Portrait de Guillaume Dumas

Guillaume Dumas

Membre académique associé
guillaume.dumas@mila.quebec
Professeur agrégé, Université de Montréal, Département de psychiatrie et d’addictologie
Professeur adjoint, McGill University, Département de psychiatrie
Sujets de recherche
Apprentissage automatique médical
Apprentissage par renforcement
Apprentissage profond
Biologie computationnelle
Neurosciences computationnelles
Systèmes dynamiques
Théorie de l'apprentissage automatique
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Biographie

Guillaume Dumas est professeur agrégé de psychiatrie computationnelle à la Faculté de médecine de l'Université de Montréal et chercheur principal du laboratoire de psychiatrie de précision et de physiologie sociale du Centre de recherche du CHU Sainte-Justine. Il est titulaire de la chaire IVADO IA en santé mentale et chercheur-boursier junior 1 du Fonds de recherche du Québec - Santé (FRQS) dans le domaine de l’ IA en santé et de la santé numérique. En 2023, il a été retenu dans le cadre du Programme des chercheurs mondiaux CIFAR-Azrieli pour le programme de recherche Cerveau, esprit et conscience. Il a également été nommé parmi les Futurs leaders canadiens de la recherche sur le cerveau par la Fondation Brain Canada.

Il a auparavant été chercheur permanent en neurosciences et en biologie computationnelle à l'Institut Pasteur (Paris, France), ainsi que chercheur postdoctoral au Center for Complex Systems and Brain Sciences à l’Université Florida Atlantic (FAU), aux États-Unis. Il est titulaire d'un diplôme d'ingénieur en ingénierie avancée et informatique (École centrale Paris), de deux masters (physique théorique, Université Paris-Saclay; sciences cognitives, ENS/EHESS/Paris 5) et d'un doctorat en neurosciences cognitives (Sorbonne Université).

Ses recherches visent à combiner l’intelligence artificielle, les neurosciences cognitives et la médecine numérique à travers un programme interdisciplinaire suivant deux axes principaux :

- L’intelligence artificielle en santé mentale, par la création de nouveaux algorithmes pour étudier le développement de l'architecture cognitive humaine et pour fournir une médecine personnalisée en neuropsychiatrie grâce à des données allant du génome à celles des téléphones intelligents;

- Les neurosciences sociales en intelligence artificielle, par la traduction de la recherche fondamentale sur le cerveau et le formalisme des systèmes dynamiques en des modèles hybrides neurocomputationnels et d’apprentissage automatique (NeuroML) et de nouvelles architectures présentant des capacités d'apprentissage social (NeuroIA Sociale et IHM).

Étudiants actuels

Saskia Helbling
Postdoctorat - UdeM
saskia.helbling@mila.quebec
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Nadine Mohamed
Maîtrise recherche - UdeM
nadine.mohamed@mila.quebec
Rémy Ramadour
Visiteur de recherche indépendant - CHU Sainte Justine / Université de Montréal
remy.ramadour.hsj@ssss.gouv.qc.ca
Site web
Github
Mahta Ramezanian
Maîtrise recherche - UdeM
Superviseur⋅e principal⋅e :
Irina Rish
mahta.ramezanian@mila.quebec
Pascal Tikeng Notsawo
Doctorat - UdeM
Superviseur⋅e principal⋅e :
Guillaume Rabusseau
pascal.tikeng@mila.quebec
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Github
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Publications

Social interactions between people of same and different generations shape longitudinal changes in interpersonal neural synchrony, loneliness, and social connection
Ryssa Moffat
Guillaume Dumas
Emily S. Cross
Loneliness is globally acknowledged as a severe and burgeoning health risk, fueling interest in helping people of all ages form meaningful s… (voir plus)ocial connections. One promising approach consists of intergenerational social programs. While behavioral and qualitative evidence derived from such programs promise health and wellbeing benefits, the physiological consequences of repeated intergenerational encounters remain unknown. Insight into physiological changes will shed light on the mechanisms of social connection. We charted longitudinal changes in interpersonal neural synchrony (INS) in 31 intergenerational (older/younger adult) and 30 same-generation (younger adult) dyads across a six-session creative drawing program. At each session, dyads completed self-report measures, drew together and alone, and had their cortical activation recorded with fNIRS. In both groups, INS was greater while dyads drew together than alone. Across sessions, intergenerational dyads' INS decreased and same-generation dyads' INS increased. INS in RIFG~RTPJ and RIFG~RIFG were predictive of loneliness levels and feelings of social closeness, respectively. This exploratory longitudinal research reinforces the multi-faceted nature of INS dynamics as social connections are forged.
2026-08-19
PLOS Biology (publié)
doi.org
Tuning in together: LSD enhances inter-brain synchrony and felt connectedness in romantic couples
Natasha L. Mason
Artur Czeszumski
Iva Totomanova
Filip Trbusek
Mauro Cavarra
Steph Ashton
Stefan Toennes
Eef Theunissen
Johannes Reckweg
P. L. Lockwood
Marieke DeWitte
Katrin Preller
Kim Kuypers
Guillaume Dumas
Pablo Mallaroni
Jan Ramaekers
Abstract Social connection is fundamental to human wellbeing. Serotonergic psychedelics such as lysergic acid diethylamide (LSD) acutely hei… (voir plus)ghten subjective connectedness, yet their effects on real-time social connection remain poorly understood. Using EEG hyperscanning in a randomized, double-blind, placebo-controlled crossover study, we recorded neural activity simultaneously from both members of healthy romantic couples (N=25) who received LSD (50 μg) or placebo together, across resting and interactive states. LSD increased subjective connectedness, including feelings of love, closeness, trust, and being “in sync,” while reducing loneliness, compared to placebo. This affiliative shift dissociated from the drug’s pharmacokinetic time-course, remaining elevated as subjective intensity and plasma concentration declined. In parallel, LSD increased inter-brain synchrony during shared rest, carried specifically by theta-band amplitude-envelope coupling. Importantly, this effect survived two complementary controls. First, it exceeded coupling between unrelated individuals and second the effects depended on contemporaneous neural alignment rather than shared drug-induced dynamics. Exploratory analyses showed that romantic partners with greater resting synchrony reported greater feelings of connectedness. These findings provide the first evidence that a psychedelic enhances brain-to-brain coupling between people, linking a pharmacologically induced state of felt connection to a measurable signature shared across interacting brains.
2026-08-17
bioRxiv (prépublication)
doi.org
Determinants of functional burden pleiotropy and gene dosage responses across human traits
Sayeh Kazem
Kuldeep Kumar
Jane Yang
Florian Benitiere
Guillaume Huguet
Josephine Mollon
Thomas Renne
Laura M. Schultz
Emma E.M. Knowles
Worrawat Engchuan
Omar Shanta
Bhooma Thiruvahindrapuram
Jeffrey R. MacDonald
Celia M. T. Greenwood
Stephen W. Scherer
Laura Almasy
Jonathan Sebat
David C. Glahn
Guillaume Dumas
Sébastien Jacquemont
Pleiotropic and monotonic effects of gene dosage are central to understanding comorbidities in developmental pediatric and psychiatric disor… (voir plus)ders, yet the underlying biological processes are not well characterized. Here we develop a functional burden analysis to investigate the association of all protein-coding copy-number variants, genome-wide, with 43 complex traits in approximately 500,000 UK Biobank participants. We test variant associations disrupting 172 tissue or cell-type gene sets, finding associations for all traits, which we replicate in the All of Us cohort. Functional burden pleiotropy, defined as the number of traits significantly associated with a gene set, correlates with genetic constraint and is higher for brain than non-brain functions, even after normalizing for genetic constraint. Levels of pleiotropy, measured by burden correlation, are similar in deletions and loss-of-function single-nucleotide variants, and higher than in common variants and duplications. Most gene dosage responses are non-monotonic, with deletions and duplications showing same-direction effects, and monotonic responses decrease with genetic constraint. We observe associations between functional gene sets and traits for either deletions or duplications, but rarely both, with negatively correlated effect sizes. Together, these results link genetic constraint and brain-specific mechanisms to the whole-body multimorbidity of neurodevelopmental and psychiatric conditions. Gene dosage can help explain comorbidities in developmental pediatric and psychiatric disorders. Here, the authors map how rare copy-number variants disrupting tissue and cell-type gene sets shape 43 human traits.
2026-08-13
Nature Communications (publié)
doi.org
Recent progress of large-scale biomarker consortia and paths forward in biomarker development for autism
Jason W. Griffin
Brianna Cairney
William E. Carson, IV
Lacey Chetcuti
Adrien E.E. Dubois
Guillaume Dumas
Sébastien Jacquemont
Shafali Jeste
Jacob P. Momsen
Adam J. Naples
James C. McPartland
2026-07-31
Biological Psychiatry (publié)
doi.org
Enhancing Psychiatry Training Using an Agentic AI Simulated Consultation Tool: Prospective Cohort Study
Alice Rueda
Huda F Al-Shamali
Zack Cote
Niloy Roy
Reinhard Janssen‐Aguilar
Jithin Joseph
Bazen Gashaw Teferra
Mohammad Amin Kamaleddin
Lisa Burback
Olga Winkler
Bill Kapralos
Andrei Torres
Divya Sharma
Sridhar Krishnan
Guillaume Dumas
Andrew J. Greenshaw
Alexandre Hudon
Sanjeev Sockalingam
Yanbo Zhang
Adam Dubrowski … (voir 1 de plus)
Venkat Bhat
Background: Canadian psychiatry residents must demonstrate consultation competency, assessed using the standardized assessment of a clinical… (voir plus) encounter report (STACER). However, opportunities to practice these skills and receive constructive assessment remain limited in clinical settings. Objective: This study aimed to evaluate the technical feasibility of an agentic AI system designed to support psychiatry residents' consultation competence through simulated patient encounters with a patient agent and structured feedback from a rater agent. Methods: We conducted a two-phase technical feasibility prospective single-arm cohort study of the STACER Agentic System, a large language model-based platform integrating a patient agent and a rater agent. Phase 1 involved automated evaluation of the patient agent using a psychiatrist agent across 227 synthetic major depressive disorder cases. Performance was assessed using DeepEval metrics (correctness, clarity, medical faithfulness, turn relevance, and role adherence) with descriptive statistics and 95% CIs. Phase 2 involved a preliminary user study with 14 convenience-sampled participants: a total of 5 members of the clinical research team and 9 psychiatry residents from the University of Alberta. Participants completed simulated diagnostic interviews and case presentations. Performance was evaluated using STACER-based scoring by the rater agent and 2 psychiatrists. Interrater reliability was assessed using intraclass correlation coefficients (α=.05). Participants rated realism, behavioral consistency, psychiatric nuance, and feedback utility using Likert scales and free-text answers. Results: The patient agent demonstrated high behavioral (51/56, 91.07%) and symptom fidelity (105/110, 95.45%), with strong automated performance (medical faithfulness mean 0.99, 95% CI 0.99-1.00; turn relevance 0.99, 95% CI 0.986-0.992). Participants rated simulations as psychiatrically plausible and diagnostically useful, particularly for depressive symptom representation, although rapport building was moderate (mean 2.78, SD 1.56 to mean 3.00, SD 1.41, out of 5.00) due to limited nonverbal cues. The rater agent generated structured STACER-aligned feedback with high intrarater consistency, especially at the section subtotal level. Interrater reliability with psychiatrists was poor at the item level (intraclass correlation coefficient range=0.25-0.49) but improved to good-to-excellent agreement at the section level for psychiatry resident sessions (intraclass correlation coefficient range=0.89-0.93). The rater agent's scores fell between those of the 2 psychiatrists for the clinical research team and were lower than both human raters for psychiatry residents. Conclusions: The STACER Agentic System demonstrates the technical feasibility of using agentic AI to simulate psychiatric consultations and deliver STACER-aligned formative feedback. By combining adaptive multiturn psychiatric simulation with competency-based evaluation, it shows promise in supporting cognitive aspects of consultation, though it remains limited in facilitating relational skills such as rapport building. These findings suggest agentic AI could expand scalable, low-risk opportunities for deliberate practice and formative feedback in competency-based psychiatric education. Further controlled studies are needed to evaluate educational effectiveness and integration into residency training.
2026-07-20
JMIR Medical Education (publié)
doi.org
Tetradic Dynamics of Dyadic Sensorimotor Coordination: A Multiscale EEG Hyperscanning Study
Emmanuel Olarewaju
Lena Palaniyappan
Guillaume Dumas
How do leader and follower roles shape the brain mechanisms that support coordinated action between people? This question has direct therape… (voir plus)utic relevance for conditions such as schizophrenia and autism spectrum disorder, where the capacity for reciprocal social coordination is a defining vulnerability. Here, we propose a tetradic framework and examine sensorimotor coordination in 16 healthy adult pairs using simultaneous dual-brain EEG hyperscanning, a 2 x 2 within-subject design crossing Role (Leader/Follower) and Condition (Mirroring/Matching). Mirroring required resonance with a partner's movement; Matching required its controlled transformation. This contrast was designed to dissociate automatic from controlled coordination processes across roles. Behaviourally, Mirroring produced a reaction-time advantage that was selective to Followers, a finding replicated in a combined cohort, and consistent with role-dependent attention-inhibition gating. At the neural level, sustained (tonic) activity was dominated by Matching-related frontoparietal engagement regardless of role, while time-resolved (phasic) activity revealed a Mirroring-dominant reorganization that differentiated into role-specific patterns: anticipatory gating in Leaders and post-response inhibitory rebound in Followers. Information-theoretic decomposition of inter-brain coupling identified a Leader-specific predictive signal in medial prefrontal and cingulate cortices, a Follower-specific adaptive signal across sensorimotor and temporal regions, and a shared redundancy scaffold in orbitofrontal and insular cortices. These findings characterize tetradic coordination within dyads as a multiscale, role-asymmetric architecture in which top-down predictive control and bottom-up adaptive regulation are functionally dissociable. The tetradic framework provides an organizing scaffold for this dissociation, and the role-specific signatures it reveals offer candidate biomarkers for clinical populations in whom interpersonal coordination is disrupted.
2026-06-24
bioRxiv (prépublication)
doi.org
Coordinating speech and body during conversation: an at-home study with 4-year-olds
Chantal-Valerie Lee
Guillaume Dumas
Ahmed Jérôme Romain
Simone Falk
2026-05-25
International Conference on Speech Prosody (publié)
doi.org
Copy number variants reveal divergent genetic and diagnostic cortical signatures across psychiatric disorders
Kuldeep Kumar
Zhijie Liao
Jakub Kopal
Clara Moreau
Christopher Ching
Claudia Modenato
Will Snyder
Sayeh Kazem
Charles-Olivier Martin
Anne-Marie Bélanger
Valerie Fontaine
Khadije Jizi
Guillaume Huguet
Rune Boen
Leila Kushan
Ana Silva
Marianne van den Bree
David Linden
Michael Owen
Jeremy Hall … (voir 14 de plus)
Sarah Lippé
Guillaume Dumas
Bodgan Draganski
Laura Almasy
Sophia Thomopoulos
Neda Jahanshad
Ida Sønderby
Ole Andreassen
David Glahn
Armin Raznahan
Carrie Bearden
Tomáš Paus
Paul Thompson
Sébastien Jacquemont
2026-05-05
Research Square (accepté)
doi.org
SCEIMA: Social Coordination Evaluation through Integrated Model Analysis
Bavo Van Kerrebroeck
Caroline Palmėr
Guillaume Dumas
Alexander P. Demos
Computational models are increasingly used as interactive partners in studies of human coordination, yet it remains unclear whether observed… (voir plus) differences in human behavior reflect properties of the models themselves, changes in human behavior elicited by such artificial partners, or both. We introduce SCEIMA (Social Coordination Evaluation through Integrated Model Analysis), a two-stage framework designed to disentangle human-specific, model-specific, and interaction-driven contributions to coordination in human–machine interaction paradigms. In the empirical stage, human participants perform a coordination task with both human partners and computational models, establishing reference human–human and human–model interaction patterns. In the analytical stage, the same models are paired with one another and optimized through simulations to reproduce empirical coordination metrics. Comparing human–human, human–model, and simulated model–model interactions reveals whether coordination differences arise from intrinsic model dynamics, from human adaptation to artificial partners, or from their interaction. SCEIMA treats computational models as contrastive instruments whose capacity to elicit and reproduce human behavior can be systematically evaluated. We illustrate the framework with two distinct case-studies, a sensorimotor synchronization task and a conversational turn-taking task, showing how distinct outcome patterns diagnose the sources of coordination differences. By providing a principled methodological framework for evaluating interactive computational models, SCEIMA improves interpretability in human–machine interaction research and informs the design of artificial agents that coordinate with humans more naturally and responsively.
2026-04-30
Computers in Human Behavior Reports (publié)
doi.org
Additional file 1 of Beta power as a neural correlate of sensory features in autistic individuals
J. Chaudet
Julien Pichot
Amandine Pedoux
Mathis Fleury
Anna Maruani
Valérie Vantalon
Elise Humeau
Thomas Bourgeron
Josselin Houenou
Guillaume Dumas
Edouard Duchesnay
Richard Delorme
Anton Iftimovici
Aline Lefebvre
Supplementary Material 1.
2026-03-17
Figshare (inconnu)
doi.org
Beta power as a neural correlate of sensory features in autistic individuals
Julie Chaudet
Julien Pichot
Amandine Pedoux
Mathis Fleury
Anna Maruani
Valérie Vantalon
Elise Humeau
Thomas Bourgeron
Josselin Houenou
Guillaume Dumas
Edouard Duchesnay
Richard Delorme
Anton Iftimovici
Aline Lefebvre
2026-03-17
Journal of Neurodevelopmental Disorders (publié)
doi.org
Theta Dual-Brain Stimulation of rTPJ Shapes Joint Agency
Yuto Kurihara
Ayaka Tsuchiya
Guillaume Dumas
Rieko Osu
Summary Joint agency, the shared feeling of “we are doing this together”, has been linked to inter-brain synchrony, but its causal role … (voir plus)in shaping this experience remains unclear. We applied dual transcranial alternating current stimulation (dual-tACS) over the right temporo-parietal junction (rTPJ) to 13 dyads performing an alternating tapping task (target ITI = 0.5 s; 180 deg. relative phase), manipulating in- and anti-phase coupling at theta (6 Hz), alpha (10 Hz), and beta (20 Hz). As a result, tapping in the theta anti-phase condition was significantly slower than the memorized reference tempo, whereas the other stimulation conditions did not influence the inter-tap interval. Meanwhile, the relative phase remained close to 180 deg. across all conditions. In the theta condition, anti-phase stimulation produced significantly lower joint agency than in-phase stimulation. Furthermore, mediation analysis suggested that the inter-tap interval may partially account for the effect of theta dual-brain stimulation on joint agency, although this indirect pathway did not reach statistical significance. These findings suggest that anti-phase theta stimulation over the rTPJ lowers joint agency, possibly by reducing coordination efficiency while preserving the overall 180 deg. alternation structure.
2026-03-11
bioRxiv (prépublication)
doi.org