Optimal detection, classification, and superposition resolution in neural waveform recordings.

I N Bankman; K O Johnson; W Schneider

doi:10.1109/10.238472

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Optimal detection, classification, and superposition resolution in neural waveform recordings.

I N Bankman·K O Johnson·W Schneider

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Abstract

The effects of noise autocorrelation on neural waveform recognition (detection, classification, and superposition resolution) are investigated in this study using microelectrode recordings from the cortex of a monkey. Optimal waveform recognition is accomplished by passing the data through a whitening filter before matched filtering for detection or template matching for classification and superposition resolution. Template matching without whitening requires about 40% higher signal-to-noise ratio than template matching with whitening for comparable classification and superposition resolution. The comparable difference for detection is 15%.

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Action Potentials Animals Artifacts Bayes Theorem Electrophysiology Haplorhini Neurons Somatosensory Cortex Comparative Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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I N Bankman, K O Johnson, W Schneider. 1993. Optimal detection, classification, and superposition resolution in neural waveform recordings.. https://doi.org/10.1109/10.238472

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