Disrupted small-world networks in schizophrenia.

By Yong Liu, Meng Liang, Yuan Zhou, Yong He, Yihui Hao, Ming Song, Chunshui Yu, Haihong Liu, Zhening Liu, T. Jiang. Brain : a journal of neurology, 2008

1,179 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/6e9b81745d18f365c66e5a57e409bb014e9be942

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Citations in the corpus

Abnormal rich club organization and functional brain dynamics in schizophrenia. (2013, neutral): “0) [33-86] Antipsychotic medication, No.”
Graph analysis of the human connectome: Promise, progress, and pitfalls (2013, neutral): “, 2008; Zalesky and Fornito, 2009) and found rapid applications in the clinical neurosciences (Bassett et al., 2008; Fornito and Bullmore, 2010, 2012; Fornito et al., 2012b; He et al., 2009; Liu et al., 2008; Micheloyannis et al., 2006; Rubinov et al., 2009a; Stam et al., 2007; van denHeuvel et al.,”
Brain Anatomical Network and Intelligence (2009, background): “in their recent study of disrupted small-world networks in schizophrenia [75].”
Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia (2015, positive): “showed prominent intra-network patterns involving the frontal, visual, subcortical, and cerebellar areas, as well as inter-network patterns involving DMNs and the fronto-temporal, cortical-thalamus, cortical– cerebellar, and subcortical–cerebellar networks (Liu et al., 2008; Salvador et al., 2005).”
Simple models of human brain functional networks (2012, result): “Consistent with prior studies of functional connectivity and functional network organization in schizophrenia, we found that topological properties of clustering and modularity were somewhat reduced in COS patients (23 – 26).”
Groupwise whole-brain parcellation from resting-state fMRI data for network node identification (2013, neutral): “This atlas results in a parcellation on the order of 90 regions but different investigators have used different numbers of regions ((van den Heuvel et al., 2010), 108 regions; (Lynall et al., 2010), 72 regions; (Liu et al., 2008), 90 regions; (Supekar et al., 2008), 90 regions).”
Network-based statistic: Identifying differences in brain networks (2010, background): “…et al., 2007), attention-deficit disorder (Wang et al., 2009), multiple sclerosis (He et al., 2009) and schizophrenia (Bassett et al., 2008, 2009; Liu et al., 2008; Rubinov et al., 2009) as well as associations with age and gender (Gong et al., 2009; Wang et al., 2010), and intelligence (van den…”
Neurophysiological and Computational Principles of Cortical Rhythms in Cognition (2010, background): “A number of theoretical, behavioral, and fMRI studies reported impaired connectivity in the schizophrenic brain (212, 336, 438, 439, 558, 596, 1059, 1063).”
Graph analysis of functional brain networks: practical issues in translational neuroscience (2014, background): “At the large topological scale, the small-world organization, whereby both integration (relatively high global-efficiency/low path length) and segregation (relatively high local-efficiency/clustering coefficient) of information between brain regions are supported, is significantly altered by several”
Whole-brain anatomical networks: Does the choice of nodes matter? (2010, methodology): “In Achard et al. (2006); Van den Heuvel et al. (2008); Liu et al. (2008), the algorithm in Maslov and Sneppen (2002) was reinvoked M times to compute M random graphs R 1 ,…, R M equivalent to G, thereby affording the Monte-Carlo approximation c R = hc R 1 ; N ; c RM i and l R = hl R1 ; N ; l RM i.…”
Disrupted Modularity and Local Connectivity of Brain Functional Networks in Childhood-Onset Schizophrenia (2010, positive): “Decreased small-worldness, which has also been reported previously in adult-onset schizophrenia (Liu et al., 2008; Lynall et al., 2010), could result if the increase in global efficiency comes at the expense of a disproportionate decrease in clustering.”
Great Expectations: Using Whole-Brain Computational Connectomics for Understanding Neuropsychiatric Disorders (2014, background): “The results show that even very precise lesions in one hemisphere can generate altered functional connectivity between distant brain regions, often across both hemispheres (Alstott et al., 2009).”
The Ubiquity of Small-World Networks (2011, background): “This metric has since gained considerable popularity(Bassett et al. 2008; Liu et al. 2008; Guye et al. 2010), particularly among neuroscientists (see(Bullmore and Sporns 2009)), and has been more extensively evaluated by Humphries and Gurney(Humphries and Gurney 2008).”