Mental health symptoms fluctuate over time and are subject to daily rhythms and varying contexts. However, assessments of mental health outcomes are often limited to a single test session and are frequently conducted in lab-based environments. Characterization of mental health issues therefore typically lacks reliability, robustness, sensitivity to natural variation and ecological validity, which may, in turn, explain difficulties in identifying biomarkers of mental health issues in a range of clinical populations. Complementing neuroimaging with ecological momentary assessment (EMA), which involves short daily assessments completed in the participant’s own environment, may improve our capacity to unveil the neurobiological underpinnings of mental health issues in clinical populations. This project combines EMA and diffusion magnetic resonance imaging (dMRI) to explore daily symptom dynamics in breast cancer survivors, stroke patients, and patients with traumatic brain injury with mental health issues. Mental health status (e.g., depressive symptoms, anxiety, fatigue, attention, working memory and executive functioning) is assessed for 30 days (1 session/day, 8min/session) using an in-house developed EMA smartphone app. Fixel-based analysis (FBA), an advanced dMRI analysis technique, is used to investigate highly specific markers of white matter fibre density and morphology and their association with daily mental health status (in terms of both their average and variability). Associations between daily life psychological factors, cognition, and dMRI metrics will be examined.