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J Neurophysiol (April 11, 2007). doi:10.1152/jn.00760.2006
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Submitted on July 21, 2006
Accepted on April 5, 2007

Decoding M1 neurons during multiple finger movements

Suliann Ben Hamed1, Marc H. Schieber2, and Alexandre Pouget3*

1 Department of Brain and Cognitive Sciences, University of Rochester, Rochester, New York, United States; Centre de Neuroscience Cognitive, UMR 5229, CNRS, France
2 Department of Neurobiology and Anatomy, University of Rochester, Rochester, New York, United States
3 Department of Brain and Cognitive Sciences, University of Rochester, Rochester, New York, United States

* To whom correspondence should be addressed. E-mail: alex{at}bcs.rochester.edu.

We tested several techniques for decoding the activity of primary motor cortex (M1) neurons during movements of single fingers or pairs of fingers. We report that single finger movements can be decoded with > 99% accuracy using as few as 30 neurons randomly selected from populations of task-related neurons recorded from the M1 hand representation. This number was reduced to 20 neurons or less when the neurons were not picked randomly, but selected on the basis of their information content. We then extended techniques for decoding single finger movements to the problem of decoding the simultaneous movement of two fingers. Movements of pairs of fingers were decoded with 90.9% accuracy from 100 neurons. The techniques we used to obtain these results can be applied, not only to movements of single fingers and pairs of fingers as reported here, but also to movements of arbitrary combinations of fingers. The remarkably small number of neurons needed to decode a relatively large repertoire of movements involving either one or two effectors is encouraging for the development of neural prosthetics that will control hand movements.




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