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Ding K, Rakhshan M, Paredes-Acuña N, Cheng G, Thakor NV. Sensory integration for neuroprostheses: from functional benefits to neural correlates. Med Biol Eng Comput 2024:10.1007/s11517-024-03118-8. [PMID: 38760597 DOI: 10.1007/s11517-024-03118-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 04/19/2024] [Indexed: 05/19/2024]
Abstract
In the field of sensory neuroprostheses, one ultimate goal is for individuals to perceive artificial somatosensory information and use the prosthesis with high complexity that resembles an intact system. To this end, research has shown that stimulation-elicited somatosensory information improves prosthesis perception and task performance. While studies strive to achieve sensory integration, a crucial phenomenon that entails naturalistic interaction with the environment, this topic has not been commensurately reviewed. Therefore, here we present a perspective for understanding sensory integration in neuroprostheses. First, we review the engineering aspects and functional outcomes in sensory neuroprosthesis studies. In this context, we summarize studies that have suggested sensory integration. We focus on how they have used stimulation-elicited percepts to maximize and improve the reliability of somatosensory information. Next, we review studies that have suggested multisensory integration. These works have demonstrated that congruent and simultaneous multisensory inputs provided cognitive benefits such that an individual experiences a greater sense of authority over prosthesis movements (i.e., agency) and perceives the prosthesis as part of their own (i.e., ownership). Thereafter, we present the theoretical and neuroscience framework of sensory integration. We investigate how behavioral models and neural recordings have been applied in the context of sensory integration. Sensory integration models developed from intact-limb individuals have led the way to sensory neuroprosthesis studies to demonstrate multisensory integration. Neural recordings have been used to show how multisensory inputs are processed across cortical areas. Lastly, we discuss some ongoing research and challenges in achieving and understanding sensory integration in sensory neuroprostheses. Resolving these challenges would help to develop future strategies to improve the sensory feedback of a neuroprosthetic system.
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Affiliation(s)
- Keqin Ding
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA.
| | - Mohsen Rakhshan
- Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, 32816, USA
- Disability, Aging, and Technology Cluster, University of Central Florida, Orlando, FL, 32816, USA
| | - Natalia Paredes-Acuña
- Institute for Cognitive Systems, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
| | - Gordon Cheng
- Institute for Cognitive Systems, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
| | - Nitish V Thakor
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
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Bao S, Wang Y, Escalante YR, Li Y, Lei Y. Modulation of Motor Cortical Inhibition and Facilitation by Touch Sensation from the Glabrous Skin of the Human Hand. eNeuro 2024; 11:ENEURO.0410-23.2024. [PMID: 38443196 PMCID: PMC10915462 DOI: 10.1523/eneuro.0410-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 03/07/2024] Open
Abstract
Touch sensation from the glabrous skin of the hand is essential for precisely controlling dexterous movements, yet the neural mechanisms by which tactile inputs influence motor circuits remain largely unexplored. By pairing air-puff tactile stimulation on the hand's glabrous skin with transcranial magnetic stimulation (TMS) over the primary motor cortex (M1), we examined the effects of tactile stimuli from single or multiple fingers on corticospinal excitability and M1's intracortical circuits. Our results showed that when we targeted the hand's first dorsal interosseous (FDI) muscle with TMS, homotopic (index finger) tactile stimulation, regardless of its point (fingertip or base), reduced corticospinal excitability. Conversely, heterotopic (ring finger) tactile stimulation had no such effect. Notably, stimulating all five fingers simultaneously led to a more pronounced decrease in corticospinal excitability than stimulating individual fingers. Furthermore, tactile stimulation significantly increased intracortical facilitation (ICF) and decreased long-interval intracortical inhibition (LICI) but did not affect short-interval intracortical inhibition (SICI). Considering the significant role of the primary somatosensory cortex (S1) in tactile processing, we also examined the effects of downregulating S1 excitability via continuous theta burst stimulation (cTBS) on tactile-motor interactions. Following cTBS, the inhibitory influence of tactile inputs on corticospinal excitability was diminished. Our findings highlight the spatial specificity of tactile inputs in influencing corticospinal excitability. Moreover, we suggest that tactile inputs distinctly modulate M1's excitatory and inhibitory pathways, with S1 being crucial in facilitating tactile-motor integration.
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Affiliation(s)
- Shancheng Bao
- Program of Motor Neuroscience, Department of Kinesiology & Sport Management, Texas A&M University, College Station, Texas 77843
| | - Yiyu Wang
- Program of Motor Neuroscience, Department of Kinesiology & Sport Management, Texas A&M University, College Station, Texas 77843
| | - Yori R Escalante
- Program of Motor Neuroscience, Department of Kinesiology & Sport Management, Texas A&M University, College Station, Texas 77843
| | - Yue Li
- Department of Neuroscience & Experimental Therapeutics, Texas A&M University, College Station, Texas 77843
| | - Yuming Lei
- Program of Motor Neuroscience, Department of Kinesiology & Sport Management, Texas A&M University, College Station, Texas 77843
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Zhao ZP, Nie C, Jiang CT, Cao SH, Tian KX, Yu S, Gu JW. Modulating Brain Activity with Invasive Brain-Computer Interface: A Narrative Review. Brain Sci 2023; 13:brainsci13010134. [PMID: 36672115 PMCID: PMC9856340 DOI: 10.3390/brainsci13010134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/17/2022] [Accepted: 01/05/2023] [Indexed: 01/15/2023] Open
Abstract
Brain-computer interface (BCI) can be used as a real-time bidirectional information gateway between the brain and machines. In particular, rapid progress in invasive BCI, propelled by recent developments in electrode materials, miniature and power-efficient electronics, and neural signal decoding technologies has attracted wide attention. In this review, we first introduce the concepts of neuronal signal decoding and encoding that are fundamental for information exchanges in BCI. Then, we review the history and recent advances in invasive BCI, particularly through studies using neural signals for controlling external devices on one hand, and modulating brain activity on the other hand. Specifically, regarding modulating brain activity, we focus on two types of techniques, applying electrical stimulation to cortical and deep brain tissues, respectively. Finally, we discuss the related ethical issues concerning the clinical application of this emerging technology.
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Affiliation(s)
- Zhi-Ping Zhao
- School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Chuang Nie
- Strategic Support Force Medical Center, Beijing 100101, China
| | - Cheng-Teng Jiang
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Sheng-Hao Cao
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kai-Xi Tian
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shan Yu
- Brainnetome Center and National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, China
- Correspondence: (S.Y.); (J.-W.G.); Tel.: +86-010-8254-4786 (S.Y.); +86-010-6635-6729 (J.-W.G.)
| | - Jian-Wen Gu
- School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
- Strategic Support Force Medical Center, Beijing 100101, China
- Correspondence: (S.Y.); (J.-W.G.); Tel.: +86-010-8254-4786 (S.Y.); +86-010-6635-6729 (J.-W.G.)
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Nanivadekar AC, Chandrasekaran S, Helm ER, Boninger ML, Collinger JL, Gaunt RA, Fisher LE. Closed-loop stimulation of lateral cervical spinal cord in upper-limb amputees to enable sensory discrimination: a case study. Sci Rep 2022; 12:17002. [PMID: 36220864 PMCID: PMC9553970 DOI: 10.1038/s41598-022-21264-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 09/26/2022] [Indexed: 12/29/2022] Open
Abstract
Modern myoelectric prosthetic hands have multiple independently controllable degrees of freedom, but require constant visual attention to use effectively. Somatosensory feedback provides information not available through vision alone and is essential for fine motor control of our limbs. Similarly, stimulation of the nervous system can potentially provide artificial somatosensory feedback to reduce the reliance on visual cues to efficiently operate prosthetic devices. We have shown previously that epidural stimulation of the lateral cervical spinal cord can evoke tactile sensations perceived as emanating from the missing arm and hand in people with upper-limb amputation. In this case study, two subjects with upper-limb amputation used this somatotopically-matched tactile feedback to discriminate object size and compliance while controlling a prosthetic hand. With less than 30 min of practice each day, both subjects were able to use artificial somatosensory feedback to perform a subset of the discrimination tasks at a success level well above chance. Subject 1 was consistently more adept at determining object size (74% accuracy; chance: 33%) while Subject 2 achieved a higher accuracy level in determining object compliance (60% accuracy; chance 33%). In each subject, discrimination of the other object property was only slightly above or at chance level suggesting that the task design and stimulation encoding scheme are important determinants of which object property could be reliably identified. Our observations suggest that changes in the intensity of artificial somatosensory feedback provided via spinal cord stimulation can be readily used to infer information about object properties with minimal training.
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Affiliation(s)
- Ameya C. Nanivadekar
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.509981.c0000 0004 7644 8442Center for Neural Basis of Cognition, Pittsburgh, PA 15213 USA
| | - Santosh Chandrasekaran
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.509981.c0000 0004 7644 8442Center for Neural Basis of Cognition, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA
| | - Eric R. Helm
- grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA
| | - Michael L. Boninger
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000University of Pittsburgh Clinical Translational Science Institute, Pittsburgh, PA 15213 USA
| | - Jennifer L. Collinger
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.509981.c0000 0004 7644 8442Center for Neural Basis of Cognition, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA ,Human Engineering Research Labs, Department of Veteran Affairs, VA Center of Excellence, Pittsburgh, PA 15206 USA ,grid.147455.60000 0001 2097 0344Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA USA
| | - Robert A. Gaunt
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.509981.c0000 0004 7644 8442Center for Neural Basis of Cognition, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.147455.60000 0001 2097 0344Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA USA
| | - Lee E. Fisher
- grid.21925.3d0000 0004 1936 9000Rehab Neural Engineering Labs, University of Pittsburgh, 3520 Fifth Avenue, Suite 300, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.509981.c0000 0004 7644 8442Center for Neural Basis of Cognition, Pittsburgh, PA 15213 USA ,grid.21925.3d0000 0004 1936 9000Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213 USA ,grid.147455.60000 0001 2097 0344Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA USA
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