Anna-Lena Stroh

On Friday, niklasmuller.bsky.social shows that estimating population receptive fields (pRF) using DNN feature maps but without assuming a Gaussian pRF shape yields better predictions of THINGS ephys data, uncovering surprising pRF geometries! 2025.ccneuro.org/poster/?id=1... Poster C105, 14:00-17:00

This is wild. Dirt-cheap, un-patentable lithium supplements might just reverse Alzheimer's (in mice, admittedly...).

fMRI experimental design and procedure

Decoding semantic sound categories in early visual cortex academic.oup.com/cercor/artic... "semantic and categorical sound information is represented in early visual cortex, potentially used to predict visual input"; #neuroscience

Addressing artifactual bias in large, automated MRI analyses of brain development - Nature Neuroscience As large-scale neurodevelopmental MRI studies gain prominence, the authors identify tradeoffs between sample size and quality control that can dramatically affect results, and they evaluate a range of...

Analysis of >11,000 pediatric MRI scans suggests that suboptimal image quality may introduce bias in cortical thickness and area estimates in over half the cases 🤔🧐

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

Spatial specificity of the functional gradient echo and spin echo BOLD signal across cortical depth at 7 T Functional magnetic resonance imaging (fMRI) at high magnetic field strengths (≥ 7 T) is a promising technique to study the functioning of the human brain at the spatial scale of cortical columns and ...

I’m happy to share that our manuscript on the cortical depth-dependency of the GE- and SE-BOLD point spread function at 7 Tesla is now available on bioRxiv!

www.biorxiv.org/content/10.1...

While many believe being ‘more in tune with your body’ improves mental health, we surprisingly found the opposite: worse mental health (higher anxiety, depression, stress, fatigue & reduced well-being)—with stronger stomach-brain connections.

four brain maps showing noise ceiling estimates in response to image presentation

New CNeuroMod-THINGS open-access fMRI dataset: 4 participants · ~4 000 images (720 categories) each shown 3× (12k trials per subject)· individual functional localizers & NSD-inspired QC . Preprint: arxiv.org/abs/2507.09024 Congrats Marie St-Laurent and @martinhebart.bsky.social !!

6/11 One of our most striking (and unexpected) findings was that an individual child’s brain functional connectivity is more similar to their childhood peers than adults are to other adults. That is, children showed less inter-individual variability than adults.

Precision functional mapping reveals less inter-individual variability in the child vs. adult human brain Human brain organization shares a common underlying structure, though recent studies have shown that features of this organization also differ significantly across individual adults. Understanding the...

1/11 Very excited to say that our preprint, Precision functional mapping reveals less inter-individual variability in the child vs. adult human brain, is up on biorxiv!
www.biorxiv.org/content/10.1...

New paper in Imaging Neuroscience by Jochen Schmidt, Nikolaus Weiskopf, et al:

High-resolution quantitative T2 mapping of the human brain at 7 T using a multi-echo spin-echo sequence and dictionary-based modeling

doi.org/10.1162/IMAG...

Brain Surfaces of 70 primate species

1
To predict the behaviour of a primate, would you rather base your guess on a closely related species or one with a similar brain shape? We looked at brains & behaviours of 70 species, you’ll be surprised!

🧵Thread on our new preprint with @r3rt0.bsky.social , doi.org/10.1101/2025...

Visual Word Form Area demonstrates individual and task-agnostic consistency but inter-individual variability https://www.biorxiv.org/content/10.1101/2025.07.23.666206v1

What a fantastic time at IMRF! 🎉

Huge thanks to the brilliant speakers for making our symposium on “Blindness as a Window into Brain Organisation” a big success! Big thanks to the organisers and the scientific community for this stellar event! Great to see so many friends and colleagues! #IMRF2025

Lénia Amaral presented her work at the ‪@imrf.bsky.social!

Her talk, “Stable, but unique: individualized connectivity in the blind V1 over time” reflects her postdoctoral work with @striemamit.bsky.social at the SAMP Lab, Georgetown University.
@durham-university.bsky.social

Today @nikaradziun.bsky.social gave a fantastic talk on cardiac interoception processing in the blind as part of the symposium "Blindness as a window into fundamental principles of brain organisation" #IMRF2025 @imrf.bsky.social

🧠✨ Excited to share that our literature review on retinotopic mapping in the human visual cortex is now published!
tinyurl.com/5d9ne68b

Amazing collab with Noah Benson and Alex Puckett! We hope this will be a helpful resource for pRF modellers and visual neuroscientists!

New paper in Imaging Neuroscience by Fakhereh Movahedian Attar, Nikolaus Weiskopf, et al:

Short association fibres form topographic sheets in the human V1–V2 processing stream

doi.org/10.1162/imag...

New mesoscale manuscript looking at functional connectivity of ocular dominance columns during resting state.
By Schmidt et al.,
doi.org/10.1101/2025...

Thrilled to be attending the #IMRF2025 @imrf.bsky.social in beautiful Durham this week! I'll be presenting in Symposium 3 on Wednesday at 11:00, kindly organized by @katarzynaraczy.bsky.social and @lenastroh.bsky.social. Looking forward to the discussions ahead! 🧠

Journal of Vision Special Issue The vision-language interface Call for papers Vision and language are often considered to be separate cognitive systems, studied by separate research teams. However, they interact when we use vision for linguistic communication: when reading printed text, when describing verbally the things we see, and when observing the expressions and gestures of an interlocutor (during sign language, for example). The development of these critical skills changes the brain, such that the visual and language systems influence one another. In particular, regions of the cerebral cortex that are typically responsive to visual stimuli are also recruited for linguistic tasks. But some of those ideas are controversial. For instance, for well over a century scientists have debated whether the brains of literate individuals contain a region that is specialized for recognizing written words. The Journal of Vision invites submissions for a Special Issue on the interface between vision and language. The unique perspectives and techniques of vision science contribute much to the understanding of language. This special issue welcomes empirical papers that use behavioral/psychophysical, neuroimaging, electrophysiological and stimulation methods. Topics include, but are not limited to: - Functional specialization in the brain for reading and naming - Semantic representations in the brain - Letter recognition and perceptual learning - Sign language comprehension - Eye movements during reading or other linguistic tasks - Development of visual skills for reading and communication - Links between visual cortical activity and representations in large language models - Visual processing differences in dyslexia Editors: Susana Chung Kalanit Grill-Spector Garikoitz Lerma-Usabiaga Hans Op de Beeck Zeynep Saygin Alex White Oscar Woolnough Deadline for submissions: December 31, 2025. All papers will be subject to peer review.

For everyone out there working at the intersection of vision and language. We are currently accepting submissions for a Journal of Vision Special Issue on the vision-language interface
Submission deadline: Dec 31st
jov.arvojournals.org/ss/visionlan...

#neuroskyence #VisionScience #PsychSciSky

Dimensions underlying the representational alignment of deep neural networks with humans - Nature Machine Intelligence An interpretability framework that compares how humans and deep neural networks process images has been presented. Their findings reveal that, unlike humans, deep neural networks focus more on visual ...

What makes humans similar or different to AI? In a paper out in @natmachintell.nature.com led by @florianmahner.bsky.social & @lukasmut.bsky.social, w/ Umut Güclü, we took a deep look at the factors underlying their representational alignment, with surprising results.

www.nature.com/articles/s42...

Feature-specific recruitment of deprived sensory cortices.

Beyond reorganization: Intrinsic cortical hierarchies constrain experience-dependent plasticity in sensory-deprived humans www.biorxiv.org/content/10.1... "we confirm that auditory and speech related features are redirected to deprived visual cortices in blind individuals"; #neuroscience #blindness

Now out in Nature Human Behaviour @nathumbehav.nature.com : “End-to-end topographic networks as models of cortical map formation and human visual behaviour”. Please check our NHB link: www.nature.com/articles/s41...

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.

🧠⚖️📉 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....
🧵⤵️

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.

🚨🚨🚨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!

Today in @nature.com , we report a spatial single-cell atlas of human cortical development, revealing surprisingly early specification of human cortical layers and areas.
We built an interactive browser to explore the spatial data: walshlab.org/research/cor...
Paper link below 👇

Fascinating talk by @rhodricusack.bsky.social showing his & @clionaod.bsky.social’s work on 2 and 9-month olds with 130 (!) infants & 20 min (!) data showing a largely similar representation of medial ventral vision but a largely absent response in LO, dovetailing with myelin development. #CAOS2025

Preprint alert 📣 Check out our new preprint where we look into the relationship between cortical thickness and functional activation during linguistic processing in early blind individuals.

Visual experience affects neural correlates of audio-haptic integration: A case study of non-sighted individuals The ability to reduce sensory uncertainty by integrating information across different senses develops late in humans and depends on cross-modal, senso…

Visual experience affects neural correlates of audio-haptic integration: A case study of non-sighted individuals www.sciencedirect.com/science/arti... by @meike-scheller.bsky.social @michaelproulx.bsky.social et al.

Unraveling the mesoscale functional connectivity of the human primary visual cortex using high-resolution functional MRI. https://www.biorxiv.org/content/10.1101/2025.03.27.645795v1