Literature DB >> 25943122

Disintegration of Sensorimotor Brain Networks in Schizophrenia.

Tobias Kaufmann1, Kristina C Skåtun2, Dag Alnæs3, Nhat Trung Doan2, Eugene P Duff4, Siren Tønnesen2, Evangelos Roussos4, Torill Ueland5, Sofie R Aminoff6, Trine V Lagerberg2, Ingrid Agartz7, Ingrid S Melle2, Stephen M Smith4, Ole A Andreassen2, Lars T Westlye5.   

Abstract

BACKGROUND: Schizophrenia is a severe mental disorder associated with derogated function across various domains, including perception, language, motor, emotional, and social behavior. Due to its complex symptomatology, schizophrenia is often regarded a disorder of cognitive processes. Yet due to the frequent involvement of sensory and perceptual symptoms, it has been hypothesized that functional disintegration between sensory and cognitive processes mediates the heterogeneous and comprehensive schizophrenia symptomatology.
METHODS: Here, using resting-state functional magnetic resonance imaging in 71 patients and 196 healthy controls, we characterized the standard deviation in BOLD (blood-oxygen-level-dependent) signal amplitude and the functional connectivity across a range of functional brain networks. We investigated connectivity on the edge and node level using network modeling based on independent component analysis and utilized the brain network features in cross-validated classification procedures.
RESULTS: Both amplitude and connectivity were significantly altered in patients, largely involving sensory networks. Reduced standard deviation in amplitude was observed in a range of visual, sensorimotor, and auditory nodes in patients. The strongest differences in connectivity implicated within-sensorimotor and sensorimotor-thalamic connections. Furthermore, sensory nodes displayed widespread alterations in the connectivity with higher-order nodes. We demonstrated robustness of effects across subjects by significantly classifying diagnostic group on the individual level based on cross-validated multivariate connectivity features.
CONCLUSION: Taken together, the findings support the hypothesis of disintegrated sensory and cognitive processes in schizophrenia, and the foci of effects emphasize that targeting the sensory and perceptual domains may be key to enhance our understanding of schizophrenia pathophysiology.
© The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  functional imaging; machine learning; resting state; schizophrenia

Mesh:

Year:  2015        PMID: 25943122      PMCID: PMC4601711          DOI: 10.1093/schbul/sbv060

Source DB:  PubMed          Journal:  Schizophr Bull        ISSN: 0586-7614            Impact factor:   9.306


  47 in total

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