8/8 Interested? Our paper is openly-available here! onlinelibrary.wiley.com/doi/10.1002/...

and of course, thanks to my co-authors @jsaramak.bsky.social , Nick Hayward, and @eglerean.bsky.social

7/8 Conclusion? The inclusion of PAD data may help elucidate what is currently considered “noise” or error signals in MRI analysis, revealing ecologically relevant variables and providing insights into the intra- and inter-individual differences

6/8 Age is not a constraint, but adherence may be. From 9 to 88 years old, individuals can use PADs. Yet, factors such as willingness and participant fatigue can affect data collection duration.

5/8 The medial prefrontal cortex, hippocampus, and dorsolateral frontal regions are most commonly associated in studies merging MRI and PAD data. The meta-analyses show significant clusters in the insula, pallidum, and anterior cingulate cortex

4/8 Combination of MRI and physiological measurements is feasible, but underexplored. This indicates a promising direction for future research, specially as PPG integration in wearables facilitate physiological data collection in real time.

3/8 The most common combinations are #fMRI, T1/T2-weighted MRI, and DWI with physical activity, #EMA/ESM, and #sleep. This is explained by their measurement is relatively simple and cost-effective.

2/8 🔍Our #PRISMA review: integrating brain #MRI & portable, automatic devices (PADs) used for #digitalphenotyping 🧠94 Selected papers combined MRI & PAD signals in real-world settings, not just lab environments.