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Brain connectivity is not only lower but different in schizophrenia: a combined anatomical and functional approach.

ABSTRACT: Schizophrenia is hypothesized to involve disordered connectivity between brain regions. Currently, there are no direct measures of brain connectivity; functional and structural connectivity used separately provide only limited insight. Simultaneous measure of anatomical and functional connectivity and its interactions allow for better understanding of schizophrenia-related alternations in brain connectivity.Twenty-seven schizophrenia patients and 27 healthy control subjects underwent magnetic resonance imaging with resting state functional magnetic resonance imaging and diffusion tensor imaging. Separate functional and anatomical connectivity maps were calculated and combined for each subject. Global, regional, and voxel measures and K-means network analysis were employed to identify group differences and correlation with clinical symptoms.A global connectivity analysis indicated that patients had lower anatomical connectivity and lower coherence between the two imaging modalities. In schizophrenia these group differences correlated with clinical symptom severity. Although anatomical connectivity nearly uniformly decreased, functional connectivity in schizophrenia was lower for some connections (e.g., middle temporal gyrus) and higher for others (e.g., cingulate and thalamus). Within the default mode network (DMN) two separate subsystems can be identified. Schizophrenia patients showed decoupling between structural and functional connectivity that can be localized to networks originating in posterior cingulate cortex as well as in the task-positive network and one of the DMN components.Combining two measures of brain connectivity provides more comprehensive descriptions of altered brain connectivity underlying schizophrenia. Patients show deficits in white matter anatomy, but functional connectivity alterations are more complex. Fusion of both methods allows identification of subsystems showing both increased and decreased functional connectivity.

SUBMITTER: Skudlarski P

PROVIDER: S-EPMC2900394 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature

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Brain connectivity is not only lower but different in schizophrenia: a combined anatomical and functional approach.

Skudlarski Pawel P Jagannathan Kanchana K Anderson Karen K Stevens Michael C MC Calhoun Vince D VD Skudlarska Beata A BA Pearlson Godfrey G

Biological psychiatry 20100523 1

<h4>Background</h4>Schizophrenia is hypothesized to involve disordered connectivity between brain regions. Currently, there are no direct measures of brain connectivity; functional and structural connectivity used separately provide only limited insight. Simultaneous measure of anatomical and functional connectivity and its interactions allow for better understanding of schizophrenia-related alternations in brain connectivity.<h4>Methods</h4>Twenty-seven schizophrenia patients and 27 healthy con ...[more]

PMID: 20497901

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Project description:Functional connectivity (FC) of the brain changes in various brain disorders. Its complexity, however, makes it difficult to obtain a systematic understanding of these alterations, especially when they are found individually and through hypothesis-based methods. It would be easier if the variety of brain connectivity alterations is extracted through data-driven approaches and expressed as variation modules (subnetworks). In the present study, we modified a blind approach to determine inter-group brain variations at the network level and applied it specifically to schizophrenia (SZ) disorder. The analysis is based on the application of independent component analysis (ICA) over the subject's dimension of the FC matrices, obtained from resting-state functional magnetic resonance imaging (rs-fMRI). The dataset included 27 SZ people and 27 completely matched healthy controls (HC). This hypothesis-free approach led to the finding of three brain subnetworks significantly discriminating SZ from HC. The area associated with these subnetworks mostly covers regions in visual, ventral attention, and somatomotor areas, which are in line with previous studies. Moreover, from the graph perspective, significant differences were observed between SZ and HC for these subnetworks, while there was no significant difference when the same parameters (path length, network strength, global/local efficiency, and clustering coefficient) across the same limited data were calculated for the whole brain network. The increased sensitivity of those subnetworks to SZ-induced alterations of connectivity suggested whether an individual scoring method based on their connectivity values can be applied to classify subjects. A simple scoring classifier was then suggested based on two of these subnetworks and resulted in acceptable sensitivity and specificity with an area under the ROC curve of 77.5%. The third subnetwork was found to be a less specific building block (module) for describing SZ alterations. It projected a wider range of inter-individual variations and, therefore, had a lower chance to be considered as a SZ biomarker. These findings confirmed that investigating brain variations from a modular viewpoint can help to find subnetworks that are more sensitive to SZ-induced alterations. Altogether, our study results illustrated the developed method's ability to systematically find brain alterations caused by SZ disorder from a network perspective.

Project description:Convergent evidence has suggested a significant effect of antipsychotic exposure on brain structure and function in patients with schizophrenia, yet the characteristics of favorable treatment outcome remains largely unknown. In this work, we aimed to examine how large-scale brain networks are modulated by antipsychotic treatment, and whether the longitudinal changes could track the improvements of psychopathologic scores. Thirty-four patients with first-episode drug-naïve schizophrenia and 28 matched healthy controls were recruited at baseline from Shanghai Mental Health Center. After 8 weeks of antipsychotic treatment, 24 patients were re-scanned. Through a systematical dynamic functional connectivity (dFC) analysis, we investigated the schizophrenia-related intrinsic alterations of dFC at baseline, followed by a longitudinal study to examine the influence of antipsychotic treatment on these abnormalities by comparing patients at baseline and follow-up. A structural connectivity (SC) association analysis was further carried out to investigate longitudinal anatomical changes that underpin the alterations of dFC. We found a significant symptomatic improvement-related increase in the occurrence of a dFC state characterized by stronger inter-network integration. Furthermore, symptom reduction was correlated with increased FC variability in a unique connectomic signature, particularly in the connections within the default mode network and between the auditory, cognitive control, and cerebellar network to other networks. Additionally, we observed that the SC between the superior frontal gyrus and medial prefrontal cortex was decreased after treatment, suggesting a relaxation of normal constraints on dFC. Taken together, these findings provide new evidence to extend the dysconnectivity hypothesis in schizophrenia from static to dynamic brain network. Moreover, our identified neuroimaging markers tied to the neurobiology of schizophrenia could be used as potential indicators in predicting the treatment outcome of antipsychotics.

Dataset Information

Brain connectivity is not only lower but different in schizophrenia: a combined anatomical and functional approach.

Publications

Brain connectivity is not only lower but different in schizophrenia: a combined anatomical and functional approach.

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