TY  - JOUR
AU  - Eickhoff, S.B.
AU  - Bzdok, D.
AU  - Laird, A.R.
AU  - Roski, C.
AU  - Caspers, S.
AU  - Zilles, K.
AU  - Fox, P.T.
TI  - Co-activation patterns distinguish cortical modules, their connectivity and functional differentiation
JO  - NeuroImage
VL  - 57
SN  - 1053-8119
CY  - Orlando, Fla.
PB  - Academic Press
M1  - PreJuSER-15399
SP  - 938 - 949
PY  - 2011
N1  - 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.).
AB  - 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.
KW  - Algorithms
KW  - Brain: anatomy & histology
KW  - Brain: physiology
KW  - Brain Mapping: methods
KW  - Cluster Analysis
KW  - Humans
KW  - Image Processing, Computer-Assisted: methods
KW  - Magnetic Resonance Imaging
KW  - Neural Pathways: anatomy & histology
KW  - Neural Pathways: physiology
KW  - J (WoSType)
LB  - PUB:(DE-HGF)16
C6  - pmid:21609770
C2  - pmc:PMC3129435
UR  - <Go to ISI:>//WOS:000292717900028
DO  - DOI:10.1016/j.neuroimage.2011.05.021
UR  - https://juser.fz-juelich.de/record/15399
ER  -