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
Website
Google Scholar
LinkedIn
X

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

Juan David Vargas
Master's Research - Université de Montréal
Kastel Natalie
PhD - Université de Montréal
Mahta Ramezanian
Master's Research - Université de Montréal
Principal supervisor :
Irina Rish
Zahra Sheikhbahaee
Postdoctorate - Université de Montréal
Co-supervisor :
Irina Rish
Github
Pascal Tikeng Notsawo
PhD - Université de Montréal
Principal supervisor :
Guillaume Rabusseau
Website
Github
Google Scholar
Tommaso Tosato
Postdoctorate - Université de Montréal
Website
Github
Google Scholar

Publications

Going beyond the means: Exploring the role of bias from digital determinants of health in technologies
Marie-Laure Charpignon
Adrien Carrel
Yihang Jiang
Teddy Kwaga
Beatriz Cantada
Terry Hyslop
Christopher E. Cox
Krista Haines
Valencia Koomson
Guillaume Dumas
Michael Morley
Jessilyn Dunn
An-Kwok Ian Wong
2023-10-01
PLOS Digital Health (published)
doi.org
W56. UNRAVELING THE IMPACT OF GENOMIC VARIATIONS ON COGNITIVE ABILITY ACROSS THE HUMAN CORTEX: INSIGHTS FROM GENE EXPRESSION AND COPY NUMBER VARIANTS
Kuldeep Kumar
Sayeh Kazem
Guillaume Huguet
Thomas Renne
Bank Engchuan
Omar Shanta
Bhooma Thiruvahindrapuram
J. MacDonald
Marieke Klein
Stephen W Scherer
Laura Almasy
Jonathan Sebat
David C. Glahn
Guillaume Dumas
Sébastien Jacquemont
2023-10-01
European Neuropsychopharmacology (published)
doi.org
Disorganized Communication and Social Dysfunction in Schizophrenia: Emerging Concepts and Methods
Emmanuel Olarewaju
Guillaume Dumas
L. Palaniyappan
2023-09-23
Current Psychiatry Reports (published)
doi.org
WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series
Jean-Christophe Gagnon-Audet
Kartik Ahuja
Mohammad Javad Darvishi Bayazi
Pooneh Mousavi
Guillaume Dumas
Irina Rish
2023-09-01
TMLR (accepted)
openreview.net
openreview.net
Subcortical Brain Alterations in Carriers of Genomic Copy Number Variants.
Kuldeep Kumar
Claudia Modenato
Clara A. Moreau
Christopher R. K. Ching
C. Ching
Annabelle Harvey
Sandra Martin-Brevet
Guillaume Huguet
Martineau Jean-Louis
Elise Douard
Charles-Olivier Martin
C.O. Martin
Nadine Younis
Petra Tamer
Anne M. Maillard
Borja Rodriguez-Herreros
Aurélie Pain
Sonia Richetin
Leila Kushan
Dmitry Isaev … (see 26 more)
Kathryn Alpert
Anjani Ragothaman
Jessica A. Turner
Wei Wang
T. Ho
Tiffany C. Ho
Lianne Schmaal
Ana I. Silva
Marianne B.M. van den Bree
V. Marianne
David E.J. Linden
M. J. Owen
Marie Owen
Jeremy Hall
Sarah Lippé
Guillaume Dumas
Bogdan Draganski
Boris A. Gutman
Ida E. Sønderby
Ole A. Andreassen
Laura Schultz
Laura Almasy
David C. Glahn
Carrie E. Bearden
Paul M. Thompson
Sébastien Jacquemont
OBJECTIVE Copy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disord… (see more)ers (NPDs), including autism (ASD) and schizophrenia. Little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, the authors investigated gross volume, vertex-level thickness, and surface maps of subcortical structures in 11 CNVs and six NPDs. METHODS Subcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (CNVs at 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2; age range, 6-80 years; 340 males) and 782 control subjects (age range, 6-80 years; 387 males) as well as ENIGMA summary statistics for ASD, schizophrenia, attention deficit hyperactivity disorder, obsessive-compulsive disorder, bipolar disorder, and major depression. RESULTS All CNVs showed alterations in at least one subcortical measure. Each structure was affected by at least two CNVs, and the hippocampus and amygdala were affected by five. Shape analyses detected subregional alterations that were averaged out in volume analyses. A common latent dimension was identified, characterized by opposing effects on the hippocampus/amygdala and putamen/pallidum, across CNVs and across NPDs. Effect sizes of CNVs on subcortical volume, thickness, and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and schizophrenia. CONCLUSIONS The findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions, as well distinct effects, with some CNVs clustering with adult-onset conditions and others with ASD. These findings provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD and why a single CNV increases the risk for a diverse set of NPDs.
2023-07-12
American Journal of Psychiatry (published)
doi.org
Cortico-Cerebellar neurodynamics during social interaction in Autism Spectrum Disorders
Fleur Gaudfernau
Aline Lefebvre
Denis-Alexander Engemann
Amandine Pedoux
Anna Bánki
Florence Baillin
Benjamin Landman
Frederique Amsellem
Anna Maruani
Thomas Bourgeron
Richard Delorme
Guillaume Dumas
2023-06-28
NeuroImage : Clinical (published)
doi.org
Attention Schema in Neural Agents
Dianbo Liu
Samuele Bolotta
Mike He Zhu
Yoshua Bengio
Guillaume Dumas
Attention has become a common ingredient in deep learning architectures. It adds a dynamical selection of information on top of the static s… (see more)election of information supported by weights. In the same way, we can imagine a higher-order informational filter built on top of attention: an Attention Schema (AS), namely, a descriptive and predictive model of attention. In cognitive neuroscience, Attention Schema Theory (AST) supports this idea of distinguishing attention from AS. A strong prediction of this theory is that an agent can use its own AS to also infer the states of other agents' attention and consequently enhance coordination with other agents. As such, multi-agent reinforcement learning would be an ideal setting to experimentally test the validity of AST. We explore different ways in which attention and AS interact with each other. Our preliminary results indicate that agents that implement the AS as a recurrent internal control achieve the best performance. In general, these exploratory experiments suggest that equipping artificial agents with a model of attention can enhance their social intelligence.
2023-05-27
ArXiv (preprint)
doi.org
arxiv.org
Distinct Social Behavior and Inter-Brain Connectivity in Dyads with autistic individuals
Quentin Moreau
Florence Brun
Anaël Ayrolles
Jacqueline Nadel
Guillaume Dumas
2023-05-01
bioRxiv (preprint)
doi.org
Tri-process model of interpersonal mindfulness: theoretical framework and study protocol
Bassam Khoury
Viktoriya Manova
Lena Adel
Guillaume Dumas
Michael Lifshitz
Rodrigo C. Vergara
Harmehr Sekhon
Soham Rej
According to the Center for Disease Control and Prevention, over 14% of the US population practice mindfulness meditation. The effects of mi… (see more)ndfulness training on physical and mental health have been consistently documented, but its effects on interpersonal relationships are not yet fully understood or investigated. Interpersonal relationships play a crucial role in the wellbeing of individuals and society, and therefore, warrants further study. The aim of this paper is to present a tri-process theoretical model of interpersonal mindfulness and a study protocol to validate the proposed model. Specifically, according to the proposed model, mindfulness meditation training increases the self-awareness, self-regulation, and prosociality of those receiving the training, which ameliorates the quality of interpersonal interactions and the socioemotional support provided to other individuals. Finally, better socioemotional support increases the support receiver’s ability to regulate their emotions. Using a multiphasic longitudinal design involving 640 participants randomized into 480 dyads, the proposed protocol aims to validate the tri-process model and to investigate its mechanisms of actions. The proposed study has important theoretical and social implications and will allow devising new and more effective interpersonal mindfulness programs with applications in multiple fields.
2023-04-26
Frontiers in Psychology (published)
doi.org
Genesis, modelling and methodological remedies to autism heterogeneity
Juliette Rabot
Eya‐mist Rødgaard
Ridha Joober
Guillaume Dumas
Danilo Bzdok
Boris C Bernhardt
Sébastien Jacquemont
Laurent Mottron
2023-04-01
Neuroscience and Biobehavioral Reviews (published)
doi.org
Cross-sectional and longitudinal neuroanatomical profiles of distinct clinical (adaptive) outcomes in autism
Charlotte M. Pretzsch
Dorothea L. Floris
Tim Schäfer
Anke Bletsch
Caroline Gurr
Michael V. Lombardo
Chris H. Chatham
Julian Tillmann
Tony Charman
Martina Arenella
Emily J. H. Jones
Sara Ambrosino
Thomas Bourgeron
Guillaume Dumas
Freddy Cliquet
Claire Leblond
Eva Loth
Beth Oakley
Jan K. Buitelaar
Simon Baron-Cohen … (see 7 more)
Christian Beckmann
Antonio Persico
Tobias Banaschewski
Sarah Durston
Christine M. Freitag
Declan Murphy
Christine Ecker
2023-03-29
Molecular Psychiatry (published)
doi.org
A Novel Model for Novelty: Modeling the Emergence of Innovation from Cumulative Culture
Natalie Kastel
Guillaume Dumas
2023-03-22
Active Inference (published)
doi.org