Document Detail

Exploring resting-state functional connectivity with total interdependence.
MedLine Citation:
PMID:  22289806     Owner:  NLM     Status:  MEDLINE    
Resting-state fMRI has become a powerful tool for studying network mechanisms of normal brain functioning and its impairments by neurological and psychiatric disorders. Analytically, independent component analysis and seed-based cross correlation are the main methods for assessing the connectivity of resting-state fMRI time series. A feature common to both methods is that they exploit the covariation structures of contemporaneously (zero-lag) measured data but ignore temporal relations that extend beyond the zero-lag. To examine whether data covariations across different lags can contribute to our understanding of functional brain networks, a measure that can uncover the overall temporal relationship between two resting-state BOLD signals is needed. In this paper we propose such a measure referred as total interdependence (TI). Comparing TI with zero-lag cross correlation (CC) we report three results. First, when combined with a random permutation procedure, TI can reveal the amount of temporal relationship between two resting-state BOLD time series that is not captured by CC. Second, comparing resting-state data with task-state data recorded in the same scanning session, we demonstrate that the resting-state functional networks constructed with TI match more precisely the networks activated by the task. Third, TI is shown to be more statistically sensitive than CC and provides better feature vectors for network clustering analysis.
Xiaotong Wen; Jue Mo; Mingzhou Ding
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Publication Detail:
Type:  Journal Article     Date:  2012-01-25
Journal Detail:
Title:  NeuroImage     Volume:  60     ISSN:  1095-9572     ISO Abbreviation:  Neuroimage     Publication Date:  2012 Apr 
Date Detail:
Created Date:  2012-03-14     Completed Date:  2012-06-29     Revised Date:  2013-06-26    
Medline Journal Info:
Nlm Unique ID:  9215515     Medline TA:  Neuroimage     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1587-95     Citation Subset:  IM    
Copyright Information:
Copyright © 2012 Elsevier Inc. All rights reserved.
J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA.
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MeSH Terms
Brain / physiology*
Magnetic Resonance Imaging*
Nerve Net / physiology*
Rest / physiology
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