Investigation into functional large-scale networks in individuals with schizophrenia using fMRI data and Dynamic Causal Modelling
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Dauvermann2014.doc (6.071Mb)
Date
28/11/2014Author
Dauvermann, Maria Regina
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Abstract
Schizophrenia is a complex and severe psychiatric disorder with positive symptoms,
negative symptoms and cognitive deficits. Preclinical neurobiological studies showed
that alterations of dopaminergic and glutamatergic neurotransmitter circuits
involving the prefrontal cortex resulted in cognitive impairment such as working
memory. Functional activation and functional connectivity findings of functional
Magnetic Resonance Imaging (fMRI) data provided support for prefrontal
dysfunction during fMRI working memory tasks in individuals with schizophrenia.
However, these findings do not offer a neurobiological interpretation of the fMRI
data.
Biophysical modelling of functional large-scale networks has been designed for the
analysis of fMRI data, which can be interpreted in a mechanistic way. This approach
may enable the interpretation of fMRI data in terms of altered synaptic plasticity
processes found in schizophrenia. One such process is gating mechanism, which has
been shown to be altered for the thalamo-cortical and meso-cortical connection in
schizophrenia. The primary aim of the thesis was to investigate altered synaptic
plasticity and gating mechanisms with Dynamic Causal Modelling (DCM) within
functional large-scale networks during two fMRI tasks in individuals with
schizophrenia.
Applying nonlinear DCM to the verbal fluency fMRI task of the Edinburgh High
Risk Study, we showed that the connection strengths with nonlinear modulation for
the thalamo-cortical connection was reduced in subjects at high familial risk of
schizophrenia when compared to healthy controls. These results suggest that
nonlinear DCM enables the investigation of altered synaptic plasticity and gating
mechanism from fMRI data.
For the Scottish Family Mental Health Study, we reported two different optimal
linear models for individuals with established schizophrenia (EST) and healthy
controls during working memory function. We suggested that this result may indicate
that EST and healthy controls used different functional large-scale networks. The
results of nonlinear DCM analyses may suggest that gating mechanism was intact in
EST and healthy controls.
In conclusion, the results presented in this thesis give evidence for the role of
synaptic plasticity processes as assessed in functional large-scale networks during
cognitive tasks in individuals with schizophrenia.