NDLI: A factor-analysis decoder for high-performance neural prostheses

Content Provider	IEEE Xplore Digital Library
Author	Santhanam, G. Yu, B.M. Gilja, V. Ryu, S.I. Afshar, A. Sahani, M. Shenoy, K.V.
Copyright Year	2008
Description	Author affiliation: Depts. of Electr. Eng., Stanford Univ., Stanford, CA (Santhanam, G.; Yu, B.M.)
Abstract	Increasing the performance of neural prostheses is necessary for assuring their clinical viability. One performance limitation is the presence of correlated trial-to-trial variability that can cause neural responses to wax and wane in concert as the subject is, for example, more attentive or more fatigued. We report here the design and characterization of a Factor- Analysis-based decoding algorithm that is able to contend with this confound. We characterize the decoder (classifier) on a previously reported dataset where monkeys performed both a real reach task and a prosthetic cursor movement task while we recorded from 96 electrodes implanted in dorsal pre- motor cortex. In principle, the decoder infers the underlying factors that co-modulate the neurons' responses and can use this information to function with reduced error rates (1 of 8 reach target prediction) of up to ~75% (~20% total prediction error using independent Gaussian or Poisson models became ~5%). Such Factor-Analysis based methods appear to be effective when attempting to combat directly unobserved trial-by-trial neural variabiliy.
Starting Page	5208
Ending Page	5211
File Size	108892
Page Count	4
File Format	PDF
ISBN	9781424414833
ISSN	15206149
DOI	10.1109/ICASSP.2008.4518833
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decoding Prosthetics Neurons Arm Brain computer interfaces Biomedical engineering Computer science Neurosurgery Educational institutions Humans neural prostheses Factor analysis premotor cortex brain-machine and brain-computer interfaces
Content Type	Text
Resource Type	Article

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