Lab Showcase: The ACE Lab

The mission of the Advanced Cognitive Engineering laboratory is to discover and apply fundamental principles of human perception and cognition to research and design issues in the aviation industry

Featuring: Dr. Chris Herdman, Dr. Kathleen Van Bentham, ÌýEmily Larkin, Amanda Clarkson, Lexy St. Pierre, Chloé Lachance-Soulard, Tal Friedman, Ashlyne Rayne, Sadia Naureen, Tamara Mendizabal and Lindsay McCauley.

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

Math Lab’s Dr. Mike Slipenkyj presents:ÌýIs 5 always 5? Context-dependent numerical representations in the human brain

Abstract:ÌýHumans use numbers in many parts of everyday life, from estimating the number of people in a checkout line to calculating the discount a coupon will offer. Understanding how numbers are acquired, stored, and accessed in the brain is important for theories of cognitive development and may have important implications for how we should teach numbers and mathematics. Prior work has focused primarily on isolating and characterizing numerical representations. However, numbers can be used in multiple ways. As such, the way that numbers are represented in the brain may depend on the context of use. In this talk, I will discuss the results of two lines of recent research using functional neuroimaging techniques demonstrating: 1) that the computational context in which numbers (and newly learned abstract symbols) are used can alter the way the brain represents them, and 2) that different contexts of number can be more (and less) related to doing mathematics in the brain. Combined, this work suggests that numerical representations are context-dependent, and that a more holistic view may be needed to fully understand how numbers are coded in the human brain. These findings offer important implications for how we evaluate the utility of neural representations in both theory and practice.

Bio: Mike is a postdoctoral fellow in the Math Lab. He works in the AIM research centre, as well as on the EMA and DEMA.

Mike’s research investigates how factors such as the learning environment, computational context, and individual differences influence numerical acquisition and processing. Mike is also interested in advanced statistical techniques and leveraging large datasets to inform education and policy. ÌýHis main research interests are number and math learning, neural representation of numbers, and order processing. Outside of research, Mike enjoys playing board games, watching movies, and reading science fiction.

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

Generative World Models and Behaviour with Thomas Parr, via Zoom

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Thomas Parr is a theoretical neurobiologist and practising physician. He completed his undergraduate medical studies and PhD at University College London, where he worked with Professor Karl Friston at the Wellcome Centre for Human Neuroimaging in Queen Square. He is interested in how our brains model our environments, and how these models become dysfunctional in neurological disease. He is an author of the first comprehensive textbook on Active Inference—an approach to understanding brain and behaviour from first principles. He currently works as an NIHR Academic Clinical Fellow in Neurology at the Nuffield Department of Clinical Neurosciences (University of Oxford) and the John Radcliffe Hospital.

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Abstract:ÌýOur brains model our world through synthesising sensory data with prior beliefs—arising from our personal and evolutionary histories. This idea underwrites Bayesian brain theories, which have been highly influential in explaining perceptual experience. One can take this idea further and understand the challenge of modelling the world as one that can be solved both by optimising perception and by acting to ensure our sensory data are compatible with our model of how the world should be. This talk provides an overview of this idea, known as active inference, motivating the core ideas from a simple physical system, unpacking the consequences for how we understand neuroanatomy, behaviour, and neurological pathologies. Ultimately, active inference offers a theoretical neurobiology under which one’s generative world model governs the structure and function of their nervous system.

How Marin Made Number: A Case Study of a Toddler’s Bilingual Number Word Learning
WithÌýDr. Rebecca Merkley

Parents’ records of their infants’ language development and behaviour changes over time, known as ‘baby diaries’, were common in early cognitive development research.ÌýÌýPiaget famously based his seminal work on observations of his own children. We conducted a diary study of the development of my daughter, Marin’s, English and French number word usage between 18 and 49 months. Data sources include diary entries of observations, video recordings of some instances of number word usage, and several structured, standard cognitive development assessments administered by trained graduate students. Marin accurately used number words to denote exact quantities in informal settings earlier than she was able to demonstrate reliable performance on standard assessments.

In this talk, Rebecca will discuss how this project has influenced some of our recent research in the Math Lab, and show several cute videos of my kid.

Bio: Rebecca Merkley is an Assistant Professor of Cognitive Science at ÐÓ°ÉÔ­´´ University in Ottawa, Canada. She studies early childhood cognitive development and education, with a focus on mathematics learning.

Words don’t just mean things-they do things to the brain. Join us on January 28th for this Lab Showcase.

L-Neuro Lab (PI Dr. Olessia Jouravlev) studies how the brain transforms sounds and symbols into meaning, and why this transformation differs across people and languages.

Using behavioural experiments together with neuroimaging methods such as EEG/ERP and NIRS, we examine language as a living neural process-shaped by experience, emotion, social context, and speakers’ trait profiles. Our work spans bilingual and monolingual speakers, typical and atypical language systems, and everyday as well as emotionally charged language, with the goal of understanding why the same words can resonate so differently across minds.

Join us on January 21st 15:00-16:00 for our next Cognitive Science Colloquium.
You can join on campus (DT 2203) or ZoomÌý()

This Lab Showcase will feature the Math Lab.ÌýPresenters: Dr. Jo-Anne LeFevre, Dr. Rebecca Merkley, Dr. Mike Slipenkyj,
Ayushi Chitranshi, Taeko Bourque, Liza Kahwaji, Sarah Kelly, Leah Marshall and Kyla Allan.

The Math Lab conducts research into the cognitive processes involved in numerical and mathematical abilities. Their researchÌýprojects are designed to study different aspects of mathematical cognition including its development across different ages and cultures. TheyÌýstudy basic cognitive processes and numeracy skills such as the retrieval and representation of mathematical knowledge and the application of that knowledge to real-world situations.

Hear from Math Lab co-directors Dr. Jo-Anne LeFevre and Dr. Rebecca Merkley, as well as post-doctoral fellow Dr. Mike Slipenkyj, research coordinator Ayushi Chitranshi. Math Lab students Taeko Bourque, Liza Kahwaji, Sarah Kelly, Leah Marshall and Kyla Allan will also present on their research.

Speaker will be on Zoom:

Abstract: More than 30 years ago, the developmental trajectory of how children learn the meaning of one, two, and three was characterized: Children go through the protracted process of learning the meaning of these first three, sometimes four, number words, one by one, over 2 to 3 years. Then, they learn the principles of counting, which allows them to represent all natural numbers. The trajectory of number word learning has been replicated across several labs and many countries. Yet, a limiting factor is that most studies have been conducted with English-speaking, middle-to-upper-middle-class, typically developing children. This narrow sampling challenges the universality of this developmental pathway. Examining children with diverse neurocognitive profiles can offer unique insight into how specific impaired abilities may disrupt numerical development.Ìý

Generative artificial intelligence (GenAI) can improve one’s scientific output in terms of quality and speed. In this talk, Dr. Jim Davies will discuss some current GenAI tools and how to use them effectively and responsibly, without hindering learning or violating research ethics. The talk will be targeted at graduate students but faculty will also find it useful.

Everyone is welcome and you can join on campus (DT 2203) or Zoom ()