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The community structure of functional brain networks exhibits scale-specific patterns of variability across individuals and time

Richard F. Betzel, Maxwell A. Bertolero, Evan M. Gordon, Caterina Gratton, Nico U.F. Dosenbach, Danielle S. Bassett
doi: https://doi.org/10.1101/413278
Richard F. Betzel
1Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, 19104 USA
2Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47401 USA
3Cognitive Science Program, Indiana University, Bloomington, IN, 47401 USA
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Maxwell A. Bertolero
1Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, 19104 USA
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Evan M. Gordon
4VISN 17 Center of Excellence for Research on Returning War Veterans, Waco, TX,76711 USA
5Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, 75235, USA
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Caterina Gratton
6Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
7Department of Psychology, Northwestern University, Evanston, IL, 60208, USA
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Nico U.F. Dosenbach
6Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
8Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO, 63110, USA
9Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, 63110, USA
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Danielle S. Bassett
1Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, 19104 USA
10Department of Electrical & Systems Engineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, 19104 USA
11Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104 USA
12Department of Physics & Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104 USA
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Abstract

The network organization of the human brain varies across individuals, changes with development and aging, and differs in disease. Discovering the major dimensions along which this variability is displayed remains a central goal of both neuroscience and clinical medicine. Such efforts can be usefully framed within the context of the brain’s modular network organization, which can be assessed quantitatively using powerful computational techniques and extended for the purposes of multi-scale analysis, dimensionality reduction, and biomarker generation. Though the concept of modularity and its utility in describing brain network organization is clear, principled methods for comparing multi-scale communities across individuals and time are surprisingly lacking. Here, we present a method that uses multi-layer networks to simultaneously discover the modular structure of many subjects at once. This method builds upon the well-known multi-layer modularity maximization technique, and provides a viable and principled tool for studying differences in network communities across individuals and within individuals across time. We test this method on two datasets and identify consistent patterns of inter-subject community variability, demonstrating that this variability – which would be undetectable using past approaches – is associated with measures of cognitive performance. In general, the multi-layer, multi-subject framework proposed here represents an advancement over current approaches by straighforwardly mapping community assignments across subjects and holds promise for future investigations of inter-subject community variation in clinical populations or as a result of task constraints.

Footnotes

  • ↵* dsb{at}seas.upenn.edu

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted September 11, 2018.
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The community structure of functional brain networks exhibits scale-specific patterns of variability across individuals and time
Richard F. Betzel, Maxwell A. Bertolero, Evan M. Gordon, Caterina Gratton, Nico U.F. Dosenbach, Danielle S. Bassett
bioRxiv 413278; doi: https://doi.org/10.1101/413278
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The community structure of functional brain networks exhibits scale-specific patterns of variability across individuals and time
Richard F. Betzel, Maxwell A. Bertolero, Evan M. Gordon, Caterina Gratton, Nico U.F. Dosenbach, Danielle S. Bassett
bioRxiv 413278; doi: https://doi.org/10.1101/413278

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