Portrait de Guillaume Dumas

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
LinkedIn
X

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
Site web
Github
Google Scholar
Nadine Mohamed
Maîtrise recherche - UdeM
Rémy Ramadour
Visiteur de recherche indépendant - CHU Sainte Justine / Université de Montréal
Site web
Github
Mahta Ramezanian
Maîtrise recherche - UdeM
Superviseur⋅e principal⋅e :
Irina Rish
Pascal Tikeng Notsawo
Doctorat - UdeM
Superviseur⋅e principal⋅e :
Guillaume Rabusseau
Site web
Github
Google Scholar

Publications

Maternal chemosignals enhance infant-adult brain-to-brain synchrony
Yaara Endevelt-Shapira
Amir Djalovski
Guillaume Dumas
Ruth Feldman
2021-12-09
Science Advances (publié)
doi.org
Hypo- and hyper- sensory processing heterogeneity in Autism Spectrum Disorder
Aline Lefebvre
Julian Tillmann
Freddy Cliquet
Frederique Amsellem
Anna Maruani
Claire Leblond
Anita Beggiato
David Germanaud
Anouck Amestoy
Myriam Ly‐Le Moal
Daniel Umbricht
Christopher Chattam
Lorraine Murtagh
Manuel Bouvard
Marion Leboyer
Tony Charman
Thomas Bourgeron
Richard Delorme
Guillaume Dumas
Background. Sensory processing atypicalities are part of the core symptoms of autism spectrum disorder (ASD) and could result from an excita… (voir plus)tion/inhibition imbalance. Yet, the convergence level of phenotypic sensory processing atypicalities with genetic alterations in GABA-ergic and glutamatergic pathways remains poorly understood. This study aimed to characterize the distribution of hypo/hyper-sensory profile among individuals with ASD and investigate the role of deleterious mutations in GABAergic and glutamatergic pathways related genes in sensory processing atypicalities. Method. From the Short Sensory Profile (SSP) questionnaire, we defined and explored a score – the differential Short Sensory Profile (dSSP) - as a normalized and centralized hypo/hypersensitivity ratio for 1136 participants (533 with ASD, 210 first-degree relatives, and 267 controls) from two independent study samples (PARIS and LEAP). We also performed an unsupervised item-based clustering analysis on SSP items scores to validate this new categorization in terms of hypo and hyper sensitivity. We then explored the link between the dSSP score and the burden of deleterious mutations in a subset of individuals for which whole-genome sequencing data were available. Results. We observed a mean dSSP score difference between ASD and controls, driven mostly by a high dSSP score variability among groups (PARIS: p0.0001, η2 = 0.0001, LEAP: p0.0001, Cohen’s d=3.67). First-degree relatives were with an intermediate distribution variability prof
2021-11-29
(publié)
doi.org
The meaning of significant mean group differences for biomarker discovery
Eva Loth
Jumana Ahmad
Chris Chatham
Beatriz López
Ben Carter
Daisy Crawley
Bethany Oakley
Hannah Hayward
Jennifer Cooke
Antonia San José Cáceres
Danilo Bzdok
Emily Jones
Tony Charman
Christian Beckmann
Thomas Bourgeron
Roberto Toro
Jan Buitelaar
Declan Murphy
Guillaume Dumas
Over the past decade, biomarker discovery has become a key goal in psychiatry to aid in the more reliable diagnosis and prognosis of heterog… (voir plus)eneous psychiatric conditions and the development of tailored therapies. Nevertheless, the prevailing statistical approach is still the mean group comparison between “cases” and “controls,” which tends to ignore within-group variability. In this educational article, we used empirical data simulations to investigate how effect size, sample size, and the shape of distributions impact the interpretation of mean group differences for biomarker discovery. We then applied these statistical criteria to evaluate biomarker discovery in one area of psychiatric research—autism research. Across the most influential areas of autism research, effect size estimates ranged from small (d = 0.21, anatomical structure) to medium (d = 0.36 electrophysiology, d = 0.5, eye-tracking) to large (d = 1.1 theory of mind). We show that in normal distributions, this translates to approximately 45% to 63% of cases performing within 1 standard deviation (SD) of the typical range, i.e., they do not have a deficit/atypicality in a statistical sense. For a measure to have diagnostic utility as defined by 80% sensitivity and 80% specificity, Cohen’s d of 1.66 is required, with still 40% of cases falling within 1 SD. However, in both normal and nonnormal distributions, 1 (skewness) or 2 (platykurtic, bimodal) biologically plausible subgroups may exist despite small or even nonsignificant mean group differences. This conclusion drastically contrasts the way mean group differences are frequently reported. Over 95% of studies omitted the “on average” when summarising their findings in their abstracts (“autistic people have deficits in X”), which can be misleading as it implies that the group-level difference applies to all individuals in that group. We outline practical approaches and steps for researchers to explore mean group comparisons for the discovery of stratification biomarkers.
2021-10-31
PLoS Computational Biology (publié)
doi.org
THE EFFECT SIZE OF GENES ON COGNITIVE ABILITIES IS LINKED TO THEIR EXPRESSION ALONG THE MAJOR HIERARCHICAL GRADIENT IN THE HUMAN BRAIN
Sébastien Jacquemont
Guillaume Huguet
Élise Douard
Zohra Saci
Guillaume Dumas
Laura Almasy
David C. Glahn
2021-10-30
European Neuropsychopharmacology (publié)
doi.org
Inter-Brain Synchronization: From Neurobehavioral Correlation to Causal Explanation
Guillaume Dumas
2021-09-30
International Journal of Psychophysiology (publié)
doi.org
Hybrid Harmony: A Multi-Person Neurofeedback Application for Interpersonal Synchrony
Phoebe Chen
Sophie Hendrikse
Kaia Sargent
Michele Romani
Matthias Oostrik
Tom F. Wilderjans
Sander Koole
Guillaume Dumas
David Medine
Suzanne Dikker
Recent years have seen a dramatic increase in studies measuring brain activity, physiological responses, and/or movement data from multiple … (voir plus)individuals during social interaction. For example, so-called “hyperscanning” research has demonstrated that brain activity may become synchronized across people as a function of a range of factors. Such findings not only underscore the potential of hyperscanning techniques to capture meaningful aspects of naturalistic interactions, but also raise the possibility that hyperscanning can be leveraged as a tool to help improve such naturalistic interactions. Building on our previous work showing that exposing dyads to real-time inter-brain synchrony neurofeedback may help boost their interpersonal connectedness, we describe the biofeedback application Hybrid Harmony, a Brain-Computer Interface (BCI) that supports the simultaneous recording of multiple neurophysiological datastreams and the real-time visualization and sonification of inter-subject synchrony. We report results from 236 dyads experiencing synchrony neurofeedback during naturalistic face-to-face interactions, and show that pairs' social closeness and affective personality traits can be reliably captured with the inter-brain synchrony neurofeedback protocol, which incorporates several different online inter-subject connectivity analyses that can be applied interchangeably. Hybrid Harmony can be used by researchers who wish to study the effects of synchrony biofeedback, and by biofeedback artists and serious game developers who wish to incorporate multiplayer situations into their practice.
2021-08-11
Frontiers in Neuroergonomics (publié)
doi.org
Temporal Profiles of Social Attention Are Different Across Development in Autistic and Neurotypical People.
Teresa Del Bianco
Luke Mason
Tony Charman
Julianne Tillman
Eva Loth
Hannah Hayward
F. Shic
Jan K. Buitelaar
Mark Johnson
Emily J. H. Jones
Jumana Ahmad
Sara Ambrosino
Tobias Banaschewski
Simon Baron-Cohen
Sarah Baumeister
Christian Beckmann
Sven Bölte
Thomas Bourgeron
Carsten Bours
M. Brammer … (voir 46 de plus)
Daniel Brandeis
Claudia Brogna
Yvette de Bruijn
Ineke Cornelissen
Daisy Crawley
Flavio Dell’Acqua
Guillaume Dumas
Sarah Durston
Christine Ecker
Jessica Faulkner
Vincent Frouin
Pilar Garcés
David Goyard
Lindsay Ham
Joerg F. Hipp
Rosemary Holt
Meng-Chuan Lai
Xavier Liogier D’ardhuy
Michael V. Lombardo
David J. Lythgoe
René Mandl
Andre Marquand
Maarten Mennes
Andreas Meyer-Lindenberg
Carolin Moessnang
Nico Mueller
Declan Murphy
Beth Oakley
Larry 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
2021-07-31
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging (publié)
doi.org
Why do sleep disorders belong to mental disorder classifications? A network analysis of the "Sleep-Wake Disorders" section of the DSM-5.
Christophe Gauld
Régis Lopez
Charles Morin
Julien Maquet
Aileen McGonigal
Pierre A. GEOFFROY
Eric Fakra
Pierre Philip
Guillaume Dumas
Jean‐Arthur Micoulaud‐Franchi
2021-07-31
Journal of Psychiatric Research (publié)
doi.org
Symptom network analysis of the sleep disorders diagnostic criteria based on the clinical text of the ICSD‐3
Christophe Gauld
Régis Lopez
Charles Morin
Pierre A. GEOFFROY
Julien Maquet
Pierre Desvergnes
Aileen McGonigal
Yves Dauvilliers
Pierre Philip
Guillaume Dumas
Jean‐Arthur Micoulaud‐Franchi
2021-07-15
Journal of Sleep Research (publié)
doi.org
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks.
Germán Abrevaya
Guillaume Dumas
Aleksandr Y. Aravkin
Peng Zheng
Jean-christophe Gagnon-audet
James R. Kozloski
Pablo Polosecki
Guillaume Lajoie
David D. Cox
Silvina Ponce Dawson
Guillermo A. Cecchi
Irina Rish
Many natural systems, especially biological ones, exhibit complex multivariate nonlinear dynamical behaviors that can be hard to capture by … (voir plus)linear autoregressive models. On the other hand, generic nonlinear models such as deep recurrent neural networks often require large amounts of training data, not always available in domains such as brain imaging; also, they often lack interpretability. Domain knowledge about the types of dynamics typically observed in such systems, such as a certain type of dynamical systems models, could complement purely data-driven techniques by providing a good prior. In this work, we consider a class of ordinary differential equation (ODE) models known as van der Pol (VDP) oscil lators and evaluate their ability to capture a low-dimensional representation of neural activity measured by different brain imaging modalities, such as calcium imaging (CaI) and fMRI, in different living organisms: larval zebrafish, rat, and human. We develop a novel and efficient approach to the nontrivial problem of parameters estimation for a network of coupled dynamical systems from multivariate data and demonstrate that the resulting VDP models are both accurate and interpretable, as VDP's coupling matrix reveals anatomically meaningful excitatory and inhibitory interactions across different brain subsystems. VDP outperforms linear autoregressive models (VAR) in terms of both the data fit accuracy and the quality of insight provided by the coupling matrices and often tends to generalize better to unseen data when predicting future brain activity, being comparable to and sometimes better than the recurrent neural networks (LSTMs). Finally, we demonstrate that our (generative) VDP model can also serve as a data-augmentation tool leading to marked improvements in predictive accuracy of recurrent neural networks. Thus, our work contributes to both basic and applied dimensions of neuroimaging: gaining scientific insights and improving brain-based predictive models, an area of potentially high practical importance in clinical diagnosis and neurotechnology.
2021-06-06
Neural Computation (inconnu)
doi.org
Brainhack: Developing a culture of open, inclusive, community-driven neuroscience
Rémi Gau
Stephanie Noble
Katja Heuer
Katherine L. Bottenhorn
Isil Poyraz Bilgin
Yufang Yang
Julia M. Huntenburg
Johanna Bayer
Richard A. I. Bethlehem
Shawn A Rhoads
Christoph Vogelbacher
Valentina Borghesani
Elizabeth Levitis
Hao-Ting Wang
Sofie Van Den Bossche
Xenia Kobeleva
Jon Haitz Legarreta
Samuel Guay
Melvin Selim Atay
Gael P. Varoquaux … (voir 80 de plus)
Dorien Huijser
Malin Sandström
Peer Herholz
Samuel A. Nastase
AmanPreet Badhwar
Guillaume Dumas
Simon Schwab
Stefano Moia
Michael Dayan
Yasmine Bassil
Paula P. Brooks
Matteo Mancini
James M. Shine
David O’Connor
Xihe Xie
Davide Poggiali
Patrick Friedrich
Anibal Sólon Heinsfeld
Lydia Riedl
Roberto Toro
César Caballero‐Gaudes
Anders Eklund
Kelly Garner
Christopher Nolan
Damion V. Demeter
Fernando A. Barrios
Junaid S. Merchant
Elizabeth A. McDevitt
Robert Oostenveld
R. Cameron Craddock
Ariel Rokem
Andrew Doyle
Satrajit Ghosh
Aki Nikolaidis
Olivia W. Stanley
Eneko Uruñuela
Nasim Anousheh
Aurina Arnatkevičiūtė
Guillaume Auzias
Dipankar Bachar
Élise Bannier
Ruggero Basanisi
Arshitha Basavaraj
Marco Bedini
Pierre Bellec
R. Austin Benn
Kathryn Berluti
Steffen Bollmann
Saskia Bollmann
Claire Bradley
Jesse A. Brown
Augusto Buchweitz
Patrick Callahan
Micaela Y. Chan
Bramsh Q. Chandio
Theresa W Cheng
Sidhant Chopra
Ai Wern Chung
Thomas Close
Etienne Combrisson
Giorgia Cona
R. Todd Constable
Claire Cury
Kamalaker Dadi
Pablo F. Damasceno
Samir Das
Fabrizio De Vico Fallani
Krista DeStasio
Erin W. Dickie
Lena Dorfschmidt
Eugene Duff
Elizabeth DuPré
Sarah L. Dziura
Nathália Bianchini Esper
Oscar Estéban
Shreyas Fadnavis
Guillaume Flandin
Jessica Flannery
John C. Flournoy
Stephanie J. Forkel

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open and inclusive environment. Depa… (voir plus)rting from the formats of typical scientific workshops, these events are based on grassroots projects and training, and foster open and reproducible scientific practices. We describe here the multifaceted, lasting benefits of Brainhacks for individual participants, particularly early career researchers. We further highlight the unique contributions that Brainhacks can make to the research community, contributing to scientific progress by complementing opportunities available in conventional formats.

2021-05-31
Neuron (publié)
doi.org
Imbalanced social-communicative and restricted repetitive behavior subtypes of autism spectrum disorder exhibit different neural circuitry
Natasha Bertelsen
Isotta Landi
Richard A.I. Bethlehem
Jakob Seidlitz
Elena Maria Busuoli
Veronica Mandelli
Eleonora Satta
Stavros Trakoshis
Bonnie Auyeung
Prantik Kundu
Eva Loth
Guillaume Dumas
Sarah Baumeister
Christian Beckmann
Sven Bölte
Thomas Bourgeron
Tony Charman
Sarah Durston
Christine Ecker
Rosemary Holt … (voir 57 de plus)
Mark Johnson
Emily J. H. Jones
Luke Mason
Andreas Meyer-Lindenberg
Carolin Moessnang
Marianne Oldehinkel
Antonio Persico
Julian Tillmann
Steve C. R. Williams
Will Spooren
Declan Murphy
Jan K. Buitelaar
Jumana Sara Tobias Carsten Michael Daniel Claudia Yvette Bhismadev Chris Ineke Daisy Flavio Jessica Vincent Pilar David Lindsay Hannah Joerg Rosemary J. Xavier Liogier David J. René Andre Maarten Nico Bethany Laurence Bob Gahan Antonio M. Barbara Amber N. V. Jessica Roberto Antonia San José Emily Roberto Heike Jack Steve C. R. Caroline Marcel P. Ahmad
Simon Baron-Cohen
Meng-Chuan Lai
Jumana Ahmad
Sara Ambrosino
Michael V. Lombardo
Tobias Banaschewski
Carsten Bours
Michael Brammer
Daniel Brandeis
Claudia Brogna
Yvette de Bruijn
Bhismadev Chakrabarti
Christopher H. Chatham
Ineke Cornelissen
Daisy Crawley
Flavio Dell’Acqua
Jessica Faulkner
Vincent Frouin
Pilar Garcés
David Goyard
Lindsay Ham
Hannah Hayward
Joerg F. Hipp
Xavier Liogier D’ardhuy
David J. Lythgoe
René Mandl
Andre Marquand
Maarten Mennes
Nico Mueller
Beth Oakley
Larry O’Dwyer
Bob Oranje
Gahan Pandina
Barbara Ruggeri
Amber N. V. Ruigrok
Jessica Sabet
Roberto Sacco
Antonia San José Cáceres
Emily Simonoff
Roberto Toro
Heike Tost
Jack Waldman
Caroline Wooldridge
Marcel P. Zwiers
2021-05-13
Communications Biology (publié)
doi.org