0.523 correlation between true and reconstructed audio. SIGNIFICANCE The ability to decode speech using intracortical electrode array signals from a nontraditional speech area suggests that placing electrode arrays in ventral speech areas is a promising direction for speech BCIs.
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Affiliation(s)
- Guy H Wilson
- Neurosciences Graduate Program, Stanford University, Stanford, CA, United States of America
| | - Sergey D Stavisky
- Department of Neurosurgery, Stanford University, Stanford, CA, United States of America
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, United States of America
- Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America
| | - Francis R Willett
- Department of Neurosurgery, Stanford University, Stanford, CA, United States of America
- Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, United States of America
| | - Donald T Avansino
- Department of Neurosurgery, Stanford University, Stanford, CA, United States of America
| | - Jessica N Kelemen
- Department of Neurology, Harvard Medical School, Boston, MA, United States of America
| | - Leigh R Hochberg
- Department of Neurology, Harvard Medical School, Boston, MA, United States of America
- Center for Neurotechnology and Neurorecovery, Dept. of Neurology, Massachusetts General Hospital, Boston, MA, United States of America
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI, United States of America
- Carney Institute for Brain Science and School of Engineering, Brown University, Providence, RI, United States of America
| | - Jaimie M Henderson
- Department of Neurosurgery, Stanford University, Stanford, CA, United States of America
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, United States of America
| | - Shaul Druckmann
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, United States of America
- Department of Neurobiology, Stanford University, Stanford, CA, United States of America
| | - Krishna V Shenoy
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, United States of America
- Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, United States of America
- Department of Neurobiology, Stanford University, Stanford, CA, United States of America
- Department of Bioengineering, Stanford University, Stanford, CA, United States of America
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35
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Even-Chen N, Muratore DG, Stavisky SD, Hochberg LR, Henderson JM, Murmann B, Shenoy KV. Power-saving design opportunities for wireless intracortical brain-computer interfaces. Nat Biomed Eng 2020; 4:984-996. [PMID: 32747834 PMCID: PMC8286886 DOI: 10.1038/s41551-020-0595-9] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Accepted: 06/30/2020] [Indexed: 12/17/2022]
Abstract
The efficacy of wireless intracortical brain-computer interfaces (iBCIs) is limited in part by the number of recording channels, which is constrained by the power budget of the implantable system. Designing wireless iBCIs that provide the high-quality recordings of today's wired neural interfaces may lead to inadvertent over-design at the expense of power consumption and scalability. Here, we report analyses of neural signals collected from experimental iBCI measurements in rhesus macaques and from a clinical-trial participant with implanted 96-channel Utah multielectrode arrays to understand the trade-offs between signal quality and decoder performance. Moreover, we propose an efficient hardware design for clinically viable iBCIs, and suggest that the circuit design parameters of current recording iBCIs can be relaxed considerably without loss of performance. The proposed design may allow for an order-of-magnitude power savings and lead to clinically viable iBCIs with a higher channel count.
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Affiliation(s)
- Nir Even-Chen
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
| | - Dante G Muratore
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Sergey D Stavisky
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Leigh R Hochberg
- Department of Veterans Affairs Medical Center, Center for Neurorestoration and Neurotechnology, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jaimie M Henderson
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Boris Murmann
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Krishna V Shenoy
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- The Bio-X Institute, Stanford University, Stanford, CA, USA
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36
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Edlow BL, Barra ME, Zhou DW, Foulkes AS, Snider SB, Threlkeld ZD, Chakravarty S, Kirsch JE, Chan ST, Meisler SL, Bleck TP, Fins JJ, Giacino JT, Hochberg LR, Solt K, Brown EN, Bodien YG. Personalized Connectome Mapping to Guide Targeted Therapy and Promote Recovery of Consciousness in the Intensive Care Unit. Neurocrit Care 2020; 33:364-375. [PMID: 32794142 DOI: 10.1007/s12028-020-01062-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 04/18/2020] [Indexed: 01/05/2023]
Abstract
There are currently no therapies proven to promote early recovery of consciousness in patients with severe brain injuries in the intensive care unit (ICU). For patients whose families face time-sensitive, life-or-death decisions, treatments that promote recovery of consciousness are needed to reduce the likelihood of premature withdrawal of life-sustaining therapy, facilitate autonomous self-expression, and increase access to rehabilitative care. Here, we present the Connectome-based Clinical Trial Platform (CCTP), a new paradigm for developing and testing targeted therapies that promote early recovery of consciousness in the ICU. We report the protocol for STIMPACT (Stimulant Therapy Targeted to Individualized Connectivity Maps to Promote ReACTivation of Consciousness), a CCTP-based trial in which intravenous methylphenidate will be used for targeted stimulation of dopaminergic circuits within the subcortical ascending arousal network (ClinicalTrials.gov NCT03814356). The scientific premise of the CCTP and the STIMPACT trial is that personalized brain network mapping in the ICU can identify patients whose connectomes are amenable to neuromodulation. Phase 1 of the STIMPACT trial is an open-label, safety and dose-finding study in 22 patients with disorders of consciousness caused by acute severe traumatic brain injury. Patients in Phase 1 will receive escalating daily doses (0.5-2.0 mg/kg) of intravenous methylphenidate over a 4-day period and will undergo resting-state functional magnetic resonance imaging and electroencephalography to evaluate the drug's pharmacodynamic properties. The primary outcome measure for Phase 1 relates to safety: the number of drug-related adverse events at each dose. Secondary outcome measures pertain to pharmacokinetics and pharmacodynamics: (1) time to maximal serum concentration; (2) serum half-life; (3) effect of the highest tolerated dose on resting-state functional MRI biomarkers of connectivity; and (4) effect of each dose on EEG biomarkers of cerebral cortical function. Predetermined safety and pharmacodynamic criteria must be fulfilled in Phase 1 to proceed to Phase 2A. Pharmacokinetic data from Phase 1 will also inform the study design of Phase 2A, where we will test the hypothesis that personalized connectome maps predict therapeutic responses to intravenous methylphenidate. Likewise, findings from Phase 2A will inform the design of Phase 2B, where we plan to enroll patients based on their personalized connectome maps. By selecting patients for clinical trials based on a principled, mechanistic assessment of their neuroanatomic potential for a therapeutic response, the CCTP paradigm and the STIMPACT trial have the potential to transform the therapeutic landscape in the ICU and improve outcomes for patients with severe brain injuries.
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Affiliation(s)
- Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. .,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
| | - Megan E Barra
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Pharmacy, Massachusetts General Hospital, Boston, MA, USA
| | - David W Zhou
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Andrea S Foulkes
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Samuel B Snider
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Zachary D Threlkeld
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA, USA
| | - Sourish Chakravarty
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA.,The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - John E Kirsch
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Suk-Tak Chan
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Steven L Meisler
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Thomas P Bleck
- Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Joseph J Fins
- Division of Medical Ethics and Consortium for the Advanced Study of Brain Injury (CASBI), Weill Cornell Medical College, New York, NY, USA.,The Rockefeller University, New York, NY, USA.,Solomon Center for Health Law and Policy, Yale Law School, New Haven, CT, USA
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Boston, MA, USA
| | - Leigh R Hochberg
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA.,Veterans Affairs RR&D Center for Neurorestoration and Neurotechnology, VA Medical Center, Providence, RI, USA
| | - Ken Solt
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Emery N Brown
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA.,The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yelena G Bodien
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Boston, MA, USA
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37
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Fischer D, Threlkeld ZD, Bodien YG, Kirsch JE, Huang SY, Schaefer PW, Rapalino O, Hochberg LR, Rosen BR, Edlow BL. Intact Brain Network Function in an Unresponsive Patient with COVID-19. Ann Neurol 2020; 88:851-854. [PMID: 32613682 PMCID: PMC7361474 DOI: 10.1002/ana.25838] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 06/29/2020] [Accepted: 06/29/2020] [Indexed: 11/30/2022]
Abstract
Many patients with severe coronavirus disease 2019 (COVID‐19) remain unresponsive after surviving critical illness. Although several structural brain abnormalities have been described, their impact on brain function and implications for prognosis are unknown. Functional neuroimaging, which has prognostic significance, has yet to be explored in this population. Here we describe a patient with severe COVID‐19 who, despite prolonged unresponsiveness and structural brain abnormalities, demonstrated intact functional network connectivity, and weeks later recovered the ability to follow commands. When prognosticating for survivors of severe COVID‐19, clinicians should consider that brain networks may remain functionally intact despite structural injury and prolonged unresponsiveness. ANN NEUROL 2020;88:851–854
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Affiliation(s)
- David Fischer
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Zachary D Threlkeld
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, California, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Boston, Massachusetts, USA
| | - John E Kirsch
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Pamela W Schaefer
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,School of Engineering and Carney Institute for Brain Science, Brown University, Providence, Rhode Island, USA.,VA Rehabilitation Research and Development Service Center for Neurorestoration and Neurotechnology, Veterans Affairs Medical Center, Providence, Rhode Island, USA
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA
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38
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Burkhart MC, Brandman DM, Franco B, Hochberg LR, Harrison MT. The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models. Neural Comput 2020; 32:969-1017. [PMID: 32187000 PMCID: PMC8259355 DOI: 10.1162/neco_a_01275] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
The Kalman filter provides a simple and efficient algorithm to compute the posterior distribution for state-space models where both the latent state and measurement models are linear and gaussian. Extensions to the Kalman filter, including the extended and unscented Kalman filters, incorporate linearizations for models where the observation model p ( observation | state ) is nonlinear. We argue that in many cases, a model for p ( state | observation ) proves both easier to learn and more accurate for latent state estimation. Approximating p ( state | observation ) as gaussian leads to a new filtering algorithm, the discriminative Kalman filter (DKF), which can perform well even when p ( observation | state ) is highly nonlinear and/or nongaussian. The approximation, motivated by the Bernstein-von Mises theorem, improves as the dimensionality of the observations increases. The DKF has computational complexity similar to the Kalman filter, allowing it in some cases to perform much faster than particle filters with similar precision, while better accounting for nonlinear and nongaussian observation models than Kalman-based extensions. When the observation model must be learned from training data prior to filtering, off-the-shelf nonlinear and nonparametric regression techniques can provide a gaussian model for p ( observation | state ) that cleanly integrates with the DKF. As part of the BrainGate2 clinical trial, we successfully implemented gaussian process regression with the DKF framework in a brain-computer interface to provide real-time, closed-loop cursor control to a person with a complete spinal cord injury. In this letter, we explore the theory underlying the DKF, exhibit some illustrative examples, and outline potential extensions.
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Affiliation(s)
- Michael C Burkhart
- Division of Applied Mathematics, Brown University, Providence, RI 02912, U.S.A.
| | - David M Brandman
- Department of Neuroscience, Brown University, Providence, RI 02912, U.S.A., and Department of Surgery (Neurosurgery), Dalhousie University, Halifax, NS, B3H 4R2, Canada
| | - Brian Franco
- Center for Neurotechnology and Neurorecovery, Neurology, Massachusetts General Hospital, Boston, MA 02114, U.S.A.
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Neurology, Massachusetts General Hospital, Boston, MA 02114, U.S.A.; School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI 02912, U.S.A.; Neurology, Harvard Medical School, Boston, MA 02115, U.S.A.; and VA RR&D Center for Neurorestoration and Neurotechnology, Providence Veterans Affairs Medical Center, Providence, RI 02908, U.S.A.
| | - Matthew T Harrison
- Division of Applied Mathematics, Brown University, Providence, RI 02912, U.S.A.
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Stavisky SD, Willett FR, Avansino DT, Hochberg LR, Shenoy KV, Henderson JM. Speech-related dorsal motor cortex activity does not interfere with iBCI cursor control. J Neural Eng 2020; 17:016049. [PMID: 32023225 PMCID: PMC8288044 DOI: 10.1088/1741-2552/ab5b72] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
OBJECTIVE Speech-related neural modulation was recently reported in 'arm/hand' area of human dorsal motor cortex that is used as a signal source for intracortical brain-computer interfaces (iBCIs). This raises the concern that speech-related modulation might deleteriously affect the decoding of arm movement intentions, for instance by affecting velocity command outputs. This study sought to clarify whether or not speaking would interfere with ongoing iBCI use. APPROACH A participant in the BrainGate2 iBCI clinical trial used an iBCI to control a computer cursor; spoke short words in a stand-alone speech task; and spoke short words during ongoing iBCI use. We examined neural activity in all three behaviors and compared iBCI performance with and without concurrent speech. MAIN RESULTS Dorsal motor cortex firing rates modulated strongly during stand-alone speech, but this activity was largely attenuated when speaking occurred during iBCI cursor control using attempted arm movements. 'Decoder-potent' projections of the attenuated speech-related neural activity were small, explaining why cursor task performance was similar between iBCI use with and without concurrent speaking. SIGNIFICANCE These findings indicate that speaking does not directly interfere with iBCIs that decode attempted arm movements. This suggests that patients who are able to speak will be able to use motor cortical-driven computer interfaces or prostheses without needing to forgo speaking while using these devices.
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Affiliation(s)
- Sergey D. Stavisky
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Francis R. Willett
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | | | - Leigh R Hochberg
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Center for Neurotechnology and Neurorecovery, Dept. of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Krishna V. Shenoy
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Jaimie M. Henderson
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
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Abstract
Brain-computer interfaces (BCIs) have the potential to improve the quality of life of individuals with severe motor disabilities. BCIs capture the user's brain activity and translate it into commands for the control of an effector, such as a computer cursor, robotic limb, or functional electrical stimulation device. Full dexterous manipulation of robotic and prosthetic arms via a BCI system has been a challenge because of the inherent need to decode high dimensional and preferably real-time control commands from the user's neural activity. Nevertheless, such functionality is fundamental if BCI-controlled robotic or prosthetic limbs are to be used for daily activities. In this chapter, we review how this challenge has been addressed by BCI researchers and how new solutions may improve the BCI user experience with robotic effectors.
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Affiliation(s)
- Marco Vilela
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, United States
| | - Leigh R Hochberg
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, United States; Center for Neurorestoration and Neurotechnology, Veterans Affairs Medical Center, Providence, RI, United States; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
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41
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Stavisky SD, Willett FR, Wilson GH, Murphy BA, Rezaii P, Avansino DT, Memberg WD, Miller JP, Kirsch RF, Hochberg LR, Ajiboye AB, Druckmann S, Shenoy KV, Henderson JM. Neural ensemble dynamics in dorsal motor cortex during speech in people with paralysis. eLife 2019; 8:e46015. [PMID: 31820736 PMCID: PMC6954053 DOI: 10.7554/elife.46015] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Accepted: 11/14/2019] [Indexed: 01/20/2023] Open
Abstract
Speaking is a sensorimotor behavior whose neural basis is difficult to study with single neuron resolution due to the scarcity of human intracortical measurements. We used electrode arrays to record from the motor cortex 'hand knob' in two people with tetraplegia, an area not previously implicated in speech. Neurons modulated during speaking and during non-speaking movements of the tongue, lips, and jaw. This challenges whether the conventional model of a 'motor homunculus' division by major body regions extends to the single-neuron scale. Spoken words and syllables could be decoded from single trials, demonstrating the potential of intracortical recordings for brain-computer interfaces to restore speech. Two neural population dynamics features previously reported for arm movements were also present during speaking: a component that was mostly invariant across initiating different words, followed by rotatory dynamics during speaking. This suggests that common neural dynamical motifs may underlie movement of arm and speech articulators.
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Affiliation(s)
- Sergey D Stavisky
- Department of NeurosurgeryStanford UniversityStanfordUnited States
- Department of Electrical EngineeringStanford UniversityStanfordUnited States
| | - Francis R Willett
- Department of NeurosurgeryStanford UniversityStanfordUnited States
- Department of Electrical EngineeringStanford UniversityStanfordUnited States
| | - Guy H Wilson
- Neurosciences ProgramStanford UniversityStanfordUnited States
| | - Brian A Murphy
- Department of Biomedical EngineeringCase Western Reserve UniversityClevelandUnited States
- FES Center, Rehab R&D ServiceLouis Stokes Cleveland Department of Veterans Affairs Medical CenterClevelandUnited States
| | - Paymon Rezaii
- Department of NeurosurgeryStanford UniversityStanfordUnited States
| | | | - William D Memberg
- Department of Biomedical EngineeringCase Western Reserve UniversityClevelandUnited States
- FES Center, Rehab R&D ServiceLouis Stokes Cleveland Department of Veterans Affairs Medical CenterClevelandUnited States
| | - Jonathan P Miller
- FES Center, Rehab R&D ServiceLouis Stokes Cleveland Department of Veterans Affairs Medical CenterClevelandUnited States
- Department of NeurosurgeryUniversity Hospitals Cleveland Medical CenterClevelandUnited States
| | - Robert F Kirsch
- Department of Biomedical EngineeringCase Western Reserve UniversityClevelandUnited States
- FES Center, Rehab R&D ServiceLouis Stokes Cleveland Department of Veterans Affairs Medical CenterClevelandUnited States
| | - Leigh R Hochberg
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D ServiceProvidence VA Medical CenterProvidenceUnited States
- Center for Neurotechnology and Neurorecovery, Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonUnited States
- School of Engineering and Robert J. & Nandy D. Carney Institute for Brain ScienceBrown UniversityProvidenceUnited States
| | - A Bolu Ajiboye
- Department of Biomedical EngineeringCase Western Reserve UniversityClevelandUnited States
- FES Center, Rehab R&D ServiceLouis Stokes Cleveland Department of Veterans Affairs Medical CenterClevelandUnited States
| | - Shaul Druckmann
- Department of NeurobiologyStanford UniversityStanfordUnited States
| | - Krishna V Shenoy
- Department of Electrical EngineeringStanford UniversityStanfordUnited States
- Department of NeurobiologyStanford UniversityStanfordUnited States
- Department of BioengineeringStanford UniversityStanfordUnited States
- Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
- Wu Tsai Neurosciences InstituteStanford UniversityStanfordUnited States
- Bio-X ProgramStanford UniversityStanfordUnited States
| | - Jaimie M Henderson
- Department of NeurosurgeryStanford UniversityStanfordUnited States
- Wu Tsai Neurosciences InstituteStanford UniversityStanfordUnited States
- Bio-X ProgramStanford UniversityStanfordUnited States
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Lin DJ, Cloutier AM, Erler KS, Cassidy JM, Snider SB, Ranford J, Parlman K, Giatsidis F, Burke JF, Schwamm LH, Finklestein SP, Hochberg LR, Cramer SC. Corticospinal Tract Injury Estimated From Acute Stroke Imaging Predicts Upper Extremity Motor Recovery After Stroke. Stroke 2019; 50:3569-3577. [PMID: 31648631 DOI: 10.1161/strokeaha.119.025898] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background and Purpose- Injury to the corticospinal tract (CST) has been shown to have a major effect on upper extremity motor recovery after stroke. This study aimed to examine how well CST injury, measured from neuroimaging acquired during the acute stroke workup, predicts upper extremity motor recovery. Methods- Patients with upper extremity weakness after ischemic stroke were assessed using the upper extremity Fugl-Meyer during the acute stroke hospitalization and again at 3-month follow-up. CST injury was quantified and compared, using 4 different methods, from images obtained as part of the stroke standard-of-care workup. Logistic and linear regression were performed using CST injury to predict ΔFugl-Meyer. Injury to primary motor and premotor cortices were included as potential modifiers of the effect of CST injury on recovery. Results- N=48 patients were enrolled 4.2±2.7 days poststroke and completed 3-month follow-up (median 90-day modified Rankin Scale score, 3; interquartile range, 1.5). CST injury distinguished patients who reached their recovery potential (as predicted from initial impairment) from those who did not, with area under the curve values ranging from 0.70 to 0.8. In addition, CST injury explained ≈20% of the variance in the magnitude of upper extremity recovery, even after controlling for the severity of initial impairment. Results were consistent when comparing 4 different methods of measuring CST injury. Extent of injury to primary motor and premotor cortices did not significantly influence the predictive value that CST injury had for recovery. Conclusions- Structural injury to the CST, as estimated from standard-of-care imaging available during the acute stroke hospitalization, is a robust way to distinguish patients who achieve their predicted recovery potential and explains a significant amount of the variance in poststroke upper extremity motor recovery.
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Affiliation(s)
- David J Lin
- From the Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (D.J.L., A.M.C., F.G., L.R.H.).,Division of Neurocritical Care and Emergency Neurology, Department of Neurology (D.J.L., S.B.S., L.R.H.), Massachusetts General Hospital, Boston
| | - Alison M Cloutier
- From the Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (D.J.L., A.M.C., F.G., L.R.H.)
| | - Kimberly S Erler
- Department of Occupational Therapy, MGH Institute of Health Professions, Boston, MA (K.S.E.)
| | - Jessica M Cassidy
- Division of Physical Therapy, Department of Allied Health Sciences, University of North Carolina at Chapel Hill (J.M.C.)
| | - Samuel B Snider
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology (D.J.L., S.B.S., L.R.H.), Massachusetts General Hospital, Boston
| | - Jessica Ranford
- Department of Occupational Therapy (J.R.), Massachusetts General Hospital, Boston
| | - Kristin Parlman
- Department of Physical Therapy (K.P.), Massachusetts General Hospital, Boston
| | - Fabio Giatsidis
- From the Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (D.J.L., A.M.C., F.G., L.R.H.).,Department of Neurology, University of Rome Tor Vergata, Italy (F.G.)
| | - James F Burke
- Department of Neurology, University of Michigan, Ann Arbor (J.F.B.)
| | - Lee H Schwamm
- Stroke Service, Department of Neurology (L.H.S., S.P.F.), Massachusetts General Hospital, Boston
| | - Seth P Finklestein
- Stroke Service, Department of Neurology (L.H.S., S.P.F.), Massachusetts General Hospital, Boston
| | - Leigh R Hochberg
- From the Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (D.J.L., A.M.C., F.G., L.R.H.).,Division of Neurocritical Care and Emergency Neurology, Department of Neurology (D.J.L., S.B.S., L.R.H.), Massachusetts General Hospital, Boston.,VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, VA Medical Center, Providence, RI (L.R.H.).,School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI (L.R.H.)
| | - Steven C Cramer
- Department of Neurology, University of California, Irvine (S.C.C.)
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43
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Brandman DM, Hosman T, Saab J, Burkhart MC, Shanahan BE, Ciancibello JG, Sarma AA, Milstein DJ, Vargas-Irwin CE, Franco B, Kelemen J, Blabe C, Murphy BA, Young DR, Willett FR, Pandarinath C, Stavisky SD, Kirsch RF, Walter BL, Bolu Ajiboye A, Cash SS, Eskandar EN, Miller JP, Sweet JA, Shenoy KV, Henderson JM, Jarosiewicz B, Harrison MT, Simeral JD, Hochberg LR. Rapid calibration of an intracortical brain-computer interface for people with tetraplegia. J Neural Eng 2019; 15:026007. [PMID: 29363625 DOI: 10.1088/1741-2552/aa9ee7] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Brain-computer interfaces (BCIs) can enable individuals with tetraplegia to communicate and control external devices. Though much progress has been made in improving the speed and robustness of neural control provided by intracortical BCIs, little research has been devoted to minimizing the amount of time spent on decoder calibration. APPROACH We investigated the amount of time users needed to calibrate decoders and achieve performance saturation using two markedly different decoding algorithms: the steady-state Kalman filter, and a novel technique using Gaussian process regression (GP-DKF). MAIN RESULTS Three people with tetraplegia gained rapid closed-loop neural cursor control and peak, plateaued decoder performance within 3 min of initializing calibration. We also show that a BCI-naïve user (T5) was able to rapidly attain closed-loop neural cursor control with the GP-DKF using self-selected movement imagery on his first-ever day of closed-loop BCI use, acquiring a target 37 s after initiating calibration. SIGNIFICANCE These results demonstrate the potential for an intracortical BCI to be used immediately after deployment by people with paralysis, without the need for user learning or extensive system calibration.
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Affiliation(s)
- David M Brandman
- Neuroscience Graduate Program, Brown University, Providence, RI, United States of America. Department of Neuroscience, Brown University, Providence, RI, United States of America. Brown Institute for Brain Science, Brown University, Providence, RI, United States of America. Department of Surgery (Neurosurgery), Dalhousie University, Halifax, NS, Canada
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44
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Young D, Willett F, Memberg WD, Murphy B, Walter B, Sweet J, Miller J, Hochberg LR, Kirsch RF, Ajiboye AB. Signal processing methods for reducing artifacts in microelectrode brain recordings caused by functional electrical stimulation. J Neural Eng 2019; 15:026014. [PMID: 29199642 DOI: 10.1088/1741-2552/aa9ee8] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE Functional electrical stimulation (FES) is a promising technology for restoring movement to paralyzed limbs. Intracortical brain-computer interfaces (iBCIs) have enabled intuitive control over virtual and robotic movements, and more recently over upper extremity FES neuroprostheses. However, electrical stimulation of muscles creates artifacts in intracortical microelectrode recordings that could degrade iBCI performance. Here, we investigate methods for reducing the cortically recorded artifacts that result from peripheral electrical stimulation. APPROACH One participant in the BrainGate2 pilot clinical trial had two intracortical microelectrode arrays placed in the motor cortex, and thirty-six stimulating intramuscular electrodes placed in the muscles of the contralateral limb. We characterized intracortically recorded electrical artifacts during both intramuscular and surface stimulation. We compared the performance of three artifact reduction methods: blanking, common average reference (CAR) and linear regression reference (LRR), which creates channel-specific reference signals, composed of weighted sums of other channels. MAIN RESULTS Electrical artifacts resulting from surface stimulation were 175 × larger than baseline neural recordings (which were 110 µV peak-to-peak), while intramuscular stimulation artifacts were only 4 × larger. The artifact waveforms were highly consistent across electrodes within each array. Application of LRR reduced artifact magnitudes to less than 10 µV and largely preserved the original neural feature values used for decoding. Unmitigated stimulation artifacts decreased iBCI decoding performance, but performance was almost completely recovered using LRR, which outperformed CAR and blanking and extracted useful neural information during stimulation artifact periods. SIGNIFICANCE The LRR method was effective at reducing electrical artifacts resulting from both intramuscular and surface FES, and almost completely restored iBCI decoding performance (>90% recovery for surface stimulation and full recovery for intramuscular stimulation). The results demonstrate that FES-induced artifacts can be easily mitigated in FES + iBCI systems by using LRR for artifact reduction, and suggest that the LRR method may also be useful in other noise reduction applications.
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Affiliation(s)
- D Young
- Case Western Reserve University, Cleveland, OH, United States of America. Department of VA Medical Center, FES Center of Excellence, Rehabilitation R&D Service, Louis Stokes Cleveland, Cleveland, OH, United States of America
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45
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Stavisky SD, Rezaii P, Willett FR, Hochberg LR, Shenoy KV, Henderson JM. Decoding Speech from Intracortical Multielectrode Arrays in Dorsal "Arm/Hand Areas" of Human Motor Cortex. Annu Int Conf IEEE Eng Med Biol Soc 2019; 2018:93-97. [PMID: 30440349 DOI: 10.1109/embc.2018.8512199] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Neural prostheses are being developed to restore speech to people with neurological injury or disease. A key design consideration is where and how to access neural correlates of intended speech. Most prior work has examined cortical field potentials at a coarse resolution using electroencephalography (EEG) or medium resolution using electrocorticography (ECoG). The few studies of speech with single-neuron resolution recorded from ventral areas known to be part of the speech network. Here, we recorded from two 96- electrode arrays chronically implanted into the 'hand knob' area of motor cortex while a person with tetraplegia spoke. Despite being located in an area previously demonstrated to modulate during attempted arm movements, many electrodes' neuronal firing rates responded to speech production. In offline analyses, we could classify which of 9 phonemes (plus silence) was spoken with 81% single-trial accuracy using a combination of spike rate and local field potential (LFP) power. This suggests that high-fidelity speech prostheses may be possible using large-scale intracortical recordings in motor cortical areas involved in controlling speech articulators.
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Proix T, Aghagolzadeh M, Madsen JR, Cosgrove R, Eskandar E, Hochberg LR, Cash SS, Truccolo W. Intracortical neural activity distal to seizure-onset-areas predicts human focal seizures. PLoS One 2019; 14:e0211847. [PMID: 31329587 PMCID: PMC6645464 DOI: 10.1371/journal.pone.0211847] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 07/04/2019] [Indexed: 01/19/2023] Open
Abstract
The apparent unpredictability of epileptic seizures has a major impact in the quality of life of people with pharmacologically resistant seizures. Here, we present initial results and a proof-of-concept of how focal seizures can be predicted early in advance based on intracortical signals recorded from small neocortical patches away from identified seizure onset areas. We show that machine learning algorithms can discriminate between interictal and preictal periods based on multiunit activity (i.e. thresholded action potential counts) and multi-frequency band local field potentials recorded via 4 X 4 mm2 microelectrode arrays. Microelectrode arrays were implanted in 5 patients undergoing neuromonitoring for resective surgery. Post-implant analysis revealed arrays were outside the seizure onset areas. Preictal periods were defined as the 1-hour period leading to a seizure. A 5-minute gap between the preictal period and the putative seizure onset was enforced to account for potential errors in the determination of actual seizure onset times. We used extreme gradient boosting and long short-term memory networks for prediction. Prediction accuracy based on the area under the receiver operating characteristic curves reached 90% for at least one feature type in each patient. Importantly, successful prediction could be achieved based exclusively on multiunit activity. This result indicates that preictal activity in the recorded neocortical patches involved not only subthreshold postsynaptic potentials, perhaps driven by the distal seizure onset areas, but also neuronal spiking in distal recurrent neocortical networks. Beyond the commonly identified seizure onset areas, our findings point to the engagement of large-scale neuronal networks in the neural dynamics building up toward a seizure. Our initial results obtained on currently available human intracortical microelectrode array recordings warrant new studies on larger datasets, and open new perspectives for seizure prediction and control by emphasizing the contribution of multiscale neural signals in large-scale neuronal networks.
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Affiliation(s)
- Timothée Proix
- Department of Neuroscience, Brown University, Providence, Rhode Island, United States of America
- Carney Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America
- Center for Neurorestoration & Neurotechnology, U.S. Department of Veterans Affairs, Providence, Rhode Island, United States of America
| | - Mehdi Aghagolzadeh
- Department of Neuroscience, Brown University, Providence, Rhode Island, United States of America
- Carney Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America
- Center for Neurorestoration & Neurotechnology, U.S. Department of Veterans Affairs, Providence, Rhode Island, United States of America
| | - Joseph R. Madsen
- Department of Neurosurgery, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Rees Cosgrove
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Emad Eskandar
- Department of Neurosurgery and Nayef Al-Rodhan Laboratories for Cellular Neurosurgery and Neurosurgical Technology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Leigh R. Hochberg
- Carney Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America
- Center for Neurorestoration & Neurotechnology, U.S. Department of Veterans Affairs, Providence, Rhode Island, United States of America
- School of Engineering, Brown University, Providence, Rhode Island, United States of America
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Sydney S. Cash
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Wilson Truccolo
- Department of Neuroscience, Brown University, Providence, Rhode Island, United States of America
- Carney Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America
- Center for Neurorestoration & Neurotechnology, U.S. Department of Veterans Affairs, Providence, Rhode Island, United States of America
- * E-mail:
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47
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Willett FR, Young DR, Murphy BA, Memberg WD, Blabe CH, Pandarinath C, Stavisky SD, Rezaii P, Saab J, Walter BL, Sweet JA, Miller JP, Henderson JM, Shenoy KV, Simeral JD, Jarosiewicz B, Hochberg LR, Kirsch RF, Bolu Ajiboye A. Principled BCI Decoder Design and Parameter Selection Using a Feedback Control Model. Sci Rep 2019; 9:8881. [PMID: 31222030 PMCID: PMC6586941 DOI: 10.1038/s41598-019-44166-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Accepted: 03/04/2019] [Indexed: 02/01/2023] Open
Abstract
Decoders optimized offline to reconstruct intended movements from neural recordings sometimes fail to achieve optimal performance online when they are used in closed-loop as part of an intracortical brain-computer interface (iBCI). This is because typical decoder calibration routines do not model the emergent interactions between the decoder, the user, and the task parameters (e.g. target size). Here, we investigated the feasibility of simulating online performance to better guide decoder parameter selection and design. Three participants in the BrainGate2 pilot clinical trial controlled a computer cursor using a linear velocity decoder under different gain (speed scaling) and temporal smoothing parameters and acquired targets with different radii and distances. We show that a user-specific iBCI feedback control model can predict how performance changes under these different decoder and task parameters in held-out data. We also used the model to optimize a nonlinear speed scaling function for the decoder. When used online with two participants, it increased the dynamic range of decoded speeds and decreased the time taken to acquire targets (compared to an optimized standard decoder). These results suggest that it is feasible to simulate iBCI performance accurately enough to be useful for quantitative decoder optimization and design.
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Affiliation(s)
- Francis R Willett
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA. .,Louis Stokes Cleveland Department of Veterans Affairs Medical Center, FES Center of Excellence, Rehab. R&D Service, Cleveland, Ohio, USA. .,Department of Neurosurgery, Stanford University, Stanford, California, USA. .,Department of Electrical Engineering, Stanford University, Stanford, California, USA.
| | - Daniel R Young
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Louis Stokes Cleveland Department of Veterans Affairs Medical Center, FES Center of Excellence, Rehab. R&D Service, Cleveland, Ohio, USA
| | - Brian A Murphy
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Louis Stokes Cleveland Department of Veterans Affairs Medical Center, FES Center of Excellence, Rehab. R&D Service, Cleveland, Ohio, USA
| | - William D Memberg
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Louis Stokes Cleveland Department of Veterans Affairs Medical Center, FES Center of Excellence, Rehab. R&D Service, Cleveland, Ohio, USA
| | - Christine H Blabe
- Department of Neurosurgery, Stanford University, Stanford, California, USA
| | - Chethan Pandarinath
- Department of Neurosurgery, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Sergey D Stavisky
- Department of Neurosurgery, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Paymon Rezaii
- Department of Neurosurgery, Stanford University, Stanford, California, USA
| | - Jad Saab
- School of Engineering, Brown University, Providence, RI, USA.,Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI, USA
| | - Benjamin L Walter
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, FES Center of Excellence, Rehab. R&D Service, Cleveland, Ohio, USA.,Department of Neurology, University Hospitals Case Medical Center, Cleveland, Ohio, USA
| | - Jennifer A Sweet
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, FES Center of Excellence, Rehab. R&D Service, Cleveland, Ohio, USA.,Department of Neurosurgery, University Hospitals Case Medical Center, Cleveland, Ohio, USA
| | - Jonathan P Miller
- Louis Stokes Cleveland Department of Veterans Affairs Medical Center, FES Center of Excellence, Rehab. R&D Service, Cleveland, Ohio, USA.,Department of Neurosurgery, University Hospitals Case Medical Center, Cleveland, Ohio, USA
| | - Jaimie M Henderson
- Department of Neurosurgery, Stanford University, Stanford, California, USA.,Stanford Neurosciences Institute, Stanford University, Stanford, 94305, California, USA
| | - Krishna V Shenoy
- Department of Electrical Engineering, Stanford University, Stanford, California, USA.,Stanford Neurosciences Institute, Stanford University, Stanford, 94305, California, USA.,Department of Bioengineering, Stanford University, Stanford, California, 94305, USA.,Department of Neurobiology, Stanford University, Stanford, California, 94305, USA.,Howard Hughes Medical Institute, Stanford University, Stanford, California, 94305, USA.,Neurosciences Program, Stanford University, Stanford, California, 94305, USA.,Bio-X Program, Stanford University, Stanford, California, 94305, USA
| | - John D Simeral
- School of Engineering, Brown University, Providence, RI, USA.,Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI, USA.,Carney Institute for Brain Science, Brown University, Providence, Rhode Island, USA.,Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Beata Jarosiewicz
- Department of Neurosurgery, Stanford University, Stanford, California, USA
| | - Leigh R Hochberg
- School of Engineering, Brown University, Providence, RI, USA.,Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Department of Veterans Affairs Medical Center, Providence, RI, USA.,Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Department of Neurology, Harvard Medical School, Boston, Massachusetts, USA
| | - Robert F Kirsch
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Louis Stokes Cleveland Department of Veterans Affairs Medical Center, FES Center of Excellence, Rehab. R&D Service, Cleveland, Ohio, USA
| | - A Bolu Ajiboye
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Louis Stokes Cleveland Department of Veterans Affairs Medical Center, FES Center of Excellence, Rehab. R&D Service, Cleveland, Ohio, USA
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48
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Park YS, Cosgrove GR, Madsen JR, Eskandar EN, Hochberg LR, Cash SS, Truccolo W. Early Detection of Human Epileptic Seizures Based on Intracortical Microelectrode Array Signals. IEEE Trans Biomed Eng 2019; 67:817-831. [PMID: 31180831 DOI: 10.1109/tbme.2019.2921448] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
OBJECTIVE We examine, for the first time, the use of intracortical microelectrode array (MEA) signals for early detection of human epileptic seizures. METHODS 4×4 mm2 96-channel-MEA recordings were obtained during neuro-monitoring preceding resective surgery in five participants. The participant-specific seizure-detection framework consisted of: first, feature extraction from local field potentials (LFPs) and multiunit activity (MUA); second, nonlinear cost-sensitive support vector machine (SVM) classification of ictal and interictal states based on LFP, MUA, and combined LFP-MUA (a SVM was trained for each participant separately); and third, Kalman filter postprocessing of SVM scoring functions. Performance was assessed on data including 17 seizures and 39.0 h interictal and preictal recordings. RESULTS The use of combined LFP-MUA features resulted in 100% sensitivity with short detection latency (average: 2.7 s; median: 2.5 s) and five false alarms (0.13/h). The average detection performance based on the area under the receiver operating characteristic corresponded to 0.97. Importantly, technically false alarms were related to epileptiform activity, subclinical seizures, and recording artifacts. Extreme gradient boosting classifiers ranked features based on LFP spectral coherence or MUA count among the top features for seizures characterized by spike-wave complexes, whereas features related to LFP power spectra were ranked higher for seizures characterized by sustained gamma LFP oscillations. CONCLUSION The combination of intracortical LFP and MUA signals may allow reliable detection of human epileptic seizures by improving latency and false alarm rate. SIGNIFICANCE Intracortical MEAs provide promising signals for closed-loop seizure-control systems based on seizure early-detection in people with pharmacologically resistant epilepsies.
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49
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Milekovic T, Bacher D, Sarma AA, Simeral JD, Saab J, Pandarinath C, Yvert B, Sorice BL, Blabe C, Oakley EM, Tringale KR, Eskandar E, Cash SS, Shenoy KV, Henderson JM, Hochberg LR, Donoghue JP. Volitional control of single-electrode high gamma local field potentials by people with paralysis. J Neurophysiol 2019; 121:1428-1450. [PMID: 30785814 DOI: 10.1152/jn.00131.2018] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Intracortical brain-computer interfaces (BCIs) can enable individuals to control effectors, such as a computer cursor, by directly decoding the user's movement intentions from action potentials and local field potentials (LFPs) recorded within the motor cortex. However, the accuracy and complexity of effector control achieved with such "biomimetic" BCIs will depend on the degree to which the intended movements used to elicit control modulate the neural activity. In particular, channels that do not record distinguishable action potentials and only record LFP modulations may be of limited use for BCI control. In contrast, a biofeedback approach may surpass these limitations by letting the participants generate new control signals and learn strategies that improve the volitional control of signals used for effector control. Here, we show that, by using a biofeedback paradigm, three individuals with tetraplegia achieved volitional control of gamma LFPs (40-400 Hz) recorded by a single microelectrode implanted in the precentral gyrus. Control was improved over a pair of consecutive sessions up to 3 days apart. In all but one session, the channel used to achieve control lacked distinguishable action potentials. Our results indicate that biofeedback LFP-based BCIs may potentially contribute to the neural modulation necessary to obtain reliable and useful control of effectors. NEW & NOTEWORTHY Our study demonstrates that people with tetraplegia can volitionally control individual high-gamma local-field potential (LFP) channels recorded from the motor cortex, and that this control can be improved using biofeedback. Motor cortical LFP signals are thought to be both informative and stable intracortical signals and, thus, of importance for future brain-computer interfaces.
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Affiliation(s)
- Tomislav Milekovic
- Department of Neuroscience, Brown University , Providence, Rhode Island.,Carney Institute for Brain Science, Brown University , Providence, Rhode Island.,Department of Fundamental Neuroscience, Faculty of Medicine, University of Geneva , Geneva , Switzerland
| | - Daniel Bacher
- Carney Institute for Brain Science, Brown University , Providence, Rhode Island.,School of Engineering, Brown University , Providence, Rhode Island
| | - Anish A Sarma
- Carney Institute for Brain Science, Brown University , Providence, Rhode Island.,School of Engineering, Brown University , Providence, Rhode Island.,Center for Neurorestoration and Neurotechnology, Rehabilitation Research & Development Service, Department of Veterans Affairs , Providence, Rhode Island
| | - John D Simeral
- Carney Institute for Brain Science, Brown University , Providence, Rhode Island.,School of Engineering, Brown University , Providence, Rhode Island.,Center for Neurorestoration and Neurotechnology, Rehabilitation Research & Development Service, Department of Veterans Affairs , Providence, Rhode Island
| | - Jad Saab
- Carney Institute for Brain Science, Brown University , Providence, Rhode Island.,School of Engineering, Brown University , Providence, Rhode Island
| | - Chethan Pandarinath
- Department of Neurosurgery, Stanford University , Stanford, California.,Department of Electrical Engineering, Stanford University , Stanford, California.,Stanford Neurosciences Institute, Stanford University , Stanford, California
| | - Blaise Yvert
- Department of Neuroscience, Brown University , Providence, Rhode Island.,Carney Institute for Brain Science, Brown University , Providence, Rhode Island.,Inserm, University of Grenoble, Clinatec-Lab U1205, Grenoble , France
| | - Brittany L Sorice
- Department of Neurology, Massachusetts General Hospital , Boston, Massachusetts
| | - Christine Blabe
- Department of Neurosurgery, Stanford University , Stanford, California
| | - Erin M Oakley
- Department of Neurology, Massachusetts General Hospital , Boston, Massachusetts
| | - Kathryn R Tringale
- Department of Neurology, Massachusetts General Hospital , Boston, Massachusetts
| | - Emad Eskandar
- Department of Neurosurgery, Massachusetts General Hospital , Boston, Massachusetts.,Harvard Medical School , Boston, Massachusetts
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital , Boston, Massachusetts.,Harvard Medical School , Boston, Massachusetts
| | - Krishna V Shenoy
- Department of Electrical Engineering, Stanford University , Stanford, California.,Stanford Neurosciences Institute, Stanford University , Stanford, California.,Neurosciences Program, Stanford University , Stanford, California.,Department of Neurobiology, Stanford University , Stanford, California.,Department of Bioengineering, Stanford University , Stanford, California
| | - Jaimie M Henderson
- Department of Neurosurgery, Stanford University , Stanford, California.,Stanford Neurosciences Institute, Stanford University , Stanford, California.,Department of Neurology and Neurological Sciences, Stanford University , Stanford, California
| | - Leigh R Hochberg
- Carney Institute for Brain Science, Brown University , Providence, Rhode Island.,School of Engineering, Brown University , Providence, Rhode Island.,Center for Neurorestoration and Neurotechnology, Rehabilitation Research & Development Service, Department of Veterans Affairs , Providence, Rhode Island.,Department of Neurology, Massachusetts General Hospital , Boston, Massachusetts.,Harvard Medical School , Boston, Massachusetts
| | - John P Donoghue
- Department of Neuroscience, Brown University , Providence, Rhode Island.,Carney Institute for Brain Science, Brown University , Providence, Rhode Island.,Center for Neurorestoration and Neurotechnology, Rehabilitation Research & Development Service, Department of Veterans Affairs , Providence, Rhode Island
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50
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Regenhardt RW, Lin DJ, Snider S, Cloutier A, Giatsidis F, Ranford JA, Parlman K, Clark J, Macdonald KS, Finklestein SP, Rosand J, Hochberg LR. Abstract TP363: Early Changes in Stroke Severity: Characterization and Impact on Patient-Centered Stroke Outcomes. Stroke 2019. [DOI: 10.1161/str.50.suppl_1.tp363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
Early changes in NIH stroke scale (NIHSS) within the first days after ischemic stroke have been associated with clinical outcomes, however association with patient-centered outcomes is unknown. Predicting outcomes is important for decisions after the acute period. We sought to characterize the magnitude of early NIHSS change and identify its impact on 90-day Stroke Impact Scale-16 (SIS).
Methods:
Data were collected as part of an ongoing single-center study of recovery for patients with upper extremity weakness. NIHSS at time of presentation (presentation NIHSS) was obtained by chart review and NIHSS at time of enrollment (enrollment NIHSS) was assessed prior to acute hospital discharge. We collected demographic, treatment, imaging, and 90-day outcomes. We used a linear regression to determine the relationship of early NIHSS improvement (presentation-enrollment NIHSS) with 90-day SIS and dichotomized the dataset (early NIHSS improvement ≥3 vs not) to compare predefined clinical variables hypothesized to be early improvement predictors.
Results:
Study participants (n=72) had median presentation NIHSS of 6 (IQR4-13) and median enrollment NIHSS of 6 (IQR4-10) with a mean of 2.7+/-2.5 days between timepoints. Seventeen subjects improved by ≥3 and 16 worsened by ≥3. Acute treatments were endovascular therapy (ET, n=10) and thrombolysis (tPA, n=16). Early NIHSS improvement was associated with better 90-day SIS (p=0.012). This association remained when subjects who underwent ET or tPA were excluded (p=0.046). Subjects with early NIHSS improvement ≥3 were less likely to have hypertension (15 vs 85%, p=0.039) and more likely to have undergone ET (60 vs 40%, p=0.010), but there were no differences in tPA treatment, infarct volume, days between timepoints, age, or other medical history.
Conclusion:
This analysis confirms that there are substantial changes in NIHSS in the first days after stroke. Early NIHSS improvement was associated with better 90-day SIS, even when excluding subjects who underwent treatment with ET or tPA suggesting this association also exists for subjects with spontaneous improvement. Early NIHSS improvement may be a useful prognostic tool for patient-centered outcomes after stroke.
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Affiliation(s)
| | - David J Lin
- Neurology, Massachusetts General Hosp, Boston, MA
| | | | | | | | | | | | - Judy Clark
- Neurology, Massachusetts General Hosp, Boston, MA
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