Literature DB >> 26282855

Multimodal connectivity of motor learning-related dorsal premotor cortex.

Robert M Hardwick1, Elise Lesage2, Claudia R Eickhoff3, Mareike Clos4, Peter Fox5, Simon B Eickhoff6.   

Abstract

The dorsal premotor cortex (dPMC) is a key region for motor learning and sensorimotor integration, yet we have limited understanding of its functional interactions with other regions. Previous work has started to examine functional connectivity in several brain areas using resting state functional connectivity (RSFC) and meta-analytical connectivity modelling (MACM). More recently, structural covariance (SC) has been proposed as a technique that may also allow delineation of functional connectivity. Here, we applied these three approaches to provide a comprehensive characterization of functional connectivity with a seed in the left dPMC that a previous meta-analysis of functional neuroimaging studies has identified as playing a key role in motor learning. Using data from two sources (the Rockland sample, containing resting state data and anatomical scans from 132 participants, and the BrainMap database, which contains peak activation foci from over 10,000 experiments), we conducted independent whole-brain functional connectivity mapping analyses of a dPMC seed. RSFC and MACM revealed similar connectivity maps spanning prefrontal, premotor, and parietal regions, while the SC map identified more widespread frontal regions. Analyses indicated a relatively consistent pattern of functional connectivity between RSFC and MACM that was distinct from that identified by SC. Notably, results indicate that the seed is functionally connected to areas involved in visuomotor control and executive functions, suggesting that the dPMC acts as an interface between motor control and cognition.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Functional connectivity; Meta-analytic connectivity modeling; Motor learning; Resting state; Resting state functional connectivity; Structural covariance

Mesh:

Year:  2015        PMID: 26282855      PMCID: PMC4780681          DOI: 10.1016/j.neuroimage.2015.08.024

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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