Join us on April 1st from 15:00 – 16:00 for our next Colloquium.
You can join on campus (DT 2203) or Zoom https://carleton-ca.zoom.us/j/96979364539
Follow this link for a complete listing of our Colloquia for Winter 2026.
Math Lab’s Dr. Mike Slipenkyj presents: Is 5 always 5? Context-dependent numerical representations in the human brain
Abstract: Humans 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. His 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.