Happy holidays, #UofT 💙 The university will be closed from Dec. 24, 2025 to Jan. 2, 2026. To find resources for the U of T community, please visit utoronto.ca/utogether. We wish you a safe & restful winter break! ❄️

Our final paper of the year. On behalf of the Computational Neuroscience Lab and the entire University of Toronto community, happy holidays! Paper: www.biorxiv.org/content/10.6... #neuroAI #compneuro #neuroscience @uhn.ca @uhnresearch.ca @vectorinstitute.ai @utoronto.ca @uoftcompsci.bsky.social

Excited to announce a new book telling the story of mathematical approaches to studying the mind, from the origins of cognitive science to modern AI! The Laws of Thought will be published in February and is available for pre-order now.

Happy holidays from the Computational Neuroscience Lab at the University of Toronto! Missing from photo: Samuel Kostousov, Justin Chow, Anastasiia Petrovych, Aditya Rajeev, and Solomiia Leno. @utoronto.ca @uhn.ca @vectorinstitute.ai @uoftcompsci.bsky.social

Why isn’t modern AI built around principles from cognitive science or neuroscience? Starting a substack (infinitefaculty.substack.com/p/why-isnt-m...) by writing down my thoughts on that question: as part of a first series of posts giving my current thoughts on the relation between these fields. 1/3

Prediction: task-based optimization will ultimately prove to have a relatively minor role in DNN models of the ventral stream. Although tasks (including self-supervised ones) are currently crucial, there are signs that a simpler approach is possible. A thread:

It was an absolute pleasure giving the University of Toronto Robotics Institute seminar on "Using Embodied Agents to Reverse-Engineer Natural Intelligence". Check out the recording here: www.youtube.com/watch?v=E4Qm...

🧠 Imagine being able to control machines by thinking. @drlaschowski.bsky.social (MIE) and his Computational Neuroscience Lab are working to make it possible. They've developed a new algorithm that could make brain decoding more accurate and efficient. Read the story: uofteng.ca/25h7c8

Hopkins Cog Sci is hiring! We have two open faculty positions: one in vision, and one language. Please repost!

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...

Amazing talk last week by Dr. Aran Nayebi at #UofT on reverse-engineering the brain and building neuroscience-inspired AI. #neuroAI #compneuro @anayebi.bsky.social @utoronto.ca @uoftcompsci.bsky.social @vectorinstitute.ai

Celebrating the first ever Sejnowski-Hinton award!

Office view at #UofT

#UofT establishes new Hinton Chair in Artificial Intelligence with support from Google 💡 uoft.me/hinton-chair

Rich Sutton takes the stage this morning to open our invited speaker series. The pioneer of reinforcement learning brings decades of insight to NeurIPS 2025. buff.ly/bruWGc1 #NeurIPS2025 #NeurIPSanDiego

🎉 Our paper has been selected for a Neurips Spotlight: “Scaling and Context Steer LLMs along the Same Computational Path as the Human Brain” 👥led by J Raugel, w/ S. Ascoli, Rapin & @valentinwyart.bsky.social 📄https://openreview.net/pdf?id=4YKlo58RcQ 📍 Hall C-E Poster #2006 🧵thread 👇

We are excited to announce that the Cognitive Computational Neuroscience meeting (CCN 2026) will be held at New York University from August 3–6, 2026. 2026.ccneuro.org

The latest superlab journal club: @hritz.bsky.social discussing his latest preprint investigating task switching in brains and machines. youtu.be/MdOkOjSa7JA

The best brain-machine interface remains the mouth. Evolution spent 4B years of evolution on R&D developing the device, so I guess it's not that surprising. Yet it still rarely appears as a baseline in evaluations of new devices.

Thanks Google Research for the non-technical summary of our latest study! #neuroscience #AI #neuroAI @utoronto.ca @uhn.ca www.youtube.com/watch?v=u1PM...

Imagine a brain decoding algorithm that could generalize across different subjects and tasks. Today, we’re one step closer to achieving that vision. Introducing the flagship paper of our brain decoding program: www.biorxiv.org/content/10.1... #neuroAI #compneuro @utoronto.ca @uhn.ca

Faculty Position: Neurocomputation Apply by December 1, 2025 WTI invites those from mathematical, computational, and related fields interested in working with experimentalists to develop new frameworks for understanding cognition. 🔗 wti.yale.edu/opportunities/faculty-neurocomputation

Congrats to Andrii Dashkovets—one of my students in #Ukraine—whose work using reinforcement learning to model human motor control in simulation has been accepted to a #NeurIPS workshop.

Honored to speak at Ottawa about how Canada can lead in #NeuroAI. With world-class talent, trusted institutions, & sustainable infrastructure, we can build a federated approach to AI that protects mental health & strengthens our society. Thanks @braincanada.bsky.social for the invitation!

This trial has two goals: ensure the brain implant is safe; and to restore a person's ability to communicate with real-time speech go.nature.com/4oSXuLj

If you're interested in dynamical systems analysis for neuroscience, definitely check out @oliviercodol.bsky.social 's revised version of our RL paper! Very cool results in the new Fig 6, worth it regardless of if you saw our previous version or if it's all new. www.biorxiv.org/content/10.1...

Pleased to share that our survey "Getting aligned on representational alignment" — on representational alignment across cognitive (neuro)science and machine learning — is now published in TMLR! openreview.net/forum?id=Hiq... Kudos to @sucholutsky.bsky.social @lukasmut.bsky.social for leading this!

Our work with @pawa-pawa.bsky.social is out in Nature Machine Intelligence! The choice of activation function affects the representations, dynamics, and circuit solutions that emerge in RNNs trained on cognitive tasks. Activation matters! www.nature.com/articles/s42...

🧠 Thrilled to share our NeuroView with Ellie Pavlick! "From Prediction to Understanding: Will AI Foundation Models Transform Brain Science?" AI foundation models are coming to neuroscience—if scaling laws hold, predictive power will be unprecedented. But is that enough? Thread 🧵👇

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

Join us December 5th at University of Toronto (in-person and online) for a special seminar by Dr. Aran Nayebi on reverse-engineering the brain and building neuroscience-inspired artificial intelligence. #neuroAI #compneuro @anayebi.bsky.social @utoronto.ca @uoftcompsci.bsky.social

Imagine being able to control machines by thinking. This communication link known as a brain-machine interface and a new algorithm developed in #UofT Prof. Brokoslaw Laschowski’s lab could soon make these interfaces more accurate and efficient. bit.ly/4qnMdDZ

Inspiring talk by theoretical neuroscientist Dr. Chris Eliasmith at the Fields Institute on building large-scale computational models of the brain. #neuroAI #compneuro

A glimpse at what #NeuroAI brain models might enable: a topographic vision model predicts stimulation patterns that steer complex object recognition behavior in primates. This could be a key 'software' component for visual prosthetic hardware 🧠🤖🧪

Imagine a brain decoding algorithm that could generalize across different subjects and tasks. Today, we’re one step closer to achieving that vision. Introducing the flagship paper of our brain decoding program: www.biorxiv.org/content/10.1... #neuroAI #compneuro @utoronto.ca @uhn.ca

A nice application of our NeuroAI Turing Test! Check out @ithobani.bsky.social's thread for more details on comparing brains to machines!

I've been arguing that #NeuroAI should model the brain in health *and* in disease -- very excited to share a first step from Melika Honarmand: inducing dyslexia in vision-language-models via targeted perturbations of visual-word-form units (analogous to human VWFA) 🧠🤖🧪 arxiv.org/abs/2509.24597

The brain isn’t tabula rasa. Evolution has encoded strong inductive priors in our neural architectures and plasticity rules, providing structured initialization that enables efficient reinforcement learning and optimization. #neuroAI #compneuro m.youtube.com/watch?v=21EY...

Inferring learning rules during de novo task learning https://www.biorxiv.org/content/10.1101/2025.09.29.679295v1

Come be our colleague at EPFL! Several open calls for positions 🧪🧠🤖 * Neuroscience www.epfl.ch/about/workin... (deadline Oct 1) * Life Science Engineering www.epfl.ch/about/workin... * CS general call www.epfl.ch/about/workin... * Learning Sciences www.epfl.ch/about/workin...

1/6 Recent discussions (e.g. Rich Sutton on @dwarkesh.bsky.social’s podcast) have highlighted why animals are a better target for intelligence — and why scaling alone isn’t enough. In my recent @cmurobotics.bsky.social seminar talk, “Using Embodied Agents to Reverse-Engineer Natural Intelligence”,

Our lab director Dr. Laschowski sat down with UofT neuroscience students to discuss brain science, AI, and machine learning www.youtube.com/watch?v=f3wJ... @uhnresearch.ca @uhn.ca @uoft.bsky.social @drlaschowski.bsky.social #neuroAI

Interested in a #PhD in machine learning & theoretical neuroscience? Applications for 2026 entry to the Gatsby Unit PhD programme are open! 💰 Fully-funded 4-year programme 🤝 Close links to @sainsburywellcome.bsky.social ℹ️ www.ucl.ac.uk/life-sciences/gatsby/study-and-work/gatsby-unit-phd-programme

Brown’s Department of Cognitive & Psychological Sciences is hiring a tenure-track Assistant Professor, working in the area of AI and the Mind (start July 1, 2026). Apply by Nov 8, 2025 👉 apply.interfolio.com/173939 #AI #CognitiveScience #AcademicJobs #BrownUniversity

But models can readily use latent information in their context. We therefore suggest that natural intelligence solves the latent learning problem via the complementary strengths of episodic memory: reinstating experiences into context makes latent information accessible. 4/

It was an honour to give the grand rounds talk this morning in the Department of Surgery at CHU Sainte-Justine and Université de Montréal. Thank you for the invitation. #neuroAI #compneuro

Are you a graduate student in #Ukraine interested in machine learning and neuroscience? My research lab at #UofT is now accepting applications for remote thesis supervision. (1/3) #neuroAI #compneuro @vectorinstitute.ai @uoft.bsky.social @uoftcompsci.bsky.social @uhn.ca

Dr. Andres Lozano, a neurosurgeon at UHN, is leading the Canadian clinical trials of the Neuralink brain implant. He shares how the implant will allow patients with spinal cord injuries to control a computer cursor with only their thoughts. Watch: https://bit.ly/4pcjcua

Despite its efficiency, the brain is oddly inefficient: requires ~8 hours of sleep for every 16 hours of runtime. We spend a third of our lives recharging.

Our clinical trial with Neuralink is officially underway! #neuroAI #compneuro @uhn.ca