38
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke

      Read this article at

      ScienceOpenPublisherPMC
      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

          Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity (FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next, we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain-behavior relationships in stroke.

          Related collections

          Most cited references35

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

          A whole brain fMRI atlas generated via spatially constrained spectral clustering.

          Connectivity analyses and computational modeling of human brain function from fMRI data frequently require the specification of regions of interests (ROIs). Several analyses have relied on atlases derived from anatomical or cyto-architectonic boundaries to specify these ROIs, yet the suitability of atlases for resting state functional connectivity (FC) studies has yet to be established. This article introduces a data-driven method for generating an ROI atlas by parcellating whole brain resting-state fMRI data into spatially coherent regions of homogeneous FC. Several clustering statistics are used to compare methodological trade-offs as well as determine an adequate number of clusters. Additionally, we evaluate the suitability of the parcellation atlas against four ROI atlases (Talairach and Tournoux, Harvard-Oxford, Eickoff-Zilles, and Automatic Anatomical Labeling) and a random parcellation approach. The evaluated anatomical atlases exhibit poor ROI homogeneity and do not accurately reproduce FC patterns present at the voxel scale. In general, the proposed functional and random parcellations perform equivalently for most of the metrics evaluated. ROI size and hence the number of ROIs in a parcellation had the greatest impact on their suitability for FC analysis. With 200 or fewer ROIs, the resulting parcellations consist of ROIs with anatomic homology, and thus offer increased interpretability. Parcellation results containing higher numbers of ROIs (600 or 1,000) most accurately represent FC patterns present at the voxel scale and are preferable when interpretability can be sacrificed for accuracy. The resulting atlases and clustering software have been made publicly available at: http://www.nitrc.org/projects/cluster_roi/. Copyright © 2011 Wiley Periodicals, Inc.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Decreased segregation of brain systems across the healthy adult lifespan.

            Healthy aging has been associated with decreased specialization in brain function. This characterization has focused largely on describing age-accompanied differences in specialization at the level of neurons and brain areas. We expand this work to describe systems-level differences in specialization in a healthy adult lifespan sample (n = 210; 20-89 y). A graph-theoretic framework is used to guide analysis of functional MRI resting-state data and describe systems-level differences in connectivity of individual brain networks. Young adults' brain systems exhibit a balance of within- and between-system correlations that is characteristic of segregated and specialized organization. Increasing age is accompanied by decreasing segregation of brain systems. Compared with systems involved in the processing of sensory input and motor output, systems mediating "associative" operations exhibit a distinct pattern of reductions in segregation across the adult lifespan. Of particular importance, the magnitude of association system segregation is predictive of long-term memory function, independent of an individual's age.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Breakdown of functional connectivity in frontoparietal networks underlies behavioral deficits in spatial neglect.

              Spatial neglect is a syndrome following stroke manifesting attentional deficits in perceiving and responding to stimuli in the contralesional field. We examined brain network integrity in patients with neglect by measuring coherent fluctuations of fMRI signals (functional connectivity). Connectivity in two largely separate attention networks located in dorsal and ventral frontoparietal areas was assessed at both acute and chronic stages of recovery. Connectivity in the ventral network, part of which directly lesioned, was diffusely disrupted and showed no recovery. In the structurally intact dorsal network, interhemispheric connectivity in posterior parietal cortex was acutely disrupted but fully recovered. This acute disruption, and disrupted connectivity in specific pathways in the ventral network, strongly correlated with impaired attentional processing across subjects. Lastly, disconnection of the white matter tracts connecting frontal and parietal cortices was associated with more severe neglect and more disrupted functional connectivity. These findings support a network view in understanding neglect.
                Bookmark

                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                July 26 2016
                July 26 2016
                July 26 2016
                July 11 2016
                : 113
                : 30
                : E4367-E4376
                Article
                10.1073/pnas.1521083113
                4968743
                27402738
                e38533ee-dc8d-4127-9768-46f3b7312917
                © 2016

                Free to read

                http://www.pnas.org/site/misc/userlicense.xhtml

                History

                Comments

                Comment on this article