Basal ganglia functional connectivity based on a meta-analysis of 126 positron emission tomography and functional magnetic resonance imaging publications.
The striatum receives projections from the entire cerebral cortex. Different, but not mutually exclusive, models of corticostriatal connectivity have been proposed, including connectivity based on proximity, parallel loops, and a model of a tripartite division of the striatum into motor, associative, and limbic areas. All these models were largely based on studies of anatomic connectivity in nonhuman mammals and lesion studies in animals and humans. Functional neuroimaging has the potential to discern patterns of functional connectivity in humans in vivo. We analyzed the functional connectivity between the cortex and the striatum in a meta-analysis of 126 published functional neuroimaging studies. We mapped the peak activations listed in each publication into stereotaxic space and used standard functional imaging statistical methods to determine which cortical areas were most likely to coactivate with different parts of the striatum. The patterns of functional connectivity between the cortex and the different striatal nuclei are broadly consistent with the predictions of the parallel loop model. The rostrocaudal and dorsoventral patterns of corticostriatal functional connectivity are consistent with the tripartite division of the striatum into motor, associative, and limbic zones.
Postuma
Ronald B
RB
Montreal Neurological Institute, Montreal General Hospital, McGill University, 3801 University Street Montreal, Quebec H3A 2B4, Canada.
Dagher
Alain
A
D001479:Basal Ganglia / Q000033:anatomy & histology* / Q000502:physiology*; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000033:anatomy & histology* / Q000502:physiology*; D006801:Humans; D016239:MEDLINE; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D009434:Neural Pathways / Q000166:cytology / Q000502:physiology; D010506:Periodicals as Topic; D049268:Positron-Emission Tomography / Q000706:statistics & numerical data*