Lightnews — Scholar-powered news

Bin Wan @wanb.bsky.social · Jul 8

congrats！Valerie

Reposted by Bin Wan

gradientsworkshop.bsky.social @gradientsworkshop.bsky.social · Jun 23

It's a wrap! BIG thanks to all speakers, chairs, attendees, and our organizing committee - particularly our superstar local organizers Johan and Saurabh - for making our gradient dreams come true for the sixth year in a row ⭐ 🌈 🧠 🚀

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Bin Wan @wanb.bsky.social · Jun 23

woooowoooo

Reposted by Bin Wan

OHBM Trainees @ohbmtrainees.bsky.social · Jun 22

🎉🎉#OHBM2025 is just around the corner! Remember to visit the SP-SIG stall next to the registration desk and add stickers to your badge describing your research interests!

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Bin Wan @wanb.bsky.social · Jun 20

I finally defended my thesis! Thanks all! I started my PhD during covid! I am really grateful that my supervisor @sofievalk.bsky.social picked me to be her first PhD student when I was naive to neuroimage. I have been so lucky to stay in this happy and respectful academic environment so far!

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Bin Wan @wanb.bsky.social · Jun 10

Congrats bro!

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Reposted by Bin Wan

Nature Methods @natmethods.nature.com · Jun 6

An Analysis of 200 pairwise statistics for functional brain connectivity in tasks such as hub mapping, distance relationships, structure-function coupling and behavior prediction highlights their effectiveness for neurophysiological applications.

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

Benchmarking methods for mapping functional connectivity in the brain - Nature Methods

In this Analysis, Liu et al. benchmark more than 200 pairwise statistics for functional brain connectivity in tasks such as hub mapping, distance relationships, structure–function coupling and behavio...

www.nature.com

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Reposted by Bin Wan

Amin Saberi @amnsbr.bsky.social · Jun 5

🧠⚖️📉 How does the cortical excitation-inhibition ratio mature during adolescence?
We asked this in our new paper just out in #ScienceAdvances ✨
“Adolescent maturation of cortical excitation-inhibition ratio based on individualized biophysical network modeling”
📄 www.science.org/doi/full/10....
🧵⤵️

Adolescent maturation of cortical excitation-inhibition ratio based on individualized biophysical network modeling

Individualized simulations reveal a decrease in excitation-inhibition ratio in association areas throughout adolescence.

www.science.org

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Reposted by Bin Wan

Aperture Neuro @apertureohbm.bsky.social · Jun 2

Merchant et al. perform a meta-analytic investigation of neurocognitive systems involved in real-time social interaction doi.org/10.52294/001...

@fmri-today.bsky.social @mallarchak.bsky.social @ohbmofficial.bsky.social

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Reposted by Bin Wan

Maciek Szul @maciekszul.bsky.social · Jun 2

🚨🚨🚨PREPRINT ALERT🚨🚨🚨
Neural dynamics across cortical layers are key to brain computations - but non-invasively, we’ve been limited to rough "deep vs. superficial" distinctions. What if we told you that it is possible to achieve full (TRUE!) laminar (I, II, III, IV, V, VI) precision with MEG!

Overview of the simulation strategy and analysis. a) Pial and white matter boundaries
surfaces are extracted from anatomical MRI volumes. b) Intermediate equidistant surfaces are
generated between the pial and white matter surfaces (labeled as superficial (S) and deep (D)
respectively). c) Surfaces are downsampled together, maintaining vertex correspondence across
layers. Dipole orientations are constrained using vectors linking corresponding vertices (link vectors).
d) The thickness of cortical laminae varies across the cortical depth (70–72), which is evenly sampled
by the equidistant source surface layers. e) Each colored line represents the model evidence (relative
to the worst model, ΔF) over source layer models, for a signal simulated at a particular layer (the
simulated layer is indicated by the line color). The source layer model with the maximal ΔF is
indicated by “˄”. f) Result matrix summarizing ΔF across simulated source locations, with peak
relative model evidence marked with “˄”. g) Error is calculated from the result matrix as the absolute
distance in mm or layers from the simulated source (*) to the peak ΔF (˄). h) Bias is calculated as the
relative position of a peak ΔF(˄) to a simulated source (*) in layers or mm.

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Bin Wan @wanb.bsky.social · May 19

Juicy

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Reposted by Bin Wan

Annie G. Bryant @anniegbryant.bsky.social · May 4

🎨🧑‍🎨 Looking for a tool to visualize subcortical/thalamic data in 2D? Check out this python-based package I put together (subcortex-visualization on PyPI), plus a guide for creating your own custom atlas meshes and vector graphics! All feedback/tips welcome 😊

anniegbryant.github.io/subcortex_vi...

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Bin Wan @wanb.bsky.social · Apr 29

See our GWAS of grapical topology🤟

Varun Warrier @vw1234.bsky.social · Apr 29

Pleased to share new work from our group, led by PhD student Edward He. Edward joined the group as a summer student interested in the genetics of resting state functional connectivity, measured using graph networks.

www.medrxiv.org/content/10.1...

www.medrxiv.org

Reposted by Bin Wan

ENIGMA Consortium @enigmabrains.bsky.social · Apr 25

As always, it was great fun to connect with our ENIGMA Consortium community last night at #SOBP2025 in Toronto - thanks to all who joined us! Cheers to science and the next SOBP conference🍻🧠

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Reposted by Bin Wan

Boris Bernhardt @borismontreal.bsky.social · Apr 25

in press @natcomms.nature.com 🌟

"Multimodal gradients unify local and global cortical organization"

7T MRI + cytoarchitectonics reveal a sensory-paralimbic axis of areal specialization & integration

led by superstar Yezhou Wang & a terrific team of friends & colleagues

▶️ doi.org/10.1038/s414...

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Bin Wan @wanb.bsky.social · Apr 5

that‘s pretty

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Reposted by Bin Wan

Donna Gift Cabalo @donnagift.bsky.social · Mar 30

Our open-source multimodal precision MRI dataset is officially out! 🧲🧠🧲

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

osf.io/mhq3f/

@borismontreal.bsky.social @jroyer.bsky.social @themindwanders.bsky.social @jordandekraker.bsky.social

Multimodal precision MRI of the individual human brain at ultra-high fields - Scientific Data

Scientific Data - Multimodal precision MRI of the individual human brain at ultra-high fields

www.nature.com

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