Dynamic Causal Models for phase coupling

Penny, W D, Litvak, V, Fuentemilla, L, Duzel, E and Friston, K (2009) Dynamic Causal Models for phase coupling. Journal of Neuroscience Methods, 183 (1). pp. 19-30. ISSN 0165-0270

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Abstract

This paper presents an extension of the Dynamic Causal Modelling (DCM) framework to the analysis of phase-coupled data. A weakly coupled oscillator approach is used to describe dynamic phase changes in a network of oscillators. The use of Bayesian model comparison allows one to infer the mechanisms underlying synchronization processes in the brain. For example, whether activity is driven by master-slave versus mutual entrainment mechanisms. Results are presented on synthetic data from physiological models and on MEG data from a study of visual working memory.

Item Type: Article
Uncontrolled Keywords: brain,computer simulation,cortical synchronization,humans,magnetoencephalography,short-term memory,biological models,nerve net,neurons,nonlinear dynamics
Faculty \ School: Faculty of Social Sciences > School of Psychology
Depositing User: Pure Connector
Date Deposited: 22 Aug 2017 06:35
Last Modified: 22 Apr 2020 05:23
URI: https://ueaeprints.uea.ac.uk/id/eprint/64613
DOI: 10.1016/j.jneumeth.2009.06.029

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