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

Author

Bankman, Isaac N. ; Johnson, Kenneth O. ; Schneider, Wolfger

Author_Institution

Applied Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA

Volume

40

Issue

8

fYear

1993

Firstpage

836

Lastpage

841

Abstract

The effects of noise autocorrelation on neural waveform recognition (detection, classification, and superposition resolution) are investigated, 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 (SNR) than template matching with whitening for comparable classification and superposition resolution. The comparable difference for detection is 15%.

Keywords

bioelectric potentials; biological techniques and instruments; neurophysiology; signal processing; classification; detection; microelectrode recordings; monkey cortex; neural waveform recordings; noise autocorrelation; optimal waveform recognition; signal-to-noise ratio; superposition resolution; template matching; whitening filter; Autocorrelation; Blood flow; Cardiology; Filtering; Forward contracts; Heart; Impedance; Matched filters; Microelectrodes; Phasor measurement units; Rabbits; Reflection; Signal resolution; Signal to noise ratio; Action Potentials; Animals; Artifacts; Bayes Theorem; Electrophysiology; Haplorhini; Neurons; Somatosensory Cortex;

fLanguage

English

Journal_Title

Biomedical Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0018-9294

Type

jour

DOI

10.1109/10.238472

Filename

238472