Inferring the dysconnection syndrome in schizophrenia: Interpretational considerations on methods for the network analyses of fMRI data

Schizophrenia has long been considered one of the most intractable of psychiatric conditions. Its etiology is likely polygenic, and its symptoms the result of complex network-level changes in neuronal activity. While easily identifiable by psychiatrists based on clear behavioral signs, the biologica...

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Main Authors: Brian Henry Silverstein, Steven L Bressler, Vaibhav A. Diwadkar
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-08-01
Series:Frontiers in Psychiatry
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fpsyt.2016.00132/full
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author Brian Henry Silverstein
Steven L Bressler
Vaibhav A. Diwadkar
author_facet Brian Henry Silverstein
Steven L Bressler
Vaibhav A. Diwadkar
author_sort Brian Henry Silverstein
collection DOAJ
description Schizophrenia has long been considered one of the most intractable of psychiatric conditions. Its etiology is likely polygenic, and its symptoms the result of complex network-level changes in neuronal activity. While easily identifiable by psychiatrists based on clear behavioral signs, the biological substrate of the disease remains poorly understood. Here we discuss current trends and key concepts in the theoretical framework surrounding schizophrenia, and critically discuss brain network approaches applied to neuroimaging data that can illuminate the correlates of the illness. We take the approach of generating a theoretical framework from early principles of brain function, neural units, and build to the highly relevant and practical perspective of network function. Next, we outline the strengths and limitations of several fMRI-based analytic methodologies for assessing in vivo brain network function, including undirected and directed functional connectivity and effective connectivity. The underlying assumptions of each approach for modeling fMRI data are treated in some quantitative detail, allowing for assessment of the utility of each for generating inferences about brain networks relevant to schizophrenia. fMRI and the analyses of fMRI signals provides a limited, yet vibrant platform from which to test specific hypotheses about brain network dysfunction in schizophrenia. Carefully considered and applied connectivity measures have the power to illuminate loss or change of function at the network level, thus providing insight into the underlying neurobiology which gives rise to the emergent symptoms seen in the altered cognition and behavior of schizophrenia patients.
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spelling doaj.art-cca7fb2ce0824a749e938f34952044472022-12-22T01:37:45ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402016-08-01710.3389/fpsyt.2016.00132214925Inferring the dysconnection syndrome in schizophrenia: Interpretational considerations on methods for the network analyses of fMRI dataBrian Henry Silverstein0Steven L Bressler1Vaibhav A. Diwadkar2Wayne State UniversityFlorida Atlantic UniversityWayne State UniversitySchizophrenia has long been considered one of the most intractable of psychiatric conditions. Its etiology is likely polygenic, and its symptoms the result of complex network-level changes in neuronal activity. While easily identifiable by psychiatrists based on clear behavioral signs, the biological substrate of the disease remains poorly understood. Here we discuss current trends and key concepts in the theoretical framework surrounding schizophrenia, and critically discuss brain network approaches applied to neuroimaging data that can illuminate the correlates of the illness. We take the approach of generating a theoretical framework from early principles of brain function, neural units, and build to the highly relevant and practical perspective of network function. Next, we outline the strengths and limitations of several fMRI-based analytic methodologies for assessing in vivo brain network function, including undirected and directed functional connectivity and effective connectivity. The underlying assumptions of each approach for modeling fMRI data are treated in some quantitative detail, allowing for assessment of the utility of each for generating inferences about brain networks relevant to schizophrenia. fMRI and the analyses of fMRI signals provides a limited, yet vibrant platform from which to test specific hypotheses about brain network dysfunction in schizophrenia. Carefully considered and applied connectivity measures have the power to illuminate loss or change of function at the network level, thus providing insight into the underlying neurobiology which gives rise to the emergent symptoms seen in the altered cognition and behavior of schizophrenia patients.http://journal.frontiersin.org/Journal/10.3389/fpsyt.2016.00132/fullSchizophreniabrain networksconnectivity analysisfMRI methodsDysconnection syndrome
spellingShingle Brian Henry Silverstein
Steven L Bressler
Vaibhav A. Diwadkar
Inferring the dysconnection syndrome in schizophrenia: Interpretational considerations on methods for the network analyses of fMRI data
Frontiers in Psychiatry
Schizophrenia
brain networks
connectivity analysis
fMRI methods
Dysconnection syndrome
title Inferring the dysconnection syndrome in schizophrenia: Interpretational considerations on methods for the network analyses of fMRI data
title_full Inferring the dysconnection syndrome in schizophrenia: Interpretational considerations on methods for the network analyses of fMRI data
title_fullStr Inferring the dysconnection syndrome in schizophrenia: Interpretational considerations on methods for the network analyses of fMRI data
title_full_unstemmed Inferring the dysconnection syndrome in schizophrenia: Interpretational considerations on methods for the network analyses of fMRI data
title_short Inferring the dysconnection syndrome in schizophrenia: Interpretational considerations on methods for the network analyses of fMRI data
title_sort inferring the dysconnection syndrome in schizophrenia interpretational considerations on methods for the network analyses of fmri data
topic Schizophrenia
brain networks
connectivity analysis
fMRI methods
Dysconnection syndrome
url http://journal.frontiersin.org/Journal/10.3389/fpsyt.2016.00132/full
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