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The role of nonlinearity in computing graph-theoretical properties of resting-state functional magnetic resonance imaging brain networks.

Abstract:

In recent years, there has been an increasing interest in the study of large-scale brain activity interaction structure from the perspective of complex networks, based on functional magnetic resonance imaging (fMRI) measurements. To assess the strength of interaction (functional connectivity, FC) between two brain regions, the linear (Pearson) correlation coefficient of the respective time series is most commonly used. Since a potential use of nonlinear FC measures has recently been discussed...

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Publisher copy:
10.1063/1.3553181

Authors


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Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author
Journal:
Chaos (Woodbury, N.Y.)
Volume:
21
Issue:
1
Pages:
013119
Publication date:
2011-03-01
DOI:
EISSN:
1089-7682
ISSN:
1054-1500
Source identifiers:
364108
Language:
English
Keywords:
Pubs id:
pubs:364108
UUID:
uuid:c4d03128-e725-42d6-9bc1-8416057fa29b
Local pid:
pubs:364108
Deposit date:
2013-11-16

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