The Organization of Local and Distant Functional Connectivity in the Human Brain

Howard Hughes Medical Institute, Cambridge, Massachusetts, United States of America.
PLoS Computational Biology (Impact Factor: 4.62). 06/2010; 6(6):e1000808. DOI: 10.1371/journal.pcbi.1000808
Source: PubMed


Information processing in the human brain arises from both interactions between adjacent areas and from distant projections that form distributed brain systems. Here we map interactions across different spatial scales by estimating the degree of intrinsic functional connectivity for the local (<or=14 mm) neighborhood directly surrounding brain regions as contrasted with distant (>14 mm) interactions. The balance between local and distant functional interactions measured at rest forms a map that separates sensorimotor cortices from heteromodal association areas and further identifies regions that possess both high local and distant cortical-cortical interactions. Map estimates of network measures demonstrate that high local connectivity is most often associated with a high clustering coefficient, long path length, and low physical cost. Task performance changed the balance between local and distant functional coupling in a subset of regions, particularly, increasing local functional coupling in regions engaged by the task. The observed properties suggest that the brain has evolved a balance that optimizes information-processing efficiency across different classes of specialized areas as well as mechanisms to modulate coupling in support of dynamically changing processing demands. We discuss the implications of these observations and applications of the present method for exploring normal and atypical brain function.

  • Source
    • "Cognitive processes begin with the encoding of sensory information in primary sensory and motor cortices. These early sensory areas have a modular structure with predominantly local connections (Sepulcre et al., 2010) and represent elementary perceptual features of stimuli (Fuster, 2003). Sensorimotor cortices produce output directed to unimodal association areas. "
    [Show abstract] [Hide abstract]
    ABSTRACT: This article introduces a novel theoretical framework for psychopathy that bridges dominant affective and cognitive models. According to the proposed impaired integration (II) framework of psychopathic dysfunction, topographical irregularities and abnormalities in neural connectivity in psychopathy hinder the complex process of information integration. Central to the II theory is the notion that psychopathic individuals are “‘wired up’ differently” (Hare, Williamson, & Harpur, 1988, p. 87). Specific theoretical assumptions include decreased functioning of the Salience and Default Mode Networks, normal functioning in executive control networks, and less coordination and flexible switching between networks. Following a review of dominant models of psychopathy, we introduce our II theory as a parsimonious account of behavioral and brain irregularities in psychopathy. The II theory provides a unified theoretical framework for understanding psychopathic dysfunction and integrates principle tenets of affective and cognitive perspectives. Moreover, it accommodates evidence regarding connectivity abnormalities in psychopathy through its network theoretical perspective.
    Full-text · Article · Oct 2015 · Psychological Review
  • Source
    • "Furthermore, we adopted an approach to capture the distant and local DC, respectively, using anatomical distance as a cutoff(Achard et al., 2006; He et al., 2008; Sepulcre et al., 2010). This method can allow us to investigate the local and distant brain interactions separately, which can explore the potential difference in the local and distant connectivity as a result of only child loss. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The loss of an only child is a negative life event and may potentially increase the risk of psychiatric disorders. However, the psychological consequences of the loss of an only child and the associated neural mechanisms remain largely unexplored. Degree centrality(DC), derived from resting-state functional magnetic resonance imaging(fMRI), was used to examine network communication in 22 older adults who lost their only child and 23 matched controls. The older adults who lost their only child exhibited an ineffective coping style. They also showed decreased distant and local DC in the precuneus and left inferior parietal lobule and decreased distant DC in the bilateral dorsolateral prefrontal cortex(DLPFC). Furthermore, the decreased local and distant DC of these regions and the decreased DLPFC-precuneus connectivity strength were negatively correlated with negative coping scores in the loss group but not in the controls. Overall, the results suggested a model that the impaired neural network communication of brain hubs within the default mode network(DMN) and central executive network(CEN) were associated with a negative coping style in older adults who lost their only child. The decreased connectivity of the hubs can be identified as a neural risk factor that is related to future psychopathology.
    Full-text · Article · Sep 2015 · Biological psychology
  • Source
    • "In stark contrast, unimodal networks including the visual and sensorimotor networks, along with the temporal and brainstem networks are balanced toward segregative processing (Fig. 5). These results are aligned with the notion that association networks participate in long-distance (Sepulcre et al., 2010), flexible (Cole et al., 2013), dynamic (Zalesky et al., 2014), and globally connected (Buckner et al., 2009; Cole et al., 2010; van den Heuvel and Sporns, 2013) information processing in the brain, and suggest that association networks may play a central role in facilitating the integration of information across distributed cortical regions (Yeo et al., 2013). Furthermore, our data provide novel evidence to suggest that subcortical structures such as the basal ganglia and the thalamus also support integration across large-scale networks of the brain (Figs. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The study of resting-state networks provides an informative paradigm for understanding the functional architecture of the human brain. Although investigating specialized resting-state networks has led to significant advances in our understanding of brain organization, the manner in which information is integrated across these networks remains unclear. Here, we have developed and validated a data-driven methodology for describing the topography of resting-state network convergence in the human brain. Our results demonstrate the importance of an ensemble of cortical and subcortical regions in supporting the convergence of multiple resting-state networks, including the rostral anterior cingulate, precuneus, posterior cingulate cortex, bilateral posterior parietal cortex, bilateral dorsal prefrontal cortex, along with the caudate head, anterior claustrum and posterior thalamus. In addition, we have demonstrated a significant correlation between voxel-wise network convergence and global brain connectivity, emphasizing the importance of resting-state network convergence in facilitating global brain communication. Finally, we examined the convergence of systems within each of the individual resting-state networks in the brain, revealing the heterogeneity by which individual resting-state networks balance the competing demands of specialized processing against the integration of information. Together, our results suggest that the convergence of resting-state networks represents an important organizational principle underpinning systems-level integration in the human brain.
    Full-text · Article · May 2015 · Brain Connectivity
Show more