%0 Journal Article
%A Eickhoff, S.B.
%A Bzdok, D.
%A Laird, A.R.
%A Roski, C.
%A Caspers, S.
%A Zilles, K.
%A Fox, P.T.
%T Co-activation patterns distinguish cortical modules, their connectivity and functional differentiation
%J NeuroImage
%V 57
%@ 1053-8119
%C Orlando, Fla.
%I Academic Press
%M PreJuSER-15399
%P 938 - 949
%D 2011
%Z This work was partly funded by the Human Brain Project (R01-MH074457-01A1; S.B.E., A.R.L., and P.T.F), the Initiative and Networking Fund of the Helmholtz Association within the Helmholtz Alliance on Systems Biology (Human Brain Model; K.Z., S.B.E.), the DFG (IRTG 1328, S.B.E., D.B.) and the Helmholtz Alliance for Mental Health in an Aging Society (HelMA; K.Z.).
%X The organization of the cerebral cortex into distinct modules may be described along several dimensions, most importantly, structure, connectivity and function. Identification of cortical modules by differences in whole-brain connectivity profiles derived from diffusion tensor imaging or resting state correlations has already been shown. These approaches, however, carry no task-related information. Hence, inference on the functional relevance of the ensuing parcellation remains tentative. Here, we demonstrate, that Meta-Analytic Connectivity Modeling (MACM) allows the delineation of cortical modules based on their whole-brain co-activation pattern across databased neuroimaging results. Using a model free approach, two regions of the medial pre-motor cortex, SMA and pre-SMA were differentiated solely based on their functional connectivity. Assessing the behavioral domain and paradigm class meta-data of the experiments associated with the clusters derived from the co-activation based parcellation moreover allows the identification of their functional characteristics. The ensuing hypotheses about functional differentiation and distinct functional connectivity between pre-SMA and SMA were then explicitly tested and confirmed in independent datasets using functional and resting state fMRI. Co-activation based parcellation thus provides a new perspective for identifying modules of functional connectivity and linking them to functional properties, hereby generating new and subsequently testable hypotheses about the organization of cortical modules.
%K Algorithms
%K Brain: anatomy & histology
%K Brain: physiology
%K Brain Mapping: methods
%K Cluster Analysis
%K Humans
%K Image Processing, Computer-Assisted: methods
%K Magnetic Resonance Imaging
%K Neural Pathways: anatomy & histology
%K Neural Pathways: physiology
%K J (WoSType)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:21609770
%2 pmc:PMC3129435
%U <Go to ISI:>//WOS:000292717900028
%R 10.1016/j.neuroimage.2011.05.021
%U https://juser.fz-juelich.de/record/15399