Multifactorial modeling of impairment of evoked gamma range oscillations in schizophrenia

Despite a significant increase in efforts to identify biomarkers and endophenotypic measuresof psychiatric illnesses, only a very limited amount of computational models of these markersand measures has been implemented so far. Moreover, existing computational models dealingwith biomarkers typically...

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Main Authors: Christoph Metzner, Achim Schweikard, Bartosz Zurowski
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-08-01
Series:Frontiers in Computational Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncom.2016.00089/full
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spelling doaj-b91fd4d1a5164efdb58e99345325886e2020-11-24T22:28:21ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882016-08-011010.3389/fncom.2016.00089195657Multifactorial modeling of impairment of evoked gamma range oscillations in schizophreniaChristoph Metzner0Achim Schweikard1Bartosz Zurowski2University of HertfordshireUniversität zu LübeckUniversität zu LübeckDespite a significant increase in efforts to identify biomarkers and endophenotypic measuresof psychiatric illnesses, only a very limited amount of computational models of these markersand measures has been implemented so far. Moreover, existing computational models dealingwith biomarkers typically only examine one possible mechanism in isolation, disregarding thepossibility that other combinations of model parameters might produce the same networkbehaviour (what has been termed ’multifactoriality’). In this study we describe a step towardsa computational instantiation of an endophenotypic finding for schizophrenia, namely theimpairment of evoked auditory gamma and beta oscillations in schizophrenia. We explorethe multifactorial nature of this impairment using an established model of primary auditorycortex, by performing an extensive search of the parameter space. We find that singlenetwork parameters contain only little information about whether the network will show impairedgamma entrainment and that different regions in the parameter space yield similar networklevel oscillation abnormalities. These regions in the parameter space, however, show strongdifferences in the underlying network dynamics. To sum up, we present a first step towards anin silico instantiation of an important biomarker of schizophrenia, which has great potential forthe identification and study of disease mechanisms and for understanding of existing treatmentsand development of novel ones.http://journal.frontiersin.org/Journal/10.3389/fncom.2016.00089/fullSchizophreniacomputational modeloscillationsParameter searchMultifactorialityAuditory Entrainment
collection DOAJ
language English
format Article
sources DOAJ
author Christoph Metzner
Achim Schweikard
Bartosz Zurowski
spellingShingle Christoph Metzner
Achim Schweikard
Bartosz Zurowski
Multifactorial modeling of impairment of evoked gamma range oscillations in schizophrenia
Frontiers in Computational Neuroscience
Schizophrenia
computational model
oscillations
Parameter search
Multifactoriality
Auditory Entrainment
author_facet Christoph Metzner
Achim Schweikard
Bartosz Zurowski
author_sort Christoph Metzner
title Multifactorial modeling of impairment of evoked gamma range oscillations in schizophrenia
title_short Multifactorial modeling of impairment of evoked gamma range oscillations in schizophrenia
title_full Multifactorial modeling of impairment of evoked gamma range oscillations in schizophrenia
title_fullStr Multifactorial modeling of impairment of evoked gamma range oscillations in schizophrenia
title_full_unstemmed Multifactorial modeling of impairment of evoked gamma range oscillations in schizophrenia
title_sort multifactorial modeling of impairment of evoked gamma range oscillations in schizophrenia
publisher Frontiers Media S.A.
series Frontiers in Computational Neuroscience
issn 1662-5188
publishDate 2016-08-01
description Despite a significant increase in efforts to identify biomarkers and endophenotypic measuresof psychiatric illnesses, only a very limited amount of computational models of these markersand measures has been implemented so far. Moreover, existing computational models dealingwith biomarkers typically only examine one possible mechanism in isolation, disregarding thepossibility that other combinations of model parameters might produce the same networkbehaviour (what has been termed ’multifactoriality’). In this study we describe a step towardsa computational instantiation of an endophenotypic finding for schizophrenia, namely theimpairment of evoked auditory gamma and beta oscillations in schizophrenia. We explorethe multifactorial nature of this impairment using an established model of primary auditorycortex, by performing an extensive search of the parameter space. We find that singlenetwork parameters contain only little information about whether the network will show impairedgamma entrainment and that different regions in the parameter space yield similar networklevel oscillation abnormalities. These regions in the parameter space, however, show strongdifferences in the underlying network dynamics. To sum up, we present a first step towards anin silico instantiation of an important biomarker of schizophrenia, which has great potential forthe identification and study of disease mechanisms and for understanding of existing treatmentsand development of novel ones.
topic Schizophrenia
computational model
oscillations
Parameter search
Multifactoriality
Auditory Entrainment
url http://journal.frontiersin.org/Journal/10.3389/fncom.2016.00089/full
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