Thomas Yeo

In a meta-analysis of 210 biomedical AI studies that statistically compared models under cross-validation, 97% used invalid statistical tests. Here's our new preprint doi.org/10.64898/202... led by @tianchu.bsky.social @hetuli.bsky.social @shaoshiz.bsky.social @nichols.bsky.social 1/N

New post! In which I discuss a truly amazing piece of science sleuthing that recently appeared on @pubpeer.com neuroskepticbsky.substack.com/p/the-sherlo...

A video of a patient who responded well to personalized TMS: www.temasekreview.com.sg/community-st...

Excited that Imaging Neuroscience has gotten its impact factor. Note that the impact factor is artificially low for the first year of any journal (because of the way it is calculated), so we expect the impact factor to improve next year. See more statistics below

Our first Impact Factor is 3.0 — an important milestone for a new journal. As with most new journals, the first IF is affected by the smaller publication volume in the launch year. Latest citation data are encouraging, and the journal’s IF is set to rise in 2027.

For those at @ohbmofficial.bsky.social @ohbmtrainees.bsky.social come check out our poster on using deep learning to accelerate biophysical model fitting & resulting insights into lifespan changes in E/I ratio! Poster number 2304 Wed, June 17 | 13:45-14:45 Thurs, June 18 | 14:45-15:45

One interpretation: baseline salience FC reflects the attractor basin characteristics of that network or how reliably it settles into coherent functional states. Low FC = shallow, poorly defined basins. The network can get there, but with more variability and less precision.

Attending #OHBM2026.🇫🇷? You will not want to miss Monday morning's keynote by Nanthia Suthana (chaired by yours truly 😊). I can't wait!!

Congrats to @shellakeilholz.bsky.social and thank you to the amazing leadership by our outgoing EIC @fmrib-steve.bsky.social Hope the community can continue to support the journal to bring imaging neuroscience to new heights!

Thank you for sharing!

This slide was particularly popular. Never had so many people cheering one of my slides before. haha

It was great fun giving the talk at the neuroimaging statistics workshop. Happy to share the slides here: www.dropbox.com/scl/fi/8riom... Hopefully, the talk was pitched at a level that was understandable to non-statisticians!

For those going to @OHBM @OHBM_Trainees you can check out our poster on spectral normative modeling! Poster Number: 1054 Monday, June 15, 14:45-15:45 Tuesday, June 16, 13:30-14:30 Our preprint has also been massively updated: doi.org/10.1101/2025...

1/ Excited to share our latest preprint! 🚀 We introduce Spectral Normative Modeling (SNM)—a novel approach leveraging graph spectral methods to advance brain charting towards personalized precision medicine. 🔗 www.medrxiv.org/content/10.1...

If you are going to @ohbmofficial.bsky.social @ohbmtrainees.bsky.social , come check out our poster to estimate & validate individualized brain networks in epilepsy! Poster Number: 0033 Mon, Jun 15 | 13:45-14:45 Tues, Jun 16 | 12:30-13:30 The paper has also been published: doi.org/10.1002/epi....

I guess the stable architecture we found must be related to your SES findings? @ndosenbach.bsky.social @smarek0502.bsky.social

What matters most for childhood brain organization? We analyzed 649 variables. The answer: Socioeconomics (SES); with brain patterns pointing at sleep & stress as drivers. Even brain-IQ associations were better explained by SES. In Science today: www.science.org/doi/10.1126/...

I guess our results of a stable architecture can be explained by your recent SES results? @smarektj.bsky.social @ndosenbach.bsky.social

Paper is now out in Nature Comms doi.org/10.1038/s414... If you are at @ohbmofficial.bsky.social @ohbmtrainees.bsky.social , come check out our poster about Simpson’s paradox in neurodevelopment. Poster number 998 Monday, June 15 | 14:45-15:45 Tuesday, June 16 | 13:30-14:30

For those attending @ohbmofficial.bsky.social @ohbmtrainees.bsky.social come check out our poster on E/I imbalance in pre-dementia individuals and the relationships with blood/CSF biomarkers. Poster 1059 Stand-by time: Monday, June 15 | 13:45-14:45 & Tuesday, June 16 | 12:30-13:30

Openly shared implementation of TMS targeting is still rare, so we are pleased to make ours freely available for research use: github.com/ThomasYeoLab... Let us know if you have any issue running it!

Our TMS algorithm is now published in @imagingneurosci.bsky.social doi.org/10.1162/IMAG... If you are coming to @ohbmofficial.bsky.social @ohbmtrainees.bsky.social, come check out our poster about our open label trial. Poster number 1152 Monday, Jun 15 | 14:45-15:45 Tuesday, Jun 16 | 13:30-14:30

For those attending @ohbmofficial.bsky.social @ohbmtrainees.bsky.social , come check out our poster finding that functional MRI brain foundation models do not outperform ridge regression. Poster number 2269 Presenting on Wednesday, June 17 | 12:45-13:45 and Thursday, June 18 | 13:45-14:45

If you are attending @ohbmofficial.bsky.social @ohbmofficial.bsky.social come by and check out our poster on how excessive censoring hurts parcellation and personalized TMS target accuracy. Poster number 2399 Presenting on Wednesday, June 17 (12:45-13:45) and Thursday, June 18 (13:45-14:45)

🎉 Registration is now OPEN for the 2026 OHBM Australian Chapter Annual Meeting! 🇦🇺🧠🇦🇺 Get your ticket now! 🎟️🎟️🎟️ Registration: events.humanitix.com/ohbm-austral... 📝 Submit your abstract: docs.google.com/forms/d/e/1F... 🏆 Nominate a colleague (or yourself) for an award: ohbm-aus.github.io/awards/

You're not going to want to miss this! More information on the Brainhack and other workshops here: ohbm.github.io/hackathon2026/

For those who are attending @ohbmofficial.bsky.social brainhack, I will be giving a short presentation of this work at the neuroimaging statistics workshop, co-hosted with brainhack: sites.google.com/view/nsw2026

Statistically crossvalidation folds are not independent. The number of papers treating them as if they were is off the charts.

For years, we've known that running a standard t-test on cross-validation folds violates sample independence. We wanted to see how widespread this issue actually is. The result? 97% of the studies used an invalid statistical test. 🧵👇

Can't stress this enough 👇 If you use ML to compare predictive models in your research (neuroscience, genetics, you name it), this paper is a must read! 👀 The majority of work in this space (mine included 🙋) misses critical nuances when reporting comparative stats.

So glad this is finally public. Grateful to my wonderful co-authors for the long journey.