DocumentCode :
3415348
Title :
Tracking changes in functional connectivity of brain networks from resting-state fMRI using particle filters
Author :
Ahmad, M. Faizan ; Murphy, James ; Vatansever, Deniz ; Stamatakis, Emmanuel A. ; Godsill, Simon
Author_Institution :
Dept. of Eng., Univ. of Cambridge, Cambridge, UK
fYear :
2015
fDate :
19-24 April 2015
Firstpage :
798
Lastpage :
802
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.
Keywords :
biomedical MRI; brain; medical image processing; neurophysiology; particle filtering (numerical methods); stochastic processes; Rao-Blackwellized filtering algorithm; brain networks; functional connectivity; functional magnetic resonance imaging; neuronal states; particle filters; resting-state fMRI; stochastic model; Biological system modeling; Brain modeling; Couplings; Filtering; Mathematical model; Noise; Stochastic processes; BOLD; Rao-Blackwellized particle filter; functional connectivity; resting state fMRI;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
Type :
conf
DOI :
10.1109/ICASSP.2015.7178079
Filename :
7178079
Link To Document :
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