The Neural Basis of Parkinson’s Disease Psychosis

Student thesis: Doctoral ThesisDoctor of Philosophy


Parkinson’s Disease Psychosis (PDP) is common, extremely challenging for both patients and carers, and yet poorly understood. Symptoms include illusions, hallucinations, and delusions. They negatively affect patients’ quality of life and are a significant predictor of dementia. Nevertheless, basic questions about PDP remain unanswered due to limitations in existing research, including small sample sizes and a lack of diverse datatypes (i.e., clinical, cognitive, and from different neuroimaging modalities). The research in this doctoral thesis therefore aims to advance our understanding of the neuro-cognitive factors associated with important components of PDP - visual hallucinations and related perceptual symptoms - by combining innovative and robust methods with different clinical and neuroimaging datasets.

To achieve this, I first explore the visuo-cognitive profile of PDP patients and employ novel meta-analytic methods in a large cohort of over 7,000 patients with and without hallucinations across 99 published studies. The results highlight the necessity of updating existing hallucinations models of Parkinson's Disease to account for impairments in a wider range of cognitive areas than previously addressed, which has significant implications for both clinical treatment and experimental research in the field.

Secondly, I investigate changes in functional brain networks associated with PDP using a combination of graph-theoretical and data-driven methods. Different chapters address three main questions: what are the changes in functional brain networks associated with PDP? How can we best define and evaluate network impairments in this population? And how do these changes relate to cognitive and clinical variables of interest? These questions are investigated in the context of data from the Parkinson's Disease Progression Markers Initiative (PPMI), a large study of individuals recently diagnosed with Parkinson's Disease.

Finally, I use a data-driven approach to investigate the changes in structural brain networks associated with psychosis in PD both cross-sectionally and longitudinally in an imaging cohort that is significantly larger than those previously utilized in longitudinal investigations of PDP. To achieve this and leverage the power of multimodal imaging, I employ a novel method (Morphometric Similarity Networks - MSNs) that can jointly synthesise data from multiple imaging modalities and provide a more comprehensive characterization of the changes in brain structure associated with psychotic symptoms in Parkinson’s Disease.

Taken together, this thesis not only advances our knowledge of important visuocognitive and network-related changes underlying psychosis in Parkinson’s Disease, but also provides a steppingstone for future research investigations with direct clinical applications for these patients.

Date of Award1 Dec 2022
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorMitul Mehta (Supervisor), Dominic Ffytche (Supervisor) & affiliated academic (Supervisor)

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