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Shaoshi Zhang

@shaoshiz.bsky.social
46 followers 51 following 5 posts

neuroscience, computational models | Computational Brain Imaging Group | Huge fan of Metroidvania and Edward Hopper.

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Shaoshi Zhang @shaoshiz.bsky.social · 21/05/2026
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. 🧵👇
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Oxford Population Health @oxpop.bsky.social · 22/07/2025
@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 👇
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John Rolston @rolstonjohn.bsky.social · 21/07/2025
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
nature.com
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.
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Brenden Tervo-Clemmens @tervoclemmensb.bsky.social · 17/07/2025
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.
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Mary Elizabeth Sutherland @meharpist.bsky.social · 17/07/2025
I'm so proud to see this great paper finally published in @nature.com!
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danilobzdok @danilobzdok.bsky.social · 16/07/2025
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...
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Laurence Hunt @lhuntneuro.bsky.social · 17/07/2025
Really nice study, and extends some of the ideas developed in this paper pubmed.ncbi.nlm.nih.gov/32673043/
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Jim Thompson @jimthommo.bsky.social · 17/07/2025
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
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Nico Dosenbach @ndosenbach.bsky.social · 17/07/2025
This new Yeo Lab tool should immediately and permanently replace sample-size-only power calculations for functional MRI. www.nature.com/articles/s41...
nature.com
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 effect...
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Ted Satterthwaite @ted-satterthwaite.bsky.social · 17/07/2025
Just incredible results from a massive effort— moves the field forward. Bravo!!!
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Nature @nature.com · 17/07/2025
Nature research paper: Longer scans boost prediction and cut costs in brain-wide association studies go.nature.com/3IME4aA
go.nature.com
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.
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Alex Fornito @alexfornito.bsky.social · 17/07/2025
Big congrats to @bttyeo.bsky.social and team on this impressive and important work!
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Thomas Nichols @nichols.bsky.social · 17/07/2025
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.
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Thomas Yeo @bttyeo.bsky.social · 17/07/2025
Everyone should try out the Trandiagnostic Connectome Project (TCP) dataset! Openly available on @openneuro.bsky.social
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Sidhant Chopra @sidchop.bsky.social · 17/07/2025
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...).
thomasyeolab.github.io
Ooi2025 Optimal Scan Time Calculator
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Leon @leonooi.bsky.social · 17/07/2025
Super thankful to @bttyeo.bsky.social @csabaorban.bsky.social and @shaoshiz.bsky.social for pouring in all the effort to make this work possible!
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Shaoshi Zhang @shaoshiz.bsky.social · 17/07/2025
🚨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👇:
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Valerie Jill Sydnor @valeriejsydnor.bsky.social · 08/07/2025
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...
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Sidhant Chopra @sidchop.bsky.social · 05/06/2025
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 👇🏾👇🏾👇🏾
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Feilong Ma @feilong.bsky.social · 16/05/2025
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 🤣🤣
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Sina Mansour L. @sinamansourl.bsky.social · 20/04/2025
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...
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Shaoshi Zhang @shaoshiz.bsky.social · 11/04/2025
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
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Thomas Yeo @bttyeo.bsky.social · 20/11/2024
🚨 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...
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