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The Journal of Neuroscience, November 18, 2009, 29(46):14496-14505; doi:10.1523/JNEUROSCI.4004-09.2009

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Behavioral/Systems/Cognitive
Investigating the Functional Heterogeneity of the Default Mode Network Using Coordinate-Based Meta-Analytic Modeling

Angela R. Laird,¹ Simon B. Eickhoff,^2,3,4 Karl Li,¹ Donald A. Robin,¹ David C. Glahn,^5,6 and Peter T. Fox¹

¹Research Imaging Center, University of Texas Health Science Center, San Antonio, Texas 78229-3900, ²Institut for Neuroscience and Biophysics–Medicine, Research Center Jülich, 52428 Jülich, Germany, ³Department of Psychiatry and Psychotherapy, RWTH Aachen University, Aachen, Germany, ⁴Jülich Aachen Research Alliance (JARA)–Translational Brain Medicine, Germany, ⁵Olin Neuropsychiatric Research Center, Institute of Living, Hartford, Connecticut 06106, and ⁶Department of Psychiatry, Yale University, Hartford, Connecticut 06106

Correspondence should be addressed to Angela R. Laird, Research Imaging Center, University of Texas Health Science Center San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229-3900. Email: lairda{at}uthscsa.edu

The default mode network (DMN) comprises a set of regions that exhibit ongoing, intrinsic activity in the resting state and task-related decreases in activity across a range of paradigms. However, DMN regions have also been reported as task-related increases, either independently or coactivated with other regions in the network. Cognitive subtractions and the use of low-level baseline conditions have generally masked the functional nature of these regions. Using a combination of activation likelihood estimation, which assesses statistically significant convergence of neuroimaging results, and tools distributed with the BrainMap database, we identified core regions in the DMN and examined their functional heterogeneity. Meta-analytic coactivation maps of task-related increases were independently generated for each region, which included both within-DMN and non-DMN connections. Their functional properties were assessed using behavioral domain metadata in BrainMap. These results were integrated to determine a DMN connectivity model that represents the patterns of interactions observed in task-related increases in activity across diverse tasks. Subnetwork components of this model were identified, and behavioral domain analysis of these cliques yielded discrete functional properties, demonstrating that components of the DMN are differentially specialized. Affective and perceptual cliques of the DMN were identified, as well as the cliques associated with a reduced preference for motor processing. In summary, we used advanced coordinate-based meta-analysis techniques to explicate behavior and connectivity in the default mode network; future work will involve applying this analysis strategy to other modes of brain function, such as executive function or sensorimotor systems.

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Received Aug. 14, 2009; revised Sept. 29, 2009; accepted Oct. 2, 2009.

Correspondence should be addressed to Angela R. Laird, Research Imaging Center, University of Texas Health Science Center San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229-3900. Email: lairda{at}uthscsa.edu

This article has been cited by other articles:

				S. B. Eickhoff, S. Jbabdi, S. Caspers, A. R. Laird, P. T. Fox, K. Zilles, and T. E. J. Behrens Anatomical and Functional Connectivity of Cytoarchitectonic Areas within the Human Parietal Operculum J. Neurosci., May 5, 2010; 30(18): 6409 - 6421. [Abstract] [Full Text] [PDF]

				D. C. Glahn, A. M. Winkler, P. Kochunov, L. Almasy, R. Duggirala, M. A. Carless, J. C. Curran, R. L. Olvera, A. R. Laird, S. M. Smith, et al. Genetic control over the resting brain PNAS, January 19, 2010; 107(3): 1223 - 1228. [Abstract] [Full Text] [PDF]

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