Estimation of Time-Varying Coherence and Its Application in Understanding Brain Functional Connectivity

EURASIP Journal on Advances in Signal Processing. 2010;2010 DOI 10.1155/2010/390910


Journal Homepage

Journal Title: EURASIP Journal on Advances in Signal Processing

ISSN: 1687-6172 (Print); 1687-6180 (Online)

Publisher: SpringerOpen

Society/Institution: European Association for Signal Processing (EURASIP)

LCC Subject Category: Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication | Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics

Country of publisher: United Kingdom

Language of fulltext: English

Full-text formats available: PDF, HTML



Cheng Liu
William Gaetz
Hongmei Zhu


Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 13 weeks


Abstract | Full Text

Time-varying coherence is a powerful tool for revealing functional dynamics between different regions in the brain. In this paper, we address ways of estimating evolutionary spectrum and coherence using the general Cohen's class distributions. We show that the intimate connection between the Cohen's class-based spectra and the evolutionary spectra defined on the locally stationary time series can be linked by the kernel functions of the Cohen's class distributions. The time-varying spectra and coherence are further generalized with the Stockwell transform, a multiscale time-frequency representation. The Stockwell measures can be studied in the framework of the Cohen's class distributions with a generalized frequency-dependent kernel function. A magnetoencephalography study using the Stockwell coherence reveals an interesting temporal interaction between contralateral and ipsilateral motor cortices under the multisource interference task.