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primary topic: Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network

Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network
type: Article
abstract: The research field of functional magnetic resonance imaging (fMRI) has made possible a remarkable progress in the understanding of the human brain enabling neuroscientists to study spatio-temporal alterations in the healthy and the diseased brain. While current theories of schizophrenia stress the critical role that plays aberrant connectivity among brain regions, other theories point towards the crucial role that plays functional excitation-inhibition (E-I) balance. Indeed, recent neuroscientific research has revealed increasing evidence that taking functional brain connectivity into account is essential to understand how the human brain works, and many studies have reviewed that serious behavioural impairments in mental disorders such as schizophrenia result from increases in the functional (E-I) balance within the neural microcircuitry. Particularly, the connection between the dorsolateral prefrontal cortex (DLPFC) and the hippocampal formation (HF) during working memory (WM) was found to be increased in carriers of schizophrenia risk genes and patients. However, less is known about causality, i.e. which region drives the altered connection. Stochastic Dynamic Causal Modelling (sDCM) is a novel mathematical algorithm for studying the causal connectivity among higher cognitive brain regions from fMRI data. The main purpose of this study is to identify alterations on genetic risk carriers and patients from the DLPFC-HF network estimated with sDCM and describe how these alterations have an impact on the behavior. Over the study, we strive to give to the sDCM parameter estimates a neurobiological explanation by linking the concepts of causal connectivity with functional (E-I) balance. In this work, we applied this methodology in two samples by constructing a systematic set of sDCMs describing interactions between right DLPFC and left HF. In a first sample, 180 healthy subjects were measured by fMRI during a standard working memory N-Back task at three different sites…
date: 2015-07-15
author list: authors
type: EPrint
type: DoctoralThesisEPrint
is part of: repository
has document: Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network (PDF)
has document: Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network (Other)
subject: 500 Naturwissenschaften und Mathematik

Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network (PDF)
type: Document
has file: BernalCasas_ProjectMemorandum_88.pdf
has part: BernalCasas_ProjectMemorandum_88.pdf

David Bernal Casas
type: Person
given name: David
family name: Bernal Casas

Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network (Other)
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Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network (Other)
type: Document
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Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network (Other)
type: Document
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Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network (Other)
type: Document
is version of: Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network (PDF)
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Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network (Other)
type: Document
is version of: Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network (PDF)
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primary topic: Of Genes and Patients: Stochastic Dynamic Causal Modelling of the Prefrontal-Hippocampal Network

500 Naturwissenschaften und Mathematik
type: Concept
preferred label: 500 Natural sciences and mathematics @en