Advancing our understanding of cognitive deficits present in Parkinson’s disease and REM sleep behavioural disorder via multimodal computational methods
File(s)
Author(s)
Balaet, Maria
Type
Thesis
Abstract
This thesis employed multimodal computational methods to enhance our understanding of cognition in Parkinson's Disease (PD) and REM Sleep Behaviour Disorder (RBD). The aims were to: (1) apply Natural Language Processing (NLP) for a data-driven topic analysis of PD and RBD literature, (2) use computerised cognitive assessments to define cognitive profiles of PD and RBD patients, and develop a concise assessment tool for early-stage detection, (3) evaluate metacognitive accuracy in these patient groups, and (4) investigate the association between cognition and probable RBD in the general population.
Chapter 1 analysed 42,243 papers from 1967 to 2022, identifying key trends and topics in PD and RBD research, primarily published in Movement Disorders and Sleep journals. The findings highlighted the importance of cognitive assessments in managing these disorders and the necessity for early monitoring of cognitive decline.
Chapter 2 documented cognitive deficits in PD and RBD patients, revealing impairments in memory, word-based, and analytical tasks. PD patients generally underperformed across tasks compared to RBD patients, who exhibited more selective impairments relative to controls. The cognitive assessment tool developed demonstrated higher sensitivity and specificity than the MoCA, suggesting its potential for early detection and monitoring of cognitive decline.
Chapter 3 showed metacognitive accuracy was preserved in early-stage PD and RBD patients. Significant correlations were observed between performance confidence, symptoms affecting daily life, and mental health, crucial for clinical interactions and patient management.
Chapter 4 illustrated that RBD symptoms are prevalent in the general population. Cognitive deficits were associated with higher RBD symptomatology, particularly when linked with anxiety, depression, antidepressant medication, and neurological diagnoses.
In conclusion, this thesis advances the field by providing insights into PD and RBD cognition, refining assessment tools, and offering a framework for future research into cognitive and metacognitive dynamics in neurological disorders.
Chapter 1 analysed 42,243 papers from 1967 to 2022, identifying key trends and topics in PD and RBD research, primarily published in Movement Disorders and Sleep journals. The findings highlighted the importance of cognitive assessments in managing these disorders and the necessity for early monitoring of cognitive decline.
Chapter 2 documented cognitive deficits in PD and RBD patients, revealing impairments in memory, word-based, and analytical tasks. PD patients generally underperformed across tasks compared to RBD patients, who exhibited more selective impairments relative to controls. The cognitive assessment tool developed demonstrated higher sensitivity and specificity than the MoCA, suggesting its potential for early detection and monitoring of cognitive decline.
Chapter 3 showed metacognitive accuracy was preserved in early-stage PD and RBD patients. Significant correlations were observed between performance confidence, symptoms affecting daily life, and mental health, crucial for clinical interactions and patient management.
Chapter 4 illustrated that RBD symptoms are prevalent in the general population. Cognitive deficits were associated with higher RBD symptomatology, particularly when linked with anxiety, depression, antidepressant medication, and neurological diagnoses.
In conclusion, this thesis advances the field by providing insights into PD and RBD cognition, refining assessment tools, and offering a framework for future research into cognitive and metacognitive dynamics in neurological disorders.
Version
Open Access
Date Issued
2024-04-15
Date Awarded
01/11/2024
License URL
Advisor
Hampshire, Adam
Malhotra, Paresh
Sponsor
Medical Research Council Doctoral Training Programme
Publisher Department
Department of Brain Sciences
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)