Yang Chang

How does our brain excel at complex object recognition, yet get fooled by simple illusory contours? What unifying principle governs all Gestalt laws of perceptual organization?

We may have an answer: integration of learned priors through feedback. New paper with @kenmiller.bsky.social! 🧵

Aligning machine and human visual representations across abstraction levels - Nature Aligning foundation models with human judgments enables them to more accurately approximate human behaviour and uncertainty across various levels of visual abstraction, while additionally improving th...

What aspects of human knowledge do vision models like CLIP fail to capture, and how can we improve them? We suggest models miss key global organization; aligning them makes them more robust. Check out LukasMuttenthaler's work, finally out (in Nature!?) www.nature.com/articles/s41... + our blog! 1/3

Dimensionality reduction may be the wrong approach to understanding neural representations. Our new paper shows that across human visual cortex, dimensionality is unbounded and scales with dataset size—we show this across nearly four orders of magnitude. journals.plos.org/ploscompbiol...

Disconnection between brain regions explains why some people don’t enjoy music. http://dlvr.it/TMMDYD

@cp-trendscognisci.bsky.social
@ub.edu Ernest Mas-Herrero, Robert J. Zatorre
@mcgill.ca Josep Marco-Pallarés

Predicting upcoming visual features during eye movements yields scene representations aligned with human visual cortex Scenes are complex, yet structured collections of parts, including objects and surfaces, that exhibit spatial and semantic relations to one another. An effective visual system therefore needs unified ...

🚨New Preprint!
How can we model natural scene representations in visual cortex? A solution is in active vision: predict the features of the next glimpse! arxiv.org/abs/2511.12715

+ @adriendoerig.bsky.social , @alexanderkroner.bsky.social , @carmenamme.bsky.social , @timkietzmann.bsky.social
🧵 1/14

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 !!

New preprint! 🚨→ Determinants of Visual Ambiguity Resolution. A new work with @ortiztudela.bsky.social @jvoeller.bsky.social @martinhebart.bsky.social and @gonzalezgarcia.bsky.social

We created ~2k images and collected ~100k responses to study visual ambiguity.

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

Higher-level spatial prediction in natural vision across mouse visual cortex Theories of predictive processing propose that sensory systems constantly predict incoming signals, based on spatial and temporal context. However, evidence for prediction in sensory cortex largely co...

New preprint, w/ @predictivebrain.bsky.social !

we've found that visual cortex, even when just viewing natural scenes, predicts *higher-level* visual features

The aligns with developments in ML, but challenges some assumptions about early sensory cortex

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

Discovering cognitive strategies with tiny recurrent neural networks - Nature Modelling biological decision-making with tiny recurrent neural networks enables more accurate predictions of animal choices than classical cognitive models and offers insights into the underlying cog...

Thrilled to see our TinyRNN paper in @nature! We show how tiny RNNs predict choices of individual subjects accurately while staying fully interpretable. This approach can transform how we model cognitive processes in both healthy and disordered decisions. doi.org/10.1038/s415...

Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior Artificial Intelligence increasingly pursues large, complex models that perform many tasks within increasingly realistic domains. How, if at all, should these developments in AI influence cognitive sc...

New preprint! In arxiv.org/abs/2502.20349 “Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior” we synthesize AI & cognitive science works to a perspective on seeking generalizable understanding of cognition. Thread:

Exciting new preprint from the lab: “Adopting a human developmental visual diet yields robust, shape-based AI vision”. A most wonderful case where brain inspiration massively improved AI solutions.

Work with @zejinlu.bsky.social @sushrutthorat.bsky.social and Radek Cichy

arxiv.org/abs/2507.03168

@neocosmliang.bsky.social demonstrating a domain general neural signature that predicts perceived beauty of objects 🌹🥀 in collab with the amazing @martinhebart.bsky.social and @dkaiserlab.bsky.social #THINGS

Meet the MIT engineer who invented an AI-powered way to restore art

Excited to share this project specifying a research direction I think will be particularly fruitful for theory-driven cognitive science that aims to explain natural behavior!

We're calling this direction "Naturalistic Computational Cognitive Science"

1. The evolution of [proto] music. My arguments against the social bonding hypothesis and in favor of the signaling hypothesis 🧪

The Explicandum: The evolution in the human lineage of vocalizations that are:

* Loud
* Synchronized
* Variable

🧵

Great seeing your work at VSS!The topic on aesthetics and NeuroAI was one of my favorites. Hope we get to discuss more next time!

Looking at Van Gogh’s Starry Night, we see not only its content (a French village beneath a night sky) but also its *style*. How does that work? How do we see style?

In @nathumbehav.nature.com, @chazfirestone.bsky.social & I take an experimental approach to style perception! osf.io/preprints/ps...

#CAOS2025 starting in Rovereto, with a fantastic talk by Wilma Bainbridge on memorability. Among others,she looked at memorability of paintings in the Art Institute of Chicago, highlighting the role of context, painting size & interestingness on memorability, & that famous pieces are more memorable.

Group of children in a class, sitting in front of a Jackson Pollock painting at the Museum of Modern Art in New York City. Stock photo.

People viewing abstract art show more interindividual variability in activity in high-order brain areas than people viewing representative art. According to the authors, abstract art is completed by the viewer, who imbues it with meaning. In PNAS: www.pnas.org/doi/10.1073/...

A move you can afford Where a person will look next can be predicted based on how much it costs the brain to move the eyes in that direction.

Where a person will look next can be predicted based on how much it costs the brain to move the eyes in that direction.
buff.ly/SXw5LPy

The Mirror Model of Art sees creativity and aesthetics as mirrors of one another.

Creativity as aesthetics in reverse? How does the Mirror Model of Art hold up when seen through the lens of neuroscience? It doesn't.

New paper with Oshin Vartanian, Delaram Farzanfar and Pablo Tinio in Neuropsychologia.
doi.org/10.1016/j.ne...

@uoftpsychology.bsky.social
@uoft.bsky.social

Mastering diverse control tasks through world models - Nature A general reinforcement-learning algorithm, called Dreamer, outperforms specialized expert algorithms across diverse tasks by learning a model of the environment and improving its behaviour by imagining future scenarios.

Nature research paper: Mastering diverse control tasks through world models

https://go.nature.com/3YigkQB

Art promotes exploration of negative content | PNAS Experiencing negative content through art has a unique power to transform our perceptions and foster engagement. While this idea has been widely di...

"Our results suggest that art stands as a powerful tool for communicating negative information, that is otherwise costly and unpleasant to engage with... Art may serve as a gateway for staying engaged, and potentially facilitate knowledge, meaningful dialog, and action"

www.pnas.org/doi/10.1073/...

Group arts interventions for depression and anxiety among older adults: a systematic review and meta-analysis - Nature Mental Health In this systematic review and meta-analysis of group arts interventions for older adults, the authors found that participation in shared artistic experience was associated with lower levels of depress...

Phenomenal paper here from Quinn and Jones published in Nature Mental Health showing

Group Arts Activitites can have moderate benefits for #anxiety and #depression for older adults.

🎨🖌️🎭👵🏻

www.nature.com/articles/s44...

#creativeageing @naturementalhealth.bsky.social

Twin modelling reveals partly distinct genetic pathways to music enjoyment - Nature Communications Here, Bignardi et al. report on a study of over 9,000 Swedish twins that indicates the ability to enjoy music is influenced by multiple partly distinct genetic factors.

“What an odd thing“ wrote Oliver Sacks “to see an entire species playing with listening to meaningless tonal patterns, preoccupied for much of their time by what they call ‘music’...“. Our new paper, led by ace student @giacomobignardi.bsky.social, unpacks this puzzle from a genetic perspective. 🧪

Happy to share our paper on the #AestheticsToolbox around the #QIP-Machine has been published #OpenAccsess in Behavior Research Methods!

It can can be used to easily and transparently compute a wide range of quantitative image properties for digital images 📸
📄 link.springer.com/article/10.3...

Out today in Nature Machine Intelligence!

From childhood on, people can create novel, playful, and creative goals. Models have yet to capture this ability. We propose a new way to represent goals and report a model that can generate human-like goals in a playful setting... 1/N

1/
Our paper is published in Nature Human Behavior!
tinyurl.com/p28jy3bx

Driving and suppressing brain activity in the human language network with model (GPT)-selected stimuli

With A. Sathe, S. Srikant, M. Taliaferro, M. Wang, @mschrimpf.bsky.social, K. Kay, @evfedorenko.bsky.social

Characterizing internal models of the visual environment: http://osf.io/wucx8_v1/

We are very excited to announce the open release of a new 170 participant dataset: Linked MEG, TMS, multimodal 3T MRI, 7T MRI, Connectom MRI, cognitive /questionnaire data. Immense effort from a fabulous
CUBRIC team. Paper by Carolyn McNabb et al: doi.org/10.1038/s415...