Portrait of Guillaume Dumas

Guillaume Dumas

Associate Academic Member
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

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

Master's Research - Université de Montréal
PhD - Université de Montréal
Master's Research - Université de Montréal
Principal supervisor :
PhD - Université de Montréal
Principal supervisor :
Postdoctorate - Université de Montréal

Publications

Collective decision making by embodied neural agents
Nicolas Coucke
Mary Katherine Heinrich
Axel Cleeremans
Marco Dorigo
Abstract Collective decision making using simple social interactions has been studied in many types of multiagent systems, including robot s… (see more)warms and human social networks. However, existing multiagent studies have rarely modeled the neural dynamics that underlie sensorimotor coordination in embodied biological agents. In this study, we investigated collective decisions that resulted from sensorimotor coordination among agents with simple neural dynamics. We equipped our agents with a model of minimal neural dynamics based on the coordination dynamics framework, and embedded them in an environment with a stimulus gradient. In our single-agent setup, the decision between two stimulus sources depends solely on the coordination of the agent’s neural dynamics with its environment. In our multiagent setup, that same decision also depends on the sensorimotor coordination between agents, via their simple social interactions. Our results show that the success of collective decisions depended on a balance of intra-agent, interagent, and agent–environment coupling, and we use these results to identify the influences of environmental factors on decision difficulty. More generally, our results illustrate how collective behaviors can be analyzed in terms of the neural dynamics of the participating agents. This can contribute to ongoing developments in neuro-AI and self-organized multiagent systems.
Grokking Beyond the Euclidean Norm of Model Parameters
Tikeng Notsawo Pascal Junior
Grokking refers to a delayed generalization following overfitting when optimizing artificial neural networks with gradient-based methods. I… (see more)n this work, we demonstrate that grokking can be induced by regularization, either explicit or implicit. More precisely, we show that when there exists a model with a property
Towards Multi-Brain Decoding in Autism: A Self-Supervised Learning Approach
Ghazaleh Ranjabaran
Quentin Moreau
Adrien Dubois
This study introduces a self-supervised learning (SSL) approach to hyperscanning electroencephalography (EEG) data, targeting the identifica… (see more)tion of autism spectrum condition (ASC) during social interactions. Hyperscanning enables simultaneous recording of neural activity across interacting individuals, offering a novel path for studying brain-to-brain synchrony in ASC. Leveraging a large-scale, single-brain EEG dataset for SSL pretraining, we developed a multi-brain classification model fine-tuned with hyperscanning data from dyadic interactions involving ASC and neurotypical participants. The SSL model demonstrated superior performance (78.13% accuracy) compared to supervised baselines and logistic regression using spectral EEG biomarkers. These results underscore the efficacy of SSL in addressing the challenges of limited labeled data, enhancing EEG-based diagnostic tools for ASC, and advancing research in social neuroscience.
La communication financière à l’épreuve de la crise COVID : une gestion des impressions ?
Corinne Bessieux-Ollier
Grégoire Davrinche
Nous étudions l’impact de la crise du COVID-19 sur la gestion des impressions pratiquée par les entreprises françaises cotées. Cette c… (see more)rise ayant eu un impact fort sur l’activité des entreprises, nous observons si les dirigeants modifient la manière de présenter l’information liée aux résultats non-GAAP, à travers l’utilisation de stratégies d’obscurcissement. Les données sur la gestion des impressions ont été collectées manuellement dans les communiqués de résultats annuels des entreprises du SBF 120 sur la période 2018-2020. Nous constatons une diminution générale du niveau de gestion des impressions en période de crise, notamment pour les entreprises des secteurs ayant été les plus impactés par la crise COVID. Cette diminution est toutefois moins prononcée pour les entreprises ayant sous-performé par rapport à leur secteur d’activité et pour les entreprises dont la performance a le plus diminué (indépendamment du secteur auquel elles appartiennent). Nos résultats suggèrent que les entreprises dont la baisse de performance pourrait être attribuée à des causes internes (résultats très défavorables, résultats en deçà du secteur d’activité) demeurent soucieuses de l’image qu’elles renvoient et maintiennent leur niveau de gestion des impressions malgré la crise.
A multivariable prediction model for invasive pulmonary aspergillosis in immunocompromised patients with acute respiratory failure (IPA-GRRR-OH score).
Alice Friol
Frédéric Pène
Alexandre Demoule
Achille Kouatchet
Laurent Argaud
Naike Bigé
Anne-Sophie Moreau
François Barbier
Djamel Mokart
Virginie Lemiale
Elie Azoulay
Mirror effect of genomic deletions and duplications on cognitive ability across the human cerebral cortex
Kuldeep Kumar
Sayeh Kazem
Guillaume Huguet
Thomas Renne
Worrawat Engchuan
Martineau Jean-Louis
Jakub Kopal
Zohra Saci
Omar Shanta
Bhooma Thiruvahindrapuram
Jeffrey R. MacDonald
Josephine Mollon
Laura Schultz
Emma E M Knowles
David Porteous
Gail Davies
Paul Redmond
Sarah E. Harris
Simon R. Cox
Gunter Schumann … (see 9 more)
Zdenka Pausova
Celia M. T. Greenwood
Tomas Paus
Stephen W Scherer
Laura Almasy
Jonathan Sebat
David C. Glahn
Sébastien Jacquemont
Regulation of gene expression shapes the interaction between brain networks which in-turn supports psychological processes such as cognitive… (see more) ability. How changes in level of gene expression across the cerebral cortex influence cognitive ability remains unknown. Here, we tackle this by leveraging genomic deletions and duplications - copy number variants (CNVs) that fully encompass one or more genes expressed in the human cortex - which lead to large effects on gene-expression levels. We assigned genes to 180 regions of the human cerebral cortex based on their preferential expression across the cortex computed using data from the Allen Human Brain Atlas. We aggregated CNVs in cortical regions, and ran a burden association analysis to compute the mean effect size of genes on general cognitive ability for each of the 180 regions. When affected by CNVs, most of the regional gene-sets were associated with lower cognitive ability. The spatial patterns of effect sizes across the cortex were correlated negatively between deletions and duplications. The largest effect sizes for deletions and duplications were observed for gene-sets with high expression in sensorimotor and association regions, respectively. These two opposing patterns of effect sizes were not influenced by intolerance to loss of function, demonstrating orthogonality to dosage-sensitivity scores. The same mirror patterns were also observed after stratifying genes based on cell types and developmental epochs markers. These results suggest that the effect size of gene dosage on cognitive ability follows a cortical gradient. The same brain region and corresponding gene-set may show different effects on cognition depending on whether variants increase or decrease transcription. The latter has major implications for the association of brain networks with phenotypes
Mirror effect of genomic deletions and duplications on cognitive ability across the human cerebral cortex
Kuldeep Kumar
Sayeh Kazem
Guillaume Huguet
Thomas Renne
Worrawat Engchuan
Martineau Jean-Louis
Jakub Kopal
Zohra Saci
Omar Shanta
Bhooma Thiruvahindrapuram
Jeffrey R. MacDonald
Josephine Mollon
Laura Schultz
Emma E M Knowles
David Porteous
Gail Davies
Paul Redmond
Sarah E. Harris
Simon R. Cox
Gunter Schumann … (see 9 more)
Zdenka Pausova
Celia M. T. Greenwood
Tomas Paus
Stephen W Scherer
Laura Almasy
Jonathan Sebat
David C. Glahn
Sébastien Jacquemont
Regulation of gene expression shapes the interaction between brain networks which in-turn supports psychological processes such as cognitive… (see more) ability. How changes in level of gene expression across the cerebral cortex influence cognitive ability remains unknown. Here, we tackle this by leveraging genomic deletions and duplications - copy number variants (CNVs) that fully encompass one or more genes expressed in the human cortex - which lead to large effects on gene-expression levels. We assigned genes to 180 regions of the human cerebral cortex based on their preferential expression across the cortex computed using data from the Allen Human Brain Atlas. We aggregated CNVs in cortical regions, and ran a burden association analysis to compute the mean effect size of genes on general cognitive ability for each of the 180 regions. When affected by CNVs, most of the regional gene-sets were associated with lower cognitive ability. The spatial patterns of effect sizes across the cortex were correlated negatively between deletions and duplications. The largest effect sizes for deletions and duplications were observed for gene-sets with high expression in sensorimotor and association regions, respectively. These two opposing patterns of effect sizes were not influenced by intolerance to loss of function, demonstrating orthogonality to dosage-sensitivity scores. The same mirror patterns were also observed after stratifying genes based on cell types and developmental epochs markers. These results suggest that the effect size of gene dosage on cognitive ability follows a cortical gradient. The same brain region and corresponding gene-set may show different effects on cognition depending on whether variants increase or decrease transcription. The latter has major implications for the association of brain networks with phenotypes
A video-based approach to decipher intubation decisions for the critically ill
Jean-Rémi Lavillegrand
Elie Azoulay
Changer le regard des étudiants sur les métiers de la comptabilité : Les effets de la simulation de gestion
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.
A “fine-cuts” approach disentangling psychopathic, autistic and alexithymic traits in their associations with affective, cognitive and motor empathy
Julia Ayache
Nikki Stevenson
Elisha Patel
Alexander Sumich
Nadja Heym
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
Is sharing always caring? Entropy, boundaries and the plurality of psychotherapeutic process.
Lena Adel
Ana Gómez-Carrillo
Jonas Mago
Michael Lifshitz