Lenny van Dyck

Lenny van Dyck

@levandyck.bsky.social

PhD candidate in CogCompNeuro at JLU Giessen Exploring brains, minds, and worlds 🧠💭🗺️ https://levandyck.github.io/

226 followers286 following28 posts

Pinned

Lenny van Dyck
@levandyck.bsky.social

Excited to share that our paper is now out in #JNeurosci! We propose a multidimensional framework of high-level visual cortex that reconciles a longstanding debate. Thanks to @kathadobs.bsky.social, @martinhebart.bsky.social, and everyone else for the great discussions along the way. More to come 🧠🌈

doi.orgMultidimensional feature tuning in category-selective areas of human visual cortexTwo prominent accounts describe the functional organization of human high-level visual cortex. A categorical view emphasizes category-selective areas, while a dimensional view highlights continuous fe...
SfN Journals@sfnjournals.bsky.social

#JNeurosci: Using a data-driven analysis of fMRI responses to natural images, @levandyck.bsky.social @martinhebart.bsky.social & @kathadobs.bsky.social identified interpretable dimensions that explain activity in face-, body-, & scene-selective areas https://doi.org/10.1523/JNEUROSCI.0038-26.2026

Lenny van Dyck reposted

Dominik Schnaus
@schnaus.bsky.social

DINOv2 has never seen a caption, and Qwen3 has never seen an image. We still aligned their embedding spaces without a single image-caption pair. It even works when the images and the captions come from different datasets. Project page: dominik-schnaus.github.io/unpaired-rosetta ⬇️

Lenny van Dyck reposted

Earl K. Miller
@earlkmiller.bsky.social

Most cortical neurons exhibit mixed selectivity rather than specializing in a single function. Our limited ability to juggle tasks may therefore reflect interference among overlapping neural representations. www.nature.com/articles/s41... #neuroscience

nature.comFeature interference underlies a neuronal basis for the behavioral cost of task uncertainty - Nature NeuroscienceUsing a combined approach of monkey electrophysiology, artificial neural networks and human psychophysics, Xue et al. show that neuronal interference from irrelevant information underlies behavioral e...

Lenny van Dyck reposted

Rhodri Cusack
@rhodricusack.bsky.social

We're hiring! 2 postdocs + 3 PhD students to join InfantNeuroAI at Trinity College Dublin: awake infant fMRI & OPM-MEG, plus computational models of how infants learn. Aims: understand infant visual cognition, infant neuroimaging methods, more energy-efficient learning 🧵 www.cusacklab.org/vacancies

Lenny van Dyck reposted

Rob Mok
@robmok.bsky.social

📢 Announcing the 11th CiNet Conference: "From Biological to General Artificial Intelligence: Computational and Experimental Approaches to Understanding and Modeling the Brain" 5–7 October 2026, CiNet, Osaka, Japan Organized by yours truly & Shinji Nishimoto #neuroskyence #psychscisky #mlsky 🧠🤖 1/

Lenny van Dyck reposted

Davide Cortinovis
@davidecortinovis.bsky.social

Final work from my PhD is out as a preprint, my last project at Trento before moving to Western! www.biorxiv.org/content/10.6... In this work, we ask: how is food represented in visual cortex?🧵

biorxiv.orgObject dimensions underlying food representations in visual cortexRecent work has revealed two food-selective areas in the lateral and ventromedial occipitotemporal cortex (OTC). These studies have shown that food selectivity in these regions cannot be explained by ...

Lenny van Dyck reposted

Tom McCoy
@rtommccoy.bsky.social

Since many are starting grad school soon, let me re-share my One Big Tip™️ for research! Research involves many skills - collaborating, writing, presenting, etc. But many of these skills can be unified under a single overarching ability: theory of mind Blog post link in reply

Lenny van Dyck reposted

Sander van Bree
@sandervanbree.bsky.social

Excited to share our preprint! w/ @martinhebart.bsky.social To understand how primates visually process objects in the world, we rely on both research in human and macaque IT. But what representations of object space are actually shared between them? biorxiv.org/content/10.6... Quick thread 🧵

biorxiv.orgShared and Distinct High-Dimensional Object Spaces in Human and Macaque Inferotemporal CortexHuman and macaque studies of inferotemporal cortex (IT) have shaped our understanding of object vision, yet the extent of their representational alignment and the precise nature of this correspondence...
Lenny van Dyck
@levandyck.bsky.social

Excited to be at #CCN2026 in New York to present brand-new work with @kathadobs.bsky.social 🥳 By testing hundreds of categories, we found striking differences in functional specialization between visual cortex and DNNs 🧠 Come find me at poster F81 on Thursday 1:45-3:30 p.m. Happy to chat!

Lenny van Dyck reposted

Katharina Dobs
@kathadobs.bsky.social

While I'm sad to miss #CCN2026, you don't have to miss out on the cool work coming out of the lab. 😊 Super proud of the diversity of projects this year—from category and unit specialization to inversion effects, shape bias, and memorability in brains and DNNs! Stop by and check them out! #NeuroAI

Lenny van Dyck reposted

Vlad Ayzenberg
@vayzenb.bsky.social

Excited to share our review in @cp-neuron.bsky.social with @lauriebayet.bsky.social and @mickbonner.bsky.social! We describe how implementing principles from child development can advance the mechanistic plausibility and capacities of AI models We packed A LOT into this review, here's a quick 🧵

Neuron@cp-neuron.bsky.social

dlvr.itAdvancing NeuroAI through developmental alignmentAyzenberg et al. describe how principles from child development can be used to improve the capacities and biological plausibility of AI models. These principles can be incorporated into every stage of the modeling process, from the architectures to the benchmarks.

Lenny van Dyck reposted

Lorenzo Posani
@lorenzoposani.com

Out today on @nature.com! Connecting neural specialization, population geometry, and their functional implications across the cortical hierarchy. So grateful for this beautiful and fun collaboration with @shuqiw.bsky.social, S Muscinelli, L Paninski, and @stefanofusi.bsky.social!

nature.comRarely categorical, highly separable representations along the cortical hierarchy - NatureCortical circuits prioritize diversity over categorical structure, supporting a computational regime geared towards high-dimensional, highly separable neural representations.

Lenny van Dyck reposted

Rob Mok
@robmok.bsky.social

Excited to share our new preprint: "Do Machines Fail Like Humans? A Human-Centered Out-of-Distribution Spectrum for Mapping Error Alignment" led by @binxia.bsky.social w @ken-lxl.bsky.social & co-senior author Luke Dickens (UCL) 🤖🧵👇 Link: arxiv.org/abs/2603.07462 🧠📈#PsychSciSky #compneuro #mlsky /1

arxiv.orgDo Machines Fail Like Humans? A Human-Centred Out-of-Distribution Spectrum for Mapping Error AlignmentDetermining whether AI systems process information similarly to humans is central to cognitive science and trustworthy AI. While modern AI models can match human accuracy on standard tasks, such parit...

Lenny van Dyck reposted

Katharina Dobs
@kathadobs.bsky.social

Category selectivity vs. behavioral relevance in visual cortex? 👁️🧠 @levandyck.bsky.social and I really enjoyed diving into this piece and appreciated the authors’ thoughtful response. We're curious to see how the field moves forward from here! ➡️

J. Brendan Ritchie@jbrendanritchie.bsky.social

Our reply to 11 commentaries on our article ("Rethinking category-selectivity in human visual cortex") is out in Cognitive Neuroscience! Thanks to @susanwardle.bsky.social @maryamvaziri.bsky.social Dwight Kravitz @cibaker.bsky.social and all who contributed! 1/x www.tandfonline.com/doi/full/10....

tandfonline.comWhat behavioral relevance is (not)We are thankful for the thoughtful commentaries of our colleagues. In our discussion article, we argued for a course correction to how the field approaches the organization of visual function in oc...

Lenny van Dyck reposted

J. Brendan Ritchie
@jbrendanritchie.bsky.social

Our reply to 11 commentaries on our article ("Rethinking category-selectivity in human visual cortex") is out in Cognitive Neuroscience! Thanks to @susanwardle.bsky.social @maryamvaziri.bsky.social Dwight Kravitz @cibaker.bsky.social and all who contributed! 1/x www.tandfonline.com/doi/full/10....

tandfonline.comWhat behavioral relevance is (not)We are thankful for the thoughtful commentaries of our colleagues. In our discussion article, we argued for a course correction to how the field approaches the organization of visual function in oc...
View full thread
Lenny van Dyck
@levandyck.bsky.social

Finally, we examined how DNNs integrate faces and bodies: DNN responses to whole persons approximated the sum of their responses to isolated faces and bodies, suggesting part-based rather than holistic integration. 8/n

Lenny van Dyck
@levandyck.bsky.social

To summarize: Both models and cortex show partially integrated face and body representations, which converge along the visual hierarchy. This may strike a balance between segregation and integration, building part-based representations that support the full range of person perception. 🧠 9/9

View full thread
Lenny van Dyck
@levandyck.bsky.social

While face- and body-selective units explained substantial unique variance in their corresponding regions, they mainly explained shared variance. Crucially, this shared component increased from posterior to anterior regions, suggesting that integration grows along the cortical hierarchy. 6/n

Lenny van Dyck
@levandyck.bsky.social

Back in DNNs, we tested whether mixed selectivity is functionally relevant: We trained a DNN on different person perception tasks and lesioned each unit type. Lesioning mixed-selective units led to deficits across tasks, confirming these units actively support person perception. 7/n

View full thread
Lenny van Dyck
@levandyck.bsky.social

Let’s first look at computational models of visual cortex: Diverse DNNs developed distinct face- and body-selective units, but also mixed-selective units responding to both categories. This suggests that face-body integration naturally arises from learning to recognize whole persons. 🕺 4/n

Lenny van Dyck
@levandyck.bsky.social

Let’s now link this to visual cortex: Mixed-selective units best predicted activity in both face- and body-selective regions, suggesting that they encode more integrated person information than generally assumed. 🪢 5/n

Lenny van Dyck
@levandyck.bsky.social

The brain has specialized regions for faces and bodies. However, in the real world, they usually appear together as whole persons. Whether and how visual cortex integrates face and body representations remains largely unclear. 🤔 2/n

Lenny van Dyck
@levandyck.bsky.social

So, here we ... 1️⃣ Used a functional localizer to test whether DNNs develop distinct and/or shared tuning for faces and bodies. 2️⃣ Applied fMRI encoding models to map DNN representations onto visual cortex. 3️⃣ Closely examined DNN representations to generate hypotheses about face-body integration. 3/n

Lenny van Dyck reposted

Cliona O'Doherty
@clionaod.bsky.social

1/7 Can infants recognise the world around them? 👶🧠 As part of the FOUNDCOG project, we scanned 134 awake infants using fMRI. Published today in Nature Neuroscience, our research reveals 2-month-old infants already possess complex visual representations in VVC that align with DNNs.

Lenny van Dyck reposted

Kelsey Han
@chihyehan.bsky.social

Human visual cortex representations may be much higher-dimensional than earlier work suggested, but are these higher dimensions of cortical activity actually relevant to behavior? Our new paper tackles this by studying how different people experience the same movies. 🧵 www.cell.com/current-biol...

cell.comHigh-dimensional structure underlying individual differences in naturalistic visual experienceHan and Bonner reveal that individual visual experience arises from high-dimensional neural geometry distributed across multiple representational scales. By characterizing the full dimensional spectru...

Lenny van Dyck reposted

Russell Epstein
@russellepstein.bsky.social

Our new paper in @sfnjournals.bsky.social shows different neural systems for integrating views into places--PPA integrates views *of* a location (e.g., views of a landmark), while RSC integrates views *from* a location (e.g., views of a panorama). Work by the bluesky-less Linfeng Tony Han.

SfN Journals@sfnjournals.bsky.social

#JNeurosci: Using fMRI, Han and Epstein explored how people integrate different kinds of views to form mental maps of places, revealing two sets of brain regions involved in integrating views of landmarks into existing mental maps of a virtual city. https://doi.org/10.1523/JNEUROSCI.0187-25.2025

Lenny van Dyck reposted

Davide Cortinovis
@davidecortinovis.bsky.social

Now in press at Nature Communications! www.nature.com/articles/s41... Check it out if you are interested in category selectivity, the organization of visual cortex, and topographic models!

nature.comInvestigating action topography in visual cortex and deep artificial neural networks - Nature CommunicationsThis study shows that interaction with objects is an important dimension that shapes the way object categories such as hands and tools are organized in visual cortex and shows that artificial neural n...
Davide Cortinovis@davidecortinovis.bsky.social

New preprint out! We propose that action is a key dimension shaping the topographic organization of object categories in lateral occipitotemporal cortex (LOTC)—and test whether standard and topographic neural networks capture this pattern. A thread: www.biorxiv.org/content/10.1... 🧵 1/n

biorxiv.orgInvestigating action topography in visual cortex and deep artificial neural networksHigh-level visual cortex contains category-selective areas embedded within larger-scale topographic maps like animacy and real-world size. Here, we propose action as a key organizing factor shaping vi...

Lenny van Dyck reposted

Sander van Bree
@sandervanbree.bsky.social

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

nature.comTop-down and bottom-up neuroscience as collections of practices - Nature Reviews NeuroscienceNature Reviews Neuroscience - Top-down and bottom-up neuroscience as collections of practices

Lenny van Dyck reposted

Joao Barbosa
@jbarbosa.org

Y’all are reading this paper in the wrong way. We love to trash dominant hypothesis, but we need to look for evidence against the manifold hypothesis elsewhere: This elegant work doesn't show neural dynamics are high D, nor that we should stop using PCA It’s quite the opposite! (thread)

Dan Levenstein@dlevenstein.bsky.social

“Our findings challenge the conventional focus on low-dimensional coding subspaces as a sufficient framework for understanding neural computations, demonstrating that dimensions previously considered task-irrelevant and accounting for little variance can have a critical role in driving behavior.”

biorxiv.orgNeural dynamics outside task-coding dimensions drive decision trajectories through transient amplificationMost behaviors involve neural dynamics in high-dimensional activity spaces. A common approach is to extract dimensions that capture task-related variability, such as those separating stimuli or choice...
Lenny van Dyck
@levandyck.bsky.social

Really looking forward to #CCN2025! On Tuesday, I'm presenting new work with @kathadobs.bsky.social on segregated vs. integrated face & body processing in visual cortex 😊🧍🧠 Using DNNs & fMRI, we test competing hypotheses, finding both distinct & shared selectivity. Come by Poster A64 for more.

Lenny van Dyck reposted

Davide Cortinovis
@davidecortinovis.bsky.social

New preprint out! We propose that action is a key dimension shaping the topographic organization of object categories in lateral occipitotemporal cortex (LOTC)—and test whether standard and topographic neural networks capture this pattern. A thread: www.biorxiv.org/content/10.1... 🧵 1/n

biorxiv.orgInvestigating action topography in visual cortex and deep artificial neural networksHigh-level visual cortex contains category-selective areas embedded within larger-scale topographic maps like animacy and real-world size. Here, we propose action as a key organizing factor shaping vi...

Lenny van Dyck reposted

Yingtian (David) Tang
@davidtyt.bsky.social

🧠 NEW PREPRINT Many-Two-One: Diverse Representations Across Visual Pathways Emerge from A Single Objective www.biorxiv.org/content/10.1...

biorxiv.orgMany-Two-One: Diverse Representations Across Visual Pathways Emerge from A Single ObjectiveHow the human brain supports diverse behaviours has been debated for decades. The canonical view divides visual processing into distinct "what" and "where/how" streams – however, their origin and inde...

Lenny van Dyck reposted

Martin Hebart
@martinhebart.bsky.social

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...

nature.comDimensions underlying the representational alignment of deep neural networks with humans - Nature Machine IntelligenceAn 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 ...