Portrait of Danilo Bzdok

Danilo Bzdok

Core Academic Member

bzdokdan@mila.quebec

Canada CIFAR AI Chair

Associate Professor, McGill University, Department of Biomedical Engineering

Research Topics

Computational Biology

Deep Learning

Large Language Models (LLM)

Natural Language Processing

Biography

Danilo Bzdok is a computer scientist and medical doctor by training with a unique dual background in systems neuroscience and machine learning algorithms. After training at RWTH Aachen University (Germany), Université de Lausanne (Switzerland) and Harvard Medical School, Bzdok completed two doctoral degrees, one in neuroscience at Forschungszentrum Jülich in Germany, and another in computer science (machine learning statistics) at INRIA–Saclay and the Neurospin brain imaging centre in Paris.

Danilo is currently an associate professor at McGill University’s Faculty of Medicine and a Canada CIFAR AI Chair at Mila – Quebec Artificial Intelligence Institute. His interdisciplinary research centres around narrowing knowledge gaps in the brain basis of human-defining types of thinking in order to uncover key computational design principles underlying human intelligence.

Current Students

Karan Bali Bali

PhD - McGill University

karan.bali@mila.quebec

PhD - McGill University

gregory.bell@mila.quebec

Anwesha Bhattacharya

PhD - McGill University

anwesha.bhattacharya@mila.quebec

Undergraduate - CentraleSupélec

titouan.brunel@mila.quebec

Pedro Carneiro Carneiro

PhD - McGill University

pedro.carneiro@mila.quebec

Arthur Communal

Collaborating researcher - École Polytechnique Montréal Paris

arthur.communal@mila.quebec

PhD - McGill University

liam.hodgson@mila.quebec

Ryan McPhedrain McPhedrain

Postdoctorate - McGill University

ryan.mcphedrain@mail.mcgill.ca

Master's Research - McGill University

david.payette@mila.quebec

Sepehr Radmannia

Independent visiting researcher - McGill University

sradmannia@gmail.com

PhD - McGill University

karin.saltoun@mila.quebec

Chloé Savignac

PhD - McGill University

chloe.savignac@mila.quebec

PhD - McGill University

jack.stanley@mila.quebec

PhD - McGill University

praneet.suresh@mila.quebec

Audric Trarieux

Collaborating researcher - Aix-Marseille Université

audric.trarieux@mila.quebec

PhD - McGill University

yutong.zheng@mail.mcgill.ca

PhD - McGill University

le.zhou@mila.quebec

Blog Posts

a Blury picture of a brain representation on a blue background

April 7, 2026

Mila’s AI drives world’s largest study on psychedelics

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A tab representation of the Pre trained CLIP Vision Transformer

October 8, 2025

Why AI Models Hallucinate and How to Fix Them

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March 25, 2025

Using LLMs to better understand autism diagnosis

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Towards Precision Medicine: Understanding Inference and Prediction Divergence in Biomedicine

September 8, 2020

Towards Precision Medicine: Understanding Inference and Prediction Divergence in Biomedicine

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Publications

Aberrant functional brain network organization is associated with relapse during 1-year follow-up in alcohol-dependent patients

Justin Böhmer

Pablo Reinhardt

Maria Garbusow

Michael Marxen

Michael N. Smolka

U. Zimmermann

Andreas Heinz

Eva Friedel

Johann Kruschwitz

Henrik Walter

Alcohol dependence (AD) is a debilitating disease associated with high relapse rates even after long periods of abstinence. Thus, elucidatin… (see more)g neurobiological substrates of relapse risk is fundamental for the development of novel targeted interventions that could promote long-lasting abstinence. In the present study, we analyzed resting-state functional magnetic resonance imaging (rsfMRI) data from a sample of recently detoxified AD patients (n = 93) who were followed-up for 12 months after rsfMRI assessment. Specifically, we employed graph theoretic analyses to compare functional brain network topology and functional connectivity between future relapsers (REL, n = 59), future abstainers (ABS, n = 28) and age and gender matched controls (CON, n = 83). Our results suggest increased whole-brain network segregation, decreased global network integration and overall blunted connectivity strength in REL compared to CON. Conversely, we found evidence for a comparable network architecture in ABS relative to CON. At the nodal level, REL exhibited decreased integration and decoupling between multiple brain systems compared to CON, encompassing regions associated with higher-order executive functions, sensory and reward processing. Among AD patients, increased coupling between nodes implicated in reward valuation and salience attribution constitutes a particular risk factor for future relapse. Importantly, aberrant network organization in REL was consistently associated with shorter abstinence duration during follow-up, portending to a putative neural signature of relapse risk in AD. Future research should further evaluate the potential diagnostic value of the identified changes in network topology and functional connectivity for relapse prediction at the individual subject level.

2023-10-01

Addiction Biology (published)

Bayesian modelling disentangles language versus executive control disruption in stroke

Gesa Hartwigsen

Jae-Sung Lim

Hee-Joon Bae

Kyung-Ho Yu

Hugo J. Kuijf

Nick A. Weaver

J. Matthijs Biesbroek

Stroke is the leading cause of long-term disability worldwide. Incurred brain damage disrupts cognition, often with persisting deficits in l… (see more)anguage and executive capacities. Despite their clinical relevance, the commonalities, and differences of language versus executive control impairments remain under-specified. We tailored a Bayesian hierarchical modeling solution in a largest-of-its-kind cohort (1080 stroke patients) to deconvolve language and executive control in the brain substrates of stroke insults. Four cognitive factors distinguished left- and right-hemispheric contributions to ischemic tissue lesion. One factor delineated language and general cognitive performance and was mainly associated with damage to left-hemispheric brain regions in the frontal and temporal cortex. A factor for executive control summarized control and visual-constructional abilities. This factor was strongly related to right-hemispheric brain damage of posterior regions in the occipital cortex. The interplay of language and executive control was reflected in two factors: executive speech functions and verbal memory. Impairments on both were mainly linked to left-hemispheric lesions. These findings shed light onto the causal implications of hemispheric specialization for cognition; and make steps towards subgroup-specific treatment protocols after stroke.

2023-08-06

bioRxiv (preprint)

Multivariate analytical approaches for investigating brain-behavior relationships

E. Leighton Durham

Andrew J. Stier

Carlos Cardenas-Iniguez

Gabrielle E. Reimann

Hee Jung Jeong

Randolph M. Dupont

Xiaoyu Dong

Tyler M. Moore

Marc G. Berman

Benjamin B. Lahey

Antonia N. Kaczkurkin

2023-07-30

Frontiers in Neuroscience (published)

The default network dominates neural responses to evolving movie stories

Filip Milisav

Avram J. Holmes

Georgios D. Mitsis

Bratislav Misic

Emily S. Finn

Neuroscientific studies exploring real-world dynamic perception often overlook the influence of continuous changes in narrative content. In … (see more)our research, we utilize machine learning tools for natural language processing to examine the relationship between movie narratives and neural responses. By analyzing over 50,000 brain images of participants watching Forrest Gump from the studyforrest dataset, we find distinct brain states that capture unique semantic aspects of the unfolding story. The default network, associated with semantic information integration, is the most engaged during movie watching. Furthermore, we identify two mechanisms that underlie how the default network liaises with the amygdala and hippocampus. Our findings demonstrate effective approaches to understanding neural processes in everyday situations and their relation to conscious awareness.

2023-07-13

Nature Communications (published)

Distinctive Whole-brain Cell-Types Predict Tissue Damage Patterns in Thirteen Neurodegenerative Conditions

Veronika Pak

Quadri Adewale

Mahsa Dadar

Yashar Zeighami

Yasser Iturria-Medina

Abstract For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most whole-brain neu… (see more)rodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell-types’ contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell-types extensively predicts tissue damage in eleven neurodegenerative disorders, including early- and late-onset Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, frontotemporal dementia, and tauopathies. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell-types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, on spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorders pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.

2023-06-08

bioRxiv (preprint)

156. Modeling Eye Gaze to Videos Using Dynamic Trajectory Variability Analysis

Qianying Wu

Na Yeon Kim

Jasmin Turner

Umit Keles

Lynn Paul

Ralph Adolphs

2023-04-30

Biological Psychiatry (published)

Using rare genetic mutations to revisit structural brain asymmetry

Kuldeep Kumar

Kimia Shafighi

Claudia Modenato

Clara A. Moreau

Guillaume Huguet

Martineau Jean-Louis

Charles-Olivier Martin

Zohra Saci

Nadine Younis

Élise Douard

Khadije Jizi

Alexis Beauchamp-Chatel

Leila Kushan

Ana I. Silva

Marianne B. M. van den Bree

David E. J. Linden

Michael J. Owen

Jeremy Hall … (see 10 more)

Sarah Lippé

Bogdan Draganski

Ida E. Sønderby

Ole A. Andreassen

David C. Glahn

Paul M. Thompson

Carrie E. Bearden

Robert Zatorre

Sébastien Jacquemont

Asymmetry between the left and right brain is a key feature of brain organization. Hemispheric functional specialization underlies some of t… (see more)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 (preprint)

Genesis, modelling and methodological remedies to autism heterogeneity

Juliette Rabot

Eya‐mist Rødgaard

Ridha Joober

Guillaume Dumas

Boris C Bernhardt

Sébastien Jacquemont

Laurent Mottron

2023-03-31

Neuroscience and Biobehavioral Reviews (published)

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

Ischemic cerebrovascular events often lead to aphasia. Previous work provided hints that such strokes may affect women and men in distinct w… (see more)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 (published)

Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease

Andrea I. Luppi

S. Parker Singleton

Justine Y. Hansen

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… (see more)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 (preprint)

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

Andreas Meyer-Lindenberg

Andreas Heinz

Henrik Walter

2023-03-12

Schizophrenia Research (unknown)

The end game: respecting major sources of population diversity

Lucina Q. Uddin

Human neuroscience is enjoying burgeoning population data resources: large-scale cohorts with thousands of participant profiles of gene expr… (see more)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 (published)