Benucci Lab

How psychedelics push your brain to dream while awake – new study theconversation.com/how-psychedeli… via @ConversationUK

Nature research paper: Evidence accumulation from experience and observation in the cingulate cortex go.nature.com/3NcJfTB

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/10.1101/2025.0…

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/scien…

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. youtube.com/watch?v=jrK3Ps…

A pair of papers on using holographic optogenetics and compressed sensing for connectomics Rapid learning of neural circuitry from holographic ensemble stimulation enabled by model-based compressed sensing nature.com/articles/s4159…

🔦 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/neurosc…

My postdoc work "Unsupervised pretraining in biological neural networks" is out now, along with more than 400GB (milliions neurons) neural data. nature.com/articles/s4158…. Figshare and Github links can be found in the paper.

Press Release -- New research shows how brain circuitry produces inferred emotions, allowing a better understanding of anxiety. #Emotions #BrainScience #RIKEN #MentalHealth @RIKEN_CBS @JoJoLab5 doi.org/10.1038/s41586… riken.jp/en/news_pubs/r…

@TJRyan_77 @JoJoLab5 @Andrea_MZamora @Akaron0884 @tcddublin @lynchielydia @DrChristineAnnD @RyanLabTCD @Nature Wonderful work. "Engram cells can be defined as neuronal ensembles [...] the reactivation of which leads to the retrieval of the target memory". Could replacing "memory" with "computation" relate engrams to, for example, sparse coding in neural nets?

Excited to share our new study: "Cold memories control whole-body thermoregulatory responses" by @Andrea_MZamora, @Akaron0884 & team at @tcddublin, in collaboration with @lynchielydia & @DrChristineAnnD @RyanLabTCD @Nature nature.com/articles/s4158…

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

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-calenda…

🚨Fully funded PhD opportunity at QMUL, London!🚨 Join us to explore optogenetic control of visual perception. Open to UK nationals & UK-ILR residents. Please share! 👇 🔗 shorturl.at/77f6U

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/10.110…

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

🌟New preprint with @LynnKASorensen and @JamesJDiCarlo When animals learn new object discrimination tasks, how much does their IT cortex change? In their untrained state, animals can still see objects but can’t attach labels—so we don’t expect the ventral stream to fully reformat with learning. But does it change at all, or does everything happen downstream? Trained vs. untrained monkeys show minor but robust IT changes—not a complete reformat, but meaningful tweaks. Interestingly, many ANN models of untrained IT show similar changes at the level of ANN-IT (which is typically not at the very end of the ANN hierarchy) with additional category training (implemented via varied learning approaches) that also generalize to category orthogonal representational shifts -- suggesting that these learning-induced changes in macaque IT are consistent with performance-optimizing updates within a visual hierarchy! biorxiv.org/content/10.110…

Temporal dynamics of energy-efficient coding in mouse primary visual cortex biorxiv.org/content/10.110… An efficient paper with few words but a lot of information. 😀

25 yrs ago, perception dominated neuroscience, and Raj's @RajeshPNRao predictive coding theory. Now, it's all about action-perception loops across the hierarchy... "active predictive coding." Also, augmenting our cognition with AI neural co-processors! braininspired.co/podcast/201/

New results! Visual adaptation changes the geometry of V1 population activity: frequent stimuli elicit smaller responses but become more discriminable, consistent with our efficient coding model. You can find me on the "new neurotwitter" at mariodipoppa. biorxiv.org/content/10.110…