Disrupted small-world networks in schizophrenia

National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China.
Brain (Impact Factor: 10.23). 05/2008; 131(Pt 4):945-61. DOI: 10.1093/brain/awn018
Source: PubMed

ABSTRACT The human brain has been described as a large, sparse, complex network characterized by efficient small-world properties, which assure that the brain generates and integrates information with high efficiency. Many previous neuroimaging studies have provided consistent evidence of 'dysfunctional connectivity' among the brain regions in schizophrenia; however, little is known about whether or not this dysfunctional connectivity causes disruption of the topological properties of brain functional networks. To this end, we investigated the topological properties of human brain functional networks derived from resting-state functional magnetic resonance imaging (fMRI). Data was obtained from 31 schizophrenia patients and 31 healthy subjects; then functional connectivity between 90 cortical and sub-cortical regions was estimated by partial correlation analysis and thresholded to construct a set of undirected graphs. Our findings demonstrated that the brain functional networks had efficient small-world properties in the healthy subjects; whereas these properties were disrupted in the patients with schizophrenia. Brain functional networks have efficient small-world properties which support efficient parallel information transfer at a relatively low cost. More importantly, in patients with schizophrenia the small-world topological properties are significantly altered in many brain regions in the prefrontal, parietal and temporal lobes. These findings are consistent with a hypothesis of dysfunctional integration of the brain in this illness. Specifically, we found that these altered topological measurements correlate with illness duration in schizophrenia. Detection and estimation of these alterations could prove helpful for understanding the pathophysiological mechanism as well as for evaluation of the severity of schizophrenia.

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Available from: Yong Liu, Sep 19, 2014
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    • "In particular, the architecture of functional connectivity in patients is significantly affected by duration of illness. Patients with longer duration of illness show reduced segregation and integration (Liu et al., 2008), and reduced connectivity among core brain hubs (Collin et al., 2013). In light of these observations, we expected a moderating effect of illness duration on FCE. "
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    ABSTRACT: Spatial variation in connectivity is an integral aspect of the brain's architecture. In the absence of this variability, the brain may act as a single homogenous entity without regional specialization. In this study, we investigate the variability in functional links categorized on the basis of the presence of direct structural paths (primary) or indirect paths mediated by one (secondary) or more (tertiary) brain regions ascertained by diffusion tensor imaging. We quantified the variability in functional connectivity using an unbiased estimate of unpredictability (functional connectivity entropy) in a neuropsychiatric disorder where structure-function relationship is considered to be abnormal; 34 patients with schizophrenia and 32 healthy controls underwent DTI and resting state functional MRI scans. Less than one-third (27.4% in patients, 27.85% in controls) of functional links between brain regions were regarded as direct primary links on the basis of DTI tractography, while the rest were secondary or tertiary. The most significant changes in the distribution of functional connectivity in schizophrenia occur in indirect tertiary paths with no direct axonal linkage in both early (P = 0.0002, d = 1.46) and late (P = 1 × 10(-17) , d = 4.66) stages of schizophrenia, and are not altered by the severity of symptoms, suggesting that this is an invariant feature of this illness. Unlike those with early stage illness, patients with chronic illness show some additional reduction in the distribution of connectivity among functional links that have direct structural paths (P = 0.08, d = 0.44). Our findings address a critical gap in the literature linking structure and function in schizophrenia, and demonstrate for the first time that the abnormal state of functional connectivity preferentially affects structurally unconstrained links in schizophrenia. It also raises the question of a continuum of dysconnectivity ranging from less direct (structurally unconstrained) to more direct (structurally constrained) brain pathways underlying the progressive clinical staging and persistence of schizophrenia. Hum Brain Mapp, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.
    Human Brain Mapping 08/2015; DOI:10.1002/hbm.22932 · 6.92 Impact Factor
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    • ", 2010 for review ) or degree of synaptic connectivity ( e . g . , Ermentrout , 1998 ; Golomb and Ermentrout , 1999 ) that we explicitly attempted to manipulate here . When those mechanisms including structural and oscillatory dynamics break down , the result may lead to a variety of neurophysiological disorders including schizophrenia ( e . g . , Liu et al . , 2008b ; Lynall et al . , 2010 ) in which functional dysconnectivity is thought to play a role ( Stephan et al . , 2009 ; Phillips and Uhlhaas , 2015 ) , autism ( Uhlhaas and Singer , 2006 ; Rippon et al . , 2007 ; Uhlhaas et al . , 2009 ) among other neurological diseases and disorders ( He et al . , 2007 , 2009 ) . In this study , we selecti"
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    ABSTRACT: We report the design and application of a Micro Electro Mechanical Systems (MEMs) device that permits investigators to create arbitrary network topologies. With this device investigators can manipulate the degree of functional connectivity among distinct neural populations by systematically altering their geometric connectivity in vitro. Each polydimethylsilxane (PDMS) device was cast from molds and consisted of two wells each containing a small neural population of dissociated rat cortical neurons. Wells were separated by a series of parallel micrometer scale tunnels that permitted passage of axonal processes but not somata; with the device placed over an 8 × 8 microelectrode array, action potentials from somata in wells and axons in microtunnels can be recorded and stimulated. In our earlier report we showed that a one week delay in plating of neurons from one well to the other led to a filling and blocking of the microtunnels by axons from the older well resulting in strong directionality (older to younger) of both axon action potentials in tunnels and longer duration and more slowly propagating bursts of action potentials between wells. Here we show that changing the number of tunnels, and hence the number of axons, connecting the two wells leads to changes in connectivity and propagation of bursting activity. More specifically, the greater the number of tunnels the stronger the connectivity, the greater the probability of bursting propagating between wells, and shorter peak-to-peak delays between bursts and time to first spike measured in the opposing well. We estimate that a minimum of 100 axons are needed to reliably initiate a burst in the opposing well. This device provides a tool for researchers interested in understanding network dynamics who will profit from having the ability to design both the degree and directionality connectivity among multiple small neural populations.
    Frontiers in Neural Circuits 07/2015; 9(32). DOI:10.3389/fncir.2015.00032 · 2.95 Impact Factor
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    • "Furthermore, abnormal small-world properties have been found in neuropsychiatric disorders, including Alzheimer's disease [Supekar et al., 2008], schizophrenia [Liu et al., 2008], epilepsy [Liao et al., 2010], and depression [Zhang et al., 2011]. Although different brain diseases show different changes, the topology of the functional network of an abnormal brain can be regarded as less optimal the more it deviates from small-world network topology, suggesting both a possible role in pathophysiology and potential use as a biomarker. "
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    Human Brain Mapping 06/2015; DOI:10.1002/hbm.22871 · 6.92 Impact Factor
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