Network community structure alterations in adult schizophrenia: identification and localization of alterations

Abstract

A growing body of literature suggests functional connectivity alterations in schizophrenia. While findings have been mixed, evidence points towards a complex pattern of hyper-connectivity and hypo-connectivity. This altered connectivity can be represented and analyzed using the mathematical frameworks provided by graph and information theory to represent functional connectivity data as graphs comprised of nodes and edges linking the nodes. One analytic technique in this framework is the determination and analysis of network community structure, which is the grouping of nodes into linked communities or modules. This data-driven technique finds a best-fit structure such that nodes in a given community have greater connectivity with nodes in their community than with nodes in other communities. These community structure representations have been found to recapitulate known neural-systems in healthy individuals, have been used to identify novel functional systems, and have identified and localized community structure alterations in a childhood onset schizophrenia cohort. In the present study, we sought to determine whether community structure alterations were present in an adult onset schizophrenia cohort while stringently controlling for sources of imaging artifacts. Group level average graphs in healthy controls and individuals with schizophrenia exhibited visually similar network community structures and high amounts of normalized mutual information (NMI). However, testing of individual subject community structures identified small but significant alterations in community structure with alterations being driven by changes in node community membership in the somatosensory, auditory, default mode, salience, and subcortical networks.

Disrupted modular organization of primary sensory brain areas in schizophrenics

“…Altogether, these analyses show widespread alterations in functional connectivity in the Schizophrenia group, entirely consistent with previous reports (Liu et al 2008;Alexander-bloch et al 2010;Alexander-Bloch et al 2013;van den Heuvel et al 2010;Fornito et al 2012;Lo et al 2015;Lerman-Sinkoff & Barch 2016;Yu et al 2012). Interestingly, though, local efficiency, defined as the efficiency of a node's local network of nearest neighbors when the node is removed, was similar or even higher in the schizophrenia group 0.6±0.09 in controls; 0.68±0.09 in patients).…”

“…Several studies have investigated the modular structure of resting state functional connectivity networks derived from functional MRI in Schizophrenia patients compared to healthy controls (Alexander-Bloch et al 2010;Alexander-Bloch et al 2013;van den Heuvel et al 2010;Fornito et al 2012;Lo et al 2015;Lerman-Sinkoff & Barch 2016;Yu et al 2012;Liu et al 2008). Reduction in Modularity, a measure of segregation of functional modules within an integrated network, was found in Childhood Onset Schizophrenia (Alexander-Bloch et al 2010).…”

Review of thalamocortical resting-state fMRI studies in schizophrenia

“…Since the initial studies by Welsh et al, (2010), Woodward et al, (2012), and Anticevic et al, (2014), several other groups have found abnormal thalamic functional connectivity in schizophrenia (Klingner et al, 2014; Tu et al, 2015; Lerman-Sinkoff and Barch, 2016; Atluri et al, 2015; Wang et al, 2015). In almost all cases, the combined pattern of thalamic under-connectivity with PFC and over-connectivity with sensory and motor areas was replicated.…”

Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity

“…Additional details on six of the seven datasets can be found in the associated references. Note that the Barch-SZ dataset only contains subjects from the second dataset (task runs) in Lerman-Sinkoff and Barch (2016). Details on participant characteristics and MRI data collection parameters in the final (Iowa Lesion) dataset can be found in the Supp.…”