Statistical Modeling of the Default Mode Brain Network Reveals a Segregated Highway Structure

We investigate the functional organization of the Default Mode Network (DMN) – an important subnetwork within the brain associated with a wide range of higher-order cognitive functions. While past work has shown the whole-brain network of functional connectivity follows small-world organizational pr...

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Bibliographic Details
Published in:Scientific reports 2017-09, Vol.7 (1), p.11694-14, Article 11694
Main Authors: Stillman, Paul E., Wilson, James D., Denny, Matthew J., Desmarais, Bruce A., Bhamidi, Shankar, Cranmer, Skyler J., Lu, Zhong-Lin
Format: Article
Language:English
Subjects:
59/36
631/378/116/1925
631/378/2649
Brain research
Cognitive ability
Functional morphology
Humanities and Social Sciences
Mathematical models
multidisciplinary
Neural networks
Neurosciences
Political science
Science
Science (multidisciplinary)
Statistical methods
Statistical models
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Summary:We investigate the functional organization of the Default Mode Network (DMN) – an important subnetwork within the brain associated with a wide range of higher-order cognitive functions. While past work has shown the whole-brain network of functional connectivity follows small-world organizational principles, subnetwork structure is less well understood. Current statistical tools, however, are not suited to quantifying the operating characteristics of functional networks as they often require threshold censoring of information and do not allow for inferential testing of the role that local processes play in determining network structure. Here, we develop the correlation Generalized Exponential Random Graph Model (cGERGM) – a statistical network model that uses local processes to capture the emergent structural properties of correlation networks without loss of information. Examining the DMN with the cGERGM, we show that, rather than demonstrating small-world properties, the DMN appears to be organized according to principles of a segregated highway – suggesting it is optimized for function-specific coordination between brain regions as opposed to information integration across the DMN. We further validate our findings through assessing the power and accuracy of the cGERGM on a testbed of simulated networks representing various commonly observed brain architectures.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-017-09896-6