TY - JOUR
T1 - Multimodal connectivity of motor learning-related dorsal premotor cortex
AU - Hardwick, Robert M.
AU - Lesage, Elise
AU - Eickhoff, Claudia R.
AU - Clos, Mareike
AU - Fox, Peter
AU - Eickhoff, Simon B.
N1 - Publisher Copyright:
© 2015 Elsevier Inc.
PY - 2015/12/1
Y1 - 2015/12/1
N2 - 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.
AB - 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.
KW - Functional connectivity
KW - Meta-analytic connectivity modeling
KW - Motor learning
KW - Resting state
KW - Resting state functional connectivity
KW - Structural covariance
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U2 - 10.1016/j.neuroimage.2015.08.024
DO - 10.1016/j.neuroimage.2015.08.024
M3 - Article
C2 - 26282855
AN - SCOPUS:84941219370
SN - 1053-8119
VL - 123
SP - 114
EP - 128
JO - NeuroImage
JF - NeuroImage
ER -