Brokoslaw Laschowski

Computational models for brain science - Microsoft Research In this talk, Dr. Laschowski will present his research on the development of new mathematical, computational, and machine learning models to reverse-engineer and/or interface with the brain. Some exam...

My talk at Microsoft Research about building computational models for brain science. Thanks for the invite!

#neuroAI #compneuro @utoronto.ca @uhn.ca @msftresearch.bsky.social www.microsoft.com/en-us/resear...

Congrats team!

Ukraine has long been a source of innovation in deep learning, beginning with Oleksii Ivakhnenko’s pioneering work on neural networks in the 1960s. Today, we’re inviting the next generation of Ukrainians to continue that legacy and help write the next chapter in artificial intelligence. APPLY TODAY!

bsky.app/profile/drla...

We're building an artificial brain to allow robots to think and control themselves. #neuroAI #compneuro

Our new study comparing neural decoding algorithms for brain-machine interfaces led by student refugees from #Ukraine

www.biorxiv.org/content/10.1...

#NeuroAI #neuroscience #AI #compneuro @uoft.bsky.social @uhnresearch.bsky.social @uhntoronto.bsky.social

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

Calling all #UofT undergraduate students in Computer Science, Psychology, Neuroscience, and Engineering!

We're still accepting applications to supervise undergraduate thesis research and course projects starting Fall 2025. #CompNeuro #NeuroAI

@utoronto.ca @uoftcompsci.bsky.social

Lots of folks cross-post. Best practice probably depends on your goals. And you’re not alone in feeling underprepared — we’re all just figuring it out.

To clarify: these projects involve building new artificial neural networks to reverse-engineer (i.e., mathematically model) the biological neural networks in the brains of older adults, both with and without neurological disorders.

If you're interested in using #AI and neural networks to study the neuroscience of aging and to model age-related neurodegenerative diseases such as Alzheimer's and Parkinson's, please reach out. We're actively pursuing research in this area.

#neuroAI #compneuro @uoftcompneuro.bsky.social

Join us July 15-16 at #UofT for the 2025 Toronto Robotics Conference. Last year, we won Best Poster Award for building a new deep constructive learning algorithm for brain-machine interfaces.

See you there! #neuroAI #compneuro @uoft.bsky.social robotics.utoronto.ca/2025-toronto...

Congrats!

Great news!

Comparative Analysis of Neural Decoding Algorithms for Brain-Machine Interfaces Accurate neural decoding of brain dynamics remains an open challenge in brain-machine interfaces. While various signal processing, feature extraction, and classification algorithms have been proposed,...

ieeexplore.ieee.org/document/110...

Looking forward to speaking at the Computational Neuroscience Summer School at Український католицький університет in #Ukraine.

#NeuroAI #CompNeuro apps.ucu.edu.ua/en/summersch...

correction: deep contrastive learning algorithm

Calling all #UofT undergraduate students in Computer Science, Psychology, Neuroscience, and Engineering!

We're still accepting applications to supervise undergraduate thesis research and course projects starting Fall 2025. #CompNeuro #NeuroAI

@utoronto.ca @uoftcompsci.bsky.social

Modeling—and thus gaining a mechanistic understanding of—how pain is represented and encoded in patterns of activity across neuronal populations in the brain can have significant implications for treatment and prevention.

#compneuro

Fascinating!!

Congrats!

We already do this in Canada for our national research funding agencies - NSERC and CIHR.

Great way to make science more accessible, help educate the general public, and maximize impact.

.... 4) neural network models of brain diseases, 5) reinforcement learning algorithms to model human motor control, and 6) mechanistic interpretability of biological and artificial neural networks.

Some potential topics: 1) brain-like deep learning models for vision and language processing, 2) neural networks with brain-inspired memory mechanisms, 3) neural decoding algorithms to predict speech and motor intent for brain-machine interfaces ....

If you're interested, please email me your resume and a sample of a research project you’ve worked on (e.g., undergraduate thesis or conference paper).

(3/3) #neuroscience #AI #neuroAI #compneuro #Ukraine

As part of this international collaboration, students will be offered a remote research position in our lab while completing their master’s or PhD studies in #Ukraine, during which we would help supervise or co-supervise your thesis research.

(2/3) #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

Does using ChatGPT change your brain activity? Study sparks debate Scientists warn against reading too much into the small experiment getting lots of buzz.

The brains of people writing an essay with ChatGPT are less engaged than those of people blocked from using any online tools for the task

https://go.nature.com/44yqUXb

Scanning for similarities between human decision-making, AI algorithm Where does the human brain even start when faced with a new task? It immediately checks with a mental library of solutions that worked pretty well in the past. A…

In a new study, Kempner associate faculty member Sam Gershman (@gershbrain.bsky.social) and collaborators found similarities between human intelligence and an AI decision-making system.

Read more in the Harvard Gazette:
news.harvard.edu/gazette/stor...

#neuroscience #AI #NeuroAI

Out today in @nature.com: we show that individual neurons have diverse tuning to a decision variable computed by the entire population, revealing a unifying geometric principle for the encoding of sensory and dynamic cognitive variables.
www.nature.com/articles/s41...