Guillaume Dumas

Membre académique associé

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

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

Juan David Vargas

Maîtrise recherche - UdeM

Kastel Natalie

Doctorat - UdeM

Mahta Ramezanian

Maîtrise recherche - UdeM

Superviseur⋅e principal⋅e :

Irina Rish

Zahra Sheikhbahaee

Postdoctorat - UdeM

Co-superviseur⋅e :

Irina Rish

Github

Pascal Tikeng Notsawo

Doctorat - UdeM

Superviseur⋅e principal⋅e :

Postdoctorat - UdeM

Publications

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 (publié)

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… (voir plus)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 (prépublication)

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 (prépublication)

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… (voir plus)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 (publié)

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 (publié)

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 … (voir 7 de plus)

Christian Beckmann

Antonio Persico

Tobias Banaschewski

Sarah Durston

Christine M. Freitag

Declan Murphy

Christine Ecker

2023-03-29

Molecular Psychiatry (publié)

doi.org

A Novel Model for Novelty: Modeling the Emergence of Innovation from Cumulative Culture

Natalie Kastel

Guillaume Dumas

2023-03-22

Active Inference (publié)

doi.org

Processing of social and monetary rewards in autism spectrum disorders

Sarah Baumeister

Carolin Moessnang

Nico Bast

Sarah Hohmann

Pascal Aggensteiner

Anna Kaiser

Julian Tillmann

David Goyard

Tony Charman

Sara Ambrosino

Simon Baron-Cohen

Christian Beckmann

Sven Bölte

Thomas Bourgeron

Annika Rausch

Daisy Crawley

Flavio Dell’Acqua

Guillaume Dumas

Sarah Durston

Christine Ecker … (voir 21 de plus)

Dorothea L. Floris

Vincent Frouin

Hannah Hayward

Rosemary Holt

Mark Johnson

Emily J. H. Jones

Meng-Chuan Lai

Michael V. Lombardo

Luke Mason

Beth Oakley

Marianne Oldehinkel

Antonio Persico

Antonia San José Cáceres

Thomas Wolfers

Eva Loth

Declan Murphy

Jan K. Buitelaar

Heike Tost

Andreas Meyer-Lindenberg

Tobias Banaschewski

Daniel Brandeis

Background Reward processing has been proposed to underpin the atypical social feature of autism spectrum disorder (ASD). However, previous … (voir plus)neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social reward processing in ASD. Aims Utilising a large sample, we aimed to assess reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD. Method Functional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6–30.6 years of age) and 181 typically developing participants (7.6–30.8 years of age). Results Across social and monetary reward anticipation, whole-brain analyses showed hypoactivation of the right ventral striatum in participants with ASD compared with typically developing participants. Further, region of interest analysis across both reward types yielded ASD-related hypoactivation in both the left and right ventral striatum. Across delivery of social and monetary reward, hyperactivation of the ventral striatum in individuals with ASD did not survive correction for multiple comparisons. Dimensional analyses of autism and attention-deficit hyperactivity disorder (ADHD) scores were not significant. In categorical analyses, post hoc comparisons showed that ASD effects were most pronounced in participants with ASD without co-occurring ADHD. Conclusions Our results do not support current theories linking atypical social interaction in ASD to specific alterations in social reward processing. Instead, they point towards a generalised hypoactivity of ventral striatum in ASD during anticipation of both social and monetary rewards. We suggest this indicates attenuated reward seeking in ASD independent of social content and that elevated ADHD symptoms may attenuate altered reward seeking in ASD.

2023-03-01

The British Journal of Psychiatry (publié)

doi.org

Interpersonal attunement in social interactions: from collective psychophysiology to inter-personalized psychiatry and beyond

Dimitris Bolis

Guillaume Dumas

Leonhard Schilbach

In this article, we analyse social interactions, drawing on diverse points of views, ranging from dialectics, second-person neuroscience and… (voir plus) enactivism to dynamical systems, active inference and machine learning. To this end, we define interpersonal attunement as a set of multi-scale processes of building up and materializing social expectations—put simply, anticipating and interacting with others and ourselves. While cultivating and negotiating common ground, via communication and culture-building activities, are indispensable for the survival of the individual, the relevant multi-scale mechanisms have been largely considered in isolation. Here, collective psychophysiology, we argue, can lend itself to the fine-tuned analysis of social interactions, without neglecting the individual. On the other hand, an interpersonal mismatch of expectations can lead to a breakdown of communication and social isolation known to negatively affect mental health. In this regard, we review psychopathology in terms of interpersonal misattunement, conceptualizing psychiatric disorders as disorders of social interaction, to describe how individual mental health is inextricably linked to social interaction. By doing so, we foresee avenues for an inter-personalized psychiatry, which moves from a static spectrum of disorders to a dynamic relational space, focusing on how the multi-faceted processes of social interaction can help to promote mental health. This article is part of the theme issue ‘Concepts in interaction: social engagement and inner experiences’.

2023-02-13

Philosophical Transactions of the Royal Society B: Biological Sciences (publié)

doi.org

Sources of richness and ineffability for phenomenally conscious states

Xu Ji

Eric Elmoznino

George Deane

Axel Constant

Guillaume Dumas

Guillaume Lajoie

Jonathan Simon

Yoshua Bengio

Abstract Conscious states—state that there is something it is like to be in—seem both rich or full of detail and ineffable or hard to fu… (voir plus)lly describe or recall. The problem of ineffability, in particular, is a longstanding issue in philosophy that partly motivates the explanatory gap: the belief that consciousness cannot be reduced to underlying physical processes. Here, we provide an information theoretic dynamical systems perspective on the richness and ineffability of consciousness. In our framework, the richness of conscious experience corresponds to the amount of information in a conscious state and ineffability corresponds to the amount of information lost at different stages of processing. We describe how attractor dynamics in working memory would induce impoverished recollections of our original experiences, how the discrete symbolic nature of language is insufficient for describing the rich and high-dimensional structure of experiences, and how similarity in the cognitive function of two individuals relates to improved communicability of their experiences to each other. While our model may not settle all questions relating to the explanatory gap, it makes progress toward a fully physicalist explanation of the richness and ineffability of conscious experience—two important aspects that seem to be part of what makes qualitative character so puzzling.

2023-02-13

ArXiv (prépublication)

doi.org

arxiv.org

Sources of richness and ineffability for phenomenally conscious states

Xu Ji

Eric Elmoznino

George Deane

Axel Constant

Guillaume Dumas

Guillaume Lajoie

Jonathan Simon