title: Multi-scale integration and predictability in resting state brain activity.
abstract: The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.
authors.affiliation: Department of Informatics, School of Informatics and Computing, Indiana University Bloomington, IN, USA ; Instituto Gulbenkian de Ciência Oeiras, Portugal.
authors.forename: Artemy
authors.initials: A
authors.lastname: Kolchinsky
authors.affiliation: Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht Utrecht, Netherlands.
authors.forename: Martijn P
authors.initials: MP
authors.lastname: van den Heuvel
authors.affiliation: Signal Processing Laboratory 5, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland ; Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL) Lausanne, Switzerland.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Griffa
authors.affiliation: Signal Processing Laboratory 5, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland ; Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL) Lausanne, Switzerland.
authors.forename: Patric
authors.initials: P
authors.lastname: Hagmann
authors.affiliation: Department of Informatics, School of Informatics and Computing, Indiana University Bloomington, IN, USA ; Instituto Gulbenkian de Ciência Oeiras, Portugal.
authors.forename: Luis M
authors.initials: LM
authors.lastname: Rocha
authors.affiliation: Department of Psychological and Brain Sciences, Indiana University Bloomington, IN, USA.
authors.forename: Olaf
authors.initials: O
authors.lastname: Sporns
authors.affiliation: Department of Psychological and Brain Sciences, Indiana University Bloomington, IN, USA.
authors.forename: Joaquín
authors.initials: J
authors.lastname: Goñi
keywords: complexity measures; human connectome; information theory; integrative regions; multivariate mutual information; resting-state
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