Cognitive fatigue is the subjective feeling of increased effort or lack of mental stamina that is accompanied by suboptimal cognitive performance.1 It is pervasive across all medical specialities, and is particularly common and debilitating in Parkinson’s disease (PD). Half of patients with PD report it to be a major problem, and it is considered by patients to be the leading symptom in need of further research.2 Fatigue can be associated with profound disruption of daily function, and is a leading cause of disability claims related to PD.3 Yet, despite its prevalence and impact, it remains ill-defined and poorly understood. Furthermore, the objective evaluation of fatigue in clinical practice is challenging because of numerous confounding factors that can impair its assessment (e.g., depression).4
This research proposes a novel approach to quantify cognitive fatigue and define its underlying neural mechanisms, by combining cutting-edge techniques in the related fields of computational modelling, neuroeconomics and cognitive neuroscience. Using a paradigm that requires participants to make sequential decisions about whether to work or rest, this research will model fatigue as an imbalance in the trade-off between the value of working versus resting. This will allow me to determine the sensitivity of individual subjects to the accumulation of fatigue, and will allow parametric quantification of moment-by-moment changes in fatigue over the course of a trial and an entire experiment, providing excellent temporal granularity to objectively describe the fatigued state. By combining this computational approach with functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), this research will delineate the neural mechanisms underlying cognitive fatigue in patients with PD relative to healthy age-matched controls.
This project will contribute substantially to our conceptualisation of cognitive fatigue theoretically and clinically. It builds directly on my recent work to computationally model aberrant cost/benefit valuations in PD. One of the outcomes of this research has been the development of techniques sensitive enough to identify distinct motivational impairments in patients who may appear otherwise unimpaired on standard clinical questionnaires.5 This has led to a framework that I recently proposed to leverage neurocomputational tools to examine Parkinsonian fatigue 4, 6 – it is this framework that forms the basis of this proposal.
In summary, this research will use a powerful, interdisciplinary approach to objectively characterise and quantify cognitive fatigue, and define its underlying neural mechanisms in patients with PD relative to healthy controls. In the near term, this will lead to new ways of objectively assessing fatigue in PD. Beyond the timeframe of this project, the flexibility of this methodology lends itself to being applied in a multitude of conditions, and will lay the foundation for a broader investigation of fatigue across other neurological disorders. It is hoped that the outcomes of this project will in turn catalyse the development of new therapies for fatigue, with the methodology developed here providing a sensitive and objective way to monitor treatment efficacy, and the neuroimaging results providing a biological basis for tailored treatments that can then target specific neural pathways that mediate fatigue accumulation.