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
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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

Germán Abrevaya
Visiteur de recherche indépendant - UdeM
Superviseur⋅e principal⋅e :
Irina Rish
Google Scholar
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 :
Guillaume Rabusseau
Site web
Github
Google Scholar
Tommie Tosato
Postdoctorat - UdeM
Github

Publications

Naming Autism in the Right Context.
Andres Roman-Urrestarazu
Guillaume Dumas
Varun Warrier
2022-04-04
JAMA pediatrics (published)
doi.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
2022-03-25
American Journal of Psychiatry (publié)
doi.org
WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series Tasks
Jean-Christophe Gagnon-Audet
Kartik Ahuja
Mohammad Javad Darvishi Bayazi
Guillaume Dumas
Irina Rish
2022-03-18
ArXiv (prépublication)
doi.org
arxiv.org
Interindividual Differences in Cortical Thickness and Their Genomic Underpinnings in Autism Spectrum Disorder.
Christine Ecker
Charlotte M. Pretzsch
Anke Bletsch
Caroline Mann
Tim Schaefer
Sara Ambrosino
Julian Tillmann
Afsheen Yousaf
Andreas Chiocchetti
Michael V. Lombardo
Varun Warrier
Nico Bast
Carolin Moessnang
Sarah Baumeister
Flavio Dell’Acqua
Dorothea L. Floris
Mariam Zabihi
Andre Marquand
Freddy Cliquet
Claire Leblond … (voir 19 de plus)
Clara A. Moreau
Nick Puts
Tobias Banaschewski
Emily J. H. Jones
Luke Mason
Sven Bölte
Andreas Meyer-Lindenberg
Antonio Persico
Sarah Durston
Simon Baron-Cohen
Will Spooren
Eva Loth
Christine M. Freitag
Tony Charman
Guillaume Dumas
Thomas Bourgeron
Christian Beckmann
Jan K. Buitelaar
Declan Murphy
2022-03-01
American Journal of Psychiatry (publié)
doi.org
Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project
Tristan Looden
Dorothea L. Floris
Alberto Llera
R. Chauvin
Jumana Sara Bonnie Tobias Simon Sarah Christian F. Sven T Ahmad Ambrosino Auyeung Banaschewski Baron-Cohen B
Jumana Ahmad
Sara Ambrosino
Bonnie Auyeung
Tobias Banaschewski
Simon Baron-Cohen
Sarah Baumeister
Christian Beckmann
Sven Bölte
Thomas Bourgeron
Carsten Bours
Michael Brammer
Daniel Brandeis
Claudia Brogna
Yvette de Bruijn
Jan K. Buitelaar … (voir 55 de plus)
Bhismadev Chakrabarti
Tony Charman
Ineke Cornelissen
Daisy Crawley
F. D. Acqua
Guillaume Dumas
Sarah Durston
Christine Ecker
Jessica Faulkner
Vincent Frouin
Pilar Garcés
David Goyard
Lindsay Ham
Hannah Hayward
Joerg F. Hipp
Rosemary Holt
Mark Johnson
Emily J. H. Jones
Prantik Kundu
Meng-Chuan Lai
Xavier Liogier D’ardhuy
Michael V. Lombardo
Eva Loth
David J. Lythgoe
René Mandl
Andre Marquand
Luke Mason
Maarten Mennes
Andreas Meyer-Lindenberg
Carolin Moessnang
Nico Mueller
Declan Murphy
Beth Oakley
Laurence O’Dwyer
Marianne Oldehinkel
Bob Oranje
Gahan Pandina
Antonio Persico
Annika Rausch
Barbara Ruggeri
Amber N. V. Ruigrok
Jessica Sabet
Roberto Sacco
Antonia San José Cáceres
Emily Simonoff
Will Spooren
Julian Tillmann
Roberto Toro
Heike Tost
Jack Waldman
Steven C. R. Williams
Caroline Wooldridge
Iva Ilioska
Ting Mei
Marcel P. Zwiers
2022-02-23
bioRxiv (preprint)
doi.org
Multilevel development of cognitive abilities in an artificial neural network
Konstantin Volzhenin
Jean-Pierre Changeux
Guillaume Dumas
Several neuronal mechanisms have been proposed to account for the formation of cognitive abilities through postnatal interactions with the p… (voir plus)hysical and socio-cultural environment. Here, we introduce a three-level computational model of information processing and acquisition of cognitive abilities. We propose minimal architectural requirements to build these levels and how the parameters affect their performance and relationships. The first sensorimotor level handles local nonconscious processing, here during a visual classification task. The second level or cognitive level globally integrates the information from multiple local processors via long-ranged connections and synthesizes it in a global, but still nonconscious manner. The third and cognitively highest level handles the information globally and consciously. It is based on the Global Neuronal Workspace (GNW) theory and is referred to as conscious level. We use trace and delay conditioning tasks to, respectively, challenge the second and third levels. Results first highlight the necessity of epigenesis through selection and stabilization of synapses at both local and global scales to allow the network to solve the first two tasks. At the global scale, dopamine appears necessary to properly provide credit assignment despite the temporal delay between perception and reward. At the third level, the presence of interneurons becomes necessary to maintain a self-sustained representation within the GNW in the absence of sensory input. Finally, while balanced spontaneous intrinsic activity facilitates epigenesis at both local and global scales, the balanced excitatory-inhibitory ratio increases performance. Finally, we discuss the plausibility of the model in both neurodevelopmental and artificial intelligence terms.
2022-01-25
bioRxiv (prépublication)
doi.org
Multilevel development of cognitive abilities in an artificial neural network
Konstantin Volzhenin
J. Changeux
Guillaume Dumas
Several neuronal mechanisms have been proposed to account for the formation of cognitive abilities through postnatal interactions with the p… (voir plus)hysical and socio-cultural environment. Here, we introduce a three-level computational model of information processing and acquisition of cognitive abilities. We propose minimal architectural requirements to build these levels and how the parameters affect their performance and relationships. The first sensorimotor level handles local nonconscious processing, here during a visual classification task. The second level or cognitive level globally integrates the information from multiple local processors via long-ranged connections and synthesizes it in a global, but still nonconscious manner. The third and cognitively highest level handles the information globally and consciously. It is based on the Global Neuronal Workspace (GNW) theory and is referred to as conscious level. We use trace and delay conditioning tasks to, respectively, challenge the second and third levels. Results first highlight the necessity of epigenesis through selection and stabilization of synapses at both local and global scales to allow the network to solve the first two tasks. At the global scale, dopamine appears necessary to properly provide credit assignment despite the temporal delay between perception and reward. At the third level, the presence of interneurons becomes necessary to maintain a self-sustained representation within the GNW in the absence of sensory input. Finally, while balanced spontaneous intrinsic activity facilitates epigenesis at both local and global scales, the balanced excitatory-inhibitory ratio increases performance. Finally, we discuss the plausibility of the model in both neurodevelopmental and artificial intelligence terms.
2022-01-25
bioRxiv (preprint)
doi.org
Analysis of the Human Pineal Proteome by Mass Spectrometry
Mariette Matondo
Guillaume Dumas
Erik Maronde
2022-01-01
Methods in molecular biology (publié)
doi.org
Generative Models of Brain Dynamics -- A review
Mahta Ramezanian Panahi
Germán Abrevaya
Jean-Christophe Gagnon-Audet
Vikram Voleti
Irina Rish
Guillaume Dumas
The principled design and discovery of biologically- and physically-informed models of neuronal dynamics has been advancing since the mid-tw… (voir plus)entieth century. Recent developments in artificial intelligence (AI) have accelerated this progress. This review article gives a high-level overview of the approaches across different scales of organization and levels of abstraction. The studies covered in this paper include fundamental models in computational neuroscience, nonlinear dynamics, data-driven methods, as well as emergent practices. While not all of these models span the intersection of neuroscience, AI, and system dynamics, all of them do or can work in tandem as generative models, which, as we argue, provide superior properties for the analysis of neuroscientific data. We discuss the limitations and unique dynamical traits of brain data and the complementary need for hypothesis- and data-driven modeling. By way of conclusion, we present several hybrid generative models from recent literature in scientific machine learning, which can be efficiently deployed to yield interpretable models of neural dynamics.
2021-12-22
ArXiv (prépublication)
arxiv.org
arxiv.org
Preference for biological motion is reduced in ASD: implications for clinical trials and the search for biomarkers
Luke Mason
F. Shic
T. Falck-Ytter
Bhismadev Chakrabarti
Tony Charman
Eva Loth
Julian Tillmann
Tobias Banaschewski
Simon Baron-Cohen
Sven Bölte
J. Buitelaar
Sarah Durston
Bob Oranje
Antonio Persico
C. Beckmann
Thomas Bougeron
Flavio Dell’Acqua
Christine Ecker
Carolin Moessnang
D. Murphy … (voir 49 de plus)
M. H. Johnson
Emily J. H. Jones
Jumana Sara Sarah Carsten Michael Daniel Claudia Yvette Chris Ineke Daisy Guillaume Jessica Vincent Pilar David Lindsay Joerg Rosemary Meng-Chuan Xavier Liogier Michael V. David J. René Andre Maarten Andreas Nico Bethany Laurence Marianne Gahan Barbara Amber Jessica Roberto Antonia San José Emily Will Roberto Heike Jack Steve C. R. Caroline Marcel P. Ahmad
Jumana Sara Sarah Carsten Michael Daniel Claudia Yvette C Ahmad Ambrosino Baumeister Bours Brammer Brandeis
Jumana Ahmad
Sara Ambrosino
Sarah Baumeister
Carsten Bours
Michael Brammer
Daniel Brandeis
Claudia Brogna
Yvette de Bruijn
Christopher H. Chatham
Ineke Cornelissen
Daisy Crawley
Guillaume Dumas
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
Nico Bast
Beth Oakley
Laurence O’Dwyer
Marianne Oldehinkel
Gahan Pandina
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
2021-12-15
Molecular Autism (publié)
doi.org
Early Transcriptional Changes in Rabies Virus-Infected Neurons and Their Impact on Neuronal Functions
Seonhee Kim
Florence Larrous
Hugo Varet
Rachel Legendre
Lena Feige
Guillaume Dumas
Rebecca Matsas
Georgia Kouroupi
Regis Grailhe
Hervé Bourhy
2021-12-13
Frontiers in Microbiology (publié)
doi.org
Maternal chemosignals enhance infant-adult brain-to-brain synchrony
Yaara Endevelt-Shapira
Amir Djalovski
Guillaume Dumas
Ruth Feldman
2021-12-10
Science Advances (publié)
doi.org