Stereotypical locomotor movements can be made without input from the brain after a complete spinal transection. However, the restoration of functional gait requires descending modulation of spinal circuits to independently control the movement of each limb. To evaluate whether a brain-machine interface (BMI) could be used to regain conscious control over the hindlimb, rats were trained to press a pedal and the encoding of hindlimb movement was assessed using a BMI paradigm. Off-line, information encoded by neurons in the hindlimb sensorimotor cortex was assessed. Next neural population functions, or weighted representations of the neuronal activity, were used to replace the hindlimb movement as a trigger for reward in real-time (on-line decoding) in three conditions: while the animal could still press the pedal, after the pedal was removed and after a complete spinal transection. A novel representation of the motor program was learned when the animals used neural control to achieve water reward (e.g. more information was conveyed faster). After complete spinal transection, the ability of these neurons to convey information was reduced by more than 40%. However, this BMI representation was relearned over time despite a persistent reduction in the neuronal firing rate during the task. Therefore, neural control is a general feature of the motor cortex, not restricted to forelimb movements, and can be regained after spinal injury.
Decoding Hindlimb Movement for a Brain Machine Interface after a Complete Spinal Transection
Creators
Anitha Manohar - Drexel University
Robert D. Flint - Drexel University
Eric Knudsen - Drexel University
Karen A. Moxon - Drexel University
Publication Details
PloS one, v 7(12), e52173
Publisher
Public Library Science
Number of pages
14
Grant note
89500 / Shriners Hospital for Children
P113 / Internationale Stiftung fur Forschung in Paraplegie
NS057419 / National Institutes of Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA
Resource Type
Journal article
Language
English
Academic Unit
School of Biomedical Engineering, Science, and Health Systems
Web of Science ID
WOS:000312829100026
Scopus ID
2-s2.0-84871659105
Other Identifier
991019168511304721
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