Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 112, Issue 49, Pages E6798-E6807Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1510619112
Keywords
modularity; hubs; cognition; graph theory; network
Categories
Funding
- NIH [NS79698]
- National Science Foundation Graduate Research Fellowship Program [DGE 1106400]
- National University of Singapore (NUS)
- Singapore Ministry of Education (MOE) [MOE2014-T2-2-016]
- NUS Strategic Research [DPRT/944/09/14]
- NUS School of Medicine Aspiration Fund [R185000271720]
- Singapore National Medical Research Council [CBRG14nov007]
- National Institutes of Health, National Institute of Mental Health [R01 MH074457]
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Network-based analyses of brain imaging data consistently reveal distinct modules and connector nodes with diverse global connectivity across the modules. How discrete the functions of modules are, how dependent the computational load of each module is to the other modules' processing, and what the precise role of connector nodes is for between-module communication remains under-specified. Here, we use a network model of the brain derived from resting-state functional MRI (rs-fMRI) data and investigate the modular functional architecture of the human brain by analyzing activity at different types of nodes in the network across 9,208 experiments of 77 cognitive tasks in the BrainMap database. Using an author-topic model of cognitive functions, we find a strong spatial correspondence between the cognitive functions and the network's modules, suggesting that each module performs a discrete cognitive function. Crucially, activity at local nodes within the modules does not increase in tasks that require more cognitive functions, demonstrating the autonomy of modules' functions. However, connector nodes do exhibit increased activity when more cognitive functions are engaged in a task. Moreover, connector nodes are located where brain activity is associated with many different cognitive functions. Connector nodes potentially play a role in between-module communication that maintains the modular function of the brain. Together, these findings provide a network account of the brain's modular yet integrated implementation of cognitive functions.
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