@nichols.bsky.social collaborated with researchers at the National University of Singapore on a recent study published in @nature.com on how longer duration fMRI brain scans reduce costs and improve prediction accuracy for AI models. Read more about the study below 👇

A human brain network linked to restoration of consciousness after deep brain stimulation - Nature Communications In people with severe brain injuries, stimulation restored consciousness by engaging a deep brain circuit for wakefulness—revealing a target that may also guide treatment in stroke and epilepsy.

Just dropped in @natcomms.nature.com: we show that re-engaging a thalamic–ventral tegmental circuit with deep brain stimulation can reignite consciousness in patients with severe brain injury. Work led by Aaron Warren, with @andreashorn.org @foxmdphd.bsky.social @ others! tinyurl.com/4kz8j89b

What a fantastic effort. Truly inspiring to see brilliant people dig deeply into these meta scientific issues.

This is the best time to be doing neuroimaging.

I'm so proud to see this great paper finally published in @nature.com!

Our Nature paper on the hashtag#scaling hashtag#behavior and economics of hashtag#machine hashtag#learning predictions in high-dimensional brain scans is out !

Congrats to the whole team.

www.nature.com/articles/s41...

Really nice study, and extends some of the ideas developed in this paper pubmed.ncbi.nlm.nih.gov/32673043/

A super important and well designed study. Curious if those who took such interest in the original "BWAS needs impossibly huge n" will pay any attention to it

This new Yeo Lab tool should immediately and permanently replace sample-size-only power calculations for functional MRI.

www.nature.com/articles/s41...

Just incredible results from a massive effort— moves the field forward. Bravo!!!

Longer scans boost prediction and cut costs in brain-wide association studies - Nature Although the number of participants is important for phenotypic prediction accuracy in brain-wide association studies using functional MRI, scanning for at least 30 min offers the greatest cost effectiveness.

Nature research paper: Longer scans boost prediction and cut costs in brain-wide association studies

go.nature.com/3IME4aA

Big congrats to @bttyeo.bsky.social and team on this impressive and important work!

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.

Everyone should try out the Trandiagnostic Connectome Project (TCP) dataset! Openly available on @openneuro.bsky.social

V useful paper by @bttyeo.bsky.social @leonooi.bsky.social @csabaorban.bsky.social @shaoshiz.bsky.social in @nature.com. Scan longer if you want to predict behav using fMRI and save $.

Great use of the TCP data: (pmc.ncbi.nlm.nih.gov/articles/PMC...).

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

🔗 Check out our online calculator for future study designs and other more interactive features!👉 thomasyeolab.github.io/OptimalScanT...

Special shoutout to @csabaorban.bsky.social and @leonooi.bsky.social for co-leading this work! Huge thanks to @nfranzme.bsky.social , @sebroemer.bsky.social and all our collaborators for contributing their invaluable datasets! Truly an amazing joint effort! ❤️

🚨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👇:

How does the human brain coordinate hierarchical cortical development? Our work in Nature Neuroscience identifies a role for thalamocortical structural connectivity in the expression of hierarchical periods of cortical plasticity & environmental receptivity in youth 🧵 www.nature.com/articles/s41...

Check out our latest open data release. n=240, most with a dsm-5 dx with extensive phenotying (~100 scales/subscale), rest and task functional imaging. See @carrisacocuzza.bsky.social's thread below for deets and links 👇🏾👇🏾👇🏾

I love the work, not only because it speed up FIC models a lot, but also how it saves poor students from grad student descent 🤣🤣

Can deep learning help us solve dynamical systems problems, particularly those used in neural mass models? Check out this preprint to read about the perks...

Check our latest preprint led by the amazing @tianchu.bsky.social and @tianfang.bsky.social where we speed up the tedious parameter optimization process for biophysical modelling

🚨 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...