Identifying patterns in temporal variation of functional connectivity using resting state FMRI

Harini Eavani, Theodore D. Satterthwaite, Raquel E. Gur, Ruben C. Gur, Christos Davatzikos

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

Abstract

Estimating functional brain networks from fMRI data has been the focus of much research in recent years. Low sample sizes (time-points) and high dimensionality of fMRI has restricted estimation to a temporally averaged connectivity matrix per subject, due to which the dynamics of functional connectivity is largely unknown. In this paper, we propose a novel method based on constrained matrix factorization that addresses two major issues. Firstly, it finds a set of basis networks that are the semantic parts of the time-varying whole-brain functional networks. The whole-brain network at any point in time, for any subject, is a non-negative combination of these basis networks. Secondly, significant dimensionality reduction is achieved by projecting the data onto this basis, facilitating subsequent analysis of temporal dynamics. Results on simulated fMRI data show that our method can effectively recover underlying basis networks. We apply this method on a normative dataset of resting state fMRI scans. Results indicate that the functional connectivity of a subject at any point during the scan is composed of combinations of overlapping task-positive/negative pairs of sub-networks.

Original languageEnglish (US)
Title of host publicationISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro
Pages1086-1089
Number of pages4
DOIs
StatePublished - Aug 22 2013
Event2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013 - San Francisco, CA, United States
Duration: Apr 7 2013Apr 11 2013

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013
CountryUnited States
CitySan Francisco, CA
Period4/7/134/11/13

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Keywords

  • functional connectivity
  • resting state fMRI
  • temporal network dynamics

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Eavani, H., Satterthwaite, T. D., Gur, R. E., Gur, R. C., & Davatzikos, C. (2013). Identifying patterns in temporal variation of functional connectivity using resting state FMRI. In ISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro (pp. 1086-1089). [6556667] (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2013.6556667