Neural prostheses have generally relied on signals from cortical motor regions to control reaching movements of a robotic arm. However, little work has been done in exploring the involvement of nonmotor cortical and associative regions during motor tasks. In this study, we identify regions which may encode direction during planning and movement of a center-out motor task. Local field potentials were collected using stereoelectroencephalography (SEEG) from nine epilepsy patients implanted with multiple depth electrodes for clinical purposes. Spectral analysis of the recorded data was performed using nonparametric statistical techniques to identify regions that may encode direction of movements during the motor task. The analysis revealed several nonmotor regions; including the right insular cortex, right temporal pole, right superior parietal lobule, and the right lingual gyrus, that encode directionality before and after movement onset. We observed that each of these regions encode direction in different frequency bands. This preliminary study suggests that nonmotor regions may be useful in assisting in neural prosthetic control.
|Original language||English (US)|
|Title of host publication||2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society|
|Subtitle of host publication||Smarter Technology for a Healthier World, EMBC 2017 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||4|
|State||Published - Sep 13 2017|
|Event||39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of|
Duration: Jul 11 2017 → Jul 15 2017
|Name||Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS|
|Other||39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017|
|Country/Territory||Korea, Republic of|
|Period||7/11/17 → 7/15/17|
Bibliographical noteFunding Information:
This work was supported by a National Science Foundation grant (EFRI-MC3: # 1137237) awarded to S.V.S., J.A.G., J.B. and J.T.G.
© 2017 IEEE.