Modeling motor connectivity using TMS/PET and structural equation modeling
Identifieur interne : 001056 ( Pmc/Corpus ); précédent : 001055; suivant : 001057Modeling motor connectivity using TMS/PET and structural equation modeling
Auteurs : Angela R. Laird ; Jacob M. Robbins ; Karl Li ; Larry R. Price ; Matthew D. Cykowski ; Shalini Narayana ; Robert W. Laird ; Crystal Franklin ; Peter T. FoxSource :
- NeuroImage [ 1053-8119 ] ; 2008.
Abstract
Structural equation modeling (SEM) was applied to positron emission tomographic (PET) images acquired during transcranial magnetic stimulation (TMS) of the primary motor cortex (M1hand). TMS was applied across a range of intensities, and responses both at the stimulation site and remotely connected brain regions covaried with stimulus intensity. Regions of interest (ROIs) were identified through an activation likelihood estimation (ALE) meta-analysis of TMS studies. That these ROIs represented the network engaged by motor planning and execution was confirmed by an ALE meta-analysis of finger movement studies. Rather than postulate connections in the form of an
Url:
DOI: 10.1016/j.neuroimage.2008.01.065
PubMed: 18387823
PubMed Central: 2871686
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