New paper in Imaging Neuroscience by Ru Kong, B.T. Thomas Yeo, et al: Network-based near-scalp personalized brain stimulation targets doi.org/10.1162/IMAG...

Here's bonus slides on cross-validation tests, separate from our preprint. Covering: 1. paired (sign-flip) permutation test 2. label-swap permutation test 3. sample-level vs fold-averaged stats 4. a common misapplication of the corrected t-test 5. three bootstrap variants 1/N

New preprint as my first post! "Monosynaptic connections link functionally similar regions in human cortex." We use electrical stimulation + fMRI in epilepsy patients to map whole-brain monosynaptic connectivity at 42 cortical sites. doi.org/10.64898/202... 1/n

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

I always assumed that brain function had to line up with cytoarchitectonics. It turns out I was wrong. Human cortex, especially PFC, is tiled by chains of functional patches that subdivide and interlink architectonic areas into parallel processing streams. www.biorxiv.org/content/10.6...

We develop a new TMS targeting algorithm and test it in an open label trial in a treatment-resistant depression population with high comorbidities. Preprints by @rubykong92.bsky.social Phern-Chern Tor 1. doi.org/10.1101/2025... 2. doi.org/10.64898/202... Our new approach ...

Do you censor high motion frames in fMRI? In two preprints by @twktan.bsky.social @mandymejia.bsky.social, we find that we may be censoring too much! doi.org/10.64898/202... arxiv.org/html/2603.07... Strict censoring leads to worse personalized TMS targets than no censoring, even with high motion!

🚨 New preprint: Objective Quality Assessment for Precision fMRI Precision functional mapping (PFM) enables individual-level brain network studies — but demands more, and better, data. We introduce an objective framework to determine when a dataset truly supports interpretable, replicable PFM.

Preprint on PANDORA by Aslan Abivardi: A massive archive of UK Biobank brain imaging from 82K subjects. For each of 98 sub-modalities (e.g., FA from dMRI), the images are collated into a convenient subjectsXvoxels HDF5 file. pages.fmrib.ox.ac.uk/pandora/web/ www.medrxiv.org/content/10.6...

Check out our new work on the relationship between glioma and system-level functional networks! We identify that nearly all gliomas localize within a common brain functional network, Action-Mode Network (AMN) . biorxiv.org/content/10.64898/2026.01.05.697608v1

This is your brain on Ritalin. Got your attention? Stimulant medications like Ritalin (methylphenidate) do, but not in the way you might think. They don't act directly on the brain’s attention systems! Find out what's really happening in @cellpress.bsky.social. doi.org/10.1016/j.ce...

Our paper on the ☀️ "summer slide" 🛝 is out now @pnas.org! www.pnas.org/doi/10.1073/... Summer slide is a replicable phenomenon across diverse datasets that's more than "forgetting" school material in vacation months, but effects of socioeconomic inequality are ➡️ 7x bigger! ⬅️ #PsychSciSky #DevPsy 🧵👇

How do internal bodily rhythms influence #brain activity & motor function? @tahnee-engelen.bsky.social &co show that #cardiac, #respiratory & #gastric rhythms independently modulate motor excitability, revealing distinct #interoceptive profiles across individuals @plosbiology.org 🧪 plos.io/4nMtpLT

Nature research paper: Adenosine signalling drives antidepressant actions of ketamine and ECT go.nature.com/3Ln1gh6

Preprint is now published! doi.org/10.1002/hbm.... Thanks to co-authors @chen-zhang.bsky.social @anlijuncn.bsky.social @csabaorban.bsky.social

Preprint is now published: doi.org/10.1002/hbm.... Special thanks to co-authors @twktan.bsky.social @kimnganngt.bsky.social @csabaorban.bsky.social

Launched in 2023, Imaging Neuroscience is now firmly established, with full indexing (PubMed, etc.) and 700 papers to date. We're very happy to announce that we are able to reduce the APC to $1400. Huge thanks to all authors, reviewers, editorial team+board, and MIT Press.

This looks pretty cool: ultrasound can now see through the skull! 🧠🔊 The skull has long been a barrier to ultrasound. This reprint shows how to make it quickly transparent → enabling full-depth, high-res fUSI in mice (& humans! 🤯🤯) Huge congrats to the authors!!! www.biorxiv.org/content/10.1...

What started as a journal club on layer decoding turned into a project thanks to @karolisdegutis.bsky.social. Our preprint challenges a widespread assumption in the field: MVPA is not immune to vascular confounds in laminar GE-BOLD decoding, as shown using a mechanistic laminar response model.

Longitudinal neuroimaging of participants with planned arm amputations shows that the cortical body map remains stable after amputation. The findings, published in Nature Neuroscience, challenge long-standing theories of brain remapping after limb loss. go.nature.com/4oLSyYO 🧪 #Neuroscience

🚨 New preprint out! 🚨 “Translating the Transcriptome: A Connectomics Approach for Gene-Network Mapping and Clinical Application” 🔗 doi.org/10.1101/2025...  🧵 A short thread:

Now out in @natneuro.nature.com What happens to the brain’s body map when a body-part is removed? Scanning patients before and up to 5 yrs after arm amputation, we discovered the brain’s body map is strikingly preserved despite amputation www.nature.com/articles/s41593-025-02037-7 🧵1/18

Great write up of our @nature.com study by @claudia-lopez.bsky.social

I still get chills Meet Mike *30+ years severe depression *first hospitalized @ 13y *20 meds *3 rounds of ECT *2 near-fatal suicide attempts Mike felt joy for the first time in decades after we turned on his new brain pacemaker or PACE see videos, read paper, follow thread doi.org/10.31234/osf...

🚨 New Preprint 🚨 Targeting intracranial electrical stimulation (ES) to network regions defined within individuals causes network-level effects By Cyr et al. *** Q: Can we use individualized network maps from precision fMRI to modulate a targeted network via intracranial ES? A: Yes! 🧵:

Did you know that seeing virtual avatars with coughs or rashes can trigger your brain's immune response? Read more in this fascinating Nature Neuroscience paper @natureportfolio.nature.com 🧪 www.nature.com/articles/s41...

I’m elated to share our latest publication - out now in @natmentalhealth.nature.com! www.nature.com/articles/s44... - tour de force by @leahbanellis.bsky.social @brainandstomach.bsky.social and the rest of the VMP team!

For me, this work is a classic @ohbmofficial.bsky.social story: In 2023 I wasn't working with @bttyeo.bsky.social but I overheard him at his poster pointing to some accuracy curves saying "I don't why they have this particular shape". That kicked off the collab that led to these results.

🚨Thrilled to share our latest work just published in @nature.com where we looked into the optimal fMRI scan time for brain-wide association studies (BWAS) 🧠⏱️! Full thread below👇:

Super thankful to @bttyeo.bsky.social @csabaorban.bsky.social and @shaoshiz.bsky.social for pouring in all the effort to make this work possible!

1/11 Excited to share our @Naturestudy led by @leonooi.bsky.social @csabaorban.bsky.social @shaoshiz.bsky.social AI performance is known to scale with logarithm of sample size (Kaplan 2020), but in many domains, sample size can be # participants or # measurements... doi.org/10.1038/s415...

—Why did you go to sleep? —My mitochondria made me do it. www.nature.com/articles/s41...

Alert!!!! “An Action Networks Model for Pain” We propose a new model for chronic pain — and highlight two functionally connected cortical networks that could revolutionize how we treat it. 👉 thread below 🧵 osf.io/preprints/ps...

Our new preprint is out! doi.org/10.1101/2025... How do brain networks and cognition co-evolve as children enter adolescence?

First post on an exciting new manuscript online today @natneuro.nature.com - in collab with @lucinauddin.bsky.social and Catie Chang. We take a fresh look at the physiological dynamics associated with the global signal 🧠 ... www.nature.com/articles/s41... Read here: rdcu.be/ek01F

While the world burns, we cook up a new preprint! doi.org/10.1101/2025... Biophysical modeling is a key tool to derive mechanistic insights into the brain. These models are governed by biologically meaningful parameters (unlike artificial neural networks), but the dirty secret ... 1/N

New paper in Imaging Neuroscience by Ian D. Driver, Michael Germuska, et al: Velocity-selective arterial spin labelling bolus duration measurements: Implications for consensus recommendations doi.org/10.1162/imag...

New paper in Imaging Neuroscience by Thomas F. Kirk, Michael A. Chappell, et al: Arterial spin labelling perfusion MRI analysis for the Human Connectome Project Lifespan Ageing and Development studies doi.org/10.1162/imag...

Thanks to everyone's feedback, we have updated our calculator to optimize sample size N & scan time T for fMRI studies: leonoqr.github.io/ORSP_Calcula... The first new feature is that users can explore how different N & T leads to different accuracy, e.g., N=1000 & T=30min => 81% max accuracy. 🧵

🚨 Brain Age vs Direct Models in Alzheimer’s disease (AD) 🚨 A thread 🧵 1/ Brain age is a powerful indicator of general brain health, trained on massive datasets. But does this translate to better prediction for specific outcomes, like AD? Preprint by @twktan.bsky.social : doi.org/10.1101/2024...

🚨 Predicting Alzheimer's Progression 🚨 A thread 🧵 1/ Accurate prediction of Alzheimer’s progression is critical for early intervention. How can we make predictions more precise and generalizable? 🧠✨ 📝 Read the preprint led by @chen-zhang.bsky.social : doi.org/10.1101/2024...

Cool study from Yeo and colleagues - balancing sample size and scan time massively improves brain behavior correlation accuracy https://www.biorxiv.org/content/10.1101/2024.02.16.580448v1 #neuroskyence

Backlog in announcing preprints, but here's goes! Preprint #1 doi.org/10.1101/2023... We extend our meta-matching framework to translate models from multiple source datasets across disparate sample sizes to predict new phenotypes in small data, yielding huge improvements over transfer learning.