Identifying Basal Ganglia divisions in individuals using resting-state functional connectivity MRI

• Published in: Frontiers in systems neuroscience Vol. 4; p. 18
• Main Authors: Barnes, Kelly Anne, Cohen, Alexander L, Power, Jonathan D, Nelson, Steven M, Dosenbach, Yannic B L, Miezin, Francis M, Petersen, Steven E, Schlaggar, Bradley L
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 01.01.2010; Frontiers Media S.A
• Subjects: connectivity; connectome; cortico-basal ganglia loops; dorsal striatum; graph theory; Neuroscience; connectome; functional connectivity; striatum; graph theory; cortico-basal ganglia loops
• ISSN: 1662-5137; 1662-5137
• DOI: 10.3389/fnsys.2010.00018

Studies in non-human primates and humans reveal that discrete regions (henceforth, "divisions") in the basal ganglia are intricately interconnected with regions in the cerebral cortex. However, divisions within basal ganglia nuclei (e.g., within the caudate) are difficult to identify using structural MRI. Resting-state functional connectivity MRI (rs-fcMRI) can be used to identify putative cerebral cortical functional areas in humans (Cohen et al., 2008). Here, we determine whether rs-fcMRI can be used to identify divisions in individual human adult basal ganglia. Putative basal ganglia divisions were generated by assigning basal ganglia voxels to groups based on the similarity of whole-brain functional connectivity correlation maps using modularity optimization, a network analysis tool. We assessed the validity of this approach by examining the spatial contiguity and location of putative divisions and whether divisions' correlation maps were consistent with previously reported patterns of anatomical and functional connectivity. Spatially constrained divisions consistent with the dorsal caudate, ventral striatum, and dorsal caudal putamen could be identified in each subject. Further, correlation maps associated with putative divisions were consistent with their presumed connectivity. These findings suggest that, as in the cerebral cortex, subcortical divisions can be identified in individuals using rs-fcMRI. Developing and validating these methods should improve the study of brain structure and function, both typical and atypical, by allowing for more precise comparison across individuals.