The presented work unites several distinct lines of research, asserting that the broader construct of complexity (with its various connotations) may be uniquely relevant and informative to our understanding and management of psychotic disorders.
Part 1 outlines the candidate’s contributions to the development of EEG methodology in clinical populations in an effort to most directly capture neural noise and complexity. The advent of oscillatory analysis facilitated the study of ongoing background activity of the EEG. Further exploration of this background activity demonstrated that increased neural noise (as quantified by Lempel-Ziv complexity) is highly correlated with, and conceptually very relevant to, positive symptoms of psychosis. Part 2 describes how considering the complexity of clinical psychosis states justifies the use of human laboratory studies using psychotomimetic drugs such as tetrahydrocannabinol and ketamine. Part 3 explains how the ideas and inferences from the work in Parts 1 and 2 can inform the environment of psychotic disorders, specifically the candidate’s work in prescribing practices and first episode psychosis service design.
The thesis concludes that EEG studies of clinical populations face particular methodological challenges, however the resultant technical advancements have expanded our view of neural function to the particular benefit of our understanding of psychosis. EEG measures of complexity may be amongst the most sensitive biomarkers associated with positive symptoms, however more empirical research is called for to confirm this observation. Human laboratory studies of psychotomimetic drugs in healthy humans may continue to prove useful, in circumventing the phenomenological and patho-etiological complexity of clinically occurring psychosis. As a next step, multi-modal studies (combining biophysical signals, individual phenomenology and even population level outcomes) in combination with data mining techniques might further characterize the complexity within psychosis. Psychotic disorders, as complex problems, warrant framing and intervention informed by complexity.
Available under License Creative Commons Attribution Non-commercial No Derivatives.
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