Neuroscientist studying human beliefs & the social brain. she/her/hers. Professor of Psychiatry & Data Science@Yale
Lab: https://www.neurocpu.org/
Conference: https://www.cpconf.org/
Journal: https://cpsyjournal.org/
Xiaosi Gu
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📢 New preprint out now!
In three samples (N=594), including a U.S.-representative cohort and a test-retest cohort, we formalize social motivation, learning, and homeostatic control within a single computational framework and identify a phenotype linked to chronic loneliness
doi.org/10.31234/osf...
And covered by @yaleschoolofmed.bsky.social
m.yale.edu/dgyx
This tour de france work would not have been possible if not for KK, who was an MD/PhD student in my lab and now a research track resident at @yaleschoolofmed.bsky.social
medicine.yale.edu/profile/kaus.... Stay tuned for more amazing work coming from him! 💯👇
Xiaosi Gu
Xiaosi Gu
Spread the word! We are recruiting for 6 new research professors at UC Davis' California National Primate Research Center. Open rank, open area, but must leverage 🐒 resources.
recruit.ucdavis.edu/JPF07561
Shawn Rhoads
📣🔥 Early bird registration now open for 2026 Computational Psychiatry Conference cpconf.org at Yale July 14-16.
Late-breaking abstracts now open (deadline: May 8)
Trainee pre-conference (July 13) registration open (free!)
See you in New Haven! #CPConf2026
New this year: free trainee pre-conference on July 13 organized by @cehaeffner.bsky.social @adanyajohnson.bsky.social
Pre-conference tickets are free for main conference attendees but space is limited to 75 people so register early!
www.cpconf.org/faq-cpconf20...
The Computational Psychiatry Pre-Conference is a one-day workshop and symposium (approximately 10:00 AM–6:30 PM) designed to prepare early-career researchers for the main conference while fostering collaboration and skill-building.
www.cpconf.org
Using computational modeling, we show that craving biases learning rates in opposite directions across groups, while expected outcomes and values simultaneously drive craving.
Model-derived parameters also predicted alcohol addiction risk—but not cannabis—highlighting potential clinical utility.
In a group of alcohol and cannabis users (n=132), we found that momentary craving and reward learning actively shape each other during substance-related choices.
These findings offer a new computational framework for understanding how craving and maladaptive choices interact across addictive disorders.
This work is the latest extension of our previous work on computational mechanisms of craving (e.g. jamanetwork.com/journals/jam... and rdcu.be/faccV)
Excited to share our new paper proposing a new computational model accounting for the dynamic interaction btw drug #craving and #decision-making, led by Kaustubh Kulkarni, MD/PhD
rdcu.be/fab6B
#AddictionScience #Neuroscience #ComputationalPsychiatry #BehavioralScience
Eliza Bliss-Moreau
Xiaosi Gu
Kaustubh Kulkarni is a psychiatry resident in the Neuroscience Research Training Program (NRTP). He earned his bachelor's in Neuroscience, with minors in
