2021
DOI: 10.48550/arxiv.2104.12356
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A tutorial on generalized eigendecomposition for denoising, contrast enhancement, and dimension reduction in multichannel electrophysiology

Abstract: The goal of this paper is to present a theoretical and practical introduction to generalized eigendecomposition (GED), which is a robust and flexible framework used for dimension reduction and source separation in multichannel signal processing. In cognitive electrophysiology, GED is used to create spatial filters that maximize a researcher-specified contrast, such as relative spectral power or experiment condition differences. GED is fast and easy to compute, performs well in simulated and real data, and is e… Show more

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“…One major advantage of this method is the ability to decompose multiple partially spatially overlapping networks. Indeed, it is possible that traditional electrode-based synchronization methods mix neurally and cognitively distinct interactions because a single electrode measures activity from multiple networks (Cunningham and Yu, 2014;Cohen, 2021).…”
Section: Lfp Microstates Reflect Mesoscale Rhythmic Coordination Acro...mentioning
confidence: 99%
“…One major advantage of this method is the ability to decompose multiple partially spatially overlapping networks. Indeed, it is possible that traditional electrode-based synchronization methods mix neurally and cognitively distinct interactions because a single electrode measures activity from multiple networks (Cunningham and Yu, 2014;Cohen, 2021).…”
Section: Lfp Microstates Reflect Mesoscale Rhythmic Coordination Acro...mentioning
confidence: 99%