Laboratory for Neural Circuit and Behavior, School of Biological and Behavioural Sciences, Queen Mary University of London

London, UK
Benucci Lab retweeted
Our approach for untangling brain-wide interactions is out today in @NeuroCellPress! Massive congrats to @mattperich for leading this incredible effort since 2020, and a huge thank you to all of our collaborators. doi.org/10.1016/j.neuron.202…
Excited to share our new @biorxivpreprint which introduces 𝘾𝙪𝙧𝙧𝙚𝙣𝙩-𝘽𝙖𝙨𝙚𝙙 𝘿𝙚𝙘𝙤𝙢𝙥𝙤𝙨𝙞𝙩𝙞𝙤𝙣 (𝘾𝙐𝙍𝘽𝘿)— an approach for inferring brain-wide interactions using data-constrained recurrent neural network (RNN) models. A thread 👇🏽 (1/8) biorxiv.org/content/10.1101/…
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Benucci Lab retweeted
New preprint from the lab! Behavioral and neural mechanisms for stochastic choices in mixed-strategy games: doi.org/10.64898/2026.07.29.… We use game theoretic tasks, cross species comparisons, modelling strategies, and mesoscale imaging to probe how we can escape predictability!
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Benucci Lab retweeted
New Anthropic research: A global workspace in language models. Of everything happening in your brain right now, only a tiny fraction is consciously accessible—thoughts you can describe, hold in mind, and reason with. We found a strikingly similar divide inside Claude.
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Benucci Lab retweeted
Great blog post from @ItsNeuronal on the interpretation of Log-Likelihood Ratios for model comparison, including a (new to me!) result on how to obtain a significance threshold for declaring one model better than another: neurostatsblog.github.io/202…
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Benucci Lab retweeted
𝗦𝗽𝗮𝘁𝗶𝗮𝗹𝗹𝘆 𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝗶𝗻 𝘁𝗵𝗲 𝗺𝗼𝘂𝘀𝗲 𝗯𝗿𝗮𝗶𝗻 Leaving aside the more extreme discussions about "everything everywhere" and modularity this is a very cool paper. Data from 260 regions and 60K neurons. doi.org/10.1101/2025.07.30.6…
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Benucci Lab retweeted
1/🧵 Out today in @FrontiersIn @FrontScience: “Consciousness science: where are we, where are we going, and what if we get there?" By @axelcleeremans, @Liad_Mudrik, & me (a @CIFAR_News & @ERC_Research production🧠). frontiersin.org/journals/sci…
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I did a podcast with Jon Stewart who has always been a hero of mine. It was a lot of fun. He really wanted to understand how AI works. piped.video/watch?v=jrK3PsD3…
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Benucci Lab retweeted
🔦 New @TrendsNeuro spotlight on our recent @NatureComms paper! How do brains generalise spatial information across sensory modalities? Our study identifies a region in the dorsal cortex of mice enabling them to transfer spatial knowledge between vision and touch!🖐🏻👀 🔗cell.com/trends/neuroscience…
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Benucci Lab retweeted
My postdoc work "Unsupervised pretraining in biological neural networks" is out now, along with more than 400GB (milliions neurons) neural data. nature.com/articles/s41586-0…. Figshare and Github links can be found in the paper.
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Benucci Lab retweeted
Video prediction foundation models implicitly learn how objects move in videos. Can we learn how to extract these representations to accurately track objects in videos _without_ any supervision? Yes! 🧵 Work done with: @Rahul_Venkatesh, @SeKim1112, @jiajunwu_cs and @dyamins
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Benucci Lab retweeted
We just finished up Winter quarter CS375: Large-Scale Neural Network Models for Neuroscience. Check out the publicly available Syllabus and lecture notes cs375.stanford.edu/course-ca…
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New study from our lab, in collab with @erlichlab We developed novel frameworks to study multi-agent decision-making in mice. Mice flexibly shift their value preference under social competition, by integrating real-time self and opponent information! biorxiv.org/content/10.1101/…
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Benucci Lab retweeted
We always see that: 1) neural responses are very diverse 2) the shattering dimensionality is as high as it can be. Now also in an extensive analysis of the IBL dataset. Wonderful collaboration with @LorenzoPosani , Shuqi Wang, Samuel Muscinelli, Liam Paninski. Many new analyses
Long-overdue thread on our latest work using the IBL data to reveal the shared organizational principles of the neural code in the cortex. A systematic analysis of categoricality 🧱 and dimensionality 📐 of the neural code across 40+ regions. doi.org/10.1101/2024.11.15.6… 👇 1/n
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