Detecting stimulus driven changes in functional brain connectivity

Pingmei Xu, Hao Xu, Peter Jeffrey Ramadge

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

We consider the problem of detecting stimulus driven changes in brain functional connectivity. Estimating functional connectivity from fMRI data sampled over a small time period is difficult - there is simply not enough data to permit reliable estimates. We investigate the use of a sparse Gaussian graphical model regularized by a graph learned from data sampled over a longer time period. We establish a framework to identify the changes in brain connectivity driven by short-term stimuli. Results of experiments on both synthetic and real fMRI data illustrate the attributes of our methods as well as the difficulty of the problem.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages3507-3511
Number of pages5
DOIs
StatePublished - Oct 18 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period5/26/135/31/13

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Brain Connectivity
  • Graphical Lasso
  • Time-Dependent Network
  • fMRI

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