Stable online control of an electrocorticographic brain-computer interface using a static decoder

Robin C. Ashmore, Bridget M. Endler, Ivan Smalianchuk, Alan D. Degenhart, Nicholas G. Hatsopoulos, Elizabeth C. Tyler-Kabara, Aaron P. Batista, Wei Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

A brain computer interface (BCI) system was implemented by recording electrocorticographic signals (ECoG) from the motor cortex of a Rhesus macaque. These signals were used to control two-dimensional cursor movements in a standard center-out task, utilizing an optimal linear estimation (OLE) method. We examined the time course over which a monkey could acquire accurate control when operating in a co-adaptive training scheme. Accurate and maintained control was achieved after 4-5 days. We then held the decode parameters constant and observed stable control over the next 28 days. We also investigated the underlying neural strategy employed for control, asking whether neural features that were correlated with a given kinematic output (e.g. velocity in a certain direction) were clustered anatomically, and whether the features were coordinated or conflicting in their contributions to the control signal.

Original languageEnglish
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages1740-1744
Number of pages5
DOIs
StatePublished - 2012
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Country/TerritoryUnited States
CitySan Diego, CA
Period08/28/1209/1/12

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