Robust Neuroprosthetic Control from the Stroke Perilesional Cortex
Intracortical brain–machine interfaces (BMIs) may eventually restore function in those with motor disability after stroke. However, current research into the development of intracortical BMIs has focused on subjects with largely intact cortical structures, such as those with spinal cord injury. Alth...
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Published in | The Journal of neuroscience Vol. 35; no. 22; pp. 8653 - 8661 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Society for Neuroscience
03.06.2015
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Subjects | |
Online Access | Get full text |
ISSN | 0270-6474 1529-2401 1529-2401 |
DOI | 10.1523/JNEUROSCI.5007-14.2015 |
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Abstract | Intracortical brain–machine interfaces (BMIs) may eventually restore function in those with motor disability after stroke. However, current research into the development of intracortical BMIs has focused on subjects with largely intact cortical structures, such as those with spinal cord injury. Although the stroke perilesional cortex (PLC) has been hypothesized as a potential site for a BMI, it remains unclear whether the injured motor cortical network can support neuroprosthetic control directly. Using chronic electrophysiological recordings in a rat stroke model, we demonstrate here the PLC's capacity for neuroprosthetic control and physiological plasticity. We initially found that the perilesional network demonstrated abnormally increased slow oscillations that also modulated neural firing. Despite these striking abnormalities, neurons in the perilesional network could be modulated volitionally to learn neuroprosthetic control. The rate of learning was surprisingly similar regardless of the electrode distance from the stroke site and was not significantly different from intact animals. Moreover, neurons achieved similar task-related modulation and, as an ensemble, formed cell assemblies with learning. Such control was even achieved in animals with poor motor recovery, suggesting that neuroprosthetic control is possible even in the absence of motor recovery. Interestingly, achieving successful control also reduced locking to abnormal oscillations significantly. Our results thus suggest that, despite the disrupted connectivity in the PLC, it may serve as an effective target for neuroprosthetic control in those with poor motor recovery after stroke. |
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AbstractList | Intracortical brain-machine interfaces (BMIs) may eventually restore function in those with motor disability after stroke. However, current research into the development of intracortical BMIs has focused on subjects with largely intact cortical structures, such as those with spinal cord injury. Although the stroke perilesional cortex (PLC) has been hypothesized as a potential site for a BMI, it remains unclear whether the injured motor cortical network can support neuroprosthetic control directly. Using chronic electrophysiological recordings in a rat stroke model, we demonstrate here the PLC's capacity for neuroprosthetic control and physiological plasticity. We initially found that the perilesional network demonstrated abnormally increased slow oscillations that also modulated neural firing. Despite these striking abnormalities, neurons in the perilesional network could be modulated volitionally to learn neuroprosthetic control. The rate of learning was surprisingly similar regardless of the electrode distance from the stroke site and was not significantly different from intact animals. Moreover, neurons achieved similar task-related modulation and, as an ensemble, formed cell assemblies with learning. Such control was even achieved in animals with poor motor recovery, suggesting that neuroprosthetic control is possible even in the absence of motor recovery. Interestingly, achieving successful control also reduced locking to abnormal oscillations significantly. Our results thus suggest that, despite the disrupted connectivity in the PLC, it may serve as an effective target for neuroprosthetic control in those with poor motor recovery after stroke.Intracortical brain-machine interfaces (BMIs) may eventually restore function in those with motor disability after stroke. However, current research into the development of intracortical BMIs has focused on subjects with largely intact cortical structures, such as those with spinal cord injury. Although the stroke perilesional cortex (PLC) has been hypothesized as a potential site for a BMI, it remains unclear whether the injured motor cortical network can support neuroprosthetic control directly. Using chronic electrophysiological recordings in a rat stroke model, we demonstrate here the PLC's capacity for neuroprosthetic control and physiological plasticity. We initially found that the perilesional network demonstrated abnormally increased slow oscillations that also modulated neural firing. Despite these striking abnormalities, neurons in the perilesional network could be modulated volitionally to learn neuroprosthetic control. The rate of learning was surprisingly similar regardless of the electrode distance from the stroke site and was not significantly different from intact animals. Moreover, neurons achieved similar task-related modulation and, as an ensemble, formed cell assemblies with learning. Such control was even achieved in animals with poor motor recovery, suggesting that neuroprosthetic control is possible even in the absence of motor recovery. Interestingly, achieving successful control also reduced locking to abnormal oscillations significantly. Our results thus suggest that, despite the disrupted connectivity in the PLC, it may serve as an effective target for neuroprosthetic control in those with poor motor recovery after stroke. Intracortical brain–machine interfaces (BMIs) may eventually restore function in those with motor disability after stroke. However, current research into the development of intracortical BMIs has focused on subjects with largely intact cortical structures, such as those with spinal cord injury. Although the stroke perilesional cortex (PLC) has been hypothesized as a potential site for a BMI, it remains unclear whether the injured motor cortical network can support neuroprosthetic control directly. Using chronic electrophysiological recordings in a rat stroke model, we demonstrate here the PLC's capacity for neuroprosthetic control and physiological plasticity. We initially found that the perilesional network demonstrated abnormally increased slow oscillations that also modulated neural firing. Despite these striking abnormalities, neurons in the perilesional network could be modulated volitionally to learn neuroprosthetic control. The rate of learning was surprisingly similar regardless of the electrode distance from the stroke site and was not significantly different from intact animals. Moreover, neurons achieved similar task-related modulation and, as an ensemble, formed cell assemblies with learning. Such control was even achieved in animals with poor motor recovery, suggesting that neuroprosthetic control is possible even in the absence of motor recovery. Interestingly, achieving successful control also reduced locking to abnormal oscillations significantly. Our results thus suggest that, despite the disrupted connectivity in the PLC, it may serve as an effective target for neuroprosthetic control in those with poor motor recovery after stroke. |
Author | Wong, Chelsea C. Won, Seok Joon Gulati, Tanuj Bodepudi, Anitha Ganguly, Karunesh Ramanathan, Dhakshin S. Swanson, Raymond A. |
Author_xml | – sequence: 1 givenname: Tanuj orcidid: 0000-0003-3243-7883 surname: Gulati fullname: Gulati, Tanuj – sequence: 2 givenname: Seok Joon surname: Won fullname: Won, Seok Joon – sequence: 3 givenname: Dhakshin S. surname: Ramanathan fullname: Ramanathan, Dhakshin S. – sequence: 4 givenname: Chelsea C. surname: Wong fullname: Wong, Chelsea C. – sequence: 5 givenname: Anitha surname: Bodepudi fullname: Bodepudi, Anitha – sequence: 6 givenname: Raymond A. orcidid: 0000-0002-3664-5359 surname: Swanson fullname: Swanson, Raymond A. – sequence: 7 givenname: Karunesh surname: Ganguly fullname: Ganguly, Karunesh |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26041930$$D View this record in MEDLINE/PubMed |
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Keywords | brain–machine interface plasticity electrophysiology stroke |
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Snippet | Intracortical brain–machine interfaces (BMIs) may eventually restore function in those with motor disability after stroke. However, current research into the... Intracortical brain-machine interfaces (BMIs) may eventually restore function in those with motor disability after stroke. However, current research into the... |
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SubjectTerms | Action Potentials - physiology Analysis of Variance Animals Brain-Computer Interfaces Male Motor Cortex - pathology Motor Cortex - physiopathology Motor Skills - physiology Neurons - physiology Rats Rats, Long-Evans Stroke - pathology User-Computer Interface |
Title | Robust Neuroprosthetic Control from the Stroke Perilesional Cortex |
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