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Angrick M, Luo S, Rabbani Q, Candrea DN, Shah S, Milsap GW, Anderson WS, Gordon CR, Rosenblatt KR, Clawson L, Tippett DC, Maragakis N, Tenore FV, Fifer MS, Hermansky H, Ramsey NF, Crone NE. Online speech synthesis using a chronically implanted brain-computer interface in an individual with ALS. Sci Rep 2024; 14:9617. [PMID: 38671062 PMCID: PMC11053081 DOI: 10.1038/s41598-024-60277-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 04/21/2024] [Indexed: 04/28/2024] Open
Abstract
Brain-computer interfaces (BCIs) that reconstruct and synthesize speech using brain activity recorded with intracranial electrodes may pave the way toward novel communication interfaces for people who have lost their ability to speak, or who are at high risk of losing this ability, due to neurological disorders. Here, we report online synthesis of intelligible words using a chronically implanted brain-computer interface (BCI) in a man with impaired articulation due to ALS, participating in a clinical trial (ClinicalTrials.gov, NCT03567213) exploring different strategies for BCI communication. The 3-stage approach reported here relies on recurrent neural networks to identify, decode and synthesize speech from electrocorticographic (ECoG) signals acquired across motor, premotor and somatosensory cortices. We demonstrate a reliable BCI that synthesizes commands freely chosen and spoken by the participant from a vocabulary of 6 keywords previously used for decoding commands to control a communication board. Evaluation of the intelligibility of the synthesized speech indicates that 80% of the words can be correctly recognized by human listeners. Our results show that a speech-impaired individual with ALS can use a chronically implanted BCI to reliably produce synthesized words while preserving the participant's voice profile, and provide further evidence for the stability of ECoG for speech-based BCIs.
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Affiliation(s)
- Miguel Angrick
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Shiyu Luo
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qinwan Rabbani
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA
| | - Daniel N Candrea
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Samyak Shah
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Griffin W Milsap
- Research and Exploratory Development Department, Johns Hopkins Applied Physics Laboratory, Laurel, MD, USA
| | - William S Anderson
- Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chad R Gordon
- Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Section of Neuroplastic and Reconstructive Surgery, Department of Plastic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kathryn R Rosenblatt
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Anesthesiology & Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Lora Clawson
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Donna C Tippett
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Otolaryngology-Head and Neck Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nicholas Maragakis
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Francesco V Tenore
- Research and Exploratory Development Department, Johns Hopkins Applied Physics Laboratory, Laurel, MD, USA
| | - Matthew S Fifer
- Research and Exploratory Development Department, Johns Hopkins Applied Physics Laboratory, Laurel, MD, USA
| | - Hynek Hermansky
- Center for Language and Speech Processing, The Johns Hopkins University, Baltimore, MD, USA
- Human Language Technology Center of Excellence, The Johns Hopkins University, Baltimore, MD, USA
| | - Nick F Ramsey
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Nathan E Crone
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Luo S, Angrick M, Coogan C, Candrea DN, Wyse‐Sookoo K, Shah S, Rabbani Q, Milsap GW, Weiss AR, Anderson WS, Tippett DC, Maragakis NJ, Clawson LL, Vansteensel MJ, Wester BA, Tenore FV, Hermansky H, Fifer MS, Ramsey NF, Crone NE. Stable Decoding from a Speech BCI Enables Control for an Individual with ALS without Recalibration for 3 Months. Adv Sci (Weinh) 2023; 10:e2304853. [PMID: 37875404 PMCID: PMC10724434 DOI: 10.1002/advs.202304853] [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] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 09/18/2023] [Indexed: 10/26/2023]
Abstract
Brain-computer interfaces (BCIs) can be used to control assistive devices by patients with neurological disorders like amyotrophic lateral sclerosis (ALS) that limit speech and movement. For assistive control, it is desirable for BCI systems to be accurate and reliable, preferably with minimal setup time. In this study, a participant with severe dysarthria due to ALS operates computer applications with six intuitive speech commands via a chronic electrocorticographic (ECoG) implant over the ventral sensorimotor cortex. Speech commands are accurately detected and decoded (median accuracy: 90.59%) throughout a 3-month study period without model retraining or recalibration. Use of the BCI does not require exogenous timing cues, enabling the participant to issue self-paced commands at will. These results demonstrate that a chronically implanted ECoG-based speech BCI can reliably control assistive devices over long time periods with only initial model training and calibration, supporting the feasibility of unassisted home use.
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Affiliation(s)
- Shiyu Luo
- Department of Biomedical EngineeringJohns Hopkins University School of MedicineBaltimoreMD21205USA
| | - Miguel Angrick
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMD21287USA
| | - Christopher Coogan
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMD21287USA
| | - Daniel N. Candrea
- Department of Biomedical EngineeringJohns Hopkins University School of MedicineBaltimoreMD21205USA
| | - Kimberley Wyse‐Sookoo
- Department of Biomedical EngineeringJohns Hopkins University School of MedicineBaltimoreMD21205USA
| | - Samyak Shah
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMD21287USA
| | - Qinwan Rabbani
- Department of Electrical and Computer EngineeringJohns Hopkins UniversityBaltimoreMD21218USA
- Center for Language and Speech ProcessingJohns Hopkins UniversityBaltimoreMD21218USA
| | - Griffin W. Milsap
- Research and Exploratory Development DepartmentJohns Hopkins University Applied Physics LaboratoryLaurelMD20723USA
| | - Alexander R. Weiss
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMD21287USA
| | - William S. Anderson
- Department of NeurosurgeryJohns Hopkins University School of MedicineBaltimoreMD21205USA
| | - Donna C. Tippett
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMD21287USA
- Department of Otolaryngology‐Head and Neck SurgeryJohns Hopkins University School of MedicineBaltimoreMD21205USA
- Department of Physical Medicine and RehabilitationJohns Hopkins University School of MedicineBaltimoreMD21205USA
| | - Nicholas J. Maragakis
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMD21287USA
| | - Lora L. Clawson
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMD21287USA
| | - Mariska J. Vansteensel
- Department of Neurology and NeurosurgeryUMC Utrecht Brain CenterUtrecht3584The Netherlands
| | - Brock A. Wester
- Research and Exploratory Development DepartmentJohns Hopkins University Applied Physics LaboratoryLaurelMD20723USA
| | - Francesco V. Tenore
- Research and Exploratory Development DepartmentJohns Hopkins University Applied Physics LaboratoryLaurelMD20723USA
| | - Hynek Hermansky
- Department of Electrical and Computer EngineeringJohns Hopkins UniversityBaltimoreMD21218USA
- Center for Language and Speech ProcessingJohns Hopkins UniversityBaltimoreMD21218USA
| | - Matthew S. Fifer
- Research and Exploratory Development DepartmentJohns Hopkins University Applied Physics LaboratoryLaurelMD20723USA
| | - Nick F. Ramsey
- Department of Neurology and NeurosurgeryUMC Utrecht Brain CenterUtrecht3584The Netherlands
| | - Nathan E. Crone
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMD21287USA
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Peterson V, Vissani M, Luo S, Rabbani Q, Crone NE, Bush A, Mark Richardson R. A supervised data-driven spatial filter denoising method for speech artifacts in intracranial electrophysiological recordings. bioRxiv 2023:2023.04.05.535577. [PMID: 37066306 PMCID: PMC10104030 DOI: 10.1101/2023.04.05.535577] [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] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Neurosurgical procedures that enable direct brain recordings in awake patients offer unique opportunities to explore the neurophysiology of human speech. The scarcity of these opportunities and the altruism of participating patients compel us to apply the highest rigor to signal analysis. Intracranial electroencephalography (iEEG) signals recorded during overt speech can contain a speech artifact that tracks the fundamental frequency (F0) of the participant's voice, involving the same high-gamma frequencies that are modulated during speech production and perception. To address this artifact, we developed a spatial-filtering approach to identify and remove acoustic-induced contaminations of the recorded signal. We found that traditional reference schemes jeopardized signal quality, whereas our data-driven method denoised the recordings while preserving underlying neural activity.
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Affiliation(s)
- Victoria Peterson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, United States
- Instituto de Matemática Aplicada del Litoral, IMAL, FIQ-UNL, CONICET, Santa Fe, Argentina
| | - Matteo Vissani
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Shiyu Luo
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine
| | - Qinwan Rabbani
- Department of Electrical & Computer Engineering, The Johns Hopkins University
| | - Nathan E. Crone
- Department of Neurology, The Johns Hopkins University School of Medicine
| | - Alan Bush
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - R. Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, United States
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
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Ramsey NF, Crone NE. Brain implants that enable speech pass performance milestones. Nature 2023; 620:954-955. [PMID: 37612488 DOI: 10.1038/d41586-023-02546-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
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Angrick M, Luo S, Rabbani Q, Candrea DN, Shah S, Milsap GW, Anderson WS, Gordon CR, Rosenblatt KR, Clawson L, Maragakis N, Tenore FV, Fifer MS, Hermansky H, Ramsey NF, Crone NE. Online speech synthesis using a chronically implanted brain-computer interface in an individual with ALS. medRxiv 2023:2023.06.30.23291352. [PMID: 37425721 PMCID: PMC10327279 DOI: 10.1101/2023.06.30.23291352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Recent studies have shown that speech can be reconstructed and synthesized using only brain activity recorded with intracranial electrodes, but until now this has only been done using retrospective analyses of recordings from able-bodied patients temporarily implanted with electrodes for epilepsy surgery. Here, we report online synthesis of intelligible words using a chronically implanted brain-computer interface (BCI) in a clinical trial participant (ClinicalTrials.gov, NCT03567213) with dysarthria due to amyotrophic lateral sclerosis (ALS). We demonstrate a reliable BCI that synthesizes commands freely chosen and spoken by the user from a vocabulary of 6 keywords originally designed to allow intuitive selection of items on a communication board. Our results show for the first time that a speech-impaired individual with ALS can use a chronically implanted BCI to reliably produce synthesized words that are intelligible to human listeners while preserving the participants voice profile.
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Affiliation(s)
- Miguel Angrick
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Shiyu Luo
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qinwan Rabbani
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA
| | - Daniel N Candrea
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Samyak Shah
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Griffin W Milsap
- Research and Exploratory Development Department, Johns Hopkins Applied Physics Laboratory, Laurel, MD, USA
| | - William S Anderson
- Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Chad R Gordon
- Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD
- Section of Neuroplastic and Reconstructive Surgery, Department of Plastic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kathryn R Rosenblatt
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Anesthesiology & Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Lora Clawson
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nicholas Maragakis
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Francesco V Tenore
- Research and Exploratory Development Department, Johns Hopkins Applied Physics Laboratory, Laurel, MD, USA
| | - Matthew S Fifer
- Research and Exploratory Development Department, Johns Hopkins Applied Physics Laboratory, Laurel, MD, USA
| | - Hynek Hermansky
- Center for Language and Speech Processing, The Johns Hopkins University, Baltimore, MD, USA
- Human Language Technology Center of Excellence, The Johns Hopkins University, Baltimore, MD, USA
| | - Nick F Ramsey
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Nathan E Crone
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Hays MA, Kamali G, Koubeissi MZ, Sarma SV, Crone NE, Smith RJ, Kang JY. Towards optimizing single pulse electrical stimulation: High current intensity, short pulse width stimulation most effectively elicits evoked potentials. Brain Stimul 2023; 16:772-782. [PMID: 37141936 PMCID: PMC10330807 DOI: 10.1016/j.brs.2023.04.023] [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: 02/04/2023] [Revised: 04/21/2023] [Accepted: 04/26/2023] [Indexed: 05/06/2023] Open
Abstract
BACKGROUND While single pulse electrical stimulation (SPES) is increasingly used to study effective connectivity, the effects of varying stimulation parameters on the resulting cortico-cortical evoked potentials (CCEPs) have not been systematically explored. OBJECTIVE We sought to understand the interacting effects of stimulation pulse width, current intensity, and charge on CCEPs through an extensive testing of this parameter space and analysis of several response metrics. METHODS We conducted SPES in 11 patients undergoing intracranial EEG monitoring using five combinations of current intensity (1.5, 2.0, 3.0, 5.0, and 7.5 mA) and pulse width at each of three charges (0.750, 1.125, and 1.500 μC/phase) to study how CCEP amplitude, distribution, latency, morphology, and stimulus artifact amplitude vary with each parameter. RESULTS Stimulations with a greater charge or a greater current intensity and shorter pulse width at a given charge generally resulted in greater CCEP amplitudes and spatial distributions, shorter latencies, and increased waveform correlation. These effects interacted such that stimulations with the lowest charge and highest current intensities resulted in greater response amplitudes and spatial distributions than stimulations with the highest charge and lowest current intensities. Stimulus artifact amplitude increased with charge, but this could be mitigated by using shorter pulse widths. CONCLUSIONS Our results indicate that individual combinations of current intensity and pulse width, in addition to charge, are important determinants of CCEP magnitude, morphology, and spatial extent. Together, these findings suggest that high current intensity, short pulse width stimulations are optimal SPES settings for eliciting strong and consistent responses while minimizing charge.
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Affiliation(s)
- Mark A Hays
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
| | - Golnoosh Kamali
- Johns Hopkins Technology Ventures, Johns Hopkins University, Baltimore, MD, USA
| | | | - Sridevi V Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Rachel J Smith
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, USA; Department of Neuroengineering, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Joon Y Kang
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
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Usami K, Matsumoto R, Korzeniewska A, Shimotake A, Matsuhashi M, Nakae T, Kikuchi T, Yoshida K, Kunieda T, Takahashi R, Crone NE, Ikeda A. The dynamics of cortical interactions in visual recognition of object category: living versus nonliving. Cereb Cortex 2023; 33:5740-5750. [PMID: 36408645 PMCID: PMC10152084 DOI: 10.1093/cercor/bhac456] [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: 07/21/2022] [Revised: 10/23/2022] [Accepted: 10/24/2022] [Indexed: 11/22/2022] Open
Abstract
Noninvasive brain imaging studies have shown that higher visual processing of objects occurs in neural populations that are separable along broad semantic categories, particularly living versus nonliving objects. However, because of their limited temporal resolution, these studies have not been able to determine whether broad semantic categories are also reflected in the dynamics of neural interactions within cortical networks. We investigated the time course of neural propagation among cortical areas activated during object naming in 12 patients implanted with subdural electrode grids prior to epilepsy surgery, with a special focus on the visual recognition phase of the task. Analysis of event-related causality revealed significantly stronger neural propagation among sites within ventral temporal lobe (VTL) at early latencies, around 250 ms, for living objects compared to nonliving objects. Differences in other features, including familiarity, visual complexity, and age of acquisition, did not significantly change the patterns of neural propagation. Our findings suggest that the visual processing of living objects relies on stronger causal interactions among sites within VTL, perhaps reflecting greater integration of visual feature processing. In turn, this may help explain the fragility of naming living objects in neurological diseases affecting VTL.
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Affiliation(s)
- Kiyohide Usami
- Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Riki Matsumoto
- Division of Neurology, Kobe University Graduate School of Medicine, Kobe 650-0017, Japan
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University School of Medicine, MD 21287, United States
| | - Akihiro Shimotake
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Masao Matsuhashi
- Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Takuro Nakae
- Department of Neurosurgery, Shiga General Hospital, Moriyama 524-8524, Japan
| | - Takayuki Kikuchi
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Takeharu Kunieda
- Department of Neurosurgery, Ehime University Graduate School of Medicine, Toon 791-0295, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, MD 21287, United States
| | - Akio Ikeda
- Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
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Xiao Y, Chou CC, Cosgrove GR, Crone NE, Stone S, Madsen JR, Reucroft I, Shih YC, Weisholtz D, Yu HY, Anderson WS, Kreiman G. Cross-task specificity and within-task invariance of cognitive control processes. Cell Rep 2023; 42:111919. [PMID: 36640346 PMCID: PMC9993332 DOI: 10.1016/j.celrep.2022.111919] [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] [Received: 05/24/2022] [Revised: 08/09/2022] [Accepted: 12/12/2022] [Indexed: 01/11/2023] Open
Abstract
Cognitive control involves flexibly combining multiple sensory inputs with task-dependent goals during decision making. Several tasks involving conflicting sensory inputs and motor outputs have been proposed to examine cognitive control, including the Stroop, Flanker, and multi-source interference task. Because these tasks have been studied independently, it remains unclear whether the neural signatures of cognitive control reflect abstract control mechanisms or specific combinations of sensory and behavioral aspects of each task. To address these questions, we record invasive neurophysiological signals from 16 patients with pharmacologically intractable epilepsy and compare neural responses within and between tasks. Neural signals differ between incongruent and congruent conditions, showing strong modulation by conflicting task demands. These neural signals are mostly specific to each task, generalizing within a task but not across tasks. These results highlight the complex interplay between sensory inputs, motor outputs, and task demands underlying cognitive control processes.
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Affiliation(s)
| | - Chien-Chen Chou
- Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
| | | | | | - Scellig Stone
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joseph R Madsen
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ian Reucroft
- Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Yen-Cheng Shih
- Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
| | - Daniel Weisholtz
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Hsiang-Yu Yu
- Department of Neurology, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
| | | | - Gabriel Kreiman
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Center for Brains, Minds and Machines, Cambridge, MA, USA.
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Weiss AR, Korzeniewska A, Chrabaszcz A, Bush A, Fiez JA, Crone NE, Richardson RM. Lexicality-Modulated Influence of Auditory Cortex on Subthalamic Nucleus During Motor Planning for Speech. Neurobiol Lang (Camb) 2023; 4:53-80. [PMID: 37229140 PMCID: PMC10205077 DOI: 10.1162/nol_a_00086] [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] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 10/18/2022] [Indexed: 05/27/2023]
Abstract
Speech requires successful information transfer within cortical-basal ganglia loop circuits to produce the desired acoustic output. For this reason, up to 90% of Parkinson's disease patients experience impairments of speech articulation. Deep brain stimulation (DBS) is highly effective in controlling the symptoms of Parkinson's disease, sometimes alongside speech improvement, but subthalamic nucleus (STN) DBS can also lead to decreases in semantic and phonological fluency. This paradox demands better understanding of the interactions between the cortical speech network and the STN, which can be investigated with intracranial EEG recordings collected during DBS implantation surgery. We analyzed the propagation of high-gamma activity between STN, superior temporal gyrus (STG), and ventral sensorimotor cortices during reading aloud via event-related causality, a method that estimates strengths and directionalities of neural activity propagation. We employed a newly developed bivariate smoothing model based on a two-dimensional moving average, which is optimal for reducing random noise while retaining a sharp step response, to ensure precise embedding of statistical significance in the time-frequency space. Sustained and reciprocal neural interactions between STN and ventral sensorimotor cortex were observed. Moreover, high-gamma activity propagated from the STG to the STN prior to speech onset. The strength of this influence was affected by the lexical status of the utterance, with increased activity propagation during word versus pseudoword reading. These unique data suggest a potential role for the STN in the feedforward control of speech.
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Affiliation(s)
- Alexander R. Weiss
- JHU Cognitive Neurophysiology and BMI Lab, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anna Korzeniewska
- JHU Cognitive Neurophysiology and BMI Lab, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anna Chrabaszcz
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alan Bush
- Brain Modulation Lab, Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Julie A. Fiez
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, USA
- University of Pittsburgh Brain Institute, Pittsburgh, PA, USA
| | - Nathan E. Crone
- JHU Cognitive Neurophysiology and BMI Lab, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Robert M. Richardson
- Brain Modulation Lab, Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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10
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Hays MA, Smith RJ, Wang Y, Coogan C, Sarma SV, Crone NE, Kang JY. Cortico-cortical evoked potentials in response to varying stimulation intensity improves seizure localization. Clin Neurophysiol 2023; 145:119-128. [PMID: 36127246 PMCID: PMC9771930 DOI: 10.1016/j.clinph.2022.08.024] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [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: 02/23/2022] [Revised: 08/05/2022] [Accepted: 08/27/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVE As single pulse electrical stimulation (SPES) is increasingly utilized to help localize the seizure onset zone (SOZ), it is important to understand how stimulation intensity can affect the ability to use cortico-cortical evoked potentials (CCEPs) to delineate epileptogenic regions. METHODS We studied 15 drug-resistant epilepsy patients undergoing intracranial EEG monitoring and SPES with titrations of stimulation intensity. The N1 amplitude and distribution of CCEPs elicited in the SOZ and non-seizure onset zone (nSOZ) were quantified at each intensity. The separability of the SOZ and nSOZ using N1 amplitudes was compared between models using responses to titrations, responses to one maximal intensity, or both. RESULTS At 2 mA and above, the increase in N1 amplitude with current intensity was greater for responses within the SOZ, and SOZ response distribution was maximized by 4-6 mA. Models incorporating titrations achieved better separability of SOZ and nSOZ compared to those using one maximal intensity. CONCLUSIONS We demonstrated that differences in CCEP amplitude over a range of current intensities can improve discriminability of SOZ regions. SIGNIFICANCE This study provides insight into the underlying excitability of the SOZ and how differences in current-dependent amplitudes of CCEPs may be used to help localize epileptogenic sites.
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Affiliation(s)
- Mark A Hays
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Rachel J Smith
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Yujing Wang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Christopher Coogan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sridevi V Sarma
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joon Y Kang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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11
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Gunnarsdottir KM, Li A, Smith RJ, Kang JY, Korzeniewska A, Crone NE, Rouse AG, Cheng JJ, Kinsman MJ, Landazuri P, Uysal U, Ulloa CM, Cameron N, Cajigas I, Jagid J, Kanner A, Elarjani T, Bicchi MM, Inati S, Zaghloul KA, Boerwinkle VL, Wyckoff S, Barot N, Gonzalez-Martinez J, Sarma SV. Source-sink connectivity: a novel interictal EEG marker for seizure localization. Brain 2022; 145:3901-3915. [PMID: 36412516 PMCID: PMC10200292 DOI: 10.1093/brain/awac300] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [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: 11/08/2021] [Revised: 07/05/2022] [Accepted: 08/01/2022] [Indexed: 07/26/2023] Open
Abstract
Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist. Localizing the epileptogenic zone is a costly and time-consuming process, which often requires days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity on individual channels occurring immediately before seizures or spikes that occur interictally (i.e. between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in epileptogenic zone localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients. IEEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aimed to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the epileptogenic zone. We hypothesized that when a patient is not clinically seizing, it is because the epileptogenic zone is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighbouring nodes ('sources') and the inhibited nodes themselves ('sinks'). Specifically, patient-specific dynamical network models were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics. We validated the algorithm in a retrospective analysis of 65 patients. The source-sink metrics identified epileptogenic regions with 73% accuracy and clinicians agreed with the algorithm in 93% of seizure-free patients. The algorithm was further validated by using the metrics of the annotated epileptogenic zone to predict surgical outcomes. The source-sink metrics predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians' predictions (surgical success rate of this dataset). In failed outcomes, we identified brain regions with high metrics that were untreated. When compared with high frequency oscillations, the most commonly proposed interictal iEEG feature for epileptogenic zone localization, source-sink metrics outperformed in predictive power (by a factor of 1.2), suggesting they may be an interictal iEEG fingerprint of the epileptogenic zone.
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Affiliation(s)
| | - Adam Li
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Rachel J Smith
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Joon-Yi Kang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Adam G Rouse
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Jennifer J Cheng
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Michael J Kinsman
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Patrick Landazuri
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Utku Uysal
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Carol M Ulloa
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Nathaniel Cameron
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Iahn Cajigas
- Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Jonathan Jagid
- Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Andres Kanner
- Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Turki Elarjani
- Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Manuel Melo Bicchi
- Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Sara Inati
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kareem A Zaghloul
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Varina L Boerwinkle
- Barrow Neurological Institute, Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
| | - Sarah Wyckoff
- Barrow Neurological Institute, Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
| | - Niravkumar Barot
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | | | - Sridevi V Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
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12
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Handelman DA, Osborn LE, Thomas TM, Badger AR, Thompson M, Nickl RW, Anaya MA, Wormley JM, Cantarero GL, McMullen D, Crone NE, Wester B, Celnik PA, Fifer MS, Tenore FV. Shared Control of Bimanual Robotic Limbs With a Brain-Machine Interface for Self-Feeding. Front Neurorobot 2022; 16:918001. [PMID: 35837250 PMCID: PMC9274256 DOI: 10.3389/fnbot.2022.918001] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [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: 04/11/2022] [Accepted: 05/25/2022] [Indexed: 11/15/2022] Open
Abstract
Advances in intelligent robotic systems and brain-machine interfaces (BMI) have helped restore functionality and independence to individuals living with sensorimotor deficits; however, tasks requiring bimanual coordination and fine manipulation continue to remain unsolved given the technical complexity of controlling multiple degrees of freedom (DOF) across multiple limbs in a coordinated way through a user input. To address this challenge, we implemented a collaborative shared control strategy to manipulate and coordinate two Modular Prosthetic Limbs (MPL) for performing a bimanual self-feeding task. A human participant with microelectrode arrays in sensorimotor brain regions provided commands to both MPLs to perform the self-feeding task, which included bimanual cutting. Motor commands were decoded from bilateral neural signals to control up to two DOFs on each MPL at a time. The shared control strategy enabled the participant to map his four-DOF control inputs, two per hand, to as many as 12 DOFs for specifying robot end effector position and orientation. Using neurally-driven shared control, the participant successfully and simultaneously controlled movements of both robotic limbs to cut and eat food in a complex bimanual self-feeding task. This demonstration of bimanual robotic system control via a BMI in collaboration with intelligent robot behavior has major implications for restoring complex movement behaviors for those living with sensorimotor deficits.
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Affiliation(s)
- David A. Handelman
- Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
| | - Luke E. Osborn
- Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
| | - Tessy M. Thomas
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Andrew R. Badger
- Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
| | - Margaret Thompson
- Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
| | - Robert W. Nickl
- Department of Physical Medicine and Rehabilition, Johns Hopkins Medicine, Baltimore, MD, United States
| | - Manuel A. Anaya
- Department of Physical Medicine and Rehabilition, Johns Hopkins Medicine, Baltimore, MD, United States
| | - Jared M. Wormley
- Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
| | - Gabriela L. Cantarero
- Department of Physical Medicine and Rehabilition, Johns Hopkins Medicine, Baltimore, MD, United States
| | - David McMullen
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Nathan E. Crone
- Department of Neurology, Johns Hopkins Medicine, Baltimore, MD, United States
| | - Brock Wester
- Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
| | - Pablo A. Celnik
- Department of Physical Medicine and Rehabilition, Johns Hopkins Medicine, Baltimore, MD, United States
| | - Matthew S. Fifer
- Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
| | - Francesco V. Tenore
- Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
- *Correspondence: Francesco V. Tenore
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13
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Smith RJ, Hays MA, Kamali G, Coogan C, Crone NE, Kang JY, Sarma SV. Stimulating native seizures with neural resonance: a new approach to localize the seizure onset zone. Brain 2022; 145:3886-3900. [PMID: 35703986 DOI: 10.1093/brain/awac214] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [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: 01/19/2022] [Revised: 05/02/2022] [Accepted: 05/26/2022] [Indexed: 11/13/2022] Open
Abstract
Successful outcomes in epilepsy surgery rely on the accurate localization of the seizure onset zone (SOZ). Localizing the SOZ is often a costly and time-consuming process wherein a patient undergoes intracranial EEG (iEEG) monitoring, and a team of clinicians wait for seizures to occur. Clinicians then analyze the iEEG before each seizure onset to identify the SOZ, and localization accuracy increases when more seizures are captured. In this study, we develop a new approach to guide clinicians to actively elicit seizures with electrical stimulation. We hypothesize that a brain region belongs to the SOZ if a periodic stimulation at a particular frequency produces large amplitude oscillations in the iEEG network that propagate seizure activity. Such responses occur when there is "resonance" in the iEEG network, and the resonant frequency can be detected by observing a sharp peak in the magnitude versus frequency response curve, called a bode plot. To test our hypothesis, we analyzed single-pulse electrical stimulation (SPES) response data in 32 epilepsy patients undergoing iEEG monitoring. For each patient and each stimulated brain region, we constructed a bode plot by estimating a transfer function model (TFM) from the iEEG "impulse" or SPES response. The bode plots were then analyzed for evidence of resonance. First, we showed that when bode plot features were used as a marker of the SOZ, it distinguished successful from failed surgical outcomes with an AUC of 0.83, an accuracy that surpassed current methods of analysis with cortico-cortical evoked potential amplitude (CCEPs) and cortico-cortical spectral responses (CCSRs). Then, we retrospectively showed that three out of five native seizures accidentally triggered in four patients during routine periodic stimulation at a given frequency corresponded to a resonant peak in the bode plot. Lastly, we prospectively stimulated peak resonant frequencies gleaned from the bode plots to elicit seizures in six patients, and this resulted in an induction of three seizures and three auras in these patients. These findings suggest neural resonance as a new biomarker of the SOZ that can guide clinicians in eliciting native seizures to more quickly and accurately localize the SOZ.
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Affiliation(s)
- Rachel J Smith
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.,Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Mark A Hays
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.,Department of Neurology, Johns Hopkins University, Baltimore, MD, 21287
| | - Golnoosh Kamali
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, 21218, USA.,Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | | | - Nathan E Crone
- Department of Neurology, Johns Hopkins University, Baltimore, MD, 21287
| | - Joon Y Kang
- Department of Neurology, Johns Hopkins University, Baltimore, MD, 21287
| | - Sridevi V Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.,Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, 21218, USA
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14
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Fifer MS, McMullen DP, Osborn LE, Thomas TM, Christie B, Nickl RW, Candrea DN, Pohlmeyer EA, Thompson MC, Anaya MA, Schellekens W, Ramsey NF, Bensmaia SJ, Anderson WS, Wester BA, Crone NE, Celnik PA, Cantarero GL, Tenore FV. Intracortical Somatosensory Stimulation to Elicit Fingertip Sensations in an Individual With Spinal Cord Injury. Neurology 2022; 98:e679-e687. [PMID: 34880087 PMCID: PMC8865889 DOI: 10.1212/wnl.0000000000013173] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [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: 05/24/2021] [Accepted: 11/19/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The restoration of touch to fingers and fingertips is critical to achieving dexterous neuroprosthetic control for individuals with sensorimotor dysfunction. However, localized fingertip sensations have not been evoked via intracortical microstimulation (ICMS). METHODS Using a novel intraoperative mapping approach, we implanted electrode arrays in the finger areas of left and right somatosensory cortex and delivered ICMS over a 2-year period in a human participant with spinal cord injury. RESULTS Stimulation evoked tactile sensations in 8 fingers, including fingertips, spanning both hands. Evoked percepts followed expected somatotopic arrangements. The subject was able to reliably identify up to 7 finger-specific sites spanning both hands in a finger discrimination task. The size of the evoked percepts was on average 33% larger than a finger pad, as assessed via manual markings of a hand image. The size of the evoked percepts increased modestly with increased stimulation intensity, growing 21% as pulse amplitude increased from 20 to 80 µA. Detection thresholds were estimated on a subset of electrodes, with estimates of 9.2 to 35 µA observed, roughly consistent with prior studies. DISCUSSION These results suggest that ICMS can enable the delivery of consistent and localized fingertip sensations during object manipulation by neuroprostheses for individuals with somatosensory deficits. CLINICALTRIALSGOV IDENTIFIER NCT03161067.
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Affiliation(s)
- Matthew S Fifer
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL.
| | - David P McMullen
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Luke E Osborn
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Tessy M Thomas
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Breanne Christie
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Robert W Nickl
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Daniel N Candrea
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Eric A Pohlmeyer
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Margaret C Thompson
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Manuel A Anaya
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Wouter Schellekens
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Nick F Ramsey
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Sliman J Bensmaia
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - William S Anderson
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Brock A Wester
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Nathan E Crone
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Pablo A Celnik
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Gabriela L Cantarero
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
| | - Francesco V Tenore
- From the Research and Exploratory Development Department (M.S.F., L.E.O., B.P.C., E.A.P., M.C.T., F.V.T.), Johns Hopkins University Applied Physics Laboratory, Laurel; National Institute of Mental Health (D.P.M.), NIH, Bethesda; Department of Biomedical Engineering (T.M.T., D.N.C.), Department of Physical Medicine and Rehabilitation (R.W.N., M.A.A., P.A.C., G.L.C.), Department of Neurosurgery (W.S.A.), and Department of Neurology (B.A.W., N.E.C.), Johns Hopkins University, Baltimore, MD; UMC Utrecht Brain Center (W.S., N.F.R.), the Netherlands; and Department of Organismal Biology and Anatomy (S.J.B.), University of Chicago, IL
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15
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Feinsinger A, Pouratian N, Ebadi H, Adolphs R, Andersen R, Beauchamp MS, Chang EF, Crone NE, Collinger JL, Fried I, Mamelak A, Richardson M, Rutishauser U, Sheth SA, Suthana N, Tandon N, Yoshor D. Ethical commitments, principles, and practices guiding intracranial neuroscientific research in humans. Neuron 2022; 110:188-194. [PMID: 35051364 PMCID: PMC9417025 DOI: 10.1016/j.neuron.2021.11.011] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [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: 05/28/2021] [Revised: 07/25/2021] [Accepted: 11/11/2021] [Indexed: 01/21/2023]
Abstract
Leveraging firsthand experience, BRAIN-funded investigators conducting intracranial human neuroscience research propose two fundamental ethical commitments: (1) maintaining the integrity of clinical care and (2) ensuring voluntariness. Principles, practices, and uncertainties related to these commitments are offered for future investigation.
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Affiliation(s)
- Ashley Feinsinger
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA,Equal Contribution
| | - Nader Pouratian
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, Texas, 75390, USA,Equal Contribution,Lead Contact and Corresponding Author
| | - Hamasa Ebadi
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, Texas, 75390, USA
| | - Ralph Adolphs
- Departments of Psychology and Neuroscience, California Institute of Technology, Pasadena, California, 91125 USA,Department of Biology, California Institute of Technology, Pasadena, California, 91125, USA
| | - Richard Andersen
- Department of Biology, California Institute of Technology, Pasadena, California, 91125, USA
| | - Michael S. Beauchamp
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Edward F Chang
- Department of Neurosurgery, UC San Francisco, San Francisco, California, 94143, USA
| | - Nathan E. Crone
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, 21287, USA, 15260, USA
| | - Jennifer L. Collinger
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania, 15260, USA
| | - Itzhak Fried
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | - Adam Mamelak
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California, 90048 USA
| | - Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, 02114, USA
| | - Ueli Rutishauser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California, 90048 USA
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas, 77030 USA
| | - Nanthia Suthana
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA,Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | - Nitin Tandon
- Department of Neurosurgery, University of Texas Houston, Houston, Texas, 77030, USA
| | - Daniel Yoshor
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
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16
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Ge A, Gutierrez EG, Wook Lee S, Shah S, Carmenate Y, Collard M, Crone NE, Krauss GL. Seizure triggers identified postictally using a smart watch reporting system. Epilepsy Behav 2022; 126:108472. [PMID: 34942507 DOI: 10.1016/j.yebeh.2021.108472] [Citation(s) in RCA: 2] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 11/22/2021] [Accepted: 11/25/2021] [Indexed: 11/24/2022]
Abstract
Persons with epilepsy (PWE) often report that seizure triggers can influence the occurrence and timing of seizures. Some previous studies of seizure triggers have relied on retrospective daily seizure diaries or surveys pertaining to all past seizures, recent and/or remote, in respondents. To assess the characteristics of seizure triggers at the granularity of individual seizures, we used a seizure-tracking app, called EpiWatch, on a smart watch system (Apple Watch and iPhone) in a national study of PWE. Participants tracked seizures during a 16-month study period using the EpiWatch app. Seizure tracking was initiated during a pre-ictal state or as the seizure was occurring and included collection of biosensor data, responsiveness testing, and completion of an immediate post-seizure survey. The survey evaluated seizure types, auras or warning symptoms, loss of awareness, use of rescue medication, and seizure triggers for each tracked seizure. Two hundred and thirty four participants tracked 2493 seizures. Ninety six participants reported triggers in 650 seizures: stress (65.8%), lack of sleep (30.5%), menstrual cycle (19.7%), and overexertion (18%) were the most common. Participants often reported having multiple combined triggers, frequent stress with lack of sleep, overexertion, or menses. Participants who reported triggers were more likely to be taking 3 or more anti-seizure medications compared to participants who did not report triggers. Participants were able to interact with the app and use mobile technology in this national study to record seizures and report common seizure triggers. These findings demonstrate the promise of longitudinal, self-reported data to improve our understanding of epilepsy and its related comorbidities.
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Affiliation(s)
- Anjie Ge
- Johns Hopkins University, Department of Neurology, 600 N. Wolfe St, Baltimore, MD 21287, USA.
| | - Erie G Gutierrez
- Johns Hopkins University, Department of Neurology, 600 N. Wolfe St, Baltimore, MD 21287, USA.
| | - Seung Wook Lee
- Johns Hopkins University, Department of Neurology, 600 N. Wolfe St, Baltimore, MD 21287, USA
| | - Samyak Shah
- Johns Hopkins University, Department of Neurology, 600 N. Wolfe St, Baltimore, MD 21287, USA.
| | - Yaretson Carmenate
- Johns Hopkins University, Department of Neurology, 600 N. Wolfe St, Baltimore, MD 21287, USA.
| | - Maxwell Collard
- Johns Hopkins University, Department of Neurology, 600 N. Wolfe St, Baltimore, MD 21287, USA.
| | - Nathan E Crone
- Johns Hopkins University, Department of Neurology, 600 N. Wolfe St, Baltimore, MD 21287, USA.
| | - Gregory L Krauss
- Johns Hopkins University, Department of Neurology, 600 N. Wolfe St, Baltimore, MD 21287, USA.
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17
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Abstract
Damage or degeneration of motor pathways necessary for speech and other movements, as in brainstem strokes or amyotrophic lateral sclerosis (ALS), can interfere with efficient communication without affecting brain structures responsible for language or cognition. In the worst-case scenario, this can result in the locked in syndrome (LIS), a condition in which individuals cannot initiate communication and can only express themselves by answering yes/no questions with eye blinks or other rudimentary movements. Existing augmentative and alternative communication (AAC) devices that rely on eye tracking can improve the quality of life for people with this condition, but brain-computer interfaces (BCIs) are also increasingly being investigated as AAC devices, particularly when eye tracking is too slow or unreliable. Moreover, with recent and ongoing advances in machine learning and neural recording technologies, BCIs may offer the only means to go beyond cursor control and text generation on a computer, to allow real-time synthesis of speech, which would arguably offer the most efficient and expressive channel for communication. The potential for BCI speech synthesis has only recently been realized because of seminal studies of the neuroanatomical and neurophysiological underpinnings of speech production using intracranial electrocorticographic (ECoG) recordings in patients undergoing epilepsy surgery. These studies have shown that cortical areas responsible for vocalization and articulation are distributed over a large area of ventral sensorimotor cortex, and that it is possible to decode speech and reconstruct its acoustics from ECoG if these areas are recorded with sufficiently dense and comprehensive electrode arrays. In this article, we review these advances, including the latest neural decoding strategies that range from deep learning models to the direct concatenation of speech units. We also discuss state-of-the-art vocoders that are integral in constructing natural-sounding audio waveforms for speech BCIs. Finally, this review outlines some of the challenges ahead in directly synthesizing speech for patients with LIS.
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Affiliation(s)
- Shiyu Luo
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Qinwan Rabbani
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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18
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Osborn LE, Christie BP, McMullen DP, Nickl RW, Thompson MC, Pawar AS, Thomas TM, Alejandro Anaya M, Crone NE, Wester BA, Bensmaia SJ, Celnik PA, Cantarero GL, Tenore FV, Fifer MS. Intracortical microstimulation of somatosensory cortex enables object identification through perceived sensations. Annu Int Conf IEEE Eng Med Biol Soc 2021; 2021:6259-6262. [PMID: 34892544 DOI: 10.1109/embc46164.2021.9630450] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Advances in brain-machine interfaces have helped restore function and independence for individuals with sensorimotor deficits; however, providing efficient and effective sensory feedback remains challenging. Intracortical microstimulation (ICMS) of sensorimotor brain regions is a promising technique for providing bioinspired sensory feedback. In a human participant with chronically-implanted microelectrode arrays, we provided ICMS to the primary somatosensory cortex to generate tactile percepts in his hand. In a 3-choice object identification task, the participant identified virtual objects using tactile sensory feedback and no visual information. We evaluated three different stimulation paradigms, each with a different weighting of the grip force and its derivative, to explore the potential benefits of a more bioinspired stimulation strategy. In all paradigms, the participant's ability to identify the objects was above-chance, with object identification accuracy reaching 80% correct when using only sustained grip force feedback and 76.7% when using equal weighting of both sustained grip force and its derivative. These results demonstrate that bioinspired ICMS can provide sensory feedback that is functionally beneficial in sensorimotor tasks. Designing more efficient stimulation paradigms is important because it will allow us to 1) provide safer stimulation delivery methods that reduce overall injected charge without sacrificing function and 2) more effectively transmit sensory information to promote intuitive integration and usage by the human body.
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19
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Ghinda DC, Salimpour Y, Crone NE, Kang J, Anderson WS. Dynamical Analysis of Seizure in Epileptic Brain: a Dynamic Phase-Amplitude Coupling Estimation Approach. Annu Int Conf IEEE Eng Med Biol Soc 2021; 2021:5970-5973. [PMID: 34892478 DOI: 10.1109/embc46164.2021.9629778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Cross-frequency coupling in general and phase-amplitude coupling (PAC) as a particular form of it, provides an opportunity to investigate the complex interactions between neural oscillations in the human brain and neurological disorders such as epilepsy. Using PAC detection methods on temporal sliding windows, we developed a map of dynamic PAC evolution to investigate the spatiotemporal changes occurring during ictal transitions in a patient with intractable mesial temporal lobe epilepsy. The map is built by computing the modulation index between the amplitude of high frequency oscillations and the phase of lower frequency rhythms from the intracranial stereoelectroencephalography recordings during seizure. Our preliminary results show early abnormal PAC changes occurring in the preictal state prior to the occurrence of clinical or visible electrographic seizure onset, and suggest that dynamic PAC measures may serve as a potential clinical technique for analyzing seizure dynamics.Clinical Relevance-Application of a dynamic temporal PAC map as a new tool may provide novel insights into the neurophysiology of epileptic seizure activity and its spatio-temporal dynamics.
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20
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Hays MA, Smith RJ, Haridas B, Coogan C, Crone NE, Kang JY. Effects of stimulation intensity on intracranial cortico-cortical evoked potentials: A titration study. Clin Neurophysiol 2021; 132:2766-2777. [PMID: 34583119 DOI: 10.1016/j.clinph.2021.08.008] [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] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 07/26/2021] [Accepted: 08/04/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVE The aim of the present study was to investigate the optimal stimulation parameters for eliciting cortico-cortical evoked potentials (CCEPs) for mapping functional and epileptogenic networks. METHODS We studied 13 patients with refractory epilepsy undergoing intracranial EEG monitoring. We systematically titrated the intensity of single-pulse electrical stimulation at multiple sites to assess the effect of increasing current on salient features of CCEPs such as N1 potential magnitude, signal to noise ratio, waveform similarity, and spatial distribution of responses. Responses at each incremental stimulation setting were compared to each other and to a final set of responses at the maximum intensity used in each patient (3.5-10 mA, median 6 mA). RESULTS We found that with a biphasic 0.15 ms/phase pulse at least 2-4 mA is needed to differentiate between non-responsive and responsive sites, and that stimulation currents of 6-7 mA are needed to maximize amplitude and spatial distribution of N1 responses and stabilize waveform morphology. CONCLUSIONS We determined a minimum stimulation threshold necessary for eliciting CCEPs, as well as a point at which the current-dependent relationship of several response metrics all saturate. SIGNIFICANCE This titration study provides practical, immediate guidance on optimal stimulation parameters to study specific features of CCEPs, which have been increasingly used to map both functional and epileptic brain networks in humans.
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Affiliation(s)
- Mark A Hays
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Rachel J Smith
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Babitha Haridas
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Christopher Coogan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joon Y Kang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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21
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Alhourani A, Korzeniewska A, Wozny TA, Lipski WJ, Kondylis ED, Ghuman AS, Crone NE, Crammond DJ, Turner RS, Richardson RM. Subthalamic Nucleus Activity Influences Sensory and Motor Cortex during Force Transduction. Cereb Cortex 2021; 30:2615-2626. [PMID: 31989165 DOI: 10.1093/cercor/bhz264] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [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: 06/04/2019] [Revised: 08/23/2019] [Accepted: 09/17/2019] [Indexed: 12/12/2022] Open
Abstract
The subthalamic nucleus (STN) is proposed to participate in pausing, or alternately, in dynamic scaling of behavioral responses, roles that have conflicting implications for understanding STN function in the context of deep brain stimulation (DBS) therapy. To examine the nature of event-related STN activity and subthalamic-cortical dynamics, we performed primary motor and somatosensory electrocorticography while subjects (n = 10) performed a grip force task during DBS implantation surgery. Phase-locking analyses demonstrated periods of STN-cortical coherence that bracketed force transduction, in both beta and gamma ranges. Event-related causality measures demonstrated that both STN beta and gamma activity predicted motor cortical beta and gamma activity not only during force generation but also prior to movement onset. These findings are consistent with the idea that the STN participates in motor planning, in addition to the modulation of ongoing movement. We also demonstrated bidirectional information flow between the STN and somatosensory cortex in both beta and gamma range frequencies, suggesting robust STN participation in somatosensory integration. In fact, interactions in beta activity between the STN and somatosensory cortex, and not between STN and motor cortex, predicted PD symptom severity. Thus, the STN contributes to multiple aspects of sensorimotor behavior dynamically across time.
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Affiliation(s)
- Ahmad Alhourani
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40292, USA
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Thomas A Wozny
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Witold J Lipski
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Efstathios D Kondylis
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Avniel S Ghuman
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA.,Brain Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Donald J Crammond
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Robert S Turner
- Brain Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA.,Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA.,Harvard Medical School, Boston, MA 02115, USA
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22
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Hays MA, Coogan C, Crone NE, Kang JY. Graph theoretical analysis of evoked potentials shows network influence of epileptogenic mesial temporal region. Hum Brain Mapp 2021; 42:4173-4186. [PMID: 34165233 PMCID: PMC8356982 DOI: 10.1002/hbm.25418] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 03/08/2021] [Accepted: 03/09/2021] [Indexed: 01/08/2023] Open
Abstract
It is now widely accepted that seizures arise from the coordinated activity of epileptic networks, and as a result, traditional methods of analyzing seizures have been augmented by techniques like single-pulse electrical stimulation (SPES) that estimate effective connectivity in brain networks. We used SPES and graph analytics in 18 patients undergoing intracranial EEG monitoring to investigate effective connectivity between recording sites within and outside mesial temporal structures. We compared evoked potential amplitude, network density, and centrality measures inside and outside the mesial temporal region (MTR) across three patient groups: focal epileptogenic MTR, multifocal epileptogenic MTR, and non-epileptogenic MTR. Effective connectivity within the MTR had significantly greater magnitude (evoked potential amplitude) and network density, regardless of epileptogenicity. However, effective connectivity between MTR and surrounding non-epileptogenic regions was of greater magnitude and density in patients with focal epileptogenic MTR compared to patients with multifocal epileptogenic MTR and those with non-epileptogenic MTR. Moreover, electrodes within focal epileptogenic MTR had significantly greater outward network centrality compared to electrodes outside non-epileptogenic regions and to multifocal and non-epileptogenic MTR. Our results indicate that the MTR is a robustly connected subnetwork that can exert an overall elevated propagative influence over other brain regions when it is epileptogenic. Understanding the underlying effective connectivity and roles of epileptogenic regions within the larger network may provide insights that eventually lead to improved surgical outcomes.
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Affiliation(s)
- Mark A Hays
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Christopher Coogan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Joon Y Kang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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23
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Wang Y, Hays MA, Coogan C, Kang JY, Flinker A, Arya R, Korzeniewska A, Crone NE. Spatial-Temporal Functional Mapping Combined With Cortico-Cortical Evoked Potentials in Predicting Cortical Stimulation Results. Front Hum Neurosci 2021; 15:661976. [PMID: 33935673 PMCID: PMC8079642 DOI: 10.3389/fnhum.2021.661976] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 03/23/2021] [Indexed: 11/13/2022] Open
Abstract
Functional human brain mapping is commonly performed during invasive monitoring with intracranial electroencephalographic (iEEG) electrodes prior to resective surgery for drug resistant epilepsy. The current gold standard, electrocortical stimulation mapping (ESM), is time consuming, sometimes elicits pain, and often induces after discharges or seizures. Moreover, there is a risk of overestimating eloquent areas due to propagation of the effects of stimulation to a broader network of language cortex. Passive iEEG spatial-temporal functional mapping (STFM) has recently emerged as a potential alternative to ESM. However, investigators have observed less correspondence between STFM and ESM maps of language than between their maps of motor function. We hypothesized that incongruities between ESM and STFM of language function may arise due to propagation of the effects of ESM to cortical areas having strong effective connectivity with the site of stimulation. We evaluated five patients who underwent invasive monitoring for seizure localization, whose language areas were identified using ESM. All patients performed a battery of language tasks during passive iEEG recordings. To estimate the effective connectivity of stimulation sites with a broader network of task-activated cortical sites, we measured cortico-cortical evoked potentials (CCEPs) elicited across all recording sites by single-pulse electrical stimulation at sites where ESM was performed at other times. With the combination of high gamma power as well as CCEPs results, we trained a logistic regression model to predict ESM results at individual electrode pairs. The average accuracy of the classifier using both STFM and CCEPs results combined was 87.7%, significantly higher than the one using STFM alone (71.8%), indicating that the correspondence between STFM and ESM results is greater when effective connectivity between ESM stimulation sites and task-activated sites is taken into consideration. These findings, though based on a small number of subjects to date, provide preliminary support for the hypothesis that incongruities between ESM and STFM may arise in part from propagation of stimulation effects to a broader network of cortical language sites activated by language tasks, and suggest that more studies, with larger numbers of patients, are needed to understand the utility of both mapping techniques in clinical practice.
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Affiliation(s)
- Yujing Wang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Mark A Hays
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Christopher Coogan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Joon Y Kang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Adeen Flinker
- Department of Neurology, New York University School of Medicine, New York, NY, United States
| | - Ravindra Arya
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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24
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McMullen DP, Thomas TM, Fifer MS, Candrea DN, Tenore FV, Nickl RW, Pohlmeyer EA, Coogan C, Osborn LE, Schiavi A, Wojtasiewicz T, Gordon CR, Cohen AB, Ramsey NF, Schellekens W, Bensmaia SJ, Cantarero GL, Celnik PA, Wester BA, Anderson WS, Crone NE. Novel intraoperative online functional mapping of somatosensory finger representations for targeted stimulating electrode placement: technical note. J Neurosurg 2021:1-8. [PMID: 33770760 DOI: 10.3171/2020.9.jns202675] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 09/29/2020] [Indexed: 11/06/2022]
Abstract
Defining eloquent cortex intraoperatively, traditionally performed by neurosurgeons to preserve patient function, can now help target electrode implantation for restoring function. Brain-machine interfaces (BMIs) have the potential to restore upper-limb motor control to paralyzed patients but require accurate placement of recording and stimulating electrodes to enable functional control of a prosthetic limb. Beyond motor decoding from recording arrays, precise placement of stimulating electrodes in cortical areas associated with finger and fingertip sensations allows for the delivery of sensory feedback that could improve dexterous control of prosthetic hands. In this study, the authors demonstrated the use of a novel intraoperative online functional mapping (OFM) technique with high-density electrocorticography to localize finger representations in human primary somatosensory cortex. In conjunction with traditional pre- and intraoperative targeting approaches, this technique enabled accurate implantation of stimulating microelectrodes, which was confirmed by postimplantation intracortical stimulation of finger and fingertip sensations. This work demonstrates the utility of intraoperative OFM and will inform future studies of closed-loop BMIs in humans.
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Affiliation(s)
- David P McMullen
- 1National Institute of Mental Health, National Institutes of Health, Bethesda
| | | | - Matthew S Fifer
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | | | - Francesco V Tenore
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | | | - Eric A Pohlmeyer
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | | | - Luke E Osborn
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
| | | | | | - Chad R Gordon
- 8Plastic and Reconstructive Surgery, Johns Hopkins University, Baltimore
| | - Adam B Cohen
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
- 5Neurology
| | - Nick F Ramsey
- 9UMC Utrecht Brain Center, Utrecht, The Netherlands; and
| | | | - Sliman J Bensmaia
- 10Department of Organismal Biology and Anatomy, University of Chicago, Illinois
| | | | | | - Brock A Wester
- 3Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland
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25
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Wang Y, Korzeniewska A, Usami K, Valenzuela A, Crone NE. The Dynamics of Language Network Interactions in Lexical Selection: An Intracranial EEG Study. Cereb Cortex 2021; 31:2058-2070. [PMID: 33283856 PMCID: PMC7945024 DOI: 10.1093/cercor/bhaa344] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 10/18/2020] [Accepted: 10/22/2020] [Indexed: 11/14/2022] Open
Abstract
Speaking in sentences requires selection from contextually determined lexical representations. Although posterior temporal cortex (PTC) and Broca's areas play important roles in storage and selection, respectively, of lexical representations, there has been no direct evidence for physiological interactions between these areas on time scales typical of lexical selection. Using intracranial recordings of cortical population activity indexed by high-gamma power (70-150 Hz) modulations, we studied the causal dynamics of cortical language networks while epilepsy surgery patients performed a sentence completion task in which the number of potential lexical responses was systematically varied. Prior to completion of sentences with more response possibilities, Broca's area was not only more active, but also exhibited more local network interactions with and greater top-down influences on PTC, consistent with activation of, and competition between, more lexical representations. These findings provide the most direct experimental support yet for network dynamics playing a role in lexical selection among competing alternatives during speech production.
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Affiliation(s)
- Yujing Wang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- Fischell Department of Bioengineering, University of Maryland College Park, College Park, MD 20742, USA
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Kiyohide Usami
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Sakyoku, Kyoto 606-8507, Japan
| | - Alyssandra Valenzuela
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
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Kamali G, Smith RJ, Hays M, Coogan C, Crone NE, Kang JY, Sarma SV. Transfer Function Models for the Localization of Seizure Onset Zone From Cortico-Cortical Evoked Potentials. Front Neurol 2020; 11:579961. [PMID: 33362689 PMCID: PMC7758451 DOI: 10.3389/fneur.2020.579961] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 10/12/2020] [Indexed: 11/26/2022] Open
Abstract
Surgical resection of the seizure onset zone (SOZ) could potentially lead to seizure-freedom in medically refractory epilepsy patients. However, localizing the SOZ can be a time consuming and tedious process involving visual inspection of intracranial electroencephalographic (iEEG) recordings captured during passive patient monitoring. Cortical stimulation is currently performed on patients undergoing invasive EEG monitoring for the main purpose of mapping functional brain networks such as language and motor networks. We hypothesized that evoked responses from single pulse electrical stimulation (SPES) can also be used to localize the SOZ as they may express the natural frequencies and connectivity of the iEEG network. To test our hypothesis, we constructed patient specific transfer function models from the evoked responses recorded from 22 epilepsy patients that underwent SPES evaluation and iEEG monitoring. We then computed the frequency and connectivity dependent “peak gain” of the system as measured by the H∞ norm from systems theory. We found that in cases for which clinicians had high confidence in localizing the SOZ, the highest peak gain transfer functions with the smallest “floor gain” (gain at which the dipped H∞ 3dB below DC gain) corresponded to when the clinically annotated SOZ and early spread regions were stimulated. In more complex cases, there was a large spread of the peak-to-floor (PF) ratios when the clinically annotated SOZ was stimulated. Interestingly for patients who had successful surgeries, our ratio of gains, agreed with clinical localization, no matter the complexity of the case. For patients with failed surgeries, the PF ratio did not match clinical annotations. Our findings suggest that transfer function gains and their corresponding frequency responses computed from SPES evoked responses may improve SOZ localization and thus surgical outcomes.
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Affiliation(s)
- Golnoosh Kamali
- Neuromedical Control Systems Laboratory, Department of Electrical and Computer Engineering, Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Rachel June Smith
- Neuromedical Control Systems Laboratory, Department of Biomedical Engineering, Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Mark Hays
- Cognitive Research, Online Neuroengineering and Electrophysiology Laboratory, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Christopher Coogan
- Cognitive Research, Online Neuroengineering and Electrophysiology Laboratory, Department of Neurology-Epilepsy, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Nathan E Crone
- Cognitive Research, Online Neuroengineering and Electrophysiology Laboratory, Department of Neurology-Epilepsy, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Joon Y Kang
- Department of Neurology-Epilepsy, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Sridevi V Sarma
- Neuromedical Control Systems Laboratory, Department of Electrical and Computer Engineering, Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.,Neuromedical Control Systems Laboratory, Department of Biomedical Engineering, Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
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27
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Smith RJ, Kamali G, Hays M, Coogan CG, Crone NE, Sarma SV, Kang JY. State-space models of evoked potentials to localize the seizure onset zone. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2020:2528-2531. [PMID: 33018521 DOI: 10.1109/embc44109.2020.9176697] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Surgical removal of the seizure onset zone (SOZ) in epilepsy patients is a potentially curative treatment, but the process heavily relies on accurate localization of the SOZ via visual inspection. SPES (Single-pulse electrical stimulation) is a method recently used to explore inter-areal connectivity in vivo to probe functional brain networks such as language and motor networks, and to a much lesser degree, seizure networks. We hypothesized that a dynamical quantification of the connectivity networks derived from the evoked responses induced by SPES could also be used to localize the SOZ. To test our hypothesis, we used an intracranial EEG (iEEG) data set in which five epilepsy patients underwent extensive SPES evaluation. For each patient, and for each dataset that stimulated a different pair of electrodes, we constructed a state-space model from the patient's data. Specifically, we simultaneously estimated model parameters under an exogenous pulse input to a dynamical system whose state vector consisted of the response iEEG signals. Then, the size of the reachable state space, as quantified by the maximum singular value of the reachability matrix, σmax(R), was computed and denoted as the "largest" network response possible when stimulating the given pair. Our results suggest high agreement between σmax(R) and clinically annotated SOZ for patients with localizable SOZs.Clinical Relevance- Our study applies dynamical systems theory to identify epileptogenic brain regions, creating a novel tool that clinicians may use in surgical planning for medically-refractory epilepsy patients.
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28
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Kamali G, Smith RJ, Hays M, Coogan C, Crone NE, Sarma SV, Kang JY. Localizing the seizure onset zone from single pulse electrical stimulation responses using transfer function models. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2020:2524-2527. [PMID: 33018520 DOI: 10.1109/embc44109.2020.9175954] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Surgical resection of the seizure onset zone (SOZ) could potentially lead to seizure-freedom in medically refractory epilepsy patients. However, localizing the SOZ can be a time consuming and tedious process involving visual inspection of intracranial electroencephalographic (iEEG) recordings captured during passive patient monitoring. Single pulse electrical stimulation (SPES) is currently performed on patients undergoing invasive EEG monitoring for the main purposes of mapping functional brain networks such as language and motor networks. We hypothesize that evoked responses from SPES can also be used to localize the SOZ as they may express the natural frequencies and connectivity of the iEEG network. To test our hypothesis, we construct patient specific single-input multi-output transfer function models from the evoked responses recorded from five epilepsy patients that underwent SPES evaluation and iEEG monitoring. Our preliminary results suggest that the stimulation electrodes that produced the highest gain transfer functions, as measured by the ${\mathcal{H}_\infty }$ norm, correspond to those electrodes clinically defined in the SOZ in successfully treated patients.Clinical Relevance- This study creates an innovative tool that allows clinicians to identify the seizure onset zone in medically refractory epilepsy patients using quantitative metrics thereby increasing surgical success outcomes, mitigating patient risks, and decreasing costs.
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29
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Duy PQ, Krauss GL, Crone NE, Ma M, Johnson EL. Antiepileptic drug withdrawal and seizure severity in the epilepsy monitoring unit. Epilepsy Behav 2020; 109:107128. [PMID: 32417383 DOI: 10.1016/j.yebeh.2020.107128] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 04/17/2020] [Accepted: 04/20/2020] [Indexed: 10/24/2022]
Abstract
OBJECTIVE The goal of this study was to identify a strategy for antiepileptic drug (AED) reduction to allow efficient recording of focal seizures (FS) in patients undergoing video-electroencephalography (EEG) in an epilepsy monitoring unit (EMU) while avoiding the risk of complications associated with more severe seizure types. METHODS We retrospectively reviewed consecutive patients admitted to our institution's EMU from July 1, 2016 to December 31, 2017. We included 114 presurgical patients who had AEDs reduced and at least one seizure during the admission. We compared AED dosages at which FS versus focal to bilateral tonic-clonic seizures (f-BTCS), seizure clusters, and lorazepam administration occurred. We also examined rate of AED reduction and seizure types. We used a receiver-operating characteristic (ROC) curve to identify a dose maximizing FS and minimizing other seizure types. RESULTS Antiepileptic drug withdrawal rates ranged from 0 to 100% in the first 24 h (mean: 20%, standard deviation: 20%). Focal to bilateral tonic-clonic seizures and lorazepam administration occurred at a lower median AED dose than did FS (0%, 7.2%, and 43.8%, respectively, expressed as a percentage of the patient's outpatient daily AED dose; p < 0.001). A daily EMU-administered dose of one-third of the patient's outpatient AED dose allowed 55.0% of FS to occur while avoiding 82.0% of more severe seizure types. The seizure types had no difference in rate of AED withdrawal in the first 24 h of EMU stay. CONCLUSIONS Focal seizures occurred at a higher AED dose than did f-BTCS. This may imply that a low minimally effective dose of AED could allow FS to be recorded while providing protection against f-BTCS. This strategy could improve efficacy and safety in the EMU.
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Affiliation(s)
- Phan Q Duy
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Yale University School of Medicine, New Haven, CT, USA
| | - Gregory L Krauss
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Molly Ma
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Emily L Johnson
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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30
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Usami K, Korzeniewska A, Matsumoto R, Kobayashi K, Hitomi T, Matsuhashi M, Kunieda T, Mikuni N, Kikuchi T, Yoshida K, Miyamoto S, Takahashi R, Ikeda A, Crone NE. The neural tides of sleep and consciousness revealed by single-pulse electrical brain stimulation. Sleep 2020; 42:5361362. [PMID: 30794319 DOI: 10.1093/sleep/zsz050] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [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: 11/03/2018] [Revised: 02/01/2019] [Indexed: 12/12/2022] Open
Abstract
Wakefulness and sleep arise from global changes in brain physiology that may also govern the flow of neural activity between cortical regions responsible for perceptual processing versus planning and action. To test whether and how the sleep/wake cycle affects the overall propagation of neural activity in large-scale brain networks, we applied single-pulse electrical stimulation (SPES) in patients implanted with intracranial EEG electrodes for epilepsy surgery. SPES elicited cortico-cortical spectral responses at high-gamma frequencies (CCSRHG, 80-150 Hz), which indexes changes in neuronal population firing rates. Using event-related causality (ERC) analysis, we found that the overall patterns of neural propagation among sites with CCSRHG were different during wakefulness and different sleep stages. For example, stimulation of frontal lobe elicited greater propagation toward parietal lobe during slow-wave sleep than during wakefulness. During REM sleep, we observed a decrease in propagation within frontal lobe, and an increase in propagation within parietal lobe, elicited by frontal and parietal stimulation, respectively. These biases in the directionality of large-scale cortical network dynamics during REM sleep could potentially account for some of the unique experiential aspects of this sleep stage. Together these findings suggest that the regulation of conscious awareness and sleep is associated with differences in the balance of neural propagation across large-scale frontal-parietal networks.
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Affiliation(s)
- Kiyohide Usami
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD.,Department of Neurology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Riki Matsumoto
- Department of Neurology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Katsuya Kobayashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Takefumi Hitomi
- Department of Clinical Laboratory Medicine, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan.,Department of Respiratory Care and Sleep Control Medicine, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Masao Matsuhashi
- Research and Educational Unit of Leaders for Integrated Medical System, Kyoto University Graduate School of medicine, Sakyo-ku, Kyoto, Japan.,Human Brain Research Center, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Takeharu Kunieda
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan.,Department of Neurosurgery, Ehime University Graduate School of Medicine, Shizukawa Toon city, Ehime, Japan
| | - Nobuhiro Mikuni
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan.,Department of Neurosurgery, Sapporo Medical University, Chuo-ku, Sapporo, Japan
| | - Takayuki Kikuchi
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Akio Ikeda
- Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
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31
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Usami K, Milsap GW, Korzeniewska A, Collard MJ, Wang Y, Lesser RP, Anderson WS, Crone NE. Cortical Responses to Input From Distant Areas are Modulated by Local Spontaneous Alpha/Beta Oscillations. Cereb Cortex 2020; 29:777-787. [PMID: 29373641 DOI: 10.1093/cercor/bhx361] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Indexed: 01/13/2023] Open
Abstract
Any given area in human cortex may receive input from multiple, functionally heterogeneous areas, potentially representing different processing threads. Alpha (8-13 Hz) and beta oscillations (13-20 Hz) have been hypothesized by other investigators to gate local cortical processing, but their influence on cortical responses to input from other cortical areas is unknown. To study this, we measured the effect of local oscillatory power and phase on cortical responses elicited by single-pulse electrical stimulation (SPES) at distant cortical sites, in awake human subjects implanted with intracranial electrodes for epilepsy surgery. In 4 out of 5 subjects, the amplitudes of corticocortical evoked potentials (CCEPs) elicited by distant SPES were reproducibly modulated by the power, but not the phase, of local oscillations in alpha and beta frequencies. Specifically, CCEP amplitudes were higher when average oscillatory power just before distant SPES (-110 to -10 ms) was high. This effect was observed in only a subset (0-33%) of sites with CCEPs and, like the CCEPs themselves, varied with stimulation at different distant sites. Our results suggest that although alpha and beta oscillations may gate local processing, they may also enhance the responsiveness of cortex to input from distant cortical sites.
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Affiliation(s)
- Kiyohide Usami
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Griffin W Milsap
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Maxwell J Collard
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Yujing Wang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA
| | - Ronald P Lesser
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - William S Anderson
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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32
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Korzeniewska A, Wang Y, Benz HL, Fifer MS, Collard M, Milsap G, Cervenka MC, Martin A, Gotts SJ, Crone NE. Changes in human brain dynamics during behavioral priming and repetition suppression. Prog Neurobiol 2020; 189:101788. [PMID: 32198060 DOI: 10.1016/j.pneurobio.2020.101788] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [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: 05/22/2019] [Revised: 01/13/2020] [Accepted: 03/13/2020] [Indexed: 11/29/2022]
Abstract
Behavioral responses to a perceptual stimulus are typically faster with repeated exposure to the stimulus (behavioral priming). This implicit learning mechanism is critical for survival but impaired in a variety of neurological disorders, including Alzheimer's disease. Many studies of the neural bases for behavioral priming have encountered an interesting paradox: in spite of faster behavioral responses, repeated stimuli usually elicit weaker neural responses (repetition suppression). Several neurophysiological models have been proposed to resolve this paradox, but noninvasive techniques for human studies have had insufficient spatial-temporal precision for testing their predictions. Here, we used the unparalleled precision of electrocorticography (ECoG) to analyze the timing and magnitude of task-related changes in neural activation and propagation while patients named novel vs repeated visual objects. Stimulus repetition was associated with faster verbal responses and decreased neural activation (repetition suppression) in ventral occipito-temporal cortex (VOTC) and left prefrontal cortex (LPFC). Interestingly, we also observed increased neural activation (repetition enhancement) in LPFC and other recording sites. Moreover, with analysis of high gamma propagation we observed increased top-down propagation from LPFC into VOTC, preceding repetition suppression. The latter results indicate that repetition suppression and behavioral priming are associated with strengthening of top-down network influences on perceptual processing, consistent with predictive coding models of repetition suppression, and they support a central role for changes in large-scale cortical dynamics in achieving more efficient and rapid behavioral responses.
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Affiliation(s)
- Anna Korzeniewska
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, 21287, USA.
| | - Yujing Wang
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, 21287, USA
| | - Heather L Benz
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, 21287, USA
| | - Matthew S Fifer
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, 21287, USA
| | - Max Collard
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, 21287, USA
| | - Griffin Milsap
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, 21287, USA
| | - Mackenzie C Cervenka
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, 21287, USA
| | - Alex Martin
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, Maryland, 20852, USA
| | - Stephen J Gotts
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, Maryland, 20852, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, 21287, USA
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33
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McAuliffe D, Hirabayashi K, Adamek JH, Luo Y, Crocetti D, Pillai AS, Zhao Y, Crone NE, Mostofsky SH, Ewen JB. Increased mirror overflow movements in ADHD are associated with altered EEG alpha/beta band desynchronization. Eur J Neurosci 2019; 51:1815-1826. [PMID: 31821643 DOI: 10.1111/ejn.14642] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 11/14/2019] [Accepted: 12/06/2019] [Indexed: 02/02/2023]
Abstract
Children with ADHD show developmentally abnormal levels of mirror overflow-unintentional movements occurring symmetrically opposite of intentional movements. Because mirror overflow correlates with ADHD behavioral symptoms, the study of disinhibition in motor control may shed light on physiologic mechanisms underlying impaired behavioral/cognitive control. This is a case-controlled study of EEG recording from 25 children with ADHD and 25 typically developing (TD) controls performing unilateral sequential finger tapping, with overflow movements measured using electronic goniometers. Consistent with previously published findings, children with ADHD showed increased mirror overflow as compared with TD peers. EEG findings revealed less lateralized alpha modulation (event-related desynchronization; ERD) and decreased magnitude of beta ERD in ADHD; both alpha and beta ERD reflect cortical activation. Moderation analysis revealed a significant association between beta ERD and overflow, independent of diagnosis; and an equivocal (p = .08) effect of diagnosis on the relationship between alpha ERD and overflow, with a significant effect in children with ADHD but not TD children. These results suggest two mechanisms involved with mirror overflow: one reflected in beta ipsilateral to the intentional movement and relevant to both children with ADHD and controls, and the other seemingly more specific to ADHD (alpha, contralateral to movement).
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Affiliation(s)
| | | | | | - Yu Luo
- Kennedy Krieger Institute, Baltimore, MD, USA.,Beihan University, Beijing, China
| | | | - Ajay S Pillai
- Kennedy Krieger Institute, Baltimore, MD, USA.,Johns Hopkins University, Baltimore, MD, USA
| | - Yi Zhao
- Johns Hopkins University, Baltimore, MD, USA
| | | | - Stewart H Mostofsky
- Kennedy Krieger Institute, Baltimore, MD, USA.,Johns Hopkins University, Baltimore, MD, USA
| | - Joshua B Ewen
- Kennedy Krieger Institute, Baltimore, MD, USA.,Johns Hopkins University, Baltimore, MD, USA
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34
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Babajani-Feremi A, Wheless JW, Papanicolaou JW, Wang Y, Fifer MS, Flinker A, Korzeniewska A, Cervenka MC, Anderson WS, Boatman-Reich DF, Crone NE. Spatial-temporal functional mapping of language at the bedside with electrocorticography. Neurology 2019; 87:2604. [PMID: 27956570 DOI: 10.1212/01.wnl.0000511287.40052.8d] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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35
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Milsap G, Collard M, Coogan C, Rabbani Q, Wang Y, Crone NE. Keyword Spotting Using Human Electrocorticographic Recordings. Front Neurosci 2019; 13:60. [PMID: 30837823 PMCID: PMC6389788 DOI: 10.3389/fnins.2019.00060] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Accepted: 01/21/2019] [Indexed: 11/13/2022] Open
Abstract
Neural keyword spotting could form the basis of a speech brain-computer-interface for menu-navigation if it can be done with low latency and high specificity comparable to the “wake-word” functionality of modern voice-activated AI assistant technologies. This study investigated neural keyword spotting using motor representations of speech via invasively-recorded electrocorticographic signals as a proof-of-concept. Neural matched filters were created from monosyllabic consonant-vowel utterances: one keyword utterance, and 11 similar non-keyword utterances. These filters were used in an analog to the acoustic keyword spotting problem, applied for the first time to neural data. The filter templates were cross-correlated with the neural signal, capturing temporal dynamics of neural activation across cortical sites. Neural vocal activity detection (VAD) was used to identify utterance times and a discriminative classifier was used to determine if these utterances were the keyword or non-keyword speech. Model performance appeared to be highly related to electrode placement and spatial density. Vowel height (/a/ vs /i/) was poorly discriminated in recordings from sensorimotor cortex, but was highly discriminable using neural features from superior temporal gyrus during self-monitoring. The best performing neural keyword detection (5 keyword detections with two false-positives across 60 utterances) and neural VAD (100% sensitivity, ~1 false detection per 10 utterances) came from high-density (2 mm electrode diameter and 5 mm pitch) recordings from ventral sensorimotor cortex, suggesting the spatial fidelity and extent of high-density ECoG arrays may be sufficient for the purpose of speech brain-computer-interfaces.
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Affiliation(s)
- Griffin Milsap
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Maxwell Collard
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Christopher Coogan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Qinwan Rabbani
- Department of Electrical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Yujing Wang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Fischell Department of Bioengineering, University of Maryland College Park, College Park, MD, United States
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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36
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Milsap G, Collard M, Coogan C, Crone NE. BCI2000Web and WebFM: Browser-Based Tools for Brain Computer Interfaces and Functional Brain Mapping. Front Neurosci 2019; 12:1030. [PMID: 30814923 PMCID: PMC6381053 DOI: 10.3389/fnins.2018.01030] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Accepted: 12/19/2018] [Indexed: 11/09/2022] Open
Abstract
BCI2000 has been a popular platform for development of real-time brain computer interfaces (BCIs). Since BCI2000's initial release, web browsers have evolved considerably, enabling rapid development of internet-enabled applications and interactive visualizations. Linking the amplifier abstraction and signal processing native to BCI2000 with the host of technologies and ease of development afforded by modern web browsers could enable a new generation of browser-based BCIs and visualizations. We developed a server and filter module called BCI2000Web providing an HTTP connection capable of escalation into an RFC6455 WebSocket, which enables direct communication between a browser and a BCI2000 distribution in real-time, facilitating a number of novel applications. We also present a JavaScript module, bci2k.js, that allows web developers to create paradigms and visualizations using this interface in an easy-to-use and intuitive manner. To illustrate the utility of BCI2000Web, we demonstrate a browser-based implementation of a real-time electrocorticographic (ECoG) functional mapping suite called WebFM. We also explore how the unique characteristics of our browser-based framework make BCI2000Web an attractive tool for future BCI applications. BCI2000Web leverages the advances of BCI2000 to provide real-time browser-based interactions with human neurophysiological recordings, allowing for web-based BCIs and other applications, including real-time functional brain mapping. Both BCI2000 and WebFM are provided under open source licenses. Enabling a powerful BCI suite to communicate with today's most technologically progressive software empowers a new cohort of developers to engage with BCI technology, and could serve as a platform for internet-enabled BCIs.
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Affiliation(s)
- Griffin Milsap
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Max Collard
- Department of Neurology, Johns Hopkins Universit, Baltimore, MD, United States
| | - Christopher Coogan
- Department of Neurology, Johns Hopkins Universit, Baltimore, MD, United States
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins Universit, Baltimore, MD, United States
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Arya R, Roth C, Leach JL, Middeler D, Wilson JA, Vannest J, Rozhkov L, Greiner HM, Buroker J, Scholle C, Fujiwara H, Horn PS, Rose DF, Crone NE, Mangano FT, Byars AW, Holland KD. Neuropsychological outcomes after resection of cortical sites with visual naming associated electrocorticographic high-gamma modulation. Epilepsy Res 2019; 151:17-23. [PMID: 30721879 DOI: 10.1016/j.eplepsyres.2019.01.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 10/24/2018] [Accepted: 01/28/2019] [Indexed: 11/16/2022]
Abstract
BACKGROUND Language mapping with high-gamma modulation (HGM) has compared well with electrical cortical stimulation mapping (ESM). However, there is limited prospective data about its functional validity. We compared changes in neuropsychological evaluation (NPE) performed before and 1-year after epilepsy surgery, between patients with/without resection of cortical sites showing HGM during a visual naming task. METHODS Pediatric drug-resistant epilepsy (DRE) patients underwent pre-surgical language localization with ESM and HGM using a visual naming task. Surgical decisions were based solely on ESM results. NPE difference scores were compared between patients with/without resection of HGM naming sites using principal component (PC) analysis. Follow-up NPE scores were modeled with resection group as main effect and respective pre-surgical score as a covariate, using analysis of covariance. RESULTS Seventeen native English speakers (12 females), aged 6.5-20.2 years, were included. One year after epilepsy surgery, first PC score increased by (mean ± standard deviation) 14.4 ± 16.5 points in patients without resection, whereas it decreased by 7.6 ± 24.6 points in those with resection of HGM naming sites (p = 0.040). This PC score represented verbal comprehension, working memory, perceptual reasoning (Wechsler subscales); Woodcock-Johnson Tests of Achievement; and Peabody Picture Vocabulary Test. Subsequent analysis showed significant difference in working memory score between patients with/without resection of HGM naming sites (-15.2 points, 95% confidence limits -29.7 to -0.7, p = 0.041). CONCLUSION We highlight the functional consequences of resecting HGM language sites, and suggest that NPE of DRE patients should include comprehensive assessment of multiple linguistic and cognitive domains besides naming ability.
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Affiliation(s)
- Ravindra Arya
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
| | - Celie Roth
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - James L Leach
- Division of Pediatric Neuroradiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Denise Middeler
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - J Adam Wilson
- Pediatric Neuroimaging Research Consortium, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Jennifer Vannest
- Pediatric Neuroimaging Research Consortium, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Leonid Rozhkov
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Hansel M Greiner
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Jason Buroker
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Division of Clinical Engineering, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Craig Scholle
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Division of Clinical Engineering, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Hisako Fujiwara
- Pediatric Neuroimaging Research Consortium, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Paul S Horn
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Douglas F Rose
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Francesco T Mangano
- Division of Pediatric Neurosurgery, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Anna W Byars
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Katherine D Holland
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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Thomas TM, Candrea DN, Fifer MS, McMullen DP, Anderson WS, Thakor NV, Crone NE. Decoding Native Cortical Representations for Flexion and Extension at Upper Limb Joints Using Electrocorticography. IEEE Trans Neural Syst Rehabil Eng 2019; 27:293-303. [PMID: 30624221 DOI: 10.1109/tnsre.2019.2891362] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Brain-machine interface (BMI) researchers have traditionally focused on modeling endpoint reaching tasks to provide the control of neurally driven prosthetic arms. Most previous research has focused on achieving an endpoint control through a Cartesian-coordinate-centered approach. However, a joint-centered approach could potentially be used to intuitively control a wide range of limb movements. We systematically investigated the feasibility of discriminating between flexion and extension of different upper limb joints using electrocorticography(ECoG) recordings from sensorimotor cortex. Four subjects implanted with macro-ECoG (10-mm spacing), high-density ECoG (5-mm spacing), and/or micro-ECoG arrays (0.9-mm spacing and 4 mm × 4 mm coverage), performed randomly cued flexions or extensions of the fingers, wrist, or elbow contralateral to the implanted hemisphere. We trained a linear model to classify six movements using averaged high-gamma power (70-110 Hz) modulations at different latencies with respect to movement onset, and within a time interval restricted to flexion or extension at each joint. Offline decoding models for each subject classified these movements with accuracies of 62%-83%. Our results suggest that the widespread ECoG coverage of sensorimotor cortex could allow a whole limb BMI to sample native cortical representations in order to control flexion and extension at multiple joints.
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Abstract
A brain-computer interface (BCI) is a technology that uses neural features to restore or augment the capabilities of its user. A BCI for speech would enable communication in real time via neural correlates of attempted or imagined speech. Such a technology would potentially restore communication and improve quality of life for locked-in patients and other patients with severe communication disorders. There have been many recent developments in neural decoders, neural feature extraction, and brain recording modalities facilitating BCI for the control of prosthetics and in automatic speech recognition (ASR). Indeed, ASR and related fields have developed significantly over the past years, and many lend many insights into the requirements, goals, and strategies for speech BCI. Neural speech decoding is a comparatively new field but has shown much promise with recent studies demonstrating semantic, auditory, and articulatory decoding using electrocorticography (ECoG) and other neural recording modalities. Because the neural representations for speech and language are widely distributed over cortical regions spanning the frontal, parietal, and temporal lobes, the mesoscopic scale of population activity captured by ECoG surface electrode arrays may have distinct advantages for speech BCI, in contrast to the advantages of microelectrode arrays for upper-limb BCI. Nevertheless, there remain many challenges for the translation of speech BCIs to clinical populations. This review discusses and outlines the current state-of-the-art for speech BCI and explores what a speech BCI using chronic ECoG might entail.
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Affiliation(s)
- Qinwan Rabbani
- Department of Electrical Engineering, The Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USA.
| | - Griffin Milsap
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Gutierrez EG, Crone NE, Kang JY, Carmenate YI, Krauss GL. Strategies for non-EEG seizure detection and timing for alerting and interventions with tonic-clonic seizures. Epilepsia 2018; 59 Suppl 1:36-41. [DOI: 10.1111/epi.14046] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/13/2017] [Indexed: 01/02/2023]
Affiliation(s)
| | - Nathan E. Crone
- Department of Neurology; Johns Hopkins University; Baltimore MD USA
| | - Joon Y. Kang
- Department of Neurology; Johns Hopkins University; Baltimore MD USA
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Kelley SA, Robinson S, Crone NE, Soares BP. Bottom-of-sulcus focal cortical dysplasia presenting as epilepsia partialis continua multimodality characterization including 7T MRI. Childs Nerv Syst 2018; 34:1267-1269. [PMID: 29445916 DOI: 10.1007/s00381-018-3749-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2017] [Accepted: 02/04/2018] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Bottom-of-sulcus focal cortical dysplasias are an under recognized, surgically treatable cause of focal epilepsy. Resection can dramatically reduce the seizure burden for children with refractory epilepsy, or eliminate seizures altogether. MATERIAL AND METHODS We report the case and present the results of multimodality evaluation of a 15-year-old young man who presented with long-standing partial epilepsy affecting his right leg, which over the years became refractory to therapy. RESULTS High-resolution 3T MRI images acquired as a dedicated epilepsyprotocol were initially interpreted as unremarkable. On further review by an experienced specialist aware of clinical and electroencephalographic findings, a subtle focal cortical dysplasia was identified at the bottom of a sulcus near the medial aspect of the left precentral gyrus. After confirmation of the extent of the lesion with PET and ultra-high field 7T MRI, the patient underwent cortical mapping and focal resection and remains free of seizures. COCLUSIONS This case emphasizes the need for a multidisciplinary approach to the evaluation of refractory focal epilepsy in children and highlights the potential role of ultra-high field 7T MRI in identifying the often subtle causative anatomic abnormalities.
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Affiliation(s)
- Sarah A Kelley
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Shenandoah Robinson
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Bruno P Soares
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 1800 Orleans Street, Zayed Tower, Room 4174, Baltimore, MD, 21287, USA.
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Arya R, Crone NE. Electrocorticographic high-gamma language mapping: Limitations of comparisons with electrocortical stimulation. Epilepsy Behav 2018; 82:200-201. [PMID: 29576436 DOI: 10.1016/j.yebeh.2018.02.017] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Accepted: 02/18/2018] [Indexed: 10/17/2022]
Affiliation(s)
- Ravindra Arya
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
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Goldenholz DM, Moss R, Jost DA, Crone NE, Krauss G, Picard R, Caborni C, Cavazos JE, Hixson J, Loddenkemper T, Salazar TD, Lubbers L, Harte-Hargrove LC, Whittemore V, Duun-Henriksen J, Dolan E, Kasturia N, Oberemk M, Cook MJ, Lehmkuhle M, Sperling MR, Shafer PO. Common data elements for epilepsy mobile health systems. Epilepsia 2018; 59:1020-1026. [PMID: 29604050 DOI: 10.1111/epi.14066] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/28/2018] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Common data elements (CDEs) are currently unavailable for mobile health (mHealth) in epilepsy devices and related applications. As a result, despite expansive growth of new digital services for people with epilepsy, information collected is often not interoperable or directly comparable. We aim to correct this problem through development of industry-wide standards for mHealth epilepsy data. METHODS Using a group of stakeholders from industry, academia, and patient advocacy organizations, we offer a consensus statement for the elements that may facilitate communication among different systems. RESULTS A consensus statement is presented for epilepsy mHealth CDEs. SIGNIFICANCE Although it is not exclusive, we believe that the use of a minimal common information denominator, specifically these CDEs, will promote innovation, accelerate scientific discovery, and enhance clinical usage across applications and devices in the epilepsy mHealth space. As a consequence, people with epilepsy will have greater flexibility and ultimately more powerful tools to improve their lives.
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Affiliation(s)
- Daniel M Goldenholz
- Division of Epilepsy, Beth Israel Deaconess Medical Center, Boston, MA, USA.,Clinical Epilepsy Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | | | - David A Jost
- Digital Strategy, Epilepsy Foundation, Landover, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Gregory Krauss
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Rosalind Picard
- Empatica, Milan, Italy.,Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Jose E Cavazos
- Brain Sentinel, San Antonio, TX, USA.,Department of Neurology, University of Texas Health San Antonio, San Antonio, TX, USA
| | - John Hixson
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Tobias Loddenkemper
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | | | - Laura Lubbers
- Citizens United for Research in Epilepsy, Chicago, IL, USA
| | | | - Vicky Whittemore
- Extramural Program Office, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Rockville, MD, USA
| | | | - Eric Dolan
- Neutun Labs, BMOS, Toronto, Ontario, Canada
| | | | | | - Mark J Cook
- Department of Neurology, University of Melbourne, Parkville, Victoria, Australia
| | | | - Michael R Sperling
- Department of Neurology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Patricia O Shafer
- Division of Epilepsy, Beth Israel Deaconess Medical Center, Boston, MA, USA.,Digital Strategy, Epilepsy Foundation, Landover, MD, USA
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Arya R, Wilson JA, Fujiwara H, Vannest J, Byars AW, Rozhkov L, Leach JL, Greiner HM, Buroker J, Scholle C, Horn PS, Crone NE, Rose DF, Mangano FT, Holland KD. Electrocorticographic high-gamma modulation with passive listening paradigm for pediatric extraoperative language mapping. Epilepsia 2018; 59:792-801. [PMID: 29460482 DOI: 10.1111/epi.14029] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/24/2018] [Indexed: 11/30/2022]
Abstract
OBJECTIVE This prospective study compared the topography of high-gamma modulation (HGM) during a story-listening task requiring negligible patient cooperation, with the conventional electrical stimulation mapping (ESM) using a picture-naming task, for presurgical language localization in pediatric drug-resistant epilepsy. METHODS Patients undergoing extraoperative monitoring with subdural electrodes were included. Electrocorticographic signals were recorded during quiet baseline and a story-listening task. The likelihood of 70- to 150-Hz power modulation during the listening task relative to the baseline was estimated for each electrode and plotted on a cortical surface model. Sensitivity, specificity, accuracy, and diagnostic odds ratio (DOR) were estimated compared to ESM, using a meta-analytic framework. RESULTS Nineteen patients (10 with left hemisphere electrodes) aged 4-19 years were analyzed. HGM during story listening was observed in bilateral posterior superior temporal, angular, supramarginal, and inferior frontal gyri, along with anatomically defined language association areas. Compared to either cognitive or both cognitive and orofacial sensorimotor interference with naming during ESM, left hemisphere HGM showed high specificity (0.82-0.84), good accuracy (0.66-0.70), and DOR of 2.23 and 3.24, respectively. HGM was a better classifier of ESM language sites in the left temporoparietal cortex compared to the frontal lobe. Incorporating visual naming with the story-listening task substantially improved the accuracy (0.80) and DOR (13.61) of HGM mapping, while the high specificity (0.85) was retained. In the right hemisphere, no ESM sites for aphasia were seen, and the results of HGM and ESM comparisons were not significant. SIGNIFICANCE HGM associated with story listening is a specific determinant of left hemisphere ESM language sites. It can be used for presurgical language mapping in children who cannot cooperate with conventional language tasks requiring active engagement. Incorporation of additional language tasks, if feasible, can further improve the diagnostic accuracy of language localization with HGM.
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Affiliation(s)
- Ravindra Arya
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - J Adam Wilson
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.,Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Hisako Fujiwara
- Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Jennifer Vannest
- Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Anna W Byars
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Leonid Rozhkov
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - James L Leach
- Division of Pediatric Neuroradiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Hansel M Greiner
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Jason Buroker
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.,Division of Clinical Engineering, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Craig Scholle
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.,Division of Clinical Engineering, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Paul S Horn
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Douglas F Rose
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Francesco T Mangano
- Division of Pediatric Neurosurgery, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Katherine D Holland
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
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Pillai AS, McAuliffe D, Lakshmanan BM, Mostofsky SH, Crone NE, Ewen JB. Altered task-related modulation of long-range connectivity in children with autism. Autism Res 2018; 11:245-257. [PMID: 28898569 PMCID: PMC5825245 DOI: 10.1002/aur.1858] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [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: 12/29/2016] [Revised: 07/19/2017] [Accepted: 08/14/2017] [Indexed: 11/07/2022]
Abstract
Functional connectivity differences between children with autism spectrum disorder (ASD) and typically developing children have been described in multiple datasets. However, few studies examine the task-related changes in connectivity in disorder-relevant behavioral paradigms. In this paper, we examined the task-related changes in functional connectivity using EEG and a movement-based paradigm that has behavioral relevance to ASD. Resting-state studies motivated our hypothesis that children with ASD would show a decreased magnitude of functional connectivity during the performance of a motor-control task. Contrary to our initial hypothesis, however, we observed that task-related modulation of functional connectivity in children with ASD was in the direction opposite to that of TDs. The task-related connectivity changes were correlated with clinical symptom scores. Our results suggest that children with ASD may have differences in cortical segregation/integration during the performance of a task, and that part of the differences in connectivity modulation may serve as a compensatory mechanism. Autism Res 2018, 11: 245-257. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY Decreased connectivity between brain regions is thought to cause the symptoms of autism. Because most of our knowledge comes from data in which children are at rest, we do not know how connectivity changes directly lead to autistic behaviors, such as impaired gestures. When typically developing children produced complex movements, connectivity decreased between brain regions. In children with autism, connectivity increased. It may be that behavior-related changes in brain connectivity are more important than absolute differences in connectivity in autism.
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Affiliation(s)
- Ajay S Pillai
- Department of Neurology and Developmental Medicine, Kennedy Krieger Institute, Baltimore, MD
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Danielle McAuliffe
- Department of Neurology and Developmental Medicine, Kennedy Krieger Institute, Baltimore, MD
| | - Balaji M Lakshmanan
- Department of Neurology and Developmental Medicine, Kennedy Krieger Institute, Baltimore, MD
| | - Stewart H Mostofsky
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Joshua B Ewen
- Department of Neurology and Developmental Medicine, Kennedy Krieger Institute, Baltimore, MD
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD
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Kam JWY, Szczepanski SM, Canolty RT, Flinker A, Auguste KI, Crone NE, Kirsch HE, Kuperman RA, Lin JJ, Parvizi J, Knight RT. Differential Sources for 2 Neural Signatures of Target Detection: An Electrocorticography Study. Cereb Cortex 2018; 28:9-20. [PMID: 29253249 PMCID: PMC6454481 DOI: 10.1093/cercor/bhw343] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [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: 03/13/2016] [Revised: 10/17/2016] [Accepted: 10/22/2016] [Indexed: 11/14/2022] Open
Abstract
Electrophysiology and neuroimaging provide conflicting evidence for the neural contributions to target detection. Scalp electroencephalography (EEG) studies localize the P3b event-related potential component mainly to parietal cortex, whereas neuroimaging studies report activations in both frontal and parietal cortices. We addressed this discrepancy by examining the sources that generate the target-detection process using electrocorticography (ECoG). We recorded ECoG activity from cortex in 14 patients undergoing epilepsy monitoring, as they performed an auditory or visual target-detection task. We examined target-related responses in 2 domains: high frequency band (HFB) activity and the P3b. Across tasks, we observed a greater proportion of electrodes that showed target-specific HFB power relative to P3b over frontal cortex, but their proportions over parietal cortex were comparable. Notably, there was minimal overlap in the electrodes that showed target-specific HFB and P3b activity. These results revealed that the target-detection process is characterized by at least 2 different neural markers with distinct cortical distributions. Our findings suggest that separate neural mechanisms are driving the differential patterns of activity observed in scalp EEG and neuroimaging studies, with the P3b reflecting EEG findings and HFB activity reflecting neuroimaging findings, highlighting the notion that target detection is not a unitary phenomenon.
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Affiliation(s)
- J W Y Kam
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - S M Szczepanski
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - R T Canolty
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - A Flinker
- Department of Psychology, New York University, New York, NY 10012, USA
| | - K I Auguste
- Department of Surgery, Division of Neurological Surgery, Children's Hospital and Research Center, Oakland, CA 94609, USA
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - N E Crone
- Department of Neurology, Epilepsy Center, Johns Hopkins Medical Institutions, Baltimore, MD 21224, USA
| | - H E Kirsch
- Department of Neurology, Division of Epilepsy and Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, USA
| | - R A Kuperman
- Department of Neurology, Children's Hospital and Research Center, Oakland, CA 94609, USA
| | - J J Lin
- Department of Neurology, University of California, Irvine, Irvine, CA 92697, USA
| | - J Parvizi
- Laboratory of Behavioral and Cognitive Neurology, Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
- Human Intracranial Cognitive Electrophysiology Program (SHICEP), Stanford University, Stanford, CA 94305, USA
| | - R T Knight
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
- Department of Psychology, University of California, Berkeley, Berkeley, CA 94720, USA
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Haller M, Case J, Crone NE, Chang EF, King-Stephens D, Laxer KD, Weber PB, Parvizi J, Knight RT, Shestyuk AY. Persistent neuronal activity in human prefrontal cortex links perception and action. Nat Hum Behav 2017; 2:80-91. [PMID: 29963646 PMCID: PMC6022844 DOI: 10.1038/s41562-017-0267-2] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [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] [Indexed: 12/15/2022]
Abstract
How do humans flexibly respond to changing environmental demands on a sub-second temporal scale? Extensive research has highlighted the key role of the prefrontal cortex in flexible decision-making and adaptive behavior, yet the core mechanisms that translate sensory information into behavior remain undefined. Utilizing direct human cortical recordings, we investigated the temporal and spatial evolution of neuronal activity, indexed by the broadband gamma signal, while sixteen participants performed a broad range of self-paced cognitive tasks. Here we describe a robust domain- and modality-independent pattern of persistent stimulus-to-response neural activation that encodes stimulus features and predicts motor output on a trial-by-trial basis with near-perfect accuracy. Observed across a distributed network of brain areas, this persistent neural activation is centered in the prefrontal cortex and is required for successful response implementation, providing a functional substrate for domain-general transformation of perception into action, critical for flexible behavior.
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Affiliation(s)
- Matar Haller
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - John Case
- Department of Psychology, University of California, Berkeley, CA, USA
| | - Nathan E Crone
- Department of Neurology, The Johns Hopkins University Medical School, Baltimore, MD, USA
| | - Edward F Chang
- Departments of Neurological Surgery, UCSF Center for Integrative Neuroscience, University of California, San Francisco, CA, USA
| | - David King-Stephens
- Department of Neurology and Neurosurgery, California Pacific Medical Center, San Francisco, CA, USA
| | - Kenneth D Laxer
- Department of Neurology and Neurosurgery, California Pacific Medical Center, San Francisco, CA, USA
| | - Peter B Weber
- Department of Neurology and Neurosurgery, California Pacific Medical Center, San Francisco, CA, USA
| | - Josef Parvizi
- Stanford Human Intracranial Cognitive Electrophysiology Program (SHICEP), Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Robert T Knight
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.,Department of Psychology, University of California, Berkeley, CA, USA
| | - Avgusta Y Shestyuk
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.
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Zea Vera A, Aungaroon G, Horn PS, Byars AW, Greiner HM, Tenney JR, Arthur TM, Crone NE, Holland KD, Mangano FT, Arya R. Language and motor function thresholds during pediatric extra-operative electrical cortical stimulation brain mapping. Clin Neurophysiol 2017; 128:2087-2093. [PMID: 28774583 DOI: 10.1016/j.clinph.2017.07.006] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [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: 05/11/2017] [Revised: 07/03/2017] [Accepted: 07/11/2017] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To examine current thresholds and their determinants for language and motor mapping with extra-operative electrical cortical stimulation (ECS). METHODS ECS electrocorticograph recordings were reviewed to determine functional thresholds. Predictors of functional thresholds were found with multivariable analyses. RESULTS In 122 patients (age 11.9±5.4years), average minimum, frontal, and temporal language thresholds were 7.4 (± 3.0), 7.8 (± 3.0), and 7.4 (± 3.1) mA respectively. Average minimum, face, upper and lower extremity motor thresholds were 5.4 (± 2.8), 6.1 (± 2.8), 4.9 (± 2.3), and 5.3 (± 3.3) mA respectively. Functional and after-discharge (AD)/seizure thresholds were significantly related. Minimum, frontal, and temporal language thresholds were higher than AD thresholds at all ages. Minimum motor threshold was higher than minimum AD threshold up to 8.0years of age, face motor threshold was higher than frontal AD threshold up to 11.8years age, and lower subsequently. UE motor thresholds remained below frontal AD thresholds throughout the age range. CONCLUSIONS Functional thresholds are frequently above AD thresholds in younger children. SIGNIFICANCE These findings raise concerns about safety and neurophysiologic validity of ECS mapping. Functional and AD/seizure thresholds relationships suggest individual differences in cortical excitability which cannot be explained by clinical variables.
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Affiliation(s)
- Alonso Zea Vera
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Gewalin Aungaroon
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Paul S Horn
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Anna W Byars
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Hansel M Greiner
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Jeffrey R Tenney
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Todd M Arthur
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Katherine D Holland
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Francesco T Mangano
- Division of Pediatric Neurosurgery, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Ravindra Arya
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
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Aungaroon G, Zea Vera A, Horn PS, Byars AW, Greiner HM, Tenney JR, Arthur TM, Crone NE, Holland KD, Mangano FT, Arya R. After-discharges and seizures during pediatric extra-operative electrical cortical stimulation functional brain mapping: Incidence, thresholds, and determinants. Clin Neurophysiol 2017; 128:2078-2086. [PMID: 28778475 DOI: 10.1016/j.clinph.2017.06.259] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [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: 05/11/2017] [Revised: 06/27/2017] [Accepted: 06/30/2017] [Indexed: 11/29/2022]
Abstract
OBJECTIVE This study examined the incidence, thresholds, and determinants of electrical cortical stimulation (ECS)-induced after-discharges (ADs) and seizures. METHODS Electrocorticograph recordings were reviewed to determine incidence of ECS-induced ADs and seizures. Multivariable analyses for predictors of AD/seizure occurrence and their thresholds were performed. RESULTS In 122 patients, the incidence of ADs and seizures was 77% (94/122) and 35% (43/122) respectively. Males (odds ratio [OR] 2.92, 95% CI 1.21-7.38, p=0.02) and MRI-negative patients (OR 3.69, 95% CI 1.24-13.7, p=0.03) were found to have higher odds of ECS-induced ADs. A significant trend for decreasing AD thresholds with age was seen (regression co-efficient -0.151, 95% CI -0.267 to -0.035, p=0.011). ECS-induced seizures were more likely in patients with lateralized functional imaging (OR 6.62, 95% CI 1.36-55.56, p=0.036, for positron emission tomography) and presence of ADs (OR 3.50, 95% CI 1.12-13.36, p=0.043). CONCLUSIONS ECS is associated with a high incidence of ADs and seizures. With age, current thresholds decrease and the probability for AD/seizure occurrence increases. SIGNIFICANCE ADs and seizures during ECS brain mapping are potentially hazardous and affect its functional validity. Thus, safer method(s) for brain mapping with improved neurophysiologic validity are desirable.
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Affiliation(s)
- Gewalin Aungaroon
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Alonso Zea Vera
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Paul S Horn
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Division of Epidemiology and Biostatistics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Anna W Byars
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Hansel M Greiner
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Jeffrey R Tenney
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Todd M Arthur
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Katherine D Holland
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Francesco T Mangano
- Division of Pediatric Neurosurgery, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Ravindra Arya
- Comprehensive Epilepsy Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
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Caceres CA, Roos MJ, Rupp KM, Milsap G, Crone NE, Wolmetz ME, Ratto CR. Feature Selection Methods for Zero-Shot Learning of Neural Activity. Front Neuroinform 2017; 11:41. [PMID: 28690513 PMCID: PMC5481359 DOI: 10.3389/fninf.2017.00041] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Accepted: 06/07/2017] [Indexed: 11/13/2022] Open
Abstract
Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.
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Affiliation(s)
- Carlos A Caceres
- Applied Physics Laboratory, Johns Hopkins UniversityLaurel, MD, United States
| | - Matthew J Roos
- Applied Physics Laboratory, Johns Hopkins UniversityLaurel, MD, United States
| | - Kyle M Rupp
- Department of Biomedical Engineering, Johns Hopkins UniversityBaltimore, MD, United States
| | - Griffin Milsap
- Department of Biomedical Engineering, Johns Hopkins UniversityBaltimore, MD, United States
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins MedicineBaltimore, MD, United States
| | - Michael E Wolmetz
- Applied Physics Laboratory, Johns Hopkins UniversityLaurel, MD, United States
| | - Christopher R Ratto
- Applied Physics Laboratory, Johns Hopkins UniversityLaurel, MD, United States
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