Optimizing recording depth to decode movement goals from cortical field potentials

David A. Markowitz, Yan T. Wong, Charles M. Gray, Bijan Pesaran

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

1 Citation (Scopus)


Brain-machine interfaces decode movement goals and trajectories from neural activity that is recorded using chronically-implanted microelectrode arrays. Fixed geometry arrays are limited for this purpose because electrodes cannot be moved after implantation, and optimization of the electrode recording configuration requires the re-implantation of a new array. Here, we optimize local field potential (LFP) recordings using a chronically-implanted microelectrode array with electrodes that can be moved after implantation. In a series of recordings, we systematically vary the depth of each electrode in the frontal eye field of a monkey performing eye movements. We find that a decoder predicting movement goals from LFP activity on 32 electrodes provides information rates as high as 5.0 bits/s and that performance varies significantly with recording depth. These results indicate that recording depth is a critical parameter for the performance of LFP-based brain-machine interfaces that decode movement goals.

Original languageEnglish
Title of host publication2011 5th International IEEE/EMBS Conference on Neural Engineering, NER 2011
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Print)9781424441402
Publication statusPublished - 2011
Externally publishedYes
EventInternational IEEE Engineering-in-Medicine-and-Biology-Society (EMBS) Conference on Neural Engineering (NER) 2011 - Cancun, Mexico
Duration: 27 Apr 20111 May 2011
Conference number: 5th


ConferenceInternational IEEE Engineering-in-Medicine-and-Biology-Society (EMBS) Conference on Neural Engineering (NER) 2011
Abbreviated titleNER 2011

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