Department Seminar Series | A computational approach to understanding motivational symptoms in depression
Professor Jonathan Rosier
Tuesday, 16 June 2026, 9.30am to 10.30am
Hosted by Rania Elgarf
Motivational symptoms of depression are debilitating and predict poor clinical outcome, but the mechanisms underlying them are poorly understood. This talk will present data examining how cognitive processes relate to effort-based decision making are linked to depression and its treatment, using a computational approach. In the first part of the talk results from two cross-sectional behavioural studies, including >200 participants (healthy volunteers, unmedicated depressed patients, first degree relatives and remitted depressed patients), will be presented.
Participants completed a rewarded physical effort task using a grip squeeze device, and motivational symptoms were assessed through questionnaires. Data were analysed using a hierarchical computational approach, with model parameters estimated in a Bayesian framework. In the non-clinical study, anhedonia was related to a lack of willingness to engage in high-effort challenges. In the clinical study, current or past depression was associated with lower overall propensity to accept challenges, independent of reward or effort level. Results from a study examining the effect of L-Dopa on effort-based decisions in patients with Parkinson's disease with and without depression will also be presented, with clear effects of dopamine on effort-based decision making observed only in the latter. Ongoing work examining the impact of physical activity on motivational symptoms and effort-based decisions, including the results of a recent pilot study, will be outlined briefly. These studies illuminate the cognitive and neurochemical mechanisms contributing to depressive symptoms related to disrupted motivation, providing some clues to potential avenues for intervention strategies for these debilitating symptoms.
This seminar is hosted in person in the Seminar Room and online via Zoom.
https://zoom.us/j/94572787318?pwd=yQZc0eWXLehppqdtcdhbak2QTPy4V0.1
Meeting ID:
945 7278 7318
Passcode:
751629