Finally out in eLife!!
"Early foveal cortex predicts the features of saccade targets through feedback from higher cortical areas."
elifesciences.org/articles/107...
10 PhD positions at JLU Giessen in the new Research Training Group "PIMON"! We will explore how humans perceive and interact with materials and objects in natural environments.
More information on the project, the PIs, and how to apply here:
www.uni-giessen.de/de/ueber-uns...
Please share!
🧨 Preprint alert
Is it easier to find a ball than a shoe? The answer lies in how variable we think these objects are in the real-world. www.biorxiv.org/content/10.6...
w/ the amazing @dkaiserlab.bsky.social & @luchunyeh.bsky.social 🦄
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Our latest paper, “Visual language models show widespread visual deficits on neuropsychological tests”, is now out in Nature Machine Intelligence: www.nature.com/articles/s42...
Non-paywalled version:
arxiv.org/abs/2504.10786
Tweet thread below from first author @genetang.bsky.social...
📢Maths in the Brain Workshop 2026 in Melbourne.
We will bring together researchers across Australia with a shared interest in understanding the brain from a quantitative perspective.
This year's keynote is delivered by Professor James Cole, University College London.
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🚨 New paper out in Science Advances 🚨
With @suryagayet.bsky.social and @peelen.bsky.social, in two fMRI studies we investigate mental object rotations that are driven by the scene context, rather than purely by cognitive operations. 🧵 www.science.org/doi/10.1126/...
The OHBM OSSIG has been operating since 2016, hosting and promoting open science education for the OHBM community and beyond. SIGs must be renewed every 5 years. Please sign the following petition by Mon, Jan 26 to help us continue operating. Thank you!
docs.google.com/document/d/1...
The ARC’s processes are back to being farcical, @jasonclaremp.bsky.social
You advocated for a streamlined, efficient, faster ARC, but all that progress has been undone.
How can they claim to fund “innovation” with more than a year between initial proposal & outcomes? It should be 6 months, not 16!
Renauld et al. present scilpy, an open-source #Python library for diffusion magnetic resonance imaging and tractography: doi.org/10.52294/001...
@ohbmofficial.bsky.social
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...
🧠New preprint!
What if cortical geometry alone already encodes much of white-matter organization?
We introduce a subject-specific, reversible cortical folding model that unfolds and refolds the brain from a single T1w MRI; no diffusion, no ML.
www.biorxiv.org/content/10.6...
BOLD signal changes can oppose oxygen metabolism across the human cortex, Nature Neuroscience
fMRI signals “up,” but neural metabolism might be going “down.”
In our @natneuro.nature.com paper, we demonstrate that about 40% of voxels with robust BOLD responses exhibit opposite oxygen metabolism, revealing two distinct hemodynamic modes.
rdcu.be/eUPO8
funds @erc.europa.eu
#neuroskyence 🧵:
Exciting announcement!
Our Institute is calling for applications for a EMCR 2-year fellowship .
Come and join a great team @turnerinstitute!
Details here:
careers.pageuppeople.com/513/ci/en/jo...
Thanks @insidehighered.com for publishing our OpEd w Annie K. Lamar #publicvoices of The Oped Project @ucsantabarbara.bsky.social !
🤖Open source software & infra accelerates scientific discoveries by removing financial & technical barriers.
It's about time we start treating it as a public good👇
New preprint w/ Malin Styrnal & @martinhebart.bsky.social
Have you ever computed noise ceilings to understand how well a model performs? We wrote a clarifying note on a subtle and common misapplication that can make models appear quite a lot better than they are.
osf.io/preprints/ps...
New Correspondence with @davidpoeppel.bsky.social in Nat Rev Neurosci. www.nature.com/articles/s41...
Here, we critique a recent paper by Rosas et al. We argue that "Bottom-up" and "Top-down" neuroscience have various meanings in the literature.
PDF: rdcu.be/eSKYI
Not sure. If there are differences in anatomy, I think we could capture potential differences in retinotopic organisation. However, there could also be differences in retinotopic organisation that are not fully captured by cortical shape, as in albinos (www.med.ovgu.de/augenklinik/...).
Really excited to see this preprint out! Fernanda did an amazing job at demonstrating how you can accurately predict retinotopy from T1w scans alone. This is important for several reasons: 1/4
@martinhebart.bsky.social @sbollmann.bsky.social forgot to tag you 😅
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Thanks to all co-authors for help with the data, code, and feedback! Special thanks to Martin and Steffen for the mentorship and knowledge! I have learned a great deal in the past three years with these two and hope we can continue to expand this work together.
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🛠️ Toolbox: github.com/felenitaribe... (software containers + available on Neurodesk)
📄 Preprint: tinyurl.com/deepretinotopy
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Beyond retinotopy, this work establishes a general framework for leveraging structure-function relationships to predict topographic organization in other parts of the brain.
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Altogether, our approach offers a standardized framework for both cross-study and cross-individual comparisons, as our methodology is invariant to magnetic field strength, scanner, and acquisition site.
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Guess what? We were able to detect these expected age-related differences, suggesting that they can emerge from changes in local cortical geometry!
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We hypothesized that if age-related differences in how the primary visual cortex represents the visual field emerge from changes in local cortical geometry, deepRetinotopy should detect them.
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We retrospectively applied deepRetinotopy to 11,060 anatomical brain scans (ABCD and HCP datasets) to uncover age-related variations in visual field representations.
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Finally, we demonstrate how deepRetinotopy toolbox enables discoveries at a population scale by providing new insights into the structure-function coupling of the visual cortex.
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We also demonstrate how our toolbox can be integrated with a Bayesian model of retinotopy to derive individual-level boundaries of the early visual areas.
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We benchmark and comprehensively assess the generalizability of our approach using multiple publicly available fMRI datasets acquired under diverse experimental conditions, including varying imaging sites, scanner types, and visual stimuli protocols used for retinotopic mapping.
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In contrast to our previous proof-of-concept work, deepRetinotopy toolbox requires only a T1w image, making it readily applicable to historical datasets. It also provides an easy-to-use command-line interface that is compatible with common neuroimaging pipelines and BIDS.
