Though there is a growing trend to examine healthy and pathological brain activity in the framework of networks, a comprehensive, robust description of human brain networks has not been established (Bullmore &Sporns, 2009). Resting state functional connectivity MRI (rs-fcMRI) is potentially capable of describing functional brain organization at the level of functional areas, but no large-scale networks at the level of functional areas have been described thus far. This proposal aims to provide a rigorous, reasoned, and accurate description of a network of functional areas in healthy young adults.
The first aim i s to use meta-analytic fMRI techniques and a recently developed data-driven rs-fcMRI technique (fc-Mapping) to define putative functional areas in humans.
The second aim i s to construct brain- wide networks in rs-fcMRI data, using putative areas as network nodes. The tendency for nodes to form groups (called modules) within the network will be quantified, with the expectation that nodes will gather into modules of functionally-related areas. Published rs-fcMRI networks typically use voxels or pre-defined anatomical parcellations of voxels as nodes in networks. There are reasons to suspect that such networks are suboptimal representations of the brain's functional architecture, and the final aim is to compare the modular structures of networks of voxels, putative areas, and parcels, all derived from the same subjects. Substantial incongruence between modular structures is expected. The biological plausibility of network modules will be tested by examining the coherence of signals within modules in task fMRI data (that was not used in Aim 1). If the rs-fcMRI signal reflects aspects of information processing, as it is thought to, then networks based on this signal should reflect information processing systems. A network of functional areas should illuminate basic features of brain organization, such as how functional areas group into functional systems, and how such systems relate to one another. A robust description of "typical" functional brain organization in healthy young adults provides a comparator for studies in pathologic conditions, and for studies of development and aging. The network approaches developed herein offer, theoretically, greater sensitivity to such changes than previous techniques, and these approaches, in combination with tools such as fc-Mapping, will be powerful methods for investigating functional brain organization.

Public Health Relevance

The brain is a network, but the functional organization of this network is not well understood. This project aims to better define functional brain networks, which can be measured quite easily in healthy and in sick people. If this project is successful, the structure and properties of functional brain networks will become more useful in diagnosing or understanding disease states, and also for understanding how the healthy brain works.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
Project #
5F30MH094032-03
Application #
8585104
Study Section
Special Emphasis Panel (ZRG1-F01-F (20))
Program Officer
Rosemond, Erica K
Project Start
2011-12-01
Project End
2015-11-30
Budget Start
2013-12-01
Budget End
2014-11-30
Support Year
3
Fiscal Year
2014
Total Cost
$47,232
Indirect Cost
Name
Washington University
Department
Neurology
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
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Siegel, Joshua S; Power, Jonathan D; Dubis, Joseph W et al. (2014) Statistical improvements in functional magnetic resonance imaging analyses produced by censoring high-motion data points. Hum Brain Mapp 35:1981-96
Power, Jonathan D; Mitra, Anish; Laumann, Timothy O et al. (2014) Methods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage 84:320-41
Power, Jonathan D; Petersen, Steven E (2013) Control-related systems in the human brain. Curr Opin Neurobiol 23:223-8
Power, Jonathan D; Barnes, Kelly Anne; Snyder, Abraham Z et al. (2013) Steps toward optimizing motion artifact removal in functional connectivity MRI; a reply to Carp. Neuroimage 76:439-41
Power, Jonathan D; Schlaggar, Bradley L; Lessov-Schlaggar, Christina N et al. (2013) Evidence for hubs in human functional brain networks. Neuron 79:798-813