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
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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

Germán Abrevaya
Independent visiting researcher - Université de Montréal
Principal supervisor :
Irina Rish
Google Scholar
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
Tommie Tosato
Postdoctorate - Université de Montréal
Github

Publications

Exploring the multidimensional nature of repetitive and restricted behaviors and interests (RRBI) in autism: neuroanatomical correlates and clinical implications
Aline Lefebvre
Nicolas Traut
Amandine Pedoux
Anna Maruani
Anita Beggiato
Monique Elmaleh
David Germanaud
Anouck Amestoy
Myriam Ly‐Le Moal
Christopher H. Chatham
Lorraine Murtagh
Manuel Bouvard
Marianne Alisson
Marion Leboyer
Thomas Bourgeron
Roberto Toro
Guillaume Dumas
Clara A. Moreau
Richard Delorme
2023-11-27
Molecular Autism (published)
doi.org
Interoceptive technologies for psychiatric interventions: From diagnosis to clinical applications
Felix Schoeller
Adam Haar Horowitz
Abhinandan Jain
Pattie Maes
Nicco Reggente
Leonardo Christov-Moore
Giovanni Pezzulo
Laura Barca
Micah Allen
Roy Salomon
Mark Miller
Daniele Di Lernia
Giuseppe Riva
Manos Tsakiris
Moussa A. Chalah
Arno Klein
Ben Zhang
Teresa Garcia
Ursula Pollack
Marion Trousselard … (see 4 more)
Charles Verdonk
Guillaume Dumas
Vladimir Adrien
Karl J. Friston
2023-11-01
Neuroscience and Biobehavioral Reviews (published)
doi.org
Attention Schema in Neural Agents
Dianbo Liu
Samuele Bolotta
Mike He Zhu
Zahra Sheikhbahaee
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.
2023-10-27
NeurIPS.cc/2023/Workshop/InfoCog (poster)
doi.org
openreview.net
The neuroanatomical substrates of autism and ADHD and their link to putative genomic underpinnings
Lisa M. Berg
Caroline Gurr
Johanna Leyhausen
Hanna Seelemeyer
Anke Bletsch
Tim Schaefer
Charlotte M. Pretzsch
Beth Oakley
Eva Loth
Dorothea L. Floris
Jan K. Buitelaar
Christian Beckmann
Tobias Banaschewski
Tony Charman
Emily J. H. Jones
Julian Tillmann
Chris H. Chatham
Thomas Bourgeron
Jumana Sara Bonnie Simon Sarah Sven Carsten Michael Danie Ahmad Ambrosino Auyeung Baron-Cohen Baumeister Böl
Jumana Sara Bonnie Simon Sarah Sven Carsten Michael Daniel Claudia Yvette Bhismadev Ineke Daisy Flavio Guillaume Sarah Jessica Vincent Pilar David Lindsay Hannah Joerg Rosemary Mark H. Prantik Meng-Chuan Xavier Liogier Michael V. David J. René Andre Luke Maarten Andreas Carolin Nico Laurence Marianne Bob Gahan Antonio M. Barbara Amber Jessica Roberto Antonia San José Emily Will Roberto Heike Jack Steve C. R. Caroline Marcel P. Ahmad … (see 58 more)
Jumana Ahmad
Sara Ambrosino
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
Jessica Faulkner
Vincent Frouin
Pilar Garcés
David Goyard
Lindsay Ham
Hannah Hayward
Joerg F. Hipp
Rosemary Holt
Mark Johnson
Prantik Kundu
Meng-Chuan Lai
Xavier Liogier D’ardhuy
Michael V. Lombardo
David J. Lythgoe
René Mandl
Andre Marquand
Luke Mason
Maarten Mennes
Andreas Meyer-Lindenberg
Carolin Moessnang
Nico Bast
Laurence O’Dwyer
Marianne Oldehinkel
Bob Oranje
Gahan Pandina
Antonio Persico
Barbara Ruggeri
Amber N. V. Ruigrok
Jessica Sabet
Roberto Sacco
Antonia San José Cáceres
Emily Simonoff
Will Spooren
Roberto Toro
Heike Tost
Jack Waldman
Steve C. R. Williams
Caroline Wooldridge
Marcel P. Zwiers
Declan Murphy
Christine Ecker
2023-10-04
Molecular Autism (published)
doi.org
F66. FROM GENE TO COGNITION: MAPPING THE EFFECTS OF GENOMIC DELETIONS AND DUPLICATIONS ON COGNITIVE ABILITY
Sayeh Kazem
Kuldeep Kumar
Guillaume Huguet
Myriam Lizotte
Thomas Renne
Jakub Kopal
Stefan Horoi
Martineau Jean-Louis
Zohra Saci
Laura Almasy
David C. Glahn
Guy Wolf
Guillaume Dumas
Sébastien Jacquemont
2023-10-01
European Neuropsychopharmacology (published)
doi.org
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
Lei 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
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