Brokoslaw Laschowski
Computational Neuroscientist. Building machine learning models to reverse-engineer the brain and human intelligence. Assistant Professor @UofT and Research Scientist @UHN
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- Our mission: build a computational brain. Follow @compneurolab.bsky.social for updates. #neuroAI #compneuro @utoronto.ca @uoftcompsci.bsky.social @kbi-uhn.bsky.social @vectorinstitute.ai
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- Reposted by Brokoslaw LaschowskiA new and improved version of TheoryCoder, which learns to play video games in a human-like way by synthesizing both high-level abstractions and a low-level model of game mechanics: arxiv.org/abs/2602.00929
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- Reposted by Brokoslaw LaschowskiNew paper from our lab on the behavioral significance of high-dimensional neural representations!
- Human visual cortex representations may be much higher-dimensional than earlier work suggested, but are these higher dimensions of cortical activity actually relevant to behavior? Our new paper tackles this by studying how different people experience the same movies. 🧵 www.cell.com/current-biol...
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- Reposted by Brokoslaw LaschowskiVoxelwise Encoding Models do some things differently from other GLM-related methods because the roots of VEM are in neurophysiology, not psychology. This 2006 paper describes system identification for neurophysiology. Change "neurons" to "voxels" and it all still applies. tinyurl.com/wu-etal-2006
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[This post could not be retrieved] - Reposted by Brokoslaw LaschowskiNew paper with @deanpospisil.bsky.social , in which we introduce a new estimator for the "signal eigenspectrum" (i.e., the eigenvalues of the noiseless population responses). We re-analyze data from Stringer et al 2019 and show eigenvalues of mouse V1 are well explained by a broken power.
- New paper out at PNAS: www.pnas.org/doi/10.1073/... Revisiting the high-dimensional geometry of population responses in the visual cortex with @jpillowtime.bsky.social. The review took forever because a reviewer was doubtful our new estimator can infer eigenvalues beyond the rank of the data! (1/6)
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- Reposted by Brokoslaw LaschowskiHow do people compute a sense of confidence? This question is usually addressed using very simple images because we don't know how complex stimuli are represented internally. In a new paper, we addressed this question using artificial neural networks (ANNs). journals.plos.org/ploscompbiol...
- Reposted by Brokoslaw LaschowskiMore than you would expect from studying AI and less than you would expect from studying neurobiology.
- "How much of the brain's learned algorithms depend on the fact it is a brain?" arxiv.org/abs/2601.02063 The brain is a neural network, but also a biological organ (unlike artificial neural networks). How much does this matter to cognition?
- Reposted by Brokoslaw LaschowskiShould you go to academia or industry for research in AI or cognitive science? It's the most common question I get asked by PhD students, and I've written up some of my thoughts on the answer, as an epilogue to my research-focused series on these fields: infinitefaculty.substack.com/p/on-researc...
- Reposted by Brokoslaw LaschowskiGoing to #AAAI2026? Join us at the “Neuro for AI & AI for Neuro: Towards Multi-Modal Natural Intelligence” workshop! Co-organized by our own Anton Arkhipov and @shixnya.bsky.social 🔗 neuroai-multimodal-workshop.github.io @aaai.org
- Reposted by Brokoslaw Laschowski📢 Applications open on 19 Jan for the 7-week #Mathematics #SummerSchool in London. You will develop the maths skills and intuition necessary to enter the #TheoreticalNeuroscience / #MachineLearning field. Find out more & register for the information webinar 👉 www.ucl.ac.uk/life-science...
- Reposted by Brokoslaw LaschowskiNature research paper: Predictive coding of reward in the hippocampus go.nature.com/49mB13V
- Join us March 20 at the University of Toronto for a special seminar by Dr. Sergey Stavisky on brain–computer interfaces. #neuroAI @utoronto.ca @uoftcompsci.bsky.social @uhn.ca @kbi-uhn.bsky.social robotics.utoronto.ca/event/roboti...
- The Centre for Theoretical Neuroscience at the University of Waterloo (my alma mater) is hosting its annual summer school on neuromorphic computing. Application deadline is January 15. #neuroscience #AI #neuroAI @uwaterloo.ca www.nengo.ai/summer-school/
- Reposted by Brokoslaw LaschowskiExcited 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.
- Reposted by Brokoslaw LaschowskiWith some trepidation, I'm putting this out into the world: gershmanlab.com/textbook.html It's a textbook called Computational Foundations of Cognitive Neuroscience, which I wrote for my class. My hope is that this will be a living document, continuously improved as I get feedback.
- Reposted by Brokoslaw LaschowskiWhen we learn complex tasks, we chunk them into sub-tasks that our brains orchestrate into action sequences. How we do this is not entirely understood. This work explores how to learn and internally control temporally abstracted sub-tasks in RL/AI with sequence models. arxiv.org/abs/2512.20605
- Reposted by Brokoslaw LaschowskiPublished @cp-trendscognsci.bsky.social with @drewlinsley.bsky.social & @tonyfeng.bsky.social: As vision models scale to human/superhuman accuracy, they’re becoming worse models of primate vision—benchmark engineering isn’t neuroscience. @carneyinstitute.bsky.social @browncopsy.bsky.social
- Reposted by Brokoslaw LaschowskiMove over ReLU 🚀 Meet **ReSU** (Rectified Spectral Unit): a biologically inspired, self-supervised unit for learning from dynamical data. A backprop-free multilayer ReSU network learns predictive features and recapitulates *Drosophila* vision. To appear at AAAI: arxiv.org/abs/2512.23146
- Reposted by Brokoslaw LaschowskiCheck out our new work on motor learning across multiple brain regions!
- 🧠 New year, new preprint! Why does motor learning involve multiple brain regions? We propose that the cortico-cerebellar system learns a "map" of actions where similar movements are nearby, while basal ganglia do RL in this simplified space. www.biorxiv.org/content/10.6...
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- Training the neural network: epoch 1 #neuroscience #neuroAI
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- Reposted by Brokoslaw LaschowskiInterested in the latest advances in neuroscience (neural dynamics and internal models) and how they can be leveraged to build smarter, adaptive AI? ➡️ My first real solo piece 🖤🫶 @natneuro.nature.com rdcu.be/eWVmA
- Living in Canada is a constant reminder that visual intelligence is a challenging machine learning problem. #neuroscience #AI
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- Reposted by Brokoslaw LaschowskiOnline Now: Better artificial intelligence does not mean better models of biology
- 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
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- Reposted by Brokoslaw LaschowskiWhy 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
- Reposted by Brokoslaw LaschowskiPrediction: 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:
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- Reposted by Brokoslaw LaschowskiHopkins Cog Sci is hiring! We have two open faculty positions: one in vision, and one language. Please repost!
- We are seeking candidates for two tenured/tenure-track faculty positions: One in high-level vision, written language and/or conceptual representation apply.interfolio.com/178825 One in language apply.interfolio.com/178813 Please help us spread the word!
- Reposted by Brokoslaw LaschowskiDimensionality 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
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- Office view at #UofT
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- Reposted by Brokoslaw Laschowski🎉 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 👇
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- Reposted by Brokoslaw LaschowskiThe 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...
- Reposted by Brokoslaw LaschowskiImagine 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
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- Reposted by Brokoslaw LaschowskiHonored 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!
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