Multi-echo fMRI and other enhanced imaging sequences (like compressed sensing diffusion spectrum imaging; CS-DSI) helps to identify person-specific variation with less data (especially valuable in developmental studies). Notably we share both raw AND fully processed data — all in BIDS on OpenNeuro!

Our study uses wearables to obtain granular measures of sleep and activity, thus overcoming questionnaire-related limitations of recall bias. You get 21-days worth of sleep (e.g. sleep duration) and physical activity (e.g. time spent in vigorous activity) data in real-world settings.

EMA offers a promising alternative to retrospective scales by measuring participants’ self-reported symptoms and activities as they occur in daily life, providing contextual richness and naturalistic data. TLDR: EMA tells us how participants feel in real time!

Dreaming of a dataset that tracks mood, sleep & activity to better understand affective instability (AI)…AND paired with advanced MRI? 🤯
Check out our new bioRxiv preprint for a 13–23 y/o community sample (n=10 and growing!) with multi-echo fMRI, EMA & actigraphy: www.biorxiv.org/content/10.1...