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• W2079663015 abstract "Phase-amplitude cross-frequency coupling (CFC)-where the phase of a low-frequency signal modulates the amplitude or power of a high-frequency signal-is a topic of increasing interest in neuroscience. However, existing methods of assessing CFC are inherently bivariate and cannot estimate CFC between more than two signals at a time. Given the increase in multielectrode recordings, this is a strong limitation. Furthermore, the phase coupling between multiple low-frequency signals is likely to produce a high rate of false positives when CFC is evaluated using bivariate methods. Here, we present a novel method for estimating the statistical dependence between one high-frequency signal and <i xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>N</i> low-frequency signals, termed multivariate phase-coupling estimation (PCE). Compared to bivariate methods, the PCE produces sparser estimates of CFC and can distinguish between direct and indirect coupling between neurophysiological signals-critical for accurately estimating coupling within multiscale brain networks." @default.
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• W2079663015 date "2012-01-01" @default.
• W2079663015 modified "2023-10-04" @default.
• W2079663015 title "Multivariate Phase–Amplitude Cross-Frequency Coupling in Neurophysiological Signals" @default.
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• W2079663015 doi "https://doi.org/10.1109/tbme.2011.2172439" @default.
• W2079663015 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4090099" @default.
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