Thalamo- and baso-cortical functional segregation of specialized brain networks in active and resting state: data-driven estimation and subsequent validation
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1
Medical Research Council Cognition and Brain Sciences Unit, United Kingdom
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2
Faculty of Psychology and Neuroscience, Maastricht University, Netherlands
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3
Institute of Medical Psychology, Johann Wolfgang Goethe-University, Germany
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4
Laboratory for Social and Neural Systems Research, University of Zürich, Switzerland
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5
Department of Cognition and Brain Sciences, Massachusetts Institute of Technology, United States
Functional connectivity defined as the functional coincidence of spatially distinct neurophysiological activity has been increasingly studied in both task-related and resting state experiments. We applied hierarchical independent component analysis (hICA) on functional magnetic resonance imaging data acquired in multisensory integration and resting state experiments. hICA decomposes data into spatially independent components which can be interpreted as functional connectivity maps. The selection procedure provided six Cluster-Representative Maps (CRMs) which included bilateral auditory cortex (AC), striate and extra-striate visual cortex (VC), bilateral sensory-motor cortex (SMC), medial frontal and parietal cortex and hippocampus (similar to the default-mode network, DMN) as well as left and right fronto-parietal cortex (r/lFP). Non-overlapping distribution of CRMs allowed further parcellation within the subcortical space that demonstrated that SMC included additional areas in bilateral putamen and the DMN, lFP, and rFP included additional areas in ventral parts of the caudate and putamen. We then used subcortical CRM regions-of-interest from the first experiment as seeds for a multiple regression analysis of the functional data of the second experiment. The cortical projections comprised regions that were also present in the CRMs of the first experiment. Spatial correlations as a measure of spatial similarity between the two maps resulted in moderate to high degrees of spatial similarity. Application of hICA on resting state data resulted in similar CRMs. These results strongly indicate the accuracy of hICA as a sensitive tool for the classification of distinct neuro-functional networks and highly support the validity of the detected thalamo- and basocortical regions.
Keywords:
Brain Signals,
resting state
Conference:
XI International Conference on Cognitive Neuroscience (ICON XI), Palma, Mallorca, Spain, 25 Sep - 29 Sep, 2011.
Presentation Type:
Poster Presentation
Topic:
Poster Sessions: Modeling and Analysis of Brain Signals
Citation:
Walther
A,
Van De Ven
VG,
Van Den Bosch
JJ,
Polony
A,
Hein
G,
Doehrmann
O,
Kaiser
J and
Naumer
MJ
(2011). Thalamo- and baso-cortical functional segregation of specialized brain networks in active and resting state: data-driven estimation and subsequent validation.
Conference Abstract:
XI International Conference on Cognitive Neuroscience (ICON XI).
doi: 10.3389/conf.fnhum.2011.207.00175
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Received:
18 Nov 2011;
Published Online:
28 Nov 2011.
*
Correspondence:
Mr. Alexander Walther, Medical Research Council Cognition and Brain Sciences Unit, Cambridge, United Kingdom, awalthermail@gmail.com