RT Journal Article
SR Electronic
T1 Amplifying the Neural Power Spectrum
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 659268
DO 10.1101/659268
A1 J. Andrew Doyle
A1 Paule-Joanne Toussaint
A1 Alan C. Evans
YR 2019
UL http://biorxiv.org/content/early/2019/06/04/659268.abstract
AB We introduce a novel method that employs a parametric model of human electroen-cephalographic (EEG) brain signal power spectra to evaluate cognitive science experiments and test scientific hypotheses. We develop the Neural Power Amplifier (NPA), a data-driven approach to EEG pre-processing that can replace current filtering strategies with a principled method based on combining filters with log-arithmic and Gaussian magnitude responses. Presenting the first time domain evidence to validate an increasingly popular model for neural power spectra [1], we show that filtering out the 1/f background signal and selecting peaks improves a time-domain decoding experiment for visual stimulus of human faces versus random noise.