When the systems fail to communicate. Cerebral resting state networks in schizophrenia spectrum disorders.

Razavi, Nadja (2014). When the systems fail to communicate. Cerebral resting state networks in schizophrenia spectrum disorders. (Dissertation, University Hospital of Psychiatry, Department of Psychiatric Neurophysiology)

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There have been numerous attempts to reveal the neurobiological basis of
schizophrenia spectrum disorders. Results however, remain as heterogeneous as the
schizophrenia spectrum disorders itself. Therefore, one aim of this thesis was to divide
patients affected by this disorder into subgroups in order to homogenize the results of
future studies.
In a first study it is suggested that psychopathological rating scales should focus on
symptoms-clusters that may have a common neurophysiological background. The here
presented Bern Psychopathology Scale (BPS) proposes that alterations in three wellknown
brain systems (motor, language, and affective) are largely leading to the
communication failures observable on a behavioral level, but also - as repeatedly
hypothesized - to dysconnectivity within and between brain systems in schizophrenia
spectrum disorders. The external validity of the motor domain in the BPS was tested
against the objective measure of 24 hours wrist actigraphy, in a second study. The
subjective, the quantitative, as well as the global rating of the degree of motor disorders
in this patient group showed significant correlations to the acquired motor activity. This
result confirmed in a first step the practicability of the motor domain of the BPS, but
needs further validation regarding pathological brain alterations.
Finally, in a third study (independent from the two other studies), two cerebral Resting
State Networks frequently altered in schizophrenia were investigated for the first time
using simultaneous EEG/fMRI: The well-known default mode network and the left
working memory network. Besides the changes in these fMRI-based networks, there are
well-documented findings that patients exhibit alterations in EEG spectra compared to
healthy controls. However, only through the multimodal approach it was possible to
discover that patients with schizophrenia spectrum disorders have a slower driving
frequency of the Resting State Networks compared to the matched healthy controls.
Such a dysfunctional coupling between neuronal frequency and functional brain
organization could explain in a uni- or multifactorial way (dysfunctional cross-frequency
coupling, maturational effects, vigilance fluctuations, task-related suppression), how the
typical psychotic symptoms might occur.
To conclude, the major contributions presented in this thesis were on one hand the
development of a psychopathology rating scale that is based on the assumption of
dysfunctional brain networks, as well as the new evidence of a dysfunctional triggering
frequency of Resting State Networks from the simultaneous EEG/fMRI study in patients
affected by a schizophrenia spectrum disorder.

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