4.7 Article

Subspecialization in the human posterior medial cortex

Journal

NEUROIMAGE
Volume 106, Issue -, Pages 55-71

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2014.11.009

Keywords

Connectivity-based parcellation; Statistical learning; Functional decoding; Parietal lobe; Posterior cingulate cortex; Retrosplenial cortex; Default mode network

Funding

  1. Deutsche Forschungsgemeinschaft (DFG) [EI 816/4-1, 3071/3-1, EI 816/6-1]
  2. National Institute of Mental Health [R01-MH074457]
  3. Helmholtz Initiative on Systems Biology
  4. German National Academic Foundation

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The posterior medial cortex (PMC) is particularly poorly understood. Its neural activity changes have been related to highly disparate mental processes. We therefore investigated PMC properties with a data-driven exploratory approach. First, we subdivided the PMC by whole-brain coactivation profiles. Second, functional connectivity of the ensuing PMC regions was compared by task-constrained meta-analytic coactivation mapping (MACM) and task-unconstrained resting-state correlations (RSFC). Third, PMC regions were functionally described by forward/reverse functional inference. A precuneal cluster was mostly connected to the intraparietal sulcus, frontal eye fields, and right temporo-parietal junction; associated with attention and motor tasks. A ventral posterior cingulate cortex (PCC) cluster was mostly connected to the ventromedial prefrontal cortex and middle left inferior parietal cortex (IPC); associated with facial appraisal and language tasks. A dorsal PCC cluster was mostly connected to the dorsomedial prefrontal cortex, anterior/posterior IPC, posterior midcingulate cortex, and left dorsolateral prefrontal cortex; associated with delay discounting. A cluster in the retrosplenial cortex was mostly connected to the anterior thalamus and hippocampus. Furthermore, all PMC clusters were congruently coupled with the default mode network according to task-unconstrained but not task-constrained connectivity. We thus identified distinct regions in the PMC and characterized their neural networks and functional implications. (C) 2014 Elsevier Inc. All rights reserved.

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