Tracking changes in functional connectivity of brain networks from resting-state fMRI using particle filters
M. Faizan Ahmad, James K. Murphy, Deniz Vatansever, Emmanuel A. Stamatakis, Simon J. Godsill
Abstract
Recent empirical research has discovered that linkages among fMRI signals of the brain in resting-state have meaningful temporal variations. Most current studies of brain networks assume that these linkages are constant. We propose a model and an accompanying algorithm to infer and track changes in these interaction strengths, thus providing a more comprehensive way to study brain dynamics. The stochastic model employed is akin to one used for neuronal states (DCM) and a Rao-Blackwellized filtering algorithm is set up for tracking purposes. Our results show that time-varying interactions among brain regions can be successfully found which have the potential of providing great clinical value.
BibTeX
@inproceedings{icassp2015_trackingchangesi,
title = {Tracking changes in functional connectivity of brain networks from resting-state fMRI using particle filters},
author = {M. Faizan Ahmad and James K. Murphy and Deniz Vatansever and Emmanuel A. Stamatakis and Simon J. Godsill},
booktitle = {ICASSP 2015},
year = {2015}
}