Portrait of Guillaume Dumas

Guillaume Dumas

Associate Academic Member
guillaume.dumas@mila.quebec
Associate Professor, Université de Montréal, Department of Psychiatry and Addiction
Adjunct Professor, McGill University, Department of Psychiatry
Research Topics
Computational Biology
Computational Neuroscience
Deep Learning
Dynamical Systems
Machine Learning Theory
Medical Machine Learning
Reinforcement Learning
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Biography

Guillaume Dumas is an associate professor of computational psychiatry in the Faculty of Medicine, Université de Montréal, and principal investigator in the Precision Psychiatry and Social Physiology laboratory at the Centre hospitalier universitaire (CHU) Sainte-Justine Research Centre. He holds the IVADO professorship for AI in Mental Health, and the Fonds de recherche du Québec - Santé (FRQS) J1 in AI and Digital Health. In 2023, Dumas was recognized as a CIFAR Azrieli Global Scholar – Brain, Mind, and Consciousness program, and nominated as a Future Leader in Canadian Brain Research by the Brain Canada Foundation.

Dumas was previously a permanent researcher in neuroscience and computational biology at the Institut Pasteur (Paris). Before that, he was a postdoctoral fellow at the Center for Complex Systems and Brain Sciences (Florida Atlanta University). He holds an engineering degree in advanced engineering and computer science (École Centrale Paris), two MSc degrees (theoretical physics, Paris-Saclay University; cognitive science, ENS/EHESS/Paris 5), and a PhD in cognitive neuroscience (Sorbonne University).

The goal of his research is to cross-fertilize AI/ML, cognitive neuroscience and digital medicine through an interdisciplinary program with two main axes:

- AI/ML for Mental Health, which aims to create new algorithms to investigate the development of human cognitive architecture and deliver personalized medicine in neuropsychiatry using data from genomes to smartphones.

- Social Neuroscience for AI/ML, which translates basic brain research and dynamical systems formalism into neurocomputational and machine learning hybrid models (NeuroML) and machines with social learning abilities (Social NeuroAI & HMI).

Current Students

Saskia Helbling
Postdoctorate - Université de Montréal
saskia.helbling@mila.quebec
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Nadine Mohamed
Master's Research - Université de Montréal
nadine.mohamed@mila.quebec
Rémy Ramadour
Independent visiting researcher - CHU Sainte Justine / Université de Montréal
remy.ramadour.hsj@ssss.gouv.qc.ca
Website
Github
Mahta Ramezanian
Master's Research - Université de Montréal
Principal supervisor :
Irina Rish
mahta.ramezanian@mila.quebec
Pascal Tikeng Notsawo
PhD - Université de Montréal
Principal supervisor :
Guillaume Rabusseau
pascal.tikeng@mila.quebec
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Publications

A video-based approach to decipher intubation decisions for the critically ill
Guillaume Dumas
Jean-Rémi Lavillegrand
Elie Azoulay
2025-01-06
Intensive Care Medicine (published)
doi.org
Changer le regard des étudiants sur les métiers de la comptabilité : Les effets de la simulation de gestion
Guillaume Dumas
Yann QUÉMÉNER
La comptabilité véhicule souvent injustement, une image terne et ennuyeuse, auprès du grand public et des jeunes étudiants choisissant l… (see more)eur orientation. Dans cet article, nous questionnons l’effet de pratiques pédagogiques sur la perception par les étudiants, des soft skills attendues par les employeurs. Pour cela nous réalisons une quasi-expérimentation dans laquelle nous comparons les perceptions des étudiants selon que le cours ait été animé sous un format classique (application des connaissances par le biais d’exercices avec corrigé par l’enseignant) ou sous la forme d’une simulation de gestion (application des connaissances en vue de prendre des décisions et piloter une entreprise fictive). Les résultats de la recherche montrent qu’une simulation de gestion, plus que les travaux dirigés classiques, permettent aux primo-apprenants en comptabilité, d’avoir une meilleure perception des soft skills attendues par les praticiens et les recruteurs. Nos résultats rappellent l’importance de donner une représentation réaliste (éloignée des clichés) de la profession, afin de rendre les filières d’enseignement de la comptabilité plus attractives.
2024-12-31
Finance Contrôle Stratégie (published)
doi.org
https://www.neuromodec.org/journal/4/2/NzBlvmDpUYspQQbvI4B Online Transcranial Random Noise Stimulation of the Right Temporoparietal Junction Acutely Modulates Human-Machine Social Interactions
Vincent Chamberland
Quentin Moreau
Lisane Moses
Gabriela Milanova
Guillaume Dumas
2024-12-31
Neuromodec Journal (published)
doi.org
Performance modulations phase-locked to action depend on internal state
Tommaso Tosato
Guillaume Dumas
Gustavo Rohenkohl
Pascal Fries
Several studies have probed perceptual performance at different times after a self-paced motor action and found frequency-specific modulatio… (see more)ns of perceptual performance phase-locked to the action. Such action-related modulation has been reported for various frequencies and modulation strengths. In an attempt to establish a basic effect at the population level, we had a relatively large number of participants (n=50) perform a self-paced button press followed by a detection task at threshold, and we applied both fixed- and random-effects tests. The combined data of all trials and participants surprisingly did not show any significant action-related modulation. However, based on previous studies, we explored the possibility that such modulation depends on the participant’s internal state. Indeed, when we split trials based on performance in neighboring trials, then trials in periods of low performance showed an action-related modulation at ≈17 Hz. When we split trials based on the performance in the preceding trial, we found that trials following a “miss” showed an action-related modulation at ≈17 Hz. Finally, when we split participants based on their false-alarm rate, we found that participants with no false alarms showed an action-related modulation at ≈17 Hz. All these effects were significant in random-effects tests, supporting an inference on the population. Together, these findings indicate that action-related modulations are not always detectable. However, the results suggest that specific internal states such as lower attentional engagement and/or higher decision criterion are characterized by a modulation in the beta-frequency range.
2024-12-31
iScience (published)
doi.org
Is sharing always caring? Entropy, boundaries and the plurality of psychotherapeutic process.
Lena Adel
Ana Gómez-Carrillo
Jonas Mago
Michael Lifshitz
Guillaume Dumas
2024-12-31
Physics of Life Reviews (published)
doi.org
Decomposing the Brain in Autism: Linking Behavioral Domains to Neuroanatomical Variation and Genomic Underpinnings.
Hanna Seelemeyer
Caroline Gurr
Johanna Leyhausen
Lisa M. Berg
Charlotte M. Pretzsch
Tim Schäfer
Bassem Hermila
Christine M. Freitag
Eva Loth
Beth Oakley
Luke Mason
Jan K. Buitelaar
Christian Beckmann
Dorothea L. Floris
Tony Charman
Tobias Banaschewski
Emily Jones
Thomas Bourgeron
Jumana Ahmad
Sara Ambrosino … (see 58 more)
Bonnie Auyeung
Simon Baron-Cohen
Sarah Baumeister
Sven Bölte
Carsten Bours
Michael Brammer
Daniel Brandeis
Claudia Brogna
Yvette de Bruijn
Bhismadev Chakrabarti
Ineke Cornelissen
Daisy Crawley
Flavio Dell’Acqua
Guillaume Dumas
Sarah Durston
Christine Ecker
Jessica Faulkner
Vincent Frouin
Pilar Garcés
David Goyard
Lindsay Ham
Hannah Hayward
Joerg F. Hipp
Rosemary Holt
Mark Johnson
Emily J. H. Jones
Prantik Kundu
Meng-Chuan Lai
Xavier Liogier D’ardhuy
Michael V. Lombardo
David J. Lythgoe
René Mandl
Andre Marquand
Maarten Mennes
Andreas Meyer-Lindenberg
Carolin Moessnang
Nico Bast
Larry O’Dwyer
Marianne Oldehinkel
Bob Oranje
Gahan Pandina
Antonio Persico
Barbara Ruggeri
Declan G.M. Murphy
Amber N. V. Ruigrok
Jessica Sabet
Roberto Sacco
Antonia San José Cáceres
Emily Simonoff
Will Spooren
Julian Tillmann
Roberto Toro
Heike Tost
Jack Waldman
Steve C. R. Williams
Caroline Wooldridge
Marcel P. Zwiers
Declan Murphy
2024-11-30
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging (published)
doi.org
Effects of gene dosage on cognitive ability: A function-based association study across brain and non-brain processes
Guillaume Huguet
Thomas Renne
Cécile Poulain
Alma Dubuc
Kuldeep Kumar
Sayeh Kazem
Worrawat Engchuan
Omar Shanta
Élise Douard
Catherine Proulx
Martineau Jean-Louis
Zohra Saci
Josephine Mollon
Laura M. Schultz
Emma E.M. Knowles
Simon R. Cox
David Porteous
Gail Davies
Paul Redmond
Sarah E. Harris … (see 10 more)
Gunter Schumann
Guillaume Dumas
Aurélie Labbe
Zdenka Pausova
Tomáš Paus
Stephen W. Scherer
Jonathan Sebat
Laura Almasy
David C. Glahn
Sébastien Jacquemont
Copy-number variants (CNVs) that increase the risk for neurodevelopmental disorders also affect cognitive ability. However, such CNVs remain… (see more) challenging to study due to their scarcity, limiting our understanding of gene-dosage-sensitive biological processes linked to cognitive ability. We performed a genome-wide association study (GWAS) in 258,292 individuals, which identified—for the first time—a duplication at 2q12.3 associated with higher cognitive performance. We developed a functional-burden analysis, which tested the association between cognition and CNVs disrupting 6,502 gene sets biologically defined across tissues, cell types, and ontologies. Among those, 864 gene sets were associated with cognition, and effect sizes of deletion and duplication were negatively correlated. The latter suggested that functions across all biological processes were sensitive to either deletions (e.g., subcortical regions, postsynaptic) or duplications (e.g., cerebral cortex, presynaptic). Associations between non-brain tissues and cognition were driven partly by constrained genes, which may shed light on medical comorbidities in neurodevelopmental disorders.
2024-11-30
Cell Genomics (published)
doi.org
Exploring the interplay of clinical reasoning and artificial intelligence in psychiatry: Current insights and future directions
Christophe Gauld
Vincent P. Martin
Hugo Bottemanne
Pierre Fourneret
Jean-Arthur Micoulaud-Franchi
Guillaume Dumas
2024-11-01
Psychiatry Research (published)
doi.org
Arbitrary methodological decisions skew inter-brain synchronization estimates in hyperscanning-EEG studies
Marius Zimmermann
Kathrine Schultz-Nielsen
Guillaume Dumas
Ivana Konvalinka
Over the past decade, hyperscanning has emerged as an important methodology to study neural processes underlying human interaction using fMR… (see more)I, EEG, fNIRS, and MEG. However, many methodological decisions regarding preprocessing and analysis of hyperscanning data have not yet been standardized in the hyperscanning community, yet may affect inter-brain estimates. Here we systematically investigate the effects common methodological choices can have on estimates of phase-based inter-brain synchronization (IBS) measures, using real and simulated hyperscanning (dual) EEG data. Notably, we introduce a new method to compute circular correlation (CCorr) coefficients in IBS studies, which performs more reliably in comparison to the standard approach, showing that the conventional CCorr implementation leads to large fluctuations in IBS estimates due to fluctuations in circular mean directions. Furthermore, we demonstrate how short epoch durations (of 1 second or less) can lead to inflated IBS estimates in scenarios with no strong underlying interaction. Finally, we show how signal-to-noise ratios and temporal factors may confound IBS estimates, particularly when comparing e.g., resting states with conditions involving motor actions. For each of these investigated effects, we provide recommendations for future research employing hyperscanning-EEG techniques, aimed at increasing validity and replicability of inter-brain synchronization studies.
2024-10-31
Imaging Neuroscience (published)
doi.org
Interpersonal neural synchrony as a mechanism of therapeutic alliance? A systematic review of hyperscanning in clinical encounters
Lena Adel
Lincoln E. Moses
Elisabeth Irvine
Kyle T. Greenway
Guillaume Dumas
Michael Lifshitz
Therapeutic alliance is defined as the collaborative relationship between patient and therapist. Strong therapeutic alliances have been asso… (see more)ciated with positive clinical outcomes, but much remains unknown about alliance and its physiological basis. Interpersonal neural synchrony (INS) – the synchronization of neural signals between interacting individuals – is emerging as a novel lens for studying interactions with relatively objective and time-sensitive neuroimaging techniques. We searched four databases to identify studies of INS in clinical encounters. Our search yielded 161 articles, 46 met criteria for full-text review and 12 were included. The included articles reported INS across a total of 174 dyads, all published since 2018. Despite diverse methodologies, INS was observed in all studies and was often related to therapeutic outcomes. However, results were mixed regarding associations between INS and therapeutic alliance. These results highlight that, while promising, additional research is needed to elucidate the relationship between INS, therapeutic alliance and clinical outcomes. Future studies should aim to standardize methodologies, explore temporal dynamics (e.g., through longitudinal assessments), and include larger sample sizes.
2024-10-21
PsyArXiv (preprint)
doi.org
Introducing Brain Foundation Models
Mohammad Javad Darvishi Bayazi
Hena Ghonia
Roland Riachi
Bruno Aristimunha
Arian Khorasani
Md Rifat Arefin
Sylvain Chevallier
Amin Darabi
Guillaume Dumas
Irina Rish
Brain function represents one of the most complex systems driving our world. Decoding its signals poses significant challenges, particularly… (see more) due to the limited availability of data and the high cost of recordings. The existence of large hospital datasets and laboratory collections partially mitigates this issue. However, the lack of standardized recording protocols, varying numbers of channels, diverse setups, scenarios, and recording devices further complicate the task. This work addresses these challenges by introducing the Brain Foundation Model (BFM), a suite of open-source models trained on brain signals. These models serve as foundational tools for various types of time-series neuroimaging tasks. This work presents the first model of the BFM series, which is trained on electroencephalogram signal data. Our results demonstrate that BFM-EEG can generate signals more accurately than other models. Upon acceptance, we will release the model weights and pipeline.
2024-10-09
NeurIPS.cc/2024/Workshop/TSALM (published)
openreview.net
openreview.net
LLMs and Personalities: Inconsistencies Across Scales
Tosato Tommaso
Mahmood Hegazy
David Lemay
Mohammed Abukalam
Irina Rish
Guillaume Dumas
This study investigates the application of human psychometric assessments to large language models (LLMs) to examine their consistency and m… (see more)alleability in exhibiting personality traits. We administered the Big Five Inventory (BFI) and the Eysenck Personality Questionnaire-Revised (EPQ-R) to various LLMs across different model sizes and persona prompts. Our results reveal substantial variability in responses due to question order shuffling, challenging the notion of a stable LLM "personality." Larger models demonstrated more consistent responses, while persona prompts significantly influenced trait scores. Notably, the assistant persona led to more predictable scaling, with larger models exhibiting more socially desirable and less variable traits. In contrast, non-conventional personas displayed unpredictable behaviors, sometimes extending personality trait scores beyond the typical human range. These findings have important implications for understanding LLM behavior under different conditions and reflect on the consequences of scaling.
2024-10-08
NeurIPS.cc/2024/Workshop/Behavioral_ML (oral)
openreview.net
openreview.net