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Articles, Systems/Circuits

Robust Neuroprosthetic Control from the Stroke Perilesional Cortex

Tanuj Gulati, Seok Joon Won, Dhakshin S. Ramanathan, Chelsea C. Wong, Anitha Bodepudi, Raymond A. Swanson and Karunesh Ganguly
Journal of Neuroscience 3 June 2015, 35 (22) 8653-8661; DOI: https://doi.org/10.1523/JNEUROSCI.5007-14.2015
Tanuj Gulati
1Neurology and Rehabilitation Service and
3Department of Neurology, University of California San Francisco, San Francisco, California 94158, and
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Seok Joon Won
1Neurology and Rehabilitation Service and
3Department of Neurology, University of California San Francisco, San Francisco, California 94158, and
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Dhakshin S. Ramanathan
1Neurology and Rehabilitation Service and
2Department of Psychiatry, San Francisco Veterans Affairs Medical Center, San Francisco, California 94158,
4Department of Psychiatry, University of California San Francisco, San Francisco, California 94143
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Chelsea C. Wong
1Neurology and Rehabilitation Service and
3Department of Neurology, University of California San Francisco, San Francisco, California 94158, and
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Anitha Bodepudi
1Neurology and Rehabilitation Service and
3Department of Neurology, University of California San Francisco, San Francisco, California 94158, and
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Raymond A. Swanson
1Neurology and Rehabilitation Service and
3Department of Neurology, University of California San Francisco, San Francisco, California 94158, and
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Karunesh Ganguly
1Neurology and Rehabilitation Service and
3Department of Neurology, University of California San Francisco, San Francisco, California 94158, and
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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.

  • brain–machine interface
  • electrophysiology
  • plasticity
  • stroke
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The Journal of Neuroscience: 35 (22)
Journal of Neuroscience
Vol. 35, Issue 22
3 Jun 2015
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Robust Neuroprosthetic Control from the Stroke Perilesional Cortex
Tanuj Gulati, Seok Joon Won, Dhakshin S. Ramanathan, Chelsea C. Wong, Anitha Bodepudi, Raymond A. Swanson, Karunesh Ganguly
Journal of Neuroscience 3 June 2015, 35 (22) 8653-8661; DOI: 10.1523/JNEUROSCI.5007-14.2015

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Robust Neuroprosthetic Control from the Stroke Perilesional Cortex
Tanuj Gulati, Seok Joon Won, Dhakshin S. Ramanathan, Chelsea C. Wong, Anitha Bodepudi, Raymond A. Swanson, Karunesh Ganguly
Journal of Neuroscience 3 June 2015, 35 (22) 8653-8661; DOI: 10.1523/JNEUROSCI.5007-14.2015
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Keywords

  • brain–machine interface
  • electrophysiology
  • plasticity
  • stroke

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