Antonino Greco

Going to Cosyne? There will be a "Biologically-inspired Artificial Intelligence: Challenges and Opportunities" workshop on Monday 16th! 🧠

Exciting lineup of speakers alongside the opportunity to present your #NeuroAI poster, more info on program & poster signup below!

#compneuro #neuroscience

Compact deep neural network models of the visual cortex Nature - Parsimonious deep neural network models can be used for prediction of visual neuron responses.

DNN models of the brain are getting bigger. Are we replacing one complicated system in vivo with another in silico?

In new work, we seek the *smallest* DNN models of visual cortex, balancing prediction with parsimony.

It turns out these compact models are surprisingly small!

rdcu.be/e5H8G

📢 PhD position in the NeuroAI of Language

Why can LLMs predict brain activity so well? We're hiring a PhD student to find out -- AI interpretability meets neuroimaging
Deadline March 20
Please RT 🙏
👇
mpi.nl/career-education/vacancies/vacancy/fully-funded-4-year-phd-position-neuroai-language

I am totally pumped about this new work . "Task-trained RNNs" are a powerful and influential framework in neuroscience, but have lacked a firm theoretical footing. This work provides one, and makes direct contact with the classical theory of random RNNs:
www.biorxiv.org/content/10.6...

Delighted to share this paper led by @hannahmcdermott.bsky.social . We examined dynamics of prediction effects (sharpening vs dampening) and found they’re completely different across time scales!

Absolutely agree with those principles, thanks for pointing them out! I believe improving scientific culture in this regard could have a profound impact, perhaps even comparable to major discoveries that have changed the course of science

"how can we make this paper better?" assumes the authors sent a version of the work that need to be improved, while most of the times this is not the case. Peer-review should be only about correctness and impact, improvement should be only suggested and not central to the evaluation at all.

Peer review would be easier if we stopped treating it like combat with the authors. Results want to be free, and perfect is the enemy of good. Do the data support the conclusions? If so, that’s enough. A paper isn’t a blank slate for projecting your own ideas.

Lack of reviewers threatens robustness of neuroscience literature Simple math suggests that small groups of scientists can significantly bias peer review.

Broad peer review is crucial for a healthy scientific literature, but neuroscientists turn down review requests too often. Simple math suggests that small groups of scientists can significantly bias the literature, writes @jvoigts.bsky.social.

#neuroskyence

www.thetransmitter.org/publishing/l...

Raccoons optimally forage for information: exploration–exploitation trade-offs in innovation Animals in rapidly changing environments, such as cities, should optimize information gathering to learn about and efficiently forage in these heterog…

Raccoon information seeking! Very cool work on raccoons optimizing information gain in puzzle solving from @sarahba.bsky.social and lab:
www.sciencedirect.com/science/arti...

Orbitofrontal cortex drives predictive filtering of sensory responses - Nature Neuroscience Top-down projections from the orbitofrontal cortex carry predictive signals that grow with sound experience and suppress the auditory cortex via inhibitory circuits, revealing a predictive mechanism f...

Orbitofrontal cortex drives predictive filtering of sensory responses

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

#neuroskyence

Why are tactile sensations suppressed during movements? In our new preprint, we explain this as optimal integration of sensory signals with an internal model.

Work led by @fatatai.bsky.social with Dimitris Voudouris, Katja Fiehler and @c-rothkopf.bsky.social

www.biorxiv.org/content/10.6...

After several years of work, my lab is starting to put out our first papers on learning in a unicellular organism (Stentor coeruleus).

Here we show evidence for a form of associative learning in Stentor:
www.biorxiv.org/content/10.6...

Vectorized instructive signals in cortical dendrites - Nature Mice learning a neurofeedback brain–computer interface task show neuron-specific teaching signals in cortical dendrites, consistent with a vectorized solution for credit assignment in the brain.

This paper on how the brain may do gradient descent is very cool: www.nature.com/articles/s41...

Renormalization in the brain?
With @andreasantoro.bsky.social and @jesseba.bsky.social we're organizing a workshop at @cosynemeeting.bsky.social (Lisbon, March 16) on how coarse-graining principles from physics can explain neural computation across scales. nplresearch.github.io/neurorenorm2...

Screening, sorting, and the feedback cycles that imperil peer review The process of peer review is vital to contemporary science, but is also under enormous strain. This study uses mathematical models to dissect the threats to the long-term viability of peer review, su...

1. Kevin Gross and I have a new paper out today PLOS Biology.

We used economic models based around screening games and the market for unpaid labor to highlight a meltdown cycle threatening peer review.

Our bilingualism paper is now published in PNAS. We used fMRI to compare semantic brain representations in English-Chinese bilinguals. Semantic representations are largely shared across languages, but finer-grained differences modulate how meaning is represented.
www.pnas.org/doi/10.1073/...

TBH the thing that is most sad about the loss of ~2015-2021 era science twitter is the loss of a public square where grad students can see, and participate in, the diversity of expert opinions in the field. It really shaped how I see science.

We've posted a new fMRI study of semantic relations (has-part, is-a, made-of, etc.), a key aspect of language. We find that relations are represented in the same brain regions as are other semantic concepts, though voxels tend to be selective for only one relation or another.
doi.org/10.64898/202...

Forward and backward prediction in learning and perception Predictive processing frameworks have emphasized the role of forward prediction as a critical ingredient for learning and perceptual inference. We ant…

These findings align well with what @clarepress.bsky.social and I discuss in our "Forward and backward prediction" paper, see www.sciencedirect.com/science/arti...

What type of relationship is learned during visual statistical learning? Statistical learning enables observers to extract regularities from their environment, but what statistical regularity is extracted remains debated. While previous research has mainly focused on condi...

Which "statistic" governs statistical learning? Find out in this new article of our lab: journals.plos.org/plosone/arti...

The strongest version of this illusion I’ve seen! Absolute head-wrecker!

underappreciated concept 🙂

for more dipoles: neighboring dipoles have different orientations & can have different stimulus preferences. so even though topographies look similar, subtle differences remain. maybe that's why it is possible to decode information from relatively few sensors?

Recent work has shown how vulnerable online survey research is to LLMs. Motivated by this, we examined our online Posner cueing data from Prolific. It's concerning. We now must carefully consider when (or whether?) online behavioral data can be trusted.
see our comment:
www.pnas.org/doi/10.1073/...

Hiring now!
📢 The CRC 1233 Robust Vision consortium at @unituebingen.bsky.social is looking for a Research Coordinator to lead science management, support project execution, and help steer our interdisciplinary research in neuroscience, machine learning and computer vision.

Man I really need to go back and watch this show again

I completely agree. I think accurately predicting future sensory input is rewarding per se!

This is because it’s one of the brain’s most fundamental objectives, arguably second only to survival itself

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

bsky.app/profile/agre...

I think this is worth a read

A perspective at how AI is becoming part of how we work 👇👇👇

Our paper is out in @natneuro.nature.com!

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

We develop a geometric theory of how neural populations support generalization across many tasks.

@zuckermanbrain.bsky.social
@flatironinstitute.org
@kempnerinstitute.bsky.social

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Bootstrapping Life-Inspired Machine Intelligence: The Biological Route from Chemistry to Cognition and Creativity Achieving advanced machine intelligence remains a central challenge in AI research, often approached through scaling neural architectures and generative models. However, biological systems offer a bro...

New preprint with Giovanni Pezzulo:
arxiv.org/abs/2602.08079
Bootstrapping Life-Inspired Machine Intelligence: The Biological Route from Chemistry to Cognition and Creativity