TY - JOUR AU - Laird, A.R. AU - Fox, P.M. AU - Eickhoff, S.B. AU - Turner, J.A. AU - Ray, K.L. AU - McKay, D.R. AU - Glahn, D.C. AU - Beckmann, C.F. AU - Smith, S.M. AU - Fox, P.T. TI - Behavioral Interpretations of Intrinsic Connectivity Networks JO - Journal of cognitive neuroscience VL - 23 SN - 0898-929X CY - Cambridge, Mass. PB - MIT Pr. Journals M1 - PreJuSER-15664 SP - 4022 - 4037 PY - 2011 N1 - This work was supported by NIMH grants R01-MH074457 (P. T. F. and A. R. L.) and R01-MH084812 (A. R. L. and J. A. T.) and the Helmholz Initiative on Systems-Biology (S. B. E.). AB - An increasingly large number of neuroimaging studies have investigated functionally connected networks during rest, providing insight into human brain architecture. Assessment of the functional qualities of resting state networks has been limited by the task-independent state, which results in an inability to relate these networks to specific mental functions. However, it was recently demonstrated that similar brain networks can be extracted from resting state data and data extracted from thousands of task-based neuroimaging experiments archived in the BrainMap database. Here, we present a full functional explication of these intrinsic connectivity networks at a standard low order decomposition using a neuroinformatics approach based on the BrainMap behavioral taxonomy as well as a stratified, data-driven ordering of cognitive processes. Our results serve as a resource for functional interpretations of brain networks in resting state studies and future investigations into mental operations and the tasks that drive them. KW - Brain: physiology KW - Brain Mapping: methods KW - Classification: methods KW - Cluster Analysis KW - Databases, Factual KW - Humans KW - Nerve Net: physiology KW - Neural Pathways: physiology KW - Psychomotor Performance: physiology KW - J (WoSType) LB - PUB:(DE-HGF)16 C6 - pmid:21671731 UR - <Go to ISI:>//WOS:000296758500028 DO - DOI:10.1162/jocn_a_00077 UR - https://juser.fz-juelich.de/record/15664 ER -