Danilo Bzdok

Pourquoi les modèles d'IA hallucinent et comment y remédier

A tab representation of the Pre trained CLIP Vision Transformer

8 octobre 2025

par

Praneet Suresh

Jack Stanley

Danilo Bzdok

Sonia Joseph

Luca Scimeca

Utiliser les LLMs pour mieux comprendre le diagnostic de l'autisme

25 mars 2025

par

Jack Stanley

Danilo Bzdok

Vers une médecine personnalisée : comprendre la divergence entre l’inférence et la prédiction en biomédecine

Towards Precision Medicine: Understanding Inference and Prediction Divergence in Biomedicine

8 octobre 2020

par

Danilo Bzdok

Publications

Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study

Jianzhong Chen

Angela Tam

Valeria Kebets

Csaba Orbán

Leon Qi Rong Ooi

Christopher L. Asplund

Scott Marek

Nico U.F. Dosenbach

Simon B. Eickhoff

Avram J. Holmes

B.T. Thomas Yeo

How individual differences in brain network organization track behavioral variability is a fundamental question in systems neuroscience. Rec… (voir plus)ent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, most studies focus on single behavioral traits, thus not capturing broader relationships across behaviors. In a large sample of 1858 typically developing children from the Adolescent Brain Cognitive Development (ABCD) study, we show that predictive network features are distinct across the domains of cognitive performance, personality scores and mental health assessments. On the other hand, traits within each behavioral domain are predicted by similar network features. Predictive network features and models generalize to other behavioral measures within the same behavioral domain. Although tasks are known to modulate the functional connectome, predictive network features are similar between resting and task states. Overall, our findings reveal shared brain network features that account for individual variation within broad domains of behavior in childhood.

2022-04-24

Nature Communications (publié)

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

Sarah W. 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… (voir plus)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.

2022-03-31

JAMA Psychiatry (publié)

Pattern learning reveals brain asymmetry to be linked to socioeconomic status

Timm B. Poeppl

Emile Dimas

Katrin Sakreida

Julius M. Kernbach

Ross D. Markello

Oliver Schöffski

Alain Dagher

Philipp Koellinger

Gideon Nave

Martha J. Farah

Bratislav Misic

Socioeconomic status (SES) anchors individuals in their social network layers. Our embedding in the societal fabric resonates with habitus, … (voir plus)world view, opportunity, and health disparity. It remains obscure how distinct facets of SES are reflected in the architecture of the central nervous system. Here, we capitalized on multivariate multi-output learning algorithms to explore possible imprints of SES in gray and white matter structure in the wider population (n ≈ 10,000 UK Biobank participants). Individuals with higher SES, compared with those with lower SES, showed a pattern of increased region volumes in the left brain and decreased region volumes in the right brain. The analogous lateralization pattern emerged for the fiber structure of anatomical white matter tracts. Our multimodal findings suggest hemispheric asymmetry as an SES-related brain signature, which was consistent across six different indicators of SES: degree, education, income, job, neighborhood and vehicle count. Hence, hemispheric specialization may have evolved in human primates in a way that reveals crucial links to SES.

2022-03-31

Cerebral Cortex Communications (publié)

Population heterogeneity in clinical cohorts affects the predictive accuracy of brain imaging

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 C. Bernhardt

Brain imaging research enjoys increasing adoption of supervised machine learning for single-participant disease classification. Yet, the suc… (voir plus)cess 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 variation. We delineate the impact of population heterogeneity on the predictive accuracy and pattern stability in 2 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 in regions part of the default mode network. Collectively, our findings highlight the limitations of prevailing deconfounding practices in mitigating the full consequences of population diversity.

2022-03-31

PLoS Biology (publié)

<i>APOE</i> ɛ2 vs <i>APOE</i> ɛ4 dosage shows sex-specific links to hippocampus-default network subregion co-variation

Chloé Savignac

Sylvia Villeneuve

AmanPreet Badhwar

Karin Saltoun

Kimia Shafighi

Chris Zajner

Vaibhav Sharma

Sarah A Gagliano Taliun

Sali Farhan

Judes Poirier

Alzheimer’s disease and related dementias (ADRD) are marked by intracellular tau aggregates in the medial-temporal lobe (MTL) and extracel… (voir plus)lular amyloid aggregates in the default network (DN). Here, we sought to clarify ADRD-related co-dependencies between the MTL’s most vulnerable structure, the hippocampus (HC), and the highly associative DN at a subregion resolution. We confronted the effects of APOE ɛ2 and ɛ4, rarely investigated together, with their impact on HC-DN co-variation regimes at the population level. In a two-pronged decomposition of structural brain scans from ∼40,000 UK Biobank participants, we located co-deviating structural patterns in HC and DN subregions as a function of ADRD family risk. Across the disclosed HC-DN signatures, recurrent deviations in the CA1, CA2/3, molecular layer, fornix’s fimbria, and their cortical partners related to ADRD risk. Phenome-wide profiling of HC-DN co- variation expressions from these population signatures revealed male-specific associations with air-pollution, and female-specific associations with cardiovascular traits. We highlighted three main factors associated with brain-APOE associations across the different gene variants: happiness, and satisfaction with friendships, and with family. We further showed that APOE ɛ2/2 interacts preferentially with HC-DN co-variation patterns in estimating social lifestyle in males and physical activity in females. Our findings reinvigorate the often-neglected interplay between APOE ɛ2 dosage and sex, which we have linked to fine-grained structural divergences indicative of ADRD susceptibility.

2022-03-14

bioRxiv (prépublication)

Cross-ethnicity/race generalization failure of behavioral prediction from resting-state functional connectivity

Jingwei Li

Jianzhong Chen

Angela Tam

Leon Qi Rong Ooi

Avram J. Holmes

Tian Ge

Kaustubh R. Patil

Mbemba Jabbi

Simon B. Eickhoff

B.T. Thomas Yeo

Sarah Genon

Algorithmic biases that favor majority populations pose a key challenge to the application of machine learning for precision medicine. Here,… (voir plus) we assessed such bias in prediction models of behavioral phenotypes from brain functional magnetic resonance imaging. We examined the prediction bias using two independent datasets (preadolescent versus adult) of mixed ethnic/racial composition. When predictive models were trained on data dominated by white Americans (WA), out-of-sample prediction errors were generally higher for African Americans (AA) than for WA. This bias toward WA corresponds to more WA-like brain-behavior association patterns learned by the models. When models were trained on AA only, compared to training only on WA or an equal number of AA and WA participants, AA prediction accuracy improved but stayed below that for WA. Overall, the results point to the need for caution and further research regarding the application of current brain-behavior prediction models in minority populations.

2022-02-28

Science Advances (publié)

More Than Meets the Eye: Art Engages the Social Brain

Janneke E. P. van Leeuwen

Jeroen Boomgaard

Sebastian J. Crutch

Jason D. Warren

2022-02-24

Frontiers in Neuroscience (publié)

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 L. Donahue

Marco J. Nardin

Adrian V. Dalca

Anne-Katrin Giese

Mark R. Etherton

Brandon L. Hancock

Steven J. T. Mocking

Elissa C. McIntosh

John Attia

Oscar R. Benavente

Stephen Bevan

John W. Cole

Amanda Donatti

Christoph J. Griessenauer … (voir 39 de plus)

Laura Heitsch

Lukas Holmegaard

Katarina Jood

Jordi Jimenez-Conde

Steven J. Kittner

Robin Lemmens

Christopher R. Levi

Caitrin W. McDonough

James F. 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

Patrick F. 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

Stroke represents a considerable burden of disease for both men and women. However, a growing body of literature suggests clinically relevan… (voir plus)t 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.

2022-01-30

Brain Communications (publié)

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

Chris Zajner

R. Nathan Spreng

Elaborate social interaction is a pivotal asset of the human species. The complexity of people’s social lives may constitute the dominatin… (voir plus)g factor in the vibrancy of many individuals’ environment. The neural substrates linked to social cognition thus appear especially susceptible when people endure periods of social isolation: here, we zoom in on the systematic inter-relationships between two such neural substrates, the allocortical hippocampus (HC) and the neocortical default network (DN). Previous human social neuroscience studies have focused on the DN, while HC subfields have been studied in most detail in rodents and monkeys. To bring into contact these two separate research streams, we directly quantified how DN subregions are coherently co-expressed with specific HC subfields in the context of social isolation. A two-pronged decomposition of structural brain scans from ∼40 000 UK Biobank participants linked lack of social support to mostly lateral subregions in the DN patterns. This lateral DN association co-occurred with HC patterns that implicated especially subiculum, presubiculum, CA2, CA3 and dentate gyrus. Overall, the subregion divergences within spatially overlapping signatures of HC–DN co-variation followed a clear segregation into the left and right brain hemispheres. Separable regimes of structural HC–DN co-variation also showed distinct associations with the genetic predisposition for lacking social support at the population level.

2022-01-24

Social Cognitive and Affective Neuroscience (publié)

Orientation and Context Entangled Network for Retinal Vessel Segmentation

Xinxu Wei

Kaifu Yang

Yongjie Li

Most of the existing deep learning based methods for vessel segmentation neglect two important aspects of retinal vessels, one is the orient… (voir plus)ation information of vessels, and the other is the contextual information of the whole fundus region. In this paper, we propose a robust Orientation and Context Entangled Network (denoted as OCE-Net), which has the capability of extracting complex orientation and context information of the blood vessels. To achieve complex orientation aware, a Dynamic Complex Orientation Aware Convolution (DCOA Conv) is proposed to extract complex vessels with multiple orientations for improving the vessel continuity. To simultaneously capture the global context information and emphasize the important local information, a Global and Local Fusion Module (GLFM) is developed to simultaneously model the long-range dependency of vessels and focus sufficient attention on local thin vessels. A novel Orientation and Context Entangled Non-local (OCE-NL) module is proposed to entangle the orientation and context information together. In addition, an Unbalanced Attention Refining Module (UARM) is proposed to deal with the unbalanced pixel numbers of background, thick and thin vessels. Extensive experiments were performed on several commonly used datasets (DRIVE, STARE and CHASEDB1) and some more challenging datasets (AV-WIDE, UoA-DR, RFMiD and UK Biobank). The ablation study shows that the proposed method achieves promising performance on maintaining the continuity of thin vessels and the comparative experiments demonstrate that our OCE-Net can achieve state-of-the-art performance on retinal vessel segmentation.

2021-12-31

SSRN Electronic Journal (inconnu)

arxiv.org

Representational ethical model calibration

Robert Carruthers

Isabel Straw

James K. Ruffle

Daniel Herron

Amy Nelson

Delmiro Fernandez-Reyes

Geraint Rees

Parashkev Nachev

2021-12-31

npj Digit. Medicine (publié)

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