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Published May 2019 | Supplemental Material + Accepted Version + Published
Journal Article Open

Technical considerations for generating somatosensation via cortical stimulation in a closed-loop sensory/motor brain-computer interface system in humans

Abstract

Somatosensory feedback is the next step in brain computer interface (BCI). Here, we compare three cortical stimulating array modalities for generating somatosensory percepts in BCI. We compared human subjects with either a 64-channel "mini"-electrocorticography grid (mECoG; 1.2-mm diameter exposed contacts with 3-mm spacing, N = 1) over the hand area of primary somatosensory cortex (S1), or a standard grid (sECoG; 1.5-mm diameter exposed contacts with 1-cm spacing, N = 1), to generate artificial somatosensation through direct electrical cortical stimulation. Finally, we reference data in the literature from a patient implanted with microelectrode arrays (MEA) placed in the S1 hand area. We compare stimulation results to assess coverage and specificity of the artificial percepts in the hand. Using the mECoG array, hand mapping revealed coverage of 41.7% of the hand area versus 100% for the sECoG array, and 18.8% for the MEA. On average, stimulation of a single electrode corresponded to sensation reported in 4.42 boxes (range 1–11 boxes) for the mECoG array, 19.11 boxes (range 4–48 boxes) for the sECoG grid, and 2.3 boxes (range 1–5 boxes) for the MEA. Sensation in any box, on average, corresponded to stimulation from 2.65 electrodes (range 1–5 electrodes) for the mECoG grid, 3.58 electrodes for the sECoG grid (range 2–4 electrodes), and 11.22 electrodes (range 2–17 electrodes) for the MEA. Based on these findings, we conclude that mECoG grids provide an excellent balance between spatial cortical coverage of the hand area of S1 and high-density resolution.

Additional Information

© 2019 Elsevier. Received 25 October 2018, Accepted 18 January 2019, Available online 31 January 2019. We wish to acknowledge the generous support of Cal-BRAIN: A Neurotechnology Program for California, National Center for Advancing Translational Science (NCATS) of the U.S. National Institutes of Health (KL2TR001854), National Institutes of Health (R25 NS099008-01), The Neurosurgery Research and Education Foundation (NREF), the Tianqiao and Chrissy Chen Brain-machine Interface Center at Caltech, the Boswell Foundation and the Della Martin Foundation. The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

Attached Files

Published - 1-s2.0-S096758681831823X-main.pdf

Accepted Version - nihms-1026930.pdf

Supplemental Material - 1-s2.0-S096758681831823X-mmc1.xml

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August 22, 2023
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