Portrait de Danilo Bzdok

Danilo Bzdok

Membre académique principal
bzdokdan@mila.quebec
Chaire en IA Canada-CIFAR
Professeur agrégé, McGill University, Département de génie biomédicale
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

Karan Bali Bali
Doctorat - McGill
Gregory Bell
Doctorat - McGill
Yanis Bencheikh
Maîtrise recherche - HEC
Co-superviseur⋅e :
Tegan Maharaj
Site web
Github
Anwesha Bhattacharya
Doctorat - McGill
Titouan Brunel
Collaborateur·rice de recherche - CentraleSupélec
Pedro Carneiro Carneiro
Doctorat - McGill
Arthur Communal
Collaborateur·rice de recherche - École Polytechnique
Liam Hodgson
Doctorat - McGill
Ryan McPhedrain McPhedrain
Postdoctorat - McGill
David Payette
Maîtrise recherche - McGill
Sepehr Radmannia
Visiteur de recherche indépendant - McGill
Karin Saltoun
Doctorat - McGill
Chloé Savignac
Doctorat - McGill
Github
Google Scholar
Jack Stanley
Doctorat - McGill
Site web
Github
Google Scholar
Praneet Suresh
Doctorat - McGill
Google Scholar
Yutong Zheng
Doctorat - McGill
Le Zhou
Doctorat - McGill

Publications

Using rare genetic mutations to revisit structural brain asymmetry
Jakub Kopal
Kuldeep Kumar
Kimia Shafighi
Karin Saltoun
Claudia Modenato
Clara A. Moreau
Guillaume Huguet
Martineau Jean-Louis
Charles-Olivier Martin
Charles-Olivier Martin
Zohra Saci
Nadine Younis
Elise Douard
Khadije Jizi
Alexis Beauchamp-Chatel
Leila Kushan
Ana I. Silva
Marianne B. M. van den Bree
David E. J. Linden
Michael J. Owen … (voir 11 de plus)
Jeremy Hall
Sarah Lippé
Bogdan Draganski
Ida E. Sønderby
Ole A. Andreassen
David C. Glahn
Paul M. Thompson
Carrie E. Bearden
Robert Zatorre
Sébastien Jacquemont
Danilo Bzdok
Asymmetry between the left and right brain is a key feature of brain organization. Hemispheric functional specialization underlies some of t… (voir plus)he most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variant studies, which typically exert small effects on brain phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We quantitatively dissected the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior mapping highlights the consequences of genetically controlled brain lateralization on human-defining cognitive traits.
2023-04-17
bioRxiv (prépublication)
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
2023-03-31
Neuroscience and Biobehavioral Reviews (publié)
doi.org
Bayesian stroke modeling details sex biases in the white matter substrates of aphasia
Julius M. Kernbach
Gesa Hartwigsen
Jae-Sung Lim
Hee-Joon Bae
Kyung-Ho Yu
Gottfried Schlaug
Anna Bonkhoff
Natalia S. Rost
Danilo Bzdok
Ischemic cerebrovascular events often lead to aphasia. Previous work provided hints that such strokes may affect women and men in distinct w… (voir plus)ays. Women tend to suffer strokes with more disabling language impairment, even if the lesion size is comparable to men. In 1401 patients, we isolate data-led representations of anatomical lesion patterns and hand-tailor a Bayesian analytical solution to carefully model the degree of sex divergence in predicting language outcomes ~3 months after stroke. We locate lesion-outcome effects in the left-dominant language network that highlight the ventral pathway as a core lesion focus across different tests of language performance. We provide detailed evidence for sex-specific brain-behavior associations in the domain-general networks associated with cortico-subcortical pathways, with unique contributions of the fornix in women and cingular fiber bundles in men. Our collective findings suggest diverging white matter substrates in how stroke causes language deficits in women and men. Clinically acknowledging such sex disparities has the potential to improve personalized treatment for stroke patients worldwide.
2023-03-30
Communications Biology (publié)
doi.org
Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease
Andrea I. Luppi
S. Parker Singleton
Justine Y. Hansen
Danilo Bzdok
Amy Kuceyeski
Richard F. Betzel
Bratislav Misic
Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain’s network architect… (voir plus)ure. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic engine. We also systematically incorporate neurotransmitter receptor density maps (18 receptors and transporters) and disease-related cortical abnormality maps (11 neurodegenerative, psychiatric and neurodevelopmental diseases; N = 17 000 patients, N = 22 000 controls). Integrating large-scale multimodal neuroimaging data from functional MRI, diffusion tractography, cortical morphometry, and positron emission tomography, we simulate how anatomically-guided transitions between cognitive states can be reshaped by pharmacological or pathological perturbation. Our results provide a comprehensive look-up table charting how brain network organisation and chemoarchitecture interact to manifest different cognitive topographies. This computational framework establishes a principled foundation for systematically identifying novel ways to promote selective transitions between desired cognitive topographies.
2023-03-16
bioRxiv (prépublication)
doi.org
Investigating the neural correlates of affective mentalizing and their association with general intelligence in patients with schizophrenia
Wladimir Tantchik
Melissa J. Green
Yann Quidé
Susanne Erk
Sebastian Mohnke
Carolin Wackerhagen
Nina Romanczuk-Seiferth
Heike Tost
Kristina Schwarz
Carolin Moessnang
Danilo Bzdok
Andreas Meyer-Lindenberg
Andreas Heinz
Henrik Walter
2023-03-12
Schizophrenia Research (inconnu)
doi.org
The end game: respecting major sources of population diversity
Jakub Kopal
Lucina Q. Uddin
Danilo Bzdok
Human neuroscience is enjoying burgeoning population data resources: large-scale cohorts with thousands of participant profiles of gene expr… (voir plus)ession, brain scanning and sociodemographic measures. The depth of phenotyping puts us in a better position than ever to fully embrace major sources of population diversity as effects of interest to illuminate mechanisms underlying brain health.
2023-03-02
Nature Methods (publié)
doi.org
Rare CNVs and phenome-wide profiling highlight brain structural divergence and phenotypical convergence
Jakub Kopal
Kuldeep Kumar
Karin Saltoun
Claudia Modenato
Clara A. Moreau
Sandra Martin-Brevet
Guillaume Huguet
Martineau Jean-Louis
Charles-Olivier Martin
Charles-Olivier Martin
Zohra Saci
Nadine Younis
Petra Tamer
Elise Douard
Anne M. Maillard
Borja Rodriguez-Herreros
Aurélie Pain
Sonia Richetin
Leila Kushan
Ana I. Silva … (voir 13 de plus)
Marianne B. M. van den Bree
David E. J. Linden
Michael J. Owen
Jeremy Hall
Sarah Lippé
Bogdan Draganski
Ida E. Sønderby
Ole A. Andreassen
David C. Glahn
Paul M. Thompson
Carrie E. Bearden
Sébastien Jacquemont
Danilo Bzdok
Copy number variations (CNVs) are rare genomic deletions and duplications that can affect brain and behaviour. Previous reports of CNV pleio… (voir plus)tropy imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, existing studies have primarily examined single CNV loci in small clinical cohorts. It remains unknown, for example, how distinct CNVs escalate vulnerability for the same developmental and psychiatric disorders. Here we quantitatively dissect the associations between brain organization and behavioural differentiation across 8 key CNVs. In 534 CNV carriers, we explored CNV-specific brain morphology patterns. CNVs were characteristic of disparate morphological changes involving multiple large-scale networks. We extensively annotated these CNV-associated patterns with ~1,000 lifestyle indicators through the UK Biobank resource. The resulting phenotypic profiles largely overlap and have body-wide implications, including the cardiovascular, endocrine, skeletal and nervous systems. Our population-level investigation established brain structural divergences and phenotypical convergences of CNVs, with direct relevance to major brain disorders.
2023-03-01
Nature Human Behaviour (inconnu)
doi.org
Social isolation is linked to classical risk factors of Alzheimer's disease-related dementias
Kimia Shafighi
Sylvia Villeneuve
Pedro Rosa Neto
AmanPreet Badhwar
Judes Poirier
Vaibhav Sharma
Yasser Iturria Medina
Patricia P. Silveira
Laurette Dubé
David Glahn
Danilo Bzdok
Alzheimer’s disease and related dementias is a major public health burden–compounding over upcoming years due to longevity. Recently, cl… (voir plus)inical evidence hinted at the experience of social isolation in expediting dementia onset. In 502,506 UK Biobank participants and 30,097 participants from the Canadian Longitudinal Study of Aging, we revisited traditional risk factors for developing dementia in the context of loneliness and lacking social support. Across these measures of subjective and objective social deprivation, we have identified strong links between individuals’ social capital and various indicators of Alzheimer’s disease and related dementias risk, which replicated across both population cohorts. The quality and quantity of daily social encounters had deep connections with key aetiopathological factors, which represent 1) personal habits and lifestyle factors, 2) physical health, 3) mental health, and 4) societal and external factors. Our population-scale assessment suggest that social lifestyle determinants are linked to most neurodegeneration risk factors, highlighting them as promising targets for preventive clinical action.
2023-01-31
PLOS ONE (publié)
doi.org
Disentangling poststroke cognitive deficits and their neuroanatomical correlates through combined multivariable and multioutcome lesion‐symptom mapping
Nick A. Weaver
Muhammad Hasnain Mamdani
Jae‐Sung Lim
Johannes Matthijs Biesbroek
Geert Jan Biessels
Irene M. C. Huenges Wajer
Yeonwook Kang
Beom Joon Kim
Byung‐Chul Lee
Keon‐Joo Lee
Kyung‐Ho Yu
Hee‐Joon Bae
Danilo Bzdok
Hugo J. Kuijf
Studies in patients with brain lesions play a fundamental role in unraveling the brain's functional anatomy. Lesion‐symptom mapping (LSM) … (voir plus)techniques can relate lesion location to cognitive performance. However, a limitation of current LSM approaches is that they can only evaluate one cognitive outcome at a time, without considering interdependencies between different cognitive tests. To overcome this challenge, we implemented canonical correlation analysis (CCA) as combined multivariable and multioutcome LSM approach. We performed a proof‐of‐concept study on 1075 patients with acute ischemic stroke to explore whether addition of CCA to a multivariable single‐outcome LSM approach (support vector regression) could identify infarct locations associated with deficits in three well‐defined verbal memory functions (encoding, consolidation, retrieval) based on four verbal memory subscores derived from the Seoul Verbal Learning Test (immediate recall, delayed recall, recognition, learning ability). We evaluated whether CCA could extract cognitive score patterns that matched prior knowledge of these verbal memory functions, and if these patterns could be linked to more specific infarct locations than through single‐outcome LSM alone. Two of the canonical modes identified with CCA showed distinct cognitive patterns that matched prior knowledge on encoding and consolidation. In addition, CCA revealed that each canonical mode was linked to a distinct infarct pattern, while with multivariable single‐outcome LSM individual verbal memory subscores were associated with largely overlapping patterns. In conclusion, our findings demonstrate that CCA can complement single‐outcome LSM techniques to help disentangle cognitive functions and their neuroanatomical correlates.
2023-01-19
Human Brain Mapping (publié)
doi.org
Functional architecture of the aging brain
Roni Setton
Laetitia Mwilambwe-Tshilobo
Manesh Girn
Amber W. Lockrow
Giulia Baracchini
Alexander J. Lowe
Benjamin N. Cassidy
Jian Li
Wen-Ming Luh
Danilo Bzdok
Richard M. Leahy
Tian Ge
Daniel S. Margulies
Bratislav Misic
Boris C Bernhardt
W. Dale Stevens
Felipe De Brigard
Prantik Kundu
Gary R. Turner
R. Nathan Spreng
The intrinsic functional connectome can reveal how a lifetime of learning and lived experience is represented in the functional architecture… (voir plus) of the aging brain. We investigated whether network dedifferentiation, a hallmark of brain aging, reflects a global shift in network dynamics, or comprises network-specific changes that reflect the changing landscape of aging cognition. We implemented a novel multi-faceted strategy involving multi-echo fMRI acquisition and de-noising, individualized cortical parcellation, and multivariate (gradient and edge-level) functional connectivity methods. Twenty minutes of resting-state fMRI data and cognitive assessments were collected in younger (n=181) and older (n=120) adults. Dimensionality in the BOLD signal was lower for older adults, consistent with global network dedifferentiation. Functional connectivity gradients were largely age-invariant. In contrast, edge-level connectivity showed widespread changes with age, revealing discrete, network-specific dedifferentiation patterns. Visual and somatosensory regions were more integrated within the functional connectome; default and frontoparietal regions showed greater coupling; and the dorsal attention network was less differentiated from transmodal regions. Associations with cognition suggest that the formation and preservation of integrated, large-scale brain networks supports complex cognitive abilities. However, into older adulthood, the connectome is dominated by large-scale network disintegration, global dedifferentiation and network-specific dedifferentiation associated with age-related cognitive change.
2022-12-31
(publié)
www.semanticscholar.org
Home alone: A population neuroscience investigation of brain morphology substrates
MaryAnn Noonan
Chris Zajner
Danilo Bzdok
As a social species, ready exchange with peers is a pivotal asset - our “social capital”. Yet, single-person households have come to per… (voir plus)vade metropolitan cities worldwide, with unknown consequences in the long run. Here, we systematically explore the morphological manifestations associated with singular living in ∼40,000 UK Biobank participants. The uncovered population-level signature spotlights the highly associative default mode network, in addition to findings such as in the amygdala central, cortical and corticoamygdaloid nuclei groups, as well as the hippocampal fimbria and dentate gyrus. Sex-stratified analyses revealed male-specific neural substrates, including somatomotor, saliency and visual systems, while female-specific neural substrates centred on the dorsomedial prefrontal cortex. In line with our demographic profiling results, the discovered neural imprint of living alone is potentially linked to alcohol and tobacco consumption, anxiety, sleep quality as well as daily TV watching. The secular trend for solitary living will require new answers from public-health decision makers.
2022-12-31
NeuroImage (publié)
doi.org
Homotopic local-global parcellation of the human cerebral cortex from resting-state functional connectivity
Xiaoxuan Yan
Ru Kong
Aihuiping Xue
Qing Yang
Csaba Orban
Lijun An
Avram J. Holmes
Xing Qian
Jianzhong Chen
Xi-Nian Zuo
Juan Helen Zhou
Marielle V Fortier
Ai Peng Tan
Peter Gluckman
Yap Seng Chong
Michael J Meaney
Danilo Bzdok
Simon B. Eickhoff
B.T. Thomas Yeo
Resting-state fMRI is commonly used to derive brain parcellations, which are widely used for dimensionality reduction and interpreting human… (voir plus) neuroscience studies. We previously developed a model that integrates local and global approaches for estimating areal-level cortical parcellations. The resulting local-global parcellations are often referred to as the Schaefer parcellations. However, the lack of homotopic correspondence between left and right Schaefer parcels has limited their use for brain lateralization studies. Here, we extend our previous model to derive homotopic areal-level parcellations. Using resting-fMRI and task-fMRI across diverse scanners, acquisition protocols, preprocessing and demographics, we show that the resulting homotopic parcellations are as homogeneous as the Schaefer parcellations, while being more homogeneous than five publicly available parcellations. Furthermore, weaker correlations between homotopic parcels are associated with greater lateralization in resting network organization, as well as lateralization in language and motor task activation. Finally, the homotopic parcellations agree with the boundaries of a number of cortical areas estimated from histology and visuotopic fMRI, while capturing sub-areal (e.g., somatotopic and visuotopic) features. Overall, these results suggest that the homotopic local-global parcellations represent neurobiologically meaningful subdivisions of the human cerebral cortex and will be a useful resource for future studies. Multi-resolution parcellations estimated from 1479 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Yan2023_homotopic).
2022-12-31
NeuroImage (publié)
doi.org