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Ian Charest

Associate Academic Member
Assistant Professor, Université de Montréal, Department of Psychology
Research Topics
Computational Neuroscience
Computer Vision
Deep Learning
Natural Language Processing

Biography

Ian Charest is a cognitive computational neuroscientist whose general research interests are high-level vision and audition.

He leads the Charest Lab at the Université de Montréal, where he and his team investigate visual recognition in the brain using neuroimaging techniques, such as magneto-electroencephalography (M-EEG) and functional magnetic resonance imaging (fMRI).

Charest’s work makes use of advanced computational modelling and analysis techniques, including machine learning, representational similarity analysis (RSA) and artificial neural networks (ANNs), to better understand human brain function.

Current topics of research in the lab include information processing in the brain during perception, memory, and visual consciousness when recognizing and interpreting natural scenes and visual objects.

The Charest lab is currently funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant to study the interaction between vision and semantics. Charest also holds a Courtois chair in cognitive and computational neuroscience, which is supporting the development of an online platform for the cross-disciplinary investigation of behavioural, computational and neuroimaging datasets.

Current Students

Publications

Re-expression of CA1 and entorhinal activity patterns preserves temporal context memory at long timescales
Futing Zou
Wanjia Guo
Emily J. Allen
Yihan Wu
Thomas Naselaris
Kendrick Kay
Brice A. Kuhl
J. Benjamin Hutchinson
Sarah DuBrow
Converging, cross-species evidence indicates that memory for time is supported by hippocampal area CA1 and entorhinal cortex. However, limit… (see more)ed evidence characterizes how these regions preserve temporal memories over long timescales (e.g., months). At long timescales, memoranda may be encountered in multiple temporal contexts, potentially creating interference. Here, using 7T fMRI, we measured CA1 and entorhinal activity patterns as human participants viewed thousands of natural scene images distributed, and repeated, across many months. We show that memory for an image’s original temporal context was predicted by the degree to which CA1/entorhinal activity patterns from the first encounter with an image were re-expressed during re-encounters occurring minutes to months later. Critically, temporal memory signals were dissociable from predictors of recognition confidence, which were carried by distinct medial temporal lobe expressions. These findings suggest that CA1 and entorhinal cortex preserve temporal memories across long timescales by coding for and reinstating temporal context information.
Researcher perspectives on ethics considerations in epigenetics: an international survey
Charles Dupras
Terese Knoppers
Nicole Palmour
Elisabeth Beauchamp
Stamatina Liosi
Reiner Siebert
Alison May Berner
Stephan Beck
Yann Joly
Sleep spindles track cortical learning patterns for memory consolidation
Marit Petzka
Alex Chatburn
George M. Balanos
Bernhard P. Staresina
Sleep spindles track cortical learning patterns for memory consolidation
Marit Petzka
Alex Chatburn
G. Balanos
Bernhard P Staresina