We will present "BrainCAP: an open-source neuroimaging toolkit to analyze 🧠 co-activation patterns" at #OHBM2025 in an #Oral session! A cool collaboration with Samuel Brege, Zailyn Tamayo, Youngsun Cho (Yale) and Catie Chang (Vanderbilt) - See you all in Brisbane! @ohbmofficial.bsky.social

Thrilled to have presented at #AES2024 investigators workshop on Multimodal Evaluation of Sleep, Epilepsy & Cognition! Huge thanks to Christophe Grova and Birgit Frauscher for organizing such an outstanding event. Truly a great experience!

Very excited to traveling to LA this weekend to give a talk on December 8 at AES 2024!

"Clinical investigator workshop: Multimodal evaluation of the interactions between sleep, epilepsy and cognition"

See you all there!

We OHBM-DIC @ohbm-dic.bsky.social wrote an editorial to discuss the benefits, challenges, and future direction of international neuroscience outreach initiatives, sharing experiences and resources from past successful OHBM "Brain Mappers of Tomorrow" events. Check it out!

doi.org/10.31234/osf...

OHBM Diversity and Inclusivity Committee (DIC) is also ready to start our 2024 events! Stay tuned!
ohbm-dic.github.io

#neuroimaging #PsychSciSky #psychology #neuroscience #neuroskyence #Psychiatry

In addition, we show that person-specific probability of occupying CAP III is reproducible and associated with neural and behavioral features. 11/n

In summary, we found that individuals who preferentially occupy CAP I and exhibit strong state persistence also demonstrate higher cognitive and affective functional outcomes and lower levels of alcohol and substance use, in contrast to those who predominantly occupy CAP II. 10/n

Here we computed a PCA model on 262 behavioral features, along with permutation tests and cross-validation. We found a reproducible principal axis of individual life function outcomes, which are associated with cognition, emotion regulation, alcohol use and substance use. 9/n

Using PCA and hierarchical clustering, we found that dimension reduction of these neural state-trait features captures general motifs of individual variation, encompassing CAP state-specific and state-general neural features that exhibit day-to-day variability. 7/n

In turn, we propose an analytic framework of joint state and trait neural variations, taking the day-to-day reliability of neural features into account. Importantly, this framework allows us to visualize how CAP properties that vary within a person also vary between people. 5/n

We identify a reproducible neural feature set at the single subject level, which involve between-subject (trait) variation and within-subject (state) variation; across the time-frames within the entire BOLD range and across days. See our preprint for details. 4/n

We found that there are individual differences in the number of reproducible brain states. For example, the presence or absence of CAP III is not a random artefact but actually associated with reproducible neural dynamics of individuals. 3/n

We leverage rich spatial-temporal information embedded in the entire range of resting state fMRI BOLD signals, which reveals three reproducible co-activation patterns (CAPs) that reflect brain-wide motifs of time-varying neural activity. 2/n