Portrait de Danilo Bzdok

Danilo Bzdok

Membre académique principal
bzdokdan@mila.quebec
Chaire en IA Canada-CIFAR
Professeur agrégé, McGill University
Sujets de recherche
Apprentissage profond
Biologie computationnelle
Grands modèles de langage (LLM)
Traitement du langage naturel

Biographie

Danilo Bzdok est informaticien et médecin de formation. Il possède une double formation unique en neurosciences systémiques et en algorithmes d'apprentissage automatique. Après une formation à l'Université d'Aix-la-Chapelle (RWTH) (Allemagne), à l'Université de Lausanne (Suisse) et à la Harvard Medical School (États-Unis), il a obtenu un doctorat en neurosciences du Centre de recherche de Jülich (Allemagne) et un doctorat en informatique dans le domaine des statistiques d'apprentissage automatique à l'INRIA Saclay et à NeuroSpin (Paris, France). Il est actuellement professeur agrégé à la Faculté de médecine de l'Université McGill et titulaire d’une chaire en IA Canada-CIFAR à Mila – Institut québécois d'intelligence artificielle. Son activité de recherche interdisciplinaire est centrée sur la réduction des lacunes dans la connaissance des bases cérébrales des types de pensée qui définissent l'être humain, afin de découvrir les principes clés de conception computationnelle qui sous-tendent l'intelligence humaine.

Étudiants actuels

Publications

The Cost of Untracked Diversity in Brain-Imaging Prediction
Oualid Benkarim
Casey Paquola
Bo-yong Park
Valeria Kebets
Seok-Jun Hong
Reinder Vos de Wael
Shaoshi Zhang
B.T. Thomas Yeo
Michael Eickenberg
Tian Ge
Jean-Baptiste Poline
Boris Bernhardt
Danilo Bzdok
Brain-imaging research enjoys increasing adoption of supervised machine learning for singlesubject disease classification. Yet, the success … (voir plus)of these algorithms likely depends on population diversity, including demographic differences and other factors that may be outside of primary scientific interest. Here, we capitalize on propensity scores as a composite confound index to quantify diversity due to major sources of population stratification. We delineate the impact of population heterogeneity on the predictive accuracy and pattern stability in two separate clinical cohorts: the Autism Brain Imaging Data Exchange (ABIDE, n=297) and the Healthy Brain Network (HBN, n=551). Across various analysis scenarios, our results uncover the extent to which cross-validated prediction performances are interlocked with diversity. The instability of extracted brain patterns attributable to diversity is located preferentially to the default mode network. Our collective findings highlight the limitations of prevailing deconfounding practices in mitigating the full consequences of population diversity.
2021-06-16
bioRxiv (prépublication)
doi.org
Publisher Correction: The default network of the human brain is associated with perceived social isolation
R. Nathan Spreng
Emile Dimas
Laetitia Mwilambwe-Tshilobo
Alain Dagher
Philipp Koellinger
Gideon Nave
Anthony Ong
Julius M. Kernbach
Thomas V. Wiecki
Tian Ge
Yue Li
Avram J. Holmes
B. T. Thomas Yeo
Gary R. Turner
Robin I. M. Dunbar
Danilo Bzdok
2021-05-20
Nature Communications (publié)
doi.org
Variability in Brain Structure and Function Reflects Lack of Peer Support
Matthias Schurz
Lucina Q. Uddin
Philipp Kanske
Claus Lamm
Jérôme Sallet
Boris C. Bernhardt
Rogier B. Mars
Danilo Bzdok
Humans are a highly social species. Complex interactions for mutual support range from helping neighbors to building social welfare institut… (voir plus)ions. During times of distress or crisis, sharing life experiences within one’s social circle is critical for well-being. By translating pattern-learning algorithms to the UK Biobank imaging-genetics cohort (n = ~40 000 participants), we have delineated manifestations of regular social support in multimodal whole-brain measurements. In structural brain variation, we identified characteristic volumetric signatures in the salience and limbic networks for high- versus low-social support individuals. In patterns derived from functional coupling, we also located interindividual differences in social support in action–perception circuits related to binding sensory cues and initiating behavioral responses. In line with our demographic profiling analysis, the uncovered neural substrates have potential implications for loneliness, substance misuse, and resilience to stress.
2021-05-12
Cerebral Cortex (New York, NY) (publié)
doi.org
How does hemispheric specialization contribute to human-defining cognition?
Gesa Hartwigsen
Yoshua Bengio
Danilo Bzdok
2021-05-10
Neuron (publié)
doi.org
Phenotypical predictors of pregnancy-related restless legs syndrome and their association with basal ganglia and the limbic circuits
Natalia Chechko
Jeremy Lefort-Besnard
Tamme W. Goecke
Markus Frensch
Patricia Schnakenberg
Susanne Stickel
Danilo Bzdok
Restless legs syndrome (RLS) in pregnancy is a common disorder with a multifactorial etiology. A neurological and obstetrical cohort of 308 … (voir plus)postpartum women was screened for RLS within 1 to 6 days of childbirth and 12 weeks postpartum. Of the 308 young mothers, 57 (prevalence rate 19%) were identified as having been affected by RLS symptoms in the recently completed pregnancy. Structural and functional MRI was obtained from 25 of these 57 participants. A multivariate two-window algorithm was employed to systematically chart the relationship between brain structures and phenotypical predictors of RLS. A decreased volume of the parietal, orbitofrontal and frontal areas shortly after delivery was found to be linked to persistent RLS symptoms up to 12 weeks postpartum, the symptoms' severity and intensity in the most recent pregnancy, and a history of RLS in previous pregnancies. The same negative relationship was observed between brain volume and not being married, not receiving any iron supplement and higher numbers of stressful life events. High cortisol levels, being married and receiving iron supplements, on the other hand, were found to be associated with increased volumes in the bilateral striatum. Investigating RLS symptoms in pregnancy within a brain-phenotype framework may help shed light on the heterogeneity of the condition.
2021-05-10
Scientific Reports (publié)
doi.org
Editorial: Social Interaction in Neuropsychiatry
Victoria Leong
Danilo Bzdok
Frieder M. Paulus
Kevin Pelphrey
Elizabeth Redcay
Leonhard Schilbach
2021-04-28
Frontiers in Psychiatry (publié)
doi.org
Generative lesion pattern decomposition of cognitive impairment after stroke
Anna K. Bonkhoff
Jae-Sung Lim
Hee-Joon Bae
Nick A. Weaver
Hugo J. Kuijf
J. Matthijs Biesbroek
Natalia S. Rost
Danilo Bzdok
Cognitive impairment is a frequent and disabling sequela of stroke. There is however incomplete understanding of how lesion topographies in … (voir plus)the left and right cerebral hemisphere brain interact to cause distinct cognitive deficits. We integrated machine learning and Bayesian hierarchical modelling to enable a hemisphere-aware analysis of 1080 acute ischaemic stroke patients with deep profiling ∼3 months after stroke. We show the relevance of the left hemisphere in the prediction of language and memory assessments and relevance of the right hemisphere in the prediction of visuospatial functioning. Global cognitive impairments were equally well predicted by lesion topographies from both sides. Damage to the hippocampal and occipital regions on the left was particularly informative about lost naming and memory functions, while damage to these regions on the right was linked to lost visuospatial functioning. Global cognitive impairment was predominantly linked to lesioned tissue in the supramarginal and angular gyrus, the post-central gyrus as well as the lateral occipital and opercular cortices of the left hemisphere. Hence, our analysis strategy uncovered that lesion patterns with unique hemispheric distributions are characteristic of how cognitive capacity is lost due to ischaemic brain tissue damage.
2021-03-31
Brain Communications (publié)
doi.org
Loneliness and Neurocognitive Aging
R. Nathan Spreng
Danilo Bzdok
2021-03-28
Advances in Geriatric Medicine and Research (publié)
doi.org
Mapping gene transcription and neurocognition across human neocortex
Justine Y. Hansen
Ross D. Markello
Jacob W. Vogel
Jakob Seidlitz
Danilo Bzdok
Bratislav Misic
2021-03-24
Nature Human Behaviour (publié)
doi.org
Functional specialization within the inferior parietal lobes across cognitive domains
Ole Numssen
Danilo Bzdok
Gesa Hartwigsen
The inferior parietal lobe (IPL) is a key neural substrate underlying diverse mental processes, from basic attention to language and social … (voir plus)cognition, that define human interactions. Its putative domain-global role appears to tie into poorly understood differences between cognitive domains in both hemispheres. Across attentional, semantic, and social cognitive tasks, our study explored functional specialization within the IPL. The task specificity of IPL subregion activity was substantiated by distinct predictive signatures identified by multivariate pattern-learning algorithms. Moreover, the left and right IPL exerted domain-specific modulation of effective connectivity among their subregions. Task-evoked functional interactions of the anterior and posterior IPL subregions involved recruitment of distributed cortical partners. While anterior IPL subregions were engaged in strongly lateralized coupling links, both posterior subregions showed more symmetric coupling patterns across hemispheres. Our collective results shed light on how under-appreciated hemispheric specialization in the IPL supports some of the most distinctive human mental capacities.
2021-03-01
eLife (publié)
doi.org
The neural correlates of ongoing conscious thought
Jonathan Smallwood
Adam Turnbull
Hao-Ting Wang
Nerissa S.P. Ho
Giulia L. Poerio
Theodoros Karapanagiotidis
Delali Konu
Brontë Mckeown
Meichao Zhang
Charlotte Murphy
Deniz Vatansever
Danilo Bzdok
Mahiko Konishi
Robert Leech
Paul Seli
Jonathan W. Schooler
Boris C Bernhardt
Daniel S. Margulies
Elizabeth Jefferies
2021-01-31
iScience (publié)
doi.org
Author response: Functional specialization within the inferior parietal lobes across cognitive domains
Ole Numssen
Danilo Bzdok
Gesa Hartwigsen
2021-01-20
(publié)
doi.org