Students presented original research and attendees got to learn about the work happening in the department. Awesome job to all our presenters and organizers!

Follow this link to view the Abstracts, posters and more.

According to Nico, “The goal of this event was to give a space for students of the brain-related fields to come together and build something to show their skills. We intentionally designed this hackathon to award evidence-based design decisions and research-backed projects. This was our core philosophy”.

Congratulations to the winners, and many thanks to Nico and Natalia, theirÌýteam of volunteers, the ÐÓ°ÉÔ­´´ Science Student Society (SciSoc), the School of Computer Science, as well as the judges: Professors Mary Kelly, Kasia Muldner, Nadiya Slobodenyuk (from Cog Sci), Nadine Mocadieh (from Comp Sci), as well as Cog Sci PhD student Nadine Charanek.

Finally, a special thank you to one of Cog Sci’s PhD graduates, Francis Jeanson of the Ontario Brain Institute, for his extremely generous sponsorship of the event.

2026 Cognitive Science Student Conference

]]> /cognitivescience/2026/colloquium-on-march-25th-is-a-lab-showcase-featuring-the-childrens-representational-development-lab/?utm_source=rss&utm_medium=rss&utm_campaign=colloquium-on-march-25th-is-a-lab-showcase-featuring-the-childrens-representational-development-lab Thu, 19 Mar 2026 12:14:10 +0000 /cognitivescience/?p=16988 Join us on March 25th from 15:00 – 16:00 for our next Colloquium.
You can join on campus (DT 2203) or Zoom

Follow this link for a complete listing of our Colloquia for Winter 2026.

The Children’s Representational Development Lab investigates multiple areas of children’s development, including saving ability, knowledge acquisition, and moral cognition.

Deepthi Kamawar

Deepthi is the Director of the Children’s Representational Development Lab. She is a full professor in the Department of Cognitive Science and Psychology. She received her B.Sc. in Cognitive Science and her PhD in Psychology (at the Centre for applied Cognitive Science) at the University of Toronto. She is currently the PI for an NSERC Discovery Grant investigating young children’s Future-Oriented Cognition, with a focus on Saving. Her other research interests include the development of Executive Function and Moral Cognition.

Follow this link for a complete listing of our Colloquia for Winter 2026.

Convergence Across the Bands of CognitionÌý with Dr. Christian Lebiere of Carnegie Mellon University, will join via Zoom

Human cognition involves processes and phenomena taking place at scales ranging across orders of magnitude in time and complexity that Allen Newell called the bands of cognition. He proposed the concept of cognitive architecture as a theoretical framework for integrating cognitive mechanisms across task domains and scales of activity. In this talk, I present evidence that this approach has enabled convergence within and across the bands of cognition. A variety of cognitive architectures, developed in distinct disciplines including cognitive psychology and artificial intelligence, have converged in the cognitive band onto a consensus framework called the Common Model of Cognition. Going down to the neural band, the structure of this framework and its cognitive mechanisms have been validated using neuroimaging data. Functionally, this mapping enables the development of neuro-symbolic architectures that combine the strengths of neural learning and generalization and symbolic representations and inference. Going up to the rational band, bounded rationality is enabled by reflecting the statistical regularities of the environment in the design of the cognitive mechanisms. However, systematic deviations from rationality known as cognitive biases emerge from the interaction of knowledge and processing limitations of cognitive architectures. Further up into the social band, integrating large groups of interacting cognitive agents enables the emergence of social and organizational behavior.

Christian Lebiere is a Research Professor in the Psychology Department at Carnegie Mellon University. He received his Ph.D. from the CMU School of Computer Science where he studied connectionist models and was the co-developer of the Cascade-Correlation neural network deep learning algorithm. Since 1991, he has worked on the development of the ACT-R cognitive architecture and was co-author of the 1998 book The Atomic Components of Thought. Most recently he has been involved with the specification of the Common Model of Cognition, a community-wide effort to consolidate and formalize the scientific progress resulting from the 50-year research program in cognitive architectures. He is a founding member of the Biologically Inspired Cognitive Architectures Society, of the International Conference on Cognitive Modeling, and of the Journal of Artificial General Intelligence. His main research interests are cognitive architectures and their applications to psychology, artificial intelligence, human-computer interaction, decision making, network science, cognitive robotics and human-machine teaming.

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ÐÓ°ÉÔ­´´ University researchers urge the province to introduce universal early numeracy screening for students, similar to what we do for reading. Published Feb 20, 2026.

Follow this link for a complete listing of our Colloquia for Winter 2026.

Studying the development of predictive language comprehension using a naturalistic EEG paradigm
Featuring Professor Jesse Snedeker

Prof. Jesse Snedeker is a cognitive scientist at Harvard University who investigates how humans create, acquire, comprehend, and produce language. Her research spans fromÌýinfancy through adulthood, examining both typical development and special populations including international adoptees, users of emergent sign languages and people with autism spectrum disorders. Using diverse methods, including eye-tracking and EEG, her lab explores fundamental questions about how language conveys meaning. Her work emphasizes methodological simplicity while addressing complex theoretical questions about linguistic representation and development.

Comprehension in adults is incremental, interactive and predictive. Not only do we interpret speech and text in light of top-down constraints, we also make predictions about upcoming lexical items before a word begins. For about 25 years, my lab has been exploring spoken language comprehension in 4- to 6-year-old children, who have considerable language experience but limited literacy. In our early work, we found that children’s syntactic processing was both incremental and interactive, but curiously impervious to top-down information. Recent work in my lab uses EEG to study lexical processing using a naturalistic listening task (the Storytime Paradigm). Our findings demonstrate that young children use top-down constraints to make form-based lexical predictions. Predictive skill improves with age and with linguistic knowledge (as measured by vocabulary). This raises several questions. Why do syntactic and lexical processes show such different trajectories? How does prediction shape language learning and early literacy? When does lexical prediction first emerge?

ÌýThe central aim of the conference is to provide a venue for students in cognitive scienceÌý– atÌýtheÌýMaster’sÌýand Ph.D. level, as well as undergraduateÌýstudents completingÌýa thesis or project– toÌýpresent and receive feedback on their work, and to interact with each other in a friendly, supportive, and inclusive environment.ÌýÌý

Abstract submission deadline is February 28, 2026.

For complete details, follow this link.