Brokoslaw Laschowski
@drlaschowski.bsky.social
Neuroscientist. Building computational models to study intelligence in brains and machines. Assistant Professor @UofT and Research Scientist @UHN
https://kite-uhn.com/scientist/brokoslaw-laschowski
https://kite-uhn.com/scientist/brokoslaw-laschowski
Pinned
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
Introducing the flagship paper of our brain decoding program: www.biorxiv.org/content/10.1...
#neuroAI #compneuro @utoronto.ca @uhn.ca
Reposted by Brokoslaw Laschowski
New 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...
High-dimensional structure underlying individual differences in naturalistic visual experience
Han and Bonner reveal that individual visual experience arises from high-dimensional
neural geometry distributed across multiple representational scales. By characterizing
the full dimensional spectru...
www.cell.com
January 30, 2026 at 6:57 PM
New paper from our lab on the behavioral significance of high-dimensional neural representations!
Reposted by Brokoslaw Laschowski
While AI systems have advanced tremendously, they still lag behind real brains in reliability & efficiency. A new computational unit developed at #FlatironCCN could help close that gap: https://www.simonsfoundation.org/biological-brains-inspire-a-new-building-block-for-artificial-neural-networks
Biological Brains Inspire a New Building Block for Artificial Neural Networks
Biological Brains Inspire a New Building Block for Artificial Neural Networks on Simons Foundation
www.simonsfoundation.org
January 27, 2026 at 10:35 PM
While AI systems have advanced tremendously, they still lag behind real brains in reliability & efficiency. A new computational unit developed at #FlatironCCN could help close that gap: https://www.simonsfoundation.org/biological-brains-inspire-a-new-building-block-for-artificial-neural-networks
Reposted by Brokoslaw Laschowski
Voxelwise 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
tinyurl.com/wu-etal-2006
(PDF) Complete functional characterization of sensory neurons by system identification
PDF | System identification is a growing approach to sensory neurophysiology that facilitates the development of quantitative functional models of... | Find, read and cite all the research you need on...
tinyurl.com
January 29, 2026 at 2:41 AM
Voxelwise 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
tinyurl.com/wu-etal-2006
Reposted by Brokoslaw Laschowski
🚨 #CCN2026 Proceedings submissions are open!
CCN 2026 again features an 8-page Proceedings track (alongside extended abstracts). Accepted papers will appear in CCN-Proceedings (CCN‑P) with DOIs on OpenReview.
CCN 2026 again features an 8-page Proceedings track (alongside extended abstracts). Accepted papers will appear in CCN-Proceedings (CCN‑P) with DOIs on OpenReview.
January 28, 2026 at 4:16 PM
🚨 #CCN2026 Proceedings submissions are open!
CCN 2026 again features an 8-page Proceedings track (alongside extended abstracts). Accepted papers will appear in CCN-Proceedings (CCN‑P) with DOIs on OpenReview.
CCN 2026 again features an 8-page Proceedings track (alongside extended abstracts). Accepted papers will appear in CCN-Proceedings (CCN‑P) with DOIs on OpenReview.
Reposted by Brokoslaw Laschowski
New 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)
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)
PNAS
Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...
www.pnas.org
January 28, 2026 at 7:39 AM
New 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.
Reposted by Brokoslaw Laschowski
January 27, 2026 at 2:55 PM
Reposted by Brokoslaw Laschowski
Looking forward to presenting at the #AAAI #NeuroAI workshop; including 3 projects that were just accepted to ICLR! arxiv.org/abs/2509.24597, arxiv.org/abs/2510.03684, arxiv.org/abs/2506.13331 🧪🧠🤖
January 27, 2026 at 6:24 AM
Looking forward to presenting at the #AAAI #NeuroAI workshop; including 3 projects that were just accepted to ICLR! arxiv.org/abs/2509.24597, arxiv.org/abs/2510.03684, arxiv.org/abs/2506.13331 🧪🧠🤖
Reposted by Brokoslaw Laschowski
You have less than a week to apply for the Summer Workshop on the Dynamic Brain in the gorgeous San Juan Islands!
Apply by February 1 to be considered for this 2-week residential course and deepen your data analysis and computational skills.
🔗 https://bit.ly/4samKOZ
Apply by February 1 to be considered for this 2-week residential course and deepen your data analysis and computational skills.
🔗 https://bit.ly/4samKOZ
Summer Workshop on the Dynamic Brain 2026
The Summer Workshop on the Dynamic Brain is an intensive, project-based residential course with a focus on the neurobiology of sensory processing, coding, and neural population dynamics.
alleninstitute.org
January 25, 2026 at 5:26 PM
You have less than a week to apply for the Summer Workshop on the Dynamic Brain in the gorgeous San Juan Islands!
Apply by February 1 to be considered for this 2-week residential course and deepen your data analysis and computational skills.
🔗 https://bit.ly/4samKOZ
Apply by February 1 to be considered for this 2-week residential course and deepen your data analysis and computational skills.
🔗 https://bit.ly/4samKOZ
Reposted by Brokoslaw Laschowski
How 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...
journals.plos.org/ploscompbiol...
Using artificial neural networks to reveal the human confidence computation
Author summary Human decisions are accompanied by a sense of confidence which reflects the decision accuracy. Conventionally, human confidence has been studied using two-choice tasks with simple stimu...
journals.plos.org
January 26, 2026 at 7:18 PM
How 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...
journals.plos.org/ploscompbiol...
Reposted by Brokoslaw Laschowski
More 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?
January 25, 2026 at 3:17 PM
More than you would expect from studying AI and less than you would expect from studying neurobiology.
Reposted by Brokoslaw Laschowski
Should 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...
On research careers in academia and industry
The epilogue to a series on Cognitive Science and AI
infinitefaculty.substack.com
January 23, 2026 at 3:13 PM
Should 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 Laschowski
Going 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
🔗 https://neuroai-multimodal-workshop.github.io/
@aaai.org
Co-organized by our own Anton Arkhipov and @shixnya.bsky.social
🔗 https://neuroai-multimodal-workshop.github.io/
@aaai.org
December 17, 2025 at 5:47 PM
Going 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
🔗 https://neuroai-multimodal-workshop.github.io/
@aaai.org
Co-organized by our own Anton Arkhipov and @shixnya.bsky.social
🔗 https://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...
Find out more & register for the information webinar 👉 www.ucl.ac.uk/life-science...
January 15, 2026 at 2:37 PM
📢 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...
Find out more & register for the information webinar 👉 www.ucl.ac.uk/life-science...
Reposted by Brokoslaw Laschowski
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...
#neuroAI @utoronto.ca @uoftcompsci.bsky.social @uhn.ca @kbi-uhn.bsky.social robotics.utoronto.ca/event/roboti...
January 18, 2026 at 10:43 AM
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...
#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/
#neuroscience #AI #neuroAI @uwaterloo.ca www.nengo.ai/summer-school/
January 12, 2026 at 4:50 PM
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/
#neuroscience #AI #neuroAI @uwaterloo.ca www.nengo.ai/summer-school/
Reposted by Brokoslaw Laschowski
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.
December 18, 2025 at 3:59 PM
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.
Reposted by Brokoslaw Laschowski
With 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.
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.
January 9, 2026 at 1:27 AM
With 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.
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 Laschowski
When 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
Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning
Large-scale autoregressive models pretrained on next-token prediction and finetuned with reinforcement learning (RL) have achieved unprecedented success on many problem domains. During RL, these model...
arxiv.org
January 6, 2026 at 4:19 PM
When 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 Laschowski
Published @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
Better artificial intelligence does not mean better models of biology
Deep neural networks (DNNs) once showed increasing alignment with primate perception
as they improved on vision benchmarks, raising hopes that advances in artificial intelligence
(AI) would naturally ...
cell.com
January 5, 2026 at 3:33 PM
Published @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 Laschowski
Move 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
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
A Network of Biologically Inspired Rectified Spectral Units (ReSUs) Learns Hierarchical Features Without Error Backpropagation
We introduce a biologically inspired, multilayer neural architecture composed of Rectified Spectral Units (ReSUs). Each ReSU projects a recent window of its input history onto a canonical direction ob...
arxiv.org
January 1, 2026 at 4:27 PM
Move 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
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 Laschowski
Check 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...
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...
January 5, 2026 at 5:00 PM
Check out our new work on motor learning across multiple brain regions!
Reposted by Brokoslaw Laschowski
What can cognitive science learn from AI? In infinitefaculty.substack.com/p/what-cogni... I outline how AI has found that scale and richness of learning experiences fundamentally change learning & generalization — and how I believe we should rethink cognitive experiments & theories in response.
What cognitive science can learn from AI
#3 in a series on cognitive science and AI
infinitefaculty.substack.com
January 5, 2026 at 6:10 PM
What can cognitive science learn from AI? In infinitefaculty.substack.com/p/what-cogni... I outline how AI has found that scale and richness of learning experiences fundamentally change learning & generalization — and how I believe we should rethink cognitive experiments & theories in response.
Reposted by Brokoslaw Laschowski
What if robots could imagine their next move? 🤯✨
Researchers at the #KempnerInstitute led by @yilundu.bsky.social have built a #foundationmodel that gives robots visual imagination—changing how they learn to move.
🔗 Blog: bit.ly/4qftkCM | 📰 News: bit.ly/49FCHWf
Researchers at the #KempnerInstitute led by @yilundu.bsky.social have built a #foundationmodel that gives robots visual imagination—changing how they learn to move.
🔗 Blog: bit.ly/4qftkCM | 📰 News: bit.ly/49FCHWf
Large Video Planner: A New Foundation Model for General-Purpose Robots - Kempner Institute
Recent progress in AI has been driven by foundation models trained on internet-scale data. This has inspired a new wave of “robot foundation models” aimed at solving generalization, but such […]
bit.ly
January 5, 2026 at 9:11 PM
What if robots could imagine their next move? 🤯✨
Researchers at the #KempnerInstitute led by @yilundu.bsky.social have built a #foundationmodel that gives robots visual imagination—changing how they learn to move.
🔗 Blog: bit.ly/4qftkCM | 📰 News: bit.ly/49FCHWf
Researchers at the #KempnerInstitute led by @yilundu.bsky.social have built a #foundationmodel that gives robots visual imagination—changing how they learn to move.
🔗 Blog: bit.ly/4qftkCM | 📰 News: bit.ly/49FCHWf
Reposted by Brokoslaw Laschowski
Founded in 2021, @yale.edu's Wu Tsai Institute 🏢 is advancing human neuroscience research by connecting cutting-edge neuroimaging, computation, and behavioral science to uncover how brain networks give rise to cognition 🧠
Read More 👇
news.yale.edu/2025/12/05/w...
Read More 👇
news.yale.edu/2025/12/05/w...
Wu Tsai Institute: Making the right connections
With state-of-the-art research facilities and collaborative spaces, Yale’s Wu Tsai Institute is on a mission to understand human cognition by bridging academic disciplines.
news.yale.edu
January 5, 2026 at 1:43 PM
Founded in 2021, @yale.edu's Wu Tsai Institute 🏢 is advancing human neuroscience research by connecting cutting-edge neuroimaging, computation, and behavioral science to uncover how brain networks give rise to cognition 🧠
Read More 👇
news.yale.edu/2025/12/05/w...
Read More 👇
news.yale.edu/2025/12/05/w...