Efficient coherence inference on complex time–frequency coefficients using a general linear model

doi:10.1016/j.jneumeth.2026.110791

Efficient coherence inference on complex time–frequency coefficients using a general linear model

2026-05-09

0

PRE

AI

Christopher K. Kovach

DOI：10.1016/j.jneumeth.2026.110791

Original

Original request for help

Save

Abstract

En 中文

• Presents a GLM-based parametric method for coherence significance testing. • Removes the need for surrogate resampling in spectral coherence analysis. • Matches the sensitivity of phase-randomization tests with continuous p-values. • Achieves ̃190-fold computational speedup over surrogate-based methods. • Scales efficiently to large multichannel EEG/iEEG datasets and high-rate recordings.

Keywords:

GLM

coherence significance testing

spectral coherence analysis

computational speedup

multichannel EEG/iEEG

Efficient coherence inference on complex time–frequency coefficients using a general linear model

Abstract

Journal

Organization