Danilo Bzdok

Google Scholar

Badr Ait Hammou

Postdoctorate - McGill University

Karan Bali Bali

PhD - McGill University

Gregory Bell

PhD - McGill University

Anwesha Bhattacharya

PhD - McGill University

Pedro Carneiro Carneiro

PhD - McGill University

Liam Hodgson

PhD - McGill University

Ryan McPhedrain McPhedrain

Postdoctorate - McGill University

[email protected]

David Payette

Master's Research - McGill University

Sepehr Radmannia

Independent visiting researcher - McGill University

[email protected]

Karin Saltoun

PhD - McGill University

Chloé Savignac

PhD - McGill University

Google Scholar

Jack Stanley

PhD - McGill University

PhD - McGill University

Celeste van Dokkum

Independent visiting researcher - Yale University

Using LLMs to better understand autism diagnosis

Le Zhou

PhD - McGill University

Blog Posts

March 25, 2025

Jack Stanley

Danilo Bzdok

Read the article

September 8, 2020

Towards Precision Medicine: Understanding Inference and Prediction Divergence in Biomedicine

Danilo Bzdok

Read the article

Publications

More Than Meets the Eye: Art Engages the Social Brain

Janneke E. P. van Leeuwen

Jeroen Boomgaard

Sebastian J. Crutch

Jason D. Warren

2022-02-25

Frontiers in Neuroscience (published)

Multivariate, Transgenerational Associations of the COVID-19 Pandemic Across Minoritized and Marginalized Communities.

S. Yip

Ayana Jordan

Robert J. Kohler

Avram J. Holmes

Importance The experienced consequences of the COVID-19 pandemic have diverged across individuals, families, and communities, resulting in i… (see more)nequity within a host of factors. There is a gap of quantitative evidence about the transgenerational impacts of these experiences and factors. Objective To identify baseline predictors of COVID-19 experiences, as defined by child and parent report, using a multivariate pattern-learning framework from the Adolescent Brain and Cognitive Development (ABCD) cohort. Design, Setting, and Participants ABCD is an ongoing prospective longitudinal study of child and adolescent development in the United States including 11 875 youths, enrolled at age 9 to 10 years. Using nationally collected longitudinal profiling data from 9267 families, a multivariate pattern-learning strategy was developed to identify factor combinations associated with transgenerational costs of the ongoing COVID-19 pandemic. ABCD data (release 3.0) collected from 2016 to 2020 and released between 2019 and 2021 were analyzed in combination with ABCD COVID-19 rapid response data from the first 3 collection points (May-August 2020). Exposures Social distancing and other response measures imposed by COVID-19, including school closures and shutdown of many childhood recreational activities. Main Outcomes and Measures Mid-COVID-19 experiences as defined by the ABCD's parent and child COVID-19 assessments. Results Deep profiles from 9267 youth (5681 female [47.8%]; mean [SD] age, 119.0 [7.5] months) and their caregivers were quantitatively examined. Enabled by a pattern-learning analysis, social determinants of inequity, including family structure, socioeconomic status, and the experience of racism, were found to be primarily associated with transgenerational impacts of COVID-19, above and beyond other candidate predictors such as preexisting medical or psychiatric conditions. Pooling information across more than 17 000 baseline pre-COVID-19 family indicators and more than 280 measures of day-to-day COVID-19 experiences, non-White (ie, families who reported being Asian, Black, Hispanic, other, or a combination of those choices) and/or Spanish-speaking families were found to have decreased resources (mode 1, canonical vector weight [CVW] = 0.19; rank 5 of 281), escalated likelihoods of financial worry (mode 1, CVW = -0.20; rank 4), and food insecurity (mode 1, CVW = 0.21; rank 2), yet were more likely to have parent-child discussions regarding COVID-19-associated health and prevention issues, such as handwashing (mode 1, CVW = 0.14; rank 9), conserving food or other items (mode 1, CVW = 0.21; rank 1), protecting elderly individuals (mode 1, CVW = 0.11; rank 21), and isolating from others (mode 1, CVW = 0.11; rank 23). In contrast, White families (mode 1, CVW = -0.07; rank 3), those with higher pre-COVID-19 income (mode 1, CVW = -0.07; rank 5), and presence of a parent with a postgraduate degree (mode 1, CVW = -0.06; rank 14) experienced reduced COVID-19-associated impact. In turn, children from families experiencing reduced COVID-19 impacts reported longer nighttime sleep durations (mode 1, CVW = 0.13; rank 14), less difficulties with remote learning (mode 2, CVW = 0.14; rank 7), and decreased worry about the impact of COVID-19 on their family's financial stability (mode 1, CVW = 0.134; rank 13). Conclusions and Relevance The findings of this study indicate that community-level, transgenerational intervention strategies may be needed to combat the disproportionate burden of pandemics on minoritized and marginalized racial and ethnic populations.

2022-02-09

JAMA psychiatry (published)

Sex-specific lesion pattern of functional outcomes after stroke

Anna K. Bonkhoff

Martin Bretzner

Sungmin Hong

Markus D. Schirmer

Alexander L. Cohen

Robert W. Regenhardt

Kathleen Donahue

Marco Nardin

Adrian Dalca

Anne-Katrin Giese

Mark R. Etherton

Brandon L. Hancock

Steven J.T. Mocking

Elissa McIntosh

John Richard Attia

Oscar Benavente

S. Bevan

John W. Cole

Amanda Donatti

Christoph Griessenauer … (see 38 more)

Laura Heitsch

Lukas Holmegaard

Katarina Jood

Jordi Jimenez-Conde

Steven Kittner

Robin Lemmens

C. Levi

Caitrin W. McDonough

James Meschia

Chia-Ling Phuah

Arndt Rolfs

Stefan Ropele

Jonathan Rosand

Jaume Roquer

Tatjana Rundek

Ralph L. Sacco

Reinhold Schmidt

Pankaj Sharma

Agnieszka Slowik

Martin Söderholm

Alessandro Sousa

Tara M. Stanne

Daniel Strbian

Turgut Tatlisumak

Vincent Thijs

Achala Vagal

Johan Wasselius

Daniel Woo

Ramin Zand

P. McArdle

Bradford B. Worrall

Christina Jern

Arne G. Lindgren

Jane Maguire

M. Fox

Ona Wu

Natalia S. Rost

Abstract Stroke represents a considerable burden of disease for both men and women. However, a growing body of literature suggests clinicall… (see more)y relevant sex differences in the underlying causes, presentations and outcomes of acute ischaemic stroke. In a recent study, we reported sex divergences in lesion topographies: specific to women, acute stroke severity was linked to lesions in the left-hemispheric posterior circulation. We here determined whether these sex-specific brain manifestations also affect long-term outcomes. We relied on 822 acute ischaemic patients [age: 64.7 (15.0) years, 39% women] originating from the multi-centre MRI-GENIE study to model unfavourable outcomes (modified Rankin Scale >2) based on acute neuroimaging data in a Bayesian hierarchical framework. Lesions encompassing bilateral subcortical nuclei and left-lateralized regions in proximity to the insula explained outcomes across men and women (area under the curve = 0.81). A pattern of left-hemispheric posterior circulation brain regions, combining left hippocampus, precuneus, fusiform and lingual gyrus, occipital pole and latero-occipital cortex, showed a substantially higher relevance in explaining functional outcomes in women compared to men [mean difference of Bayesian posterior distributions (men – women) = −0.295 (90% highest posterior density interval = −0.556 to −0.068)]. Once validated in prospective studies, our findings may motivate a sex-specific approach to clinical stroke management and hold the promise of enhancing outcomes on a population level.

2022-02-02

Brain Communications (published)

Sex-specific lesion pattern of functional outcomes after stroke

Anna K. Bonkhoff

Martin Bretzner

Sungmin Hong

Markus D. Schirmer

Alexander Cohen

Robert W. Regenhardt

Kathleen Donahue

Marco Nardin

Adrian Dalca

Anne-Katrin Giese

Mark R. Etherton

Brandon L. Hancock

Steven J.T. Mocking

Elissa McIntosh

John Attia

Oscar Benavente

Stephen Bevan

John W. Cole

Amanda Donatti

Christoph Griessenauer … (see 39 more)

Laura Heitsch

Lukas Holmegaard

Katarina Jood

Jordi Jimenez-Conde

Steven Kittner

Robin Lemmens

Christopher Levi

Caitrin W. McDonough

James Meschia

Chia-Ling Phuah

Arndt Rolfs

Stefan Ropele

Jonathan Rosand

Jaume Roquer

Tatjana Rundek

Ralph L. Sacco

Reinhold Schmidt

Pankaj Sharma

Agnieszka Slowik

Martin Soederholm

Alessandro Sousa

Tara M. Stanne

Daniel Strbian

Turgut Tatlisumak

Vincent Thijs

Achala Vagal

Johan Wasselius

Daniel Woo

Ramin Zand

Patrick McArdle

Bradford B. Worrall

Christina Jern

Arne G. Lindgren

Jane Maguire

Michael D. Fox

Ona Wu

Natalia S. Rost

Anna K. Martin Sungmin Markus D. Alexander Robert W. Kathleen L. Marco J. Adrian V. Anne-Katrin Mark R. Brandon L. Steven J. T. Elissa C. John Oscar R. Stephen John W. Amanda Christoph J. Laura Lukas Katarina Jordi Steven J. Robin Christopher R. Caitrin W. James F. Chia-Ling Arndt Stefan Jonathan Jaume Tatjana Ralph L. Reinhold Pankaj Agnieszka Martin Alessandro Tara M. Daniel Turgut Vincent Achala Johan Daniel Ramin Patrick F. Bradford B. Christina Arne G. Jane Michael D. Danilo Ona Natalia S. Bonkhoff

2022-02-02

Brain Communications (published)

Lacking social support is associated with structural divergences in hippocampus–default network co-variation patterns

Chris Zajner

Nathan Spreng

2022-01-27

Social Cognitive and Affective Neuroscience (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 K. Bonkhoff

Natalia S. Rost

2022-01-18

bioRxiv (preprint)

Age differences in the functional architecture of the human brain

Roni Setton

Laetitia Mwilambwe-Tshilobo

Manesh Girn

Amber W. Lockrow

Giulia Baracchini

Colleen Hughes

Alexander J. Lowe

Benjamin N. Cassidy

Jian Li

Wen-Ming Luh

Richard M. Leahy

Tian Ge

Daniel S. Margulies

Bratislav Mišić

Boris C Bernhardt

W. Dale Stevens

Felipe De Brigard

Prantik Kundu

Gary R. Turner … (see 1 more)

R. Nathan Spreng

The intrinsic functional organization of the brain changes into older adulthood. Age differences are observed at multiple spatial scales, fr… (see more)om global reductions in modularity and segregation of distributed brain systems, to network-specific patterns of dedifferentiation. Whether dedifferentiation reflects an inevitable, global shift in brain function with age, circumscribed, experience dependent changes, or both, is uncertain. We employed a multi-method strategy to interrogate dedifferentiation at multiple spatial scales. Multi-echo (ME) resting-state fMRI was collected in younger (n=181) and older (n=120) healthy adults. Cortical parcellation sensitive to individual variation was implemented for precision functional mapping of each participant, while preserving group-level parcel and network labels. ME-fMRI processing and gradient mapping identified global and macroscale network differences. Multivariate functional connectivity methods tested for microscale, edge-level differences. Older adults had lower BOLD signal dimensionality, consistent with global network dedifferentiation. Gradients were largely age-invariant. Edge-level analyses revealed discrete, network-specific dedifferentiation patterns in older adults. Visual and somatosensory regions were more integrated within the functional connectome; default and frontoparietal control network regions showed greater connectivity; and the dorsal attention network was more integrated with heteromodal regions. These findings highlight the importance of multi-scale, multi-method approaches to characterize the architecture of functional brain aging.

2022-01-05

bioRxiv (preprint)

Orientation and Context Entangled Network for Retinal Vessel Segmentation

Xinxu Wei

Kaifu Yang

Yongming Li

2022-01-01

SSRN Electronic Journal (published)

arxiv.org

Representational ethical model calibration

Robert Carruthers

Isabel Straw

James K. Ruffle

Daniel Herron

Amy Nelson

Delmiro Fernandez-Reyes

Geraint Rees

Parashkev Nachev

2022-01-01

npj Digit. Medicine (published)

arxiv.org

There is no fundamental trade-off between prediction accuracy and feature importance reliability

Jianzhong Chen

L.Q.R. Ooi

Jingwei Li

L. Christopher

Asplund

Simon B. Eickhoff

Avram J. Holmes

Blake T. Thomas

Yeo

There is significant interest in using neuroimaging data to predict behavior. The predictive models are often interpreted by the computation… (see more) of feature importance, which quantifies the predictive relevance of an imaging feature. Tian and Zalesky (2021) suggest that feature importance estimates exhibit low test-retest reliability, pointing to a potential trade-off between prediction accuracy and feature importance reliability. This trade-off is counter-intuitive because both prediction accuracy and test-retest reliability reflect the reliability of brain-behavior relationships across independent samples. Here, we revisit the relationship between prediction accuracy and feature importance reliability in a large well-powered dataset across a wide range of behavioral measures. We demonstrate that, with a sufficient sample size, feature importance (operationalized as Haufe-transformed weights) can achieve fair to excellent test-retest reliability. More specifically, with a sample size of about 2600 participants, Haufe-transformed weights achieve average intra-class correlation coefficients of 0.75, 0.57 and 0.53 for cognitive, personality and mental health measures respectively. Haufe-transformed weights are much more reliable than original regression weights and univariate FC-behavior correlations. Intriguingly, feature importance reliability is strongly positively correlated with prediction accuracy across phenotypes. Within a particular behavioral domain, there was no clear relationship between prediction performance and feature importance reliability across regression algorithms. Finally, we show mathematically that feature importance reliability is necessary, but not sufficient, for low feature importance error. In the case of linear models, lower feature importance error leads to lower prediction error (up to a scaling by the feature covariance matrix). Overall, we find no fundamental trade-off between feature importance reliability and prediction accuracy.

Title: 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

Richard M. Leahy

Tian Ge

Daniel S. Margulies

Bratislav Mišić

Boris C Bernhardt

W. Dale Stevens

Felipe De Brigard

Prantik Kundu

Richard S. Gary

Gary R. Turner … (see 1 more)

R. Nathan Spreng

The intrinsic functional connectome can reveal how a lifetime of learning and lived experience is represented in the functional architecture… (see more) 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.

Recovery after stroke: the severely impaired are a distinct group

Anna K. Bonkhoff

Thomas Hope

Adrian G Guggisberg

Rachel L Hawe

Sean P Dukelow

F. Chollet

D. X. Lin

Christian Grefkes

Howard Bowman

2021-12-22

Journal of Neurology Neurosurgery & Psychiatry (published)