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Amplifying the Neural Power Spectrum

View ORCID ProfileJ. Andrew Doyle, Paule-Joanne Toussaint, View ORCID ProfileAlan C. Evans
doi: https://doi.org/10.1101/659268
J. Andrew Doyle
Montreal Neurological Institute, McGill University
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  • For correspondence: andrew.doyle@mcgill.ca
Paule-Joanne Toussaint
Montreal Neurological Institute, McGill University
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Alan C. Evans
Montreal Neurological Institute, McGill University
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Abstract

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.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted June 04, 2019.
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Amplifying the Neural Power Spectrum
J. Andrew Doyle, Paule-Joanne Toussaint, Alan C. Evans
bioRxiv 659268; doi: https://doi.org/10.1101/659268
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Amplifying the Neural Power Spectrum
J. Andrew Doyle, Paule-Joanne Toussaint, Alan C. Evans
bioRxiv 659268; doi: https://doi.org/10.1101/659268

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