Max Rolison, MD

New in @JACEPOpen : We examined factors linked to physical restraint use in pediatric EDs. Findings highlight opportunities to improve behavioral health care for all children. 🔗 sciencedirect.com/science/articl… #ChildPsych #PedsED @YaleCSC @YalePsych @YalePediatrics @YalePediatricEM

Congratulations to the #yalepsych Residency Class of 2025 on their graduation tonight. @YaleMed

In @eLife: Trends in self-citation rates in high-impact neurology, neuroscience, and psychiatry journals doi.org/10.7554/eLife.… @DScheinost

📑Meet Kaiulani Shulman, Medical Student at Harvard Medical School @harvardmed with a focus on pediatric research. Learn about their research “Reading for life-long health” ⬇️

Last day to apply!

Looking for a #postdoc? Interested in #autism #neuroscience #research? Join this awesome team! Specifically interested in applicants with experience in #EEG #ERP #TMS #DataScience #eyetracking @YaleCSC @YaleMed medicine.yale.edu/lab/mcpartland…

Ever wondered how data leakage can affect neuroimaging (specifically functional/structural connectivity) predictive models? Check out our new preprint⬇️ biorxiv.org/content/10.110…

What are your favorite papers on Predictive modeling, Neuroimaging, Deep learning, Data science and Computational psychiatry / cognitive neuroscience? I add 9 of mine here. Yours?👇👇👇

Predicting the future of neuroimaging predictive models in mental health Tejavibulya, Rolison, Gao, Liang, Peterson, Dadashkarimi, Farruggia, Hahn, Noble, Lichenstein, Pollatou, Dufford & Scheinost @molpsychiatry volume 27, pages 3129–3137 (2022) nature.com/articles/s4138…

New article: Revisiting best practices: a reflection on the online evaluation and treatment of ADHD and implications for future practice rdcu.be/c8Ica @YaleCSC @YalePsych @acamh @TheCAMH

A true team effort by @dscheinost🌟 @AngelPollatou @ajdneuro @925452096Andy @M_Farruggia @RosenblattMatt @R_X_Rodriguez @JDadashkarimi @liang_qinghao @mlfoster47 @WeiDai19 @chrisclaycamp @LinkTejavibulya @huili_sun @JeanSYe_ @N3early @MaxRolison & my 🔥co-last @maggieeastfire 5/5

Finally, we look to the future and anticipate practical and ethical challenges to come, including: - fair + trustworthy models - responsible interpretation - validating evolving methods - increasing sample sizes As usual, data sharing + transparent reporting are key! 4/5

Do you do: 👶 fetal/infant/toddler (FIT) neuroimaging? 💻 machine learning? Want to do both? If so, we’re excited to announce a new primer and review on FIT-specific machine learning —a reflection on 100+ studies from the past decade authors.elsevier.com/c/1gZ0j1S07mWib 1/5

Still time to apply for a #postdoc @YaleMedicine @YaleCSC!

Have you wondered how predictive ML modelling has been used in the #FIT research? Freshly published work by @DScheinost et al. summarizes the existing studies and outlines the methodological & ethical considerations! #MachineLearning #fitng biologicalpsychiatryjournal.com/article/S0006-…

New paper led by @M6hexnut with @MindmapVinod molecularautism.biomedcentral.com/articles/10.11…

🧠Does depression affect fMRI reliability? ⚖️Can we compare multivariate and univariate reliability? @sNeuroble, @DScheinost, Argyris Stringaris, @shotgunosine, and I (an NIH-Yale collaboration!) answer these questions in our new preprint: medrxiv.org/content/10.110…

📢 New paper! We provide experimental evidence that placement into high-quality, family-based care early in life positively impacts how brain structure develops over the course of adolescence in previously-institutionalized youth🧠 Children need nurturing families to thrive!

So fun to work on this project! Make sure to check out our github page where you can evaluate your own self-citation rate: github.com/mattrosenblatt…

Super excited to be part of this great work led by @RosenblattMatt and @DScheinost… read thread for more details