Improving neural prosthetic system performance by combining plan and peri-movement activity

While most neural prosthetic systems to date estimate arm movements based solely on the activity prior to reaching movements during a delay period (plan activity) or solely on the activity during reaching movements (peri-movement activity), we show that decode classification can be improved by 56% a...

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Bibliographic Details
Published in:Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.) Vol. 2; pp. 4516 - 4519
Main Authors: Yu, B.M., Ryu, S.I., Santhanam, G., Churchland, M.M., Shenoy, K.V.
Format: Conference Proceeding Journal Article
Language:English
Published: United States IEEE 2004
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ISBN:9780780384392, 0780384393
ISSN:1557-170X
Online Access:Get full text
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Summary:While most neural prosthetic systems to date estimate arm movements based solely on the activity prior to reaching movements during a delay period (plan activity) or solely on the activity during reaching movements (peri-movement activity), we show that decode classification can be improved by 56% and 71% respectively by using both types of activity together. We recorded from the pre-motor cortex of a rhesus monkey performing a delayed-reach task to one of seven targets. We found that taking into account the time-varying structure in peri-movement activity further improved performance by 15%, while doing the same for plan activity did not improve performance. We also found low correlations in activity between pairs of simultaneously-recorded units and across time periods within a given trial condition. These results show that decode performance can be significantly improved by combining information from the plan and peri-movement periods, and that there is nearly no loss in performance when assuming independence between units and across tune periods within a given trial condition.
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ISBN:9780780384392
0780384393
ISSN:1557-170X
DOI:10.1109/IEMBS.2004.1404254