Ian Charest

Associate Academic Member

ian.charest@mila.quebec

Assistant Professor, Université de Montréal, Department of Psychology

Research Topics

Computational Neuroscience

Computer Vision

Deep Learning

Natural Language Processing

Website

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

Peter Brotherwood Brotherwood

PhD - Université de Montréal

Co-supervisor :

Shahab Bakhtiari

p.brotherwood@outlook.com

Master's Research - Université de Montréal

morteza.mahdiani@umontreal.ca

Website

Google Scholar

Publications

SHINIER: An open-source Python package for controlling low-level image properties

Mathias Salvas-Hébert

Nicolas Dupuis-Roy

Catherine Landry

Ian Charest

Frédéric Gosselin

2026-08-31

SoftwareX (published)

doi.org

Representations in vision and language converge in a shared, multidimensional space of perceived similarities

Katerina M. Simkova

Adrien Doerig

Clayton Hickey

Ian Charest

Humans can effortlessly describe what they see, yet establishing a shared representational format between vision and language remains a sign… (see more)ificant challenge. Emerging evidence suggests that human brain representations in both vision and language are well predicted by semantic feature spaces obtained from large language models (LLMs). This raises the possibility that sensory systems converge in their inherent ability to transform their inputs onto shared, embedding-like representational space. However, it remains unclear how such a space manifests in human behavior. To investigate this, 63 participants performed behavioral similarity judgments separately on 100 natural scene images and 100 corresponding sentence captions from the Natural Scenes Dataset. We found that visual and linguistic similarity judgments not only converge at the behavioral level but also predict a remarkably similar network of functional magnetic resonance imaging brain responses evoked by viewing the natural scene images. Furthermore, computational models trained to map images onto LLM-embeddings outperformed both category-trained and AlexNet controls in predicting the behavioral similarity structure. These findings demonstrate that human visual and linguistic similarity judgments are grounded in a shared, modality-agnostic representational structure that mirrors how the visual system encodes experience. The convergence between sensory and artificial systems observed here suggests a common capacity of how conceptual representations are formed-not as arbitrary products of first order, modality-specific input, but as structured representations that reflect the stable, relational properties of the external world.

2026-05-19

Journal of Vision (published)

doi.org

Partitioning Signal and Noise (PSN): A modality-general denoising technique for neural responses

Jacob S. Prince

Heiko H. Schütt

Dora Hermes

Greta Tuckute

Ian Charest

Peter Brotherwood

David G. C. Hildebrand

Michael J. Tarr

George A. Alvarez

Talia Konkle

Kendrick Kay

Large-scale neural datasets typically contain only a few repeated trials per stimulus, resulting in substantial residual noise even after tr… (see more)ial averaging. This noise limits our ability to characterize neural tuning, assess representational geometry, and evaluate computational models. We introduce Partitioning Signal and Noise (PSN), a low-rank denoising method applicable to any repeated-trial dataset. Unlike standard PCA, which retains dimensions with high total variance and therefore conflates signal with noise, PSN uses a generative model to explicitly estimate the signal and noise covariance structure of the data. This enables low-rank reconstruction that targets signal-rich dimensions while suppressing noise-dominated ones. Applied to human fMRI data from the Natural Scenes Dataset, PSN substantially improves voxel reliability, stability of ROI tuning profiles and representational geometry, and encoding model performance relative to both trial averaging and PCA denoising. Because PSN can operate on any repeated-trial data matrix, it extends naturally to intracranial EEG, scalp EEG, electrophysiology, and calcium imaging, suggesting its utility as a general-purpose tool for improving signal fidelity across neural recording modalities.

2026-05-13

Cognitive Computational Neuroscience (poster)

openreview.net

A French Canadian adaptation and validation of the Vividness of Visual Imagery Questionnaire and Plymouth Sensory Imagery Questionnaire.

Catherine Landry

Laurence Lessard

Jeffrey Saint-Louis

Frédéric Gosselin

Ian Charest

Vincent Taschereau-Dumouchel

Guillaume T. Vallet

Mental imagery plays a central role in various cognitive processes and is increasingly investigated in cognitive science. Yet standardized t… (see more)ools for its assessment in French-speaking populations remain scarce. This study examined the psychometric properties of two widely used self-report instruments of mental imagery within the French Canadian population: the Vividness of Visual Imagery Questionnaire (VVIQ) and the Plymouth Sensory Imagery Questionnaire (Psi-Q)-here termed VVIQ-Québec (QC) and Psiq-QC. A total of 328 adults completed the VVIQ-QC and Psiq-QC, with a randomly selected subsample (n = 73) repeating the assessment 1 month later. Exploratory factor analysis of the VVIQ-QC (eyes-open) revealed, as in the original VVIQ, distinct factors corresponding to each prompt cluster (i.e., relative, sunrise, landscape, and storefront). The Psiq-QC yielded a six-factor solution after excluding the Body modality, diverging from the original seven-factor model. Both instruments showed strong internal consistency, temporal stability, and convergent validity. No significant effects of age, sex, or education were observed on imagery scores. These findings provide the first validated French Canadian versions of the VVIQ and Psi-Q, available via the Open Science Framework at https://osf.io/wuhja, offering reliable tools for both research and clinical applications. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

2025-12-14

Canadian Journal of Experimental Psychology / Revue canadienne de psychologie expérimentale (published)

doi.org

Neural activity resolved in space and time through fusion of large-scale EEG and fMRI datasets.

Ian Charest

Peter Brotherwood

Mathias Salvas-Hébert

Kendrick Kay

Frédéric Gosselin

2025-07-14

Journal of Vision (published)

doi.org

A Python Toolbox for Representational Similarity Analysis

Jasper JF van den Bosch

Tal Golan

Benjamin Peters

JohnMark Taylor

Mahdiyar Shahbazi

Baihan Lin

Ian Charest

Jörn Diedrichsen

Nikolaus Kriegeskorte

Marieke Mur

Heiko H. Schütt

2025-05-26

bioRxiv (preprint)

doi.org

What makes a theory of consciousness unscientific?

IIT-Concerned

Derek H. Arnold

Mark G. Baxter

Tristan A. Bekinschtein

Yoshua Bengio

James W. Bisley

Jacob Browning

Dean V. Buonomano

David Carmel

Marisa Carrasco

Peter Carruthers

Olivia Carter

Dorita H. F. Chang

Ian Charest

Mouslim Cherkaoui

Axel Cleeremans

Michael A. Cohen

Philip R. Corlett

Kalina Christoff

Sam Cumming … (see 80 more)

Cody A. Cushing

Beatrice de Gelder

Felipe De Brigard

Daniel C. Dennett

Nadine Dijkstra

Adrien Doerig

Paul E. Dux

Stephen M. Fleming

Keith Frankish

Chris Frith

Sarah Garfinkel

Melvyn A. Goodale

Jacqueline Gottlieb

Jake R. Hanson

Ran R. Hassin

Michael H. Herzog

Cecilia Heyes

Po‐Jang Hsieh

Shao‐Min Hung

Robert W. Kentridge

Tomas Knapen

Nikos Konstantinou

Konrad P. Kording

Timo L. Kvamme

Sze Chai Kwok

Renzo C. Lanfranco

Hakwan Lau

Joseph E. LeDoux

Alan Lee

Camilo Libedinsky

Matthew D. Lieberman

Ying-Tung Lin

Kayuet Liu

Maro G. Machizawa

Julio Martínez-Trujillo

Janet Metcalfe

Matthias Michel

Kenneth D. Miller

Partha P. Mitra

Dean Mobbs

Robert M. Mok

Jorge Morales

Myrto Mylopoulos

Brian Odegaard

Charles C.-F. Or

Adrian M. Owen

David Pereplyotchik

Franco Pestilli

Megan A. K. Peters

Ian Phillips

Rosanne L. Rademaker

Dobromir Rahnev

Geraint Rees

Dario L. Ringach

Adina L. Roskies

Daniela Schiller

Aaron Schurger

D. Samuel Schwarzkopf

R. B. Y. Scott

Aaron R. Seitz

Joshua Shepherd

Juha Silvanto

Heleen A. Slagter

Barry Smith

Guillermo Solovey

David Soto

Hugo J. Spiers

Timo Stein

Vincent Taschereau‐Dumouchel

Frank Tong

Peter U. Tse

Jonas Vibell

Sebastian Watzl

Taylor W. Webb

Josh Weisberg

Thalia Wheatley

Michał Wierzchoń

Martijn E. Wokke

Karen Yan

Michał Klincewicz

2025-03-09

Nature Neuroscience (unknown)

doi.org

Meeting and Missing Minds: Children and Adults Use Alignment of Intuitions to Solve Pure Coordination Games

Daniel Perez-Zapata

Xavia McKenzie-Smart

Ian Charest

Ian Apperly

In pure coordination games players seek to coordinate responses with one another without communicating. Without a logically correct response… (see more), success depends upon players intuiting a response that is mutually obvious. Previous work suggests that such coordination requires a distinctive form of “group” thinking and sufficient mutual knowledge, but reveals little about the basis for the intuitive judgements themselves. Here, that question was addressed for the first time by examining the basis of coordination performance of groups whose intuitions might plausibly differ: children versus adults. Twenty-five 5-year-olds, 30 7-year-olds, and 25 adults undertook four types of coordination game, and novel metrics allowed “intuitive alignment” in responses to be evaluated within- and between-groups. All groups performed above chance, and adults showed higher levels of alignment than children, but adults and children showed different patterns in their intuitions. Implications for intergenerational understanding and mis-understanding are discussed.

2025-01-22

Journal of Cognitive Psychology (published)

doi.org

Paper Quality Assessment based on Individual Wisdom Metrics from Open Peer Review

Andrii Zahorodnii

Jasper van den Bosch

Ian Charest

Christopher Summerfield

Ila Rani Fiete

This study proposes a data-driven framework for enhancing the accuracy and efficiency of scientific peer review through an open, bottom-up p… (see more)rocess that estimates reviewer quality. Traditional closed peer review systems, while essential for quality control, are often slow, costly, and subject to biases that can impede scientific progress. Here, we introduce a method that evaluates individual reviewer reliability by quantifying agreement with community consensus scores and applying Bayesian weighting to refine paper quality assessments. We analyze open peer review data from two major scientific conferences, and demonstrate that reviewer-specific quality scores significantly improve the reliability of paper quality estimation. Perhaps surprisingly, we find that reviewer quality scores are unrelated to authorship quality. Our model incorporates incentive structures to recognize high-quality reviewers and encourage broader coverage of submitted papers, thereby mitigating the common "rich-get-richer" pitfall of social media. These findings suggest that open peer review, with mechanisms for estimating and incentivizing reviewer quality, offers a scalable and equitable alternative for scientific publishing, with potential to enhance the speed, fairness, and transparency of the peer review process.

2025-01-21

ArXiv (preprint)

doi.org

arxiv.org

Reconstructing Spatio-Temporal Trajectories of Visual Object Memories in the Human Brain

Julia Lifanov

Benjamin J. Griffiths

Juan Linde-Domingo

Catarina S. Ferreira

Martin Wilson

Stephen D. Mayhew

Ian Charest