Nov 1, 2018

A comparison of bivariate frequency domain measures of electrophysiological connectivity

BioRxiv : the Preprint Server for Biology
Roberto Pascual-MarquiMasafumi Yoshimura

Abstract

The problem of interest here concerns electrophysiological signals from two cortical sites, acquired as invasive intracranial recordings, or from non-invasive estimates of cortical electric neuronal activity computed from EEG or MEG recordings (see e.g. https://doi.org/10.1101/269753). In the absence of other sources, these measured signals consist of an instantaneous linear mixture of the true, actual, unobserved local signals, due to low spatial resolution and volume conduction. A connectivity measure is unreliable as a true indicator of electrophysiological connectivity if it is not invariant to mixing, or if it reports a significant connection for a mixture of independent signals. In (Vinck et al 2011 Neuroimage 55:1548) it was shown that coherence, imaginary coherence, and phase locking value are not invariant to mixing, while the phase lag index (PLI) and the weighted version (wPLI) are invariant to mixing. Here we show that the lagged coherence (LagCoh) measure (2007, https://arxiv.org/abs/0711.1455), not studied in Vinck et al, is invariant to mixing. Additionally, we present here a new mixture-invariant connectivity statistic: the "standardized imaginary covariance" (sImCov). We also include in the comparisons the dire...Continue Reading

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Mentioned in this Paper

Body Site
Electroencephalography
Spatial Distribution
Magnetoencephalography
Etiology
STAM gene
Structure of Cortex of Kidney
Neuronal
Intracranial
SERPINF2

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