22
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Identifying Basal Ganglia Divisions in Individuals Using Resting-State Functional Connectivity MRI

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          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.

          Related collections

          Most cited references19

          • Record: found
          • Abstract: not found
          • Article: not found

          Parallel organization of functionally segregated circuits linking basal ganglia and cortex.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Modularity and community structure in networks

            M. Newman (2006)
            Many networks of interest in the sciences, including a variety of social and biological networks, are found to divide naturally into communities or modules. The problem of detecting and characterizing this community structure has attracted considerable recent attention. One of the most sensitive detection methods is optimization of the quality function known as "modularity" over the possible divisions of a network, but direct application of this method using, for instance, simulated annealing is computationally costly. Here we show that the modularity can be reformulated in terms of the eigenvectors of a new characteristic matrix for the network, which we call the modularity matrix, and that this reformulation leads to a spectral algorithm for community detection that returns results of better quality than competing methods in noticeably shorter running times. We demonstrate the algorithm with applications to several network data sets.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Functional connectivity of human striatum: a resting state FMRI study.

              Classically regarded as motor structures, the basal ganglia subserve a wide range of functions, including motor, cognitive, motivational, and emotional processes. Consistent with this broad-reaching involvement in brain function, basal ganglia dysfunction has been implicated in numerous neurological and psychiatric disorders. Despite recent advances in human neuroimaging, models of basal ganglia circuitry continue to rely primarily upon inference from animal studies. Here, we provide a comprehensive functional connectivity analysis of basal ganglia circuitry in humans through a functional magnetic resonance imaging examination during rest. Voxelwise regression analyses substantiated the hypothesized motor, cognitive, and affective divisions among striatal subregions, and provided in vivo evidence of a functional organization consistent with parallel and integrative loop models described in animals. Our findings also revealed subtler distinctions within striatal subregions not previously appreciated by task-based imaging approaches. For instance, the inferior ventral striatum is functionally connected with medial portions of orbitofrontal cortex, whereas a more superior ventral striatal seed is associated with medial and lateral portions. The ability to map multiple distinct striatal circuits in a single study in humans, as opposed to relying on meta-analyses of multiple studies, is a principal strength of resting state functional magnetic resonance imaging. This approach holds promise for studying basal ganglia dysfunction in clinical disorders.
                Bookmark

                Author and article information

                Journal
                Front Syst Neurosci
                Front. Syst. Neurosci.
                Frontiers in Systems Neuroscience
                Frontiers Research Foundation
                1662-5137
                23 March 2010
                10 June 2010
                2010
                : 4
                : 18
                Affiliations
                [1] 1simpleDepartment of Neurology, Washington University School of Medicine St. Louis, MO, USA
                [2] 2simpleDepartment of Radiology, Washington University School of Medicine St. Louis, MO, USA
                [3] 3simpleDepartment of Psychology, Washington University School of Medicine St. Louis, MO, USA
                [4] 4simpleDepartment of Anatomy and Neurobiology, Washington University School of Medicine St. Louis, MO, USA
                [5] 5simpleDepartment of Pediatrics, Washington University School of Medicine St. Louis, MO, USA
                Author notes

                Edited by: Lucina Q. Uddin, Stanford University, USA

                Reviewed by: Adriana Di Martino, New York University Langone Medical Center, USA; Bogdan Draganski, University College London, UK

                *Correspondence: Kelly Anne Barnes, Department of Neurology, Washington University School of Medicine, 4525 Scott Avenue, Room 2220, St. Louis, MO 63110, USA. e-mail: barnesk@ 123456npg.wustl.edu
                Article
                10.3389/fnsys.2010.00018
                2892946
                20589235
                1c0c6d20-04fe-4ba8-b654-305fc8cb488b
                Copyright © 2010 Barnes, Cohen, Power, Nelson, Dosenbach, Miezin, Petersen and Schlaggar.

                This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.

                History
                : 19 February 2010
                : 11 May 2010
                Page count
                Figures: 4, Tables: 1, Equations: 0, References: 38, Pages: 10, Words: 7518
                Categories
                Neuroscience
                Original Research

                Neurosciences
                graph theory,striatum,cortico-basal ganglia loops,functional connectivity,connectome
                Neurosciences
                graph theory, striatum, cortico-basal ganglia loops, functional connectivity, connectome

                Comments

                Comment on this article