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
Site web
Google Scholar
LinkedIn
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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

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
Site web
Github
Google Scholar

Publications

Generative Models of Brain Dynamics
Mahta Ramezanian-Panahi
Germán Abrevaya
Jean-christophe Gagnon-audet
Vikram Voleti
Irina Rish
Guillaume Dumas
2022-07-14
Frontiers in Artificial Intelligence (publié)
doi.org
Naming Autism in the Right Context
Andres Roman-Urrestarazu
Guillaume Dumas
Varun Warrier
2022-06-30
JAMA Pediatrics (publié)
doi.org
Popular and Scientific Discourse on Autism: Representational Cross-Cultural Analysis of Epistemic Communities to Inform Policy and Practice
Christophe Gauld
Julien Maquet
Jean‐Arthur Micoulaud‐Franchi
Guillaume Dumas
Background Social media provide a window onto the circulation of ideas in everyday folk psychiatry, revealing the themes and issues discusse… (voir plus)d both by the public and by various scientific communities. Objective This study explores the trends in health information about autism spectrum disorder within popular and scientific communities through the systematic semantic exploration of big data gathered from Twitter and PubMed. Methods First, we performed a natural language processing by text-mining analysis and with unsupervised (machine learning) topic modeling on a sample of the last 10,000 tweets in English posted with the term #autism (January 2021). We built a network of words to visualize the main dimensions representing these data. Second, we performed precisely the same analysis with all the articles using the term “autism” in PubMed without time restriction. Lastly, we compared the results of the 2 databases. Results We retrieved 121,556 terms related to autism in 10,000 tweets and 5.7x109 terms in 57,121 biomedical scientific articles. The 4 main dimensions extracted from Twitter were as follows: integration and social support, understanding and mental health, child welfare, and daily challenges and difficulties. The 4 main dimensions extracted from PubMed were as follows: diagnostic and skills, research challenges, clinical and therapeutical challenges, and neuropsychology and behavior. Conclusions This study provides the first systematic and rigorous comparison between 2 corpora of interests, in terms of lay representations and scientific research, regarding the significant increase in information available on autism spectrum disorder and of the difficulty to connect fragments of knowledge from the general population. The results suggest a clear distinction between the focus of topics used in the social media and that of scientific communities. This distinction highlights the importance of knowledge mobilization and exchange to better align research priorities with personal concerns and to address dimensions of well-being, adaptation, and resilience. Health care professionals and researchers can use these dimensions as a framework in their consultations to engage in discussions on issues that matter to beneficiaries and develop clinical approaches and research policies in line with these interests. Finally, our study can inform policy makers on the health and social needs and concerns of individuals with autism and their caregivers, especially to define health indicators based on important issues for beneficiaries.
2022-06-14
Journal of Medical Internet Research (publié)
doi.org
Technologically-assisted communication attenuates inter-brain synchrony
Linoy Schwartz
Jonathan Levy
Yaara Endevelt-Shapira
Amir Djalovski
Olga Hayut
Guillaume Dumas
Ruth Pinkenson Feldman
2022-06-05
NeuroImage (publié)
doi.org
How Can Digital Mental Health Enhance Psychiatry?
Emilie Stern
Jean-Arthur MICOULAUD FRANCHI
Guillaume Dumas
Jeverson Moreira
Stephane Mouchabac
Julia Maruani
Pierre Philip
Michel Lejoyeux
Pierre A. GEOFFROY
The use of digital technologies is constantly growing around the world. The wider-spread adoption of digital technologies and solutions in t… (voir plus)he daily clinical practice in psychiatry seems to be a question of when, not if. We propose a synthesis of the scientific literature on digital technologies in psychiatry and discuss the main aspects of its possible uses and interests in psychiatry according to three domains of influence that appeared to us: 1) assist and improve current care: digital psychiatry allows for more people to have access to care by simply being more accessible but also by being less stigmatized and more convenient; 2) develop new treatments: digital psychiatry allows for new treatments to be distributed via apps, and practical guidelines can reduce ethical challenges and increase the efficacy of digital tools; and 3) produce scientific and medical knowledge: digital technologies offer larger and more objective data collection, allowing for more detection and prevention of symptoms. Finally, ethical and efficacy issues remain, and some guidelines have been put forth on how to safely use these solutions and prepare for the future.
2022-06-03
The Neuroscientist (publié)
doi.org
Genetic correlates of phenotypic heterogeneity in autism
Varun Warrier
Xinhe Zhang
Patrick Reed
Alexandra Havdahl
Tyler M. Moore
Freddy Cliquet
Claire Leblond
Thomas Rolland
Anders Rosengren
Antonia San Jose Hannah Daisy Jessica Jessica Claire Bethany Eva Tony Declan Rosemary Jack Jessica Nicola Meng-Chuan Gwilym Amber Emily Hisham Julia Sara Ambrosino Sarai Yvonne Tabitha Miriam Alyssia Iris Maarten Anna Ver Loren Nico Sarah Larry Carsten Annika Daniel Ineke Yvette Maartje Elzbieta Elodie Kristiina Rouslan Guillaume Yang-Min Thomas Caceres
Antonia San Jose Hannah Daisy Jessica Jessica Claire Betha Caceres Hayward Crawley Faulkner Sabet Ellis Oakle
Antonia San José Cáceres
Hannah Hayward
Daisy Crawley
Jessica Faulkner
Jessica Sabet
Claire Ellis
Beth Oakley
Eva Loth
Tony Charman … (voir 67 de plus)
Declan Murphy
Rosemary Holt
Jack Waldman
Jessica Upadhyay
Nicola Gunby
Meng-Chuan Lai
Gwilym Renouf
Amber N. V. Ruigrok
Emily Taylor
Hisham Ziauddeen
Julia Deakin
Sara Ambrosino di Bruttopilo
Sarai van Dijk
Yvonne Rijks
Tabitha Koops
Miriam Douma
Alyssia Spaan
Iris Selten
Maarten Steffers
Anna Ver Loren van Themaat
Nico Bast
Sarah Baumeister
Larry O’Dwyer
Carsten Bours
Annika Rausch
Daniel von Rhein
Ineke Cornelissen
Yvette de Bruin
Maartje Graauwmans
Elzbieta Kostrzewa
Elodie Cauvet
Kristiina Tammimies
Rouslan Sitnikow
Guillaume Dumas
Yang-Min Kim
Thomas Bourgeron
David M. Jonas Thomas Preben Bo Ole Merete Hougaard
David M. Hougaard
Jonas Bybjerg-Grauholm
Thomas Werge
Preben Bo Mortensen
Ole Mors
Merete Nordentoft
Dwaipayan Armandina Carrie Isabelle Tracey Paula Alex Graham J. Alexander E. P. Lidia V. Tal Madeline A. Deepak P. Jonathan Adhya
Dwaipayan Armandina Carrie Isabelle Tracey Paula Alex Graham Adhya Alamanza Allison Garvey Parsons Smith Tsompa
Dwaipayan Adhya
Armandina Alamanza
Carrie Allison
Isabelle Garvey
Tracey Parsons
Paula Smith
Alex Tsompanidis
Graham J. Burton
Alexander E. P. Heazell
Lidia V. Gabis
Tal Biron-Shental
Madeline A. Lancaster
Deepak P. Srivastava
Jonathan Mill
David H. Rowitch
Matthew E. Hurles
Daniel H. Geschwind
Anders D. Børglum
Elise B. Robinson
Jakob Grove
Hilary C. Martin
Simon Baron-Cohen
2022-06-01
Nature Genetics (publié)
doi.org
From inter‐brain connectivity to inter‐personal psychiatry
Guillaume Dumas
2022-05-06
World Psychiatry (publié)
doi.org
Social Neuro AI: Social Interaction as the "Dark Matter" of AI
Samuele Bolotta
Guillaume Dumas
This article introduces a three-axis framework indicating how AI can be informed by biological examples of social learning mechanisms. We ar… (voir plus)gue that the complex human cognitive architecture owes a large portion of its expressive power to its ability to engage in social and cultural learning. However, the field of AI has mostly embraced a solipsistic perspective on intelligence. We thus argue that social interactions not only are largely unexplored in this field but also are an essential element of advanced cognitive ability, and therefore constitute metaphorically the dark matter of AI. In the first section, we discuss how social learning plays a key role in the development of intelligence. We do so by discussing social and cultural learning theories and empirical findings from social neuroscience. Then, we discuss three lines of research that fall under the umbrella of Social NeuroAI and can contribute to developing socially intelligent embodied agents in complex environments. First, neuroscientific theories of cognitive architecture, such as the global workspace theory and the attention schema theory, can enhance biological plausibility and help us understand how we could bridge individual and social theories of intelligence. Second, intelligence occurs in time as opposed to over time, and this is naturally incorporated by dynamical systems. Third, embodiment has been demonstrated to provide more sophisticated array of communicative signals. To conclude, we discuss the example of active inference, which offers powerful insights for developing agents that possess biological realism, can self-organize in time, and are socially embodied.
2022-05-05
Frontiers in Computer Science (publié)
doi.org
arxiv.org
Neurobiological Correlates of Change in Adaptive Behavior in Autism.
Charlotte M. Pretzsch
Tim Schäfer
Michael V. Lombardo
Varun Warrier
Caroline Mann
Anke Bletsch
Chris H. Chatham
Dorothea L. Floris
Julian Tillmann
Afsheen Yousaf
Emily J. H. Jones
Tony Charman
Sara Ambrosino
Thomas Bourgeron
Guillaume Dumas
Eva Loth
Beth Oakley
Jan K. Buitelaar
Freddy Cliquet
Claire Leblond … (voir 7 de plus)
Simon Baron-Cohen
Christian Beckmann
Tobias Banaschewski
Sarah Durston
Christine M. Freitag
Declan Murphy
Christine Ecker
2022-04-30
American Journal of Psychiatry (publié)
doi.org
P397. Genomic Deletions and Duplications Show Mirror Effects on Cognitive Ability According to Spatial Patterns of Gene Expression in the Human Brain
Kuldeep Kumar
Sayeh Kazem
Guillaume Huguet
Élise Douard
Zohra Saci
Laura Almasy
David Glahn
Guillaume Dumas
Sébastien Jacquemont
2022-04-30
Biological Psychiatry (publié)
doi.org
Exploring age-related changes in inter-brain synchrony during verbal communication
Suzanne Dikker
Emily N. Mech
Laura Gwilliams
Tessa West
Guillaume Dumas
Kara D. Federmeier

Successful communication is key to health in older age. This is true in the narrow sense of being able to gain critical information e.g.,… (voir plus) from health care providers, but also more broadly in being able to maintain social ties and pursue meaningful activities, which, in turn, are central to maintaining health and well-being. Compared to younger adults, older adults show both quantitative and qualitative changes in how information is processed and used over time to achieve comprehension. Such systematic age-related neural dissimilarities in processing dynamics and strategies raise fundamental questions about how the human brain supports cross-generational communication, especially in light of accumulating evidence linking interpersonal similarities in brain responses to communicative success. Yet despite its prevalence and tangible health-related importance, naturalistic intergenerational communication involving older adults is understudied. In this paper, we lay out why filling this research gap is critical in advancing our understanding of naturalistic communication, with implications for both science and practice.

2022-04-18
PsyArXiv (OSF Preprints) (prépublication)
doi.org
From Generative Models to Generative Passages: A Computational Approach to (Neuro) Phenomenology
Maxwell J. D. Ramstead
Anil K. Seth
Casper Hesp
Lars Sandved-Smith
Jonas Mago
Michael Lifshitz
Giuseppe Pagnoni
Ryan Smith
Guillaume Dumas
Antoine Lutz
Karl Friston
Axel Constant
This paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and bio… (voir plus)logy. Our approach can be described as computational phenomenology because it applies methods originally developed in computational modelling to provide a formal model of the descriptions of lived experience in the phenomenological tradition of philosophy (e.g., the work of Edmund Husserl, Maurice Merleau-Ponty, etc.). The first section presents a brief review of the overall project to naturalize phenomenology. The second section presents and evaluates philosophical objections to that project and situates our version of computational phenomenology with respect to these projects. The third section reviews the generative modelling framework. The final section presents our approach in detail. We conclude by discussing how our approach differs from previous attempts to use generative modelling to help understand consciousness. In summary, we describe a version of computational phenomenology which uses generative modelling to construct a computational model of the inferential or interpretive processes that best explain this or that kind of lived experience.
2022-03-17
Review of Philosophy and Psychology (publié)
doi.org