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

The blueprint of human functional architecture shifts from cognition to anatomy during perturbations of consciousness

Andrea I. Luppi

Dragana Manasova

Justine Y. Hansen

Zhen-Qi Liu

Asa Farahani

Yonatan Sanz Perl

Jakub Vohryzek

Daniel Golkowski

Andreas Ranft

R. Ilg

Denis Jordan

Vincent Bonhomme

Audrey Vanhaudenhuyse

Athéna Demertzi

Océane Jaquet

Mohamed Ali Bahri

Naji Alnagger

Paolo Cardone

Lorina Naci

Adrian M. Owen … (voir 9 de plus)

John Pickard

Guy Williams

Judith Allanson

Enrico Amico

Jacobo Sitt

David Menon

Emmanuel A. Stamatakis

Bratislav Misic

Consciousness and cognition arise from the ongoing interactions between brain regions. Synchronous fluctuations of fMRI signals may indicate… (voir plus) that two brain regions perform similar cognitive functions, but neural interactions are also constrained by anatomical connectivity and regions' molecular, cytoarchitectonic, and metabolic profiles. Here we disentangle the respective contributions of ongoing cognition and multimodal neurobiological constraints in shaping functional connectivity. We jointly contextualise haemodynamic FC against eight distinct multimodal representations of the human connectome: (i) structural connectivity from diffusion tractography; (ii) spatial embedding; (iii) similarity of transcriptional profiles from gene expression; (iv) similarity of receptor profiles from Positron Emission Tomography; (v) laminar profile similarity from histology; (vi) correlated electrophysiological activity from magnetoencephalography; (vii) correlated metabolic activity from PET glucose uptake; (viii) coordinated activation across 123 cognitive operations from the NeuroSynth meta-analytic engine. We demonstrate that cognitive co-activation is the dominant predictor of inter-regional fMRI synchrony in the awake human brain, even when quantified using intracranial electrical stimulation. Crucially, this predominance of cognitive co-activation for shaping functional connectivity is systematically obliterated across five datasets of pharmacological and pathological perturbations of consciousness (chronic disorders of consciousness; anaesthesia with sevoflurane, propofol, or ketamine) when cognition is disconnected from the environment or altogether abolished. Altogether, we show that multimodal predictors of functional architecture shift away from cognitive co-activation and toward anatomical-molecular constraints during pharmacological and pathological perturbations of consciousness.

2026-06-09

bioRxiv (accepté)

Danilo Bzdok

2026-05-31

Neuron (publié)

Cell type transcriptomic modules reveal shared molecular mechanisms in Alzheimer’s and Parkinson’s disease

Anwesha Bhattacharya

Edward A. Fon

Alain Dagher

Yasser Iturria-Medina

Jo Anne Stratton

L. M. Hodgson

David A Bennett

Historically, Alzheimer's disease (AD) and Parkinson's disease (PD) have been investigated as two distinct disorders of the brain. However, … (voir plus)a few similarities in neuropathology and clinical symptoms have been documented over the years. Traditional single-gene centric studies, such as differential gene expression analyses, have struggled to unravel the molecular basis for the observed pathological links between AD and PD. To address this, we tailor a latent factor framework to analyze synchronous gene co-expression at sub-cell-type resolution. Utilizing large, single-nucleus transcriptomics datasets in AD (70,634 nuclei) and PD (340,902 nuclei) from postmortem human brains, we systematically extract and juxtapose disease-critical molecular signatures in the brain. Our transcriptomic analysis reveals shared molecular programs between AD and PD that systematically localize to specific glial and neuronal cell types. In neurons, convergent gene groups in AD and PD relate to cytoskeletal dynamics and mitochondrial stress mechanisms. Similarly, overlapping gene groups in microglia modules implicate T cell activation mechanisms and synapse pruning pathways. In parallel, AD- and PD-associated genes in astrocytes are involved in heavy metal processing; oligodendrocytes highlight convergent dysregulation in myelin synthesis. In addition, our analysis reveals APOE, an AD GWAS gene, has disease predictive roles in PD-associated gene modules. Conversely, SNCA, a PD GWAS gene, emerges within AD associated gene modules. Our multi-module sub-cell-type approach offers unique insights into the molecular basis of shared neuropathology in AD and PD.

2026-05-20

GigaScience (publié)

Widespread use of invalid statistical tests in biomedical machine learning

Tianchu Zeng

Hui Li

Shaoshi Zhang

Yan Quan Tan

Fang Tian

Csaba Orbán

Lijun An

Wanyu Che

Jingwen Cheng

Joanna Su Xian Chong

Niousha Dehestani

Zijian Dong

Xin Li

Zhizhou Li

Mervyn Jun Rui Lim

Yi Lin

Qinrui Ling

Zijie Ling

Xi Zhi Low

Sina Mansour L. … (voir 24 de plus)

Kwun Kei Ng

Thuan Tinh Nguyen

Leon Qi Rong Ooi

Shreya Pande

Xing Qian

Jingxuan Ruan

Z WANG

Yapei Xie

Chen Zhang

Yichi Zhang

K Patil

Linden Parkes

Elvisha Dhamala

Sidhant Chopra

Andrew Zalesky

Avram Holmes

S Eickhoff

Juan Helen Zhou

Olivier Renaud

Nico Dosenbach

Konrad P. Kording

Thomas Nichols

B T Thomas Yeo

Abstract Machine learning is accelerating biomedical research. Cross-validation is widely used to compare predictive performance – not onl… (voir plus)y to benchmark algorithms, but also to inform scientific applications, such as ranking biomarkers. However, prediction performance estimates across cross-validation folds are not independent. Standard tests for comparing prediction performance (e.g., paired t-test) assume independence and can therefore inflate false positive rates. In a PRISMA-guided meta-analysis of 210 studies (impact factor ≥15, 1 June 2020 – 1 June 2025), we find that 97% ignored fold dependence when comparing prediction performance. This problem is ubiquitous across scientific fields and unaffected by impact factor, rigor-promoting policies, or open science practices. Simulations across 420 scenarios spanning four diverse datasets show that ignoring fold dependence leads to invalid false positive control in most settings. Repeated cross-validation further compounds this problem, with false positive rates rising toward 100% as the number of repetitions grows. Existing fold-dependence-aware tests rely on strong assumptions because the variance of fold-level statistics and the between-fold correlation cannot be disentangled under standard cross-validation. We therefore propose the SHARP (Split-HAlf RePeated) test, a simple modification to standard cross-validation that enables direct estimation of variance and correlation. Benchmarked against 12 tests, SHARP provides the best overall balance of false-positive control, statistical power, and confidence-interval calibration across simulation schemes. We conclude by providing best practices and reporting guidelines for valid model comparison inference in biomedical machine learning and beyond.

2026-05-19

bioRxiv (prépublication)

Profiling the Cell-Type Specific Effects of Psilocybin in Medial Prefrontal Cortexh

Heike Schuler

Delong Zhou

Chloé Savignac

Vedrana Cvetkovska

Yiu-Chung Tse

Juliet Meccia

Rosemary C. Bagot

2026-04-30

Biological Psychiatry (publié)

Neurovascular Coupling as Early, High-Sensitive Biomarker for Cognitive Decline and Vascular Pathology: Protocol for Systematic Review and Meta-Analysis

V. D. Abramova

Veronika Egovtseva

Ksenya Pronyaeva

Shamsa H. Alshamsi

Marta Estrada

Rustam Talybov

Taleb~M. Almansoori

Bassem Sadek

Mohammed Khogali

Mohammad~I.K. Hamad

Milos Ljubisavljevic

Yauhen Statsenko

2026-04-14

Research Square (accepté)

An international mega-analysis of psychedelic drug effects on brain circuit function

Manesh Girn

Manoj K. Doss

Leor Roseman

Katrin H. Preller

Fernanda Palhano-Fontes

Lorenzo Pasquini

Frederick S. Barrett

Pablo Mallaroni

Natasha L. Mason

Christopher Timmermann

Drummond E. McCulloch

Patrick M. Fisher

Brian S. Winston

Flora Moujaes

Felix Muller

Matthias E. Liechti

Franz X. Vollenweider

Johannes G. Ramaekers

Kim Kuypers

Draulio B. Araujo … (voir 7 de plus)

Olaf Sporns

Joshua Siegel

Nico Dosenbach

David J. Nutt

Robin L. Carhart-Harris

Emmanuel A. Stamatakis

Psychedelic drugs are re-emerging as promising scientific and clinical tools. However, despite a rapidly expanding literature on their thera… (voir plus)peutic value, the neural mechanisms underlying psychedelic effects remain unclear. Resting-state functional magnetic resonance imaging studies of acute psychedelic effects, conducted independently by several research groups, have so far yielded fragmented and sometimes inconsistent findings. Here, to help facilitate greater convergence, we conducted a 'mega-analysis' integrating 11 independent resting-state functional magnetic resonance imaging datasets across five psychedelic drugs (psilocybin, lysergic acid diethylamide, mescaline, N,N-dimethyltryptamine and ayahuasca) from research groups spanning three continents and five countries. By applying a uniform preprocessing pipeline and a Bayesian hierarchical modeling framework, we discovered several common features in the induced alterations to brain function across drugs and sites. Most prominently, we identified a core signature of increased functional connectivity between transmodal (default, frontoparietal and limbic) and unimodal networks (visual and somatomotor), with subnetwork specificity. Furthermore, key subcortical regions (thalamus, caudate and putamen) and the cerebellum exhibited altered coupling with sensorimotor networks. In contrast to several single-site reports, Bayesian modeling revealed weak-to-moderate and selective reductions in within-network functional connectivity, with substantial variability across drugs and networks. Together, these findings extend past work by demonstrating that psychedelics reconfigure large-scale cortical organization while selectively engaging subcortical circuitry. This study provides the most comprehensive synthesis of psychedelic brain action to date, helping resolve inconsistencies and offering a probabilistic map of how psychedelics alter large-scale brain organization. We hereby provide a cornerstone to benchmark and shepherd future psychedelic neuroimaging research.

2026-04-05

Nature Medicine (publié)

Multiscale reorganization of brain and behavior under large-scale electrical perturbation

Sarah Kreuzer

Juergen Dukart

Justine Y. Hansen

Hoang K. Nguyen

Michael Bentsch

Sophia Zieger

Katrin Sakreida

Thomas C. Baghai

Caroline Nothdurfter

Michael Groezinger

Bogdan Draganski

Bratislav Misic

Simon B. Eickhoff

Timm B. Poeppl

2026-03-24

bioRxiv (prépublication)

Sex Differences in P-Tau217, Tau Aggregation, and Cognitive Decline

Gillian Coughlan

Valentin Ourry

Diana Townsend

Hannah M Klinger

Jane A. Brown

Madison Cuppels

Tobey Betthauser

Rebecca Langhough

Karly Alex Cody

Mabel Seto

Colin Birkenbihl

Annie Li

Michelle Farrell

Emma G. Thibault

Pia Kivisäkk Webb

S. R. Arnold

Robert A. Rissman

Michael Properzi

Aaron Schultz

Keith Johnson … (voir 81 de plus)

Oliver Langford

Michael C. Donohue

Sylvia Villeneuve

Sterling C. Johnson

Hyun-Sik Yang

JoAnn E. Manson

Reisa Sperling

Rachel F. Buckley

Orest Hurko

Sanra E Black

Rachelle Doody

Murali Doraiswamy

Anthony Gamst

Jeffrey Kaye

Thomas Obisesan

Henry Rusinek

Doug Scharre

Reisa Sperling

Michael W Weiner

R. Green

Paul Aisen

Keith Johnson

Jason Karlawish

Kenneth Marek

Karen Holdridge

REMA RAMAN

R. Yaari

Cheryl Brown

John R. Sims

Robert A. Rissman

Michael C. Donohue

Maria Arampatizdou

Jeremy Pizzola

Mike Rafii

Clifford Jack Jr.

Marybeth Howlett

John Seibyl

Isabella Velon

Paula Cohen

Gustavo Jimenez-Maggiora

Marianne Manire

James B. Brewer

Paul Maruff

Mark Mintun

Alison Belsha

Jennifer Salazar

Cecily Jenkins

Vedeline Torreon

Renarda Jones

Sylvia Villeneuve

Judes Poirier

John C.S. Breitner

Mohamed Badawy

Sylvain Baillet

Andrée‐Ann Baril

Bellec Pierre

Véronique D. Bohbot

Mallar Chakravarty

D. Louis Collins

Mahsa Dadar

Simon Ducharme

Alan C. Evans

Claudine Gauthier

Maiya Geddes

Rick Hoge

Yasser Ituria-Medina

Maxime Montembeault

Gerhard Multhaup

Lisa-Marie Münter

Alexa Pichet Binette

Natasha Rajah

Pedro Rosa-Neto

Taylor W. Schmitz

Jean-Paul Soucy

Nathan R Spreng

Christine Tardif

Etienne Vachon-Presseau

Christian Bocti

Maxime Descoteaux

Pierre Bellec

Importance: Among individuals with high levels of amyloid-β (Aβ), women exhibit higher insoluble tau burden and accumulation than age-matc… (voir plus)hed men. It remains unclear whether this sex difference is influenced by soluble phosphorylated tau (p-tau), a biomarker that changes early in Alzheimer disease. Objective: To investigate whether sex and aggregated Aβ synergistically predict plasma phosphorylated tau 217 (p-tau217) levels and whether levels of p-tau217 predict cross-sectional and longitudinal tau aggregation in a sex-specific manner (as measured by positron emission tomography [PET]). Design, Setting, and Participants: This longitudinal study analyzed data between September 7, 2024, and October 29, 2025, from 1 clinical trial cohort and 4 observational study cohorts including men and women without cognitive impairment who had undergone multiple assessments via tau PET (18F-flortaucipir or 18F-MK-6240) and plasma p-tau217 assay at baseline. Cognitive performance was measured with the Preclinical Alzheimer Cognitive Composite. Data on cognitive performance were available from 3 of the 5 cohorts for a mean of 4.6 years (SD, 3.1 years). Across the 5 cohorts, the mean follow-up for tau PET was 3.6 years (SD, 1.7 years). Exposures: Self-reported sex (male or female), tau PET, and p-tau217 assay. Main Outcomes and Measures: The primary analyses used linear and mixed-effects models to assess baseline and longitudinal sex × p-tau217 interactions for 9 tau PET regions. The secondary analyses assessed sex × p-tau217 interactions for cognitive change using the Preclinical Alzheimer Cognitive Composite. Results: Across the 5 cohorts, there were a total of 1292 participants (63.6% women; mean age, 70.6 [SD, 6.4] years) with tau PET assessments. Compared with men, women had significantly higher baseline p-tau217 levels at higher aggregated Aβ Centiloid levels (β, -0.21 [95% CI, -0.37 to -0.05], P = .009; highest interaction was found in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease/Longitudinal Evaluation of Amyloid Risk and Neurodegeneration [A4/LEARN] cohort). The sex × p-tau217 interactions at baseline were significant for 1 tau PET region in the Harvard Aging Brain Study (HABS) cohort, for 2 tau PET regions in the A4/LEARN cohort, for 6 tau PET regions in the Wisconsin Registry of Alzheimer's Prevention (WRAP) cohort, and for 4 tau PET regions in the Presymptomatic Evaluation of Experimental or Novel Treatments for Alzheimer's Disease (PREVENT-AD) cohort. Longitudinal interactions were significant for 4 tau PET regions in the A4/LEARN cohort, for 5 tau PET regions in both the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort and the WRAP cohort, and for 2 PET regions in both the HABS cohort and the PREVENT-AD cohort. Compared with men, women displayed greater tau deposition and accumulation at higher p-tau217 levels. Use of a secondary model showed women with higher p-tau217 levels also exhibited faster rates of cognitive decline relative to men in the both the WRAP cohort and the ADNI cohort. Conclusion and Relevance: These findings add to growing evidence that women have a differential tau response to Aβ that may emerge at the point of p-tau secretion. These findings have implications for the therapeutics and diagnostics of preclinical Alzheimer disease.

2026-02-15

JAMA Neurology (publié)

Morphometric dissimilarity in association cortices linked to autism subtype with more severe symptoms

Hongxiu Jiang

Raul Rodriguez-Cruces

Ke Xie

Valeria Kebets

Yezhou Wang

Clara F. Weber

Ying He

Jonah Kember

Hilary Sweatman

Zeus Gracia Tabuenca

Jean-Baptiste Poline

Seok-Jun Hong

Boris Bernhardt

Xiaoqian Chai

Autism spectrum disorder (ASD) is a prevalent and heterogeneous neurodevelopmental condition marked by atypical brain connectivity. Understa… (voir plus)nding ASD neural subtypes at the network level is critical for clarifying its neuroanatomical heterogeneity. Morphometric similarity networks (MSNs), derived from region-to-region similarity across multiple anatomical features, offer a powerful approach for capturing individual-level neural architecture. In this study, MSNs were estimated from seven anatomical features in 348 individuals with ASD and 452 typically developing (TD) controls. Across all ASD participants, the first principal component of MSN values was negatively correlated with social and communication severity. Three ASD subtypes with distinct MSN patterns were identified. Subtype-1, characterized by weaker morphometric similarity values in frontotemporal association regions compared to TD individuals, exhibited the most severe symptoms in social, communication and repetitive behaviors, and displayed hyperconnectivity between the salience and visual networks, and between language and visual networks. Subtype-2 showed greater values of morphometric similarities than TD and less severe social symptoms compared to subtype-1, along with hyperconnectivity between default and salience networks relative to TD. Subtype-3 displayed morphometric similarity values largely comparable to TD and the least severe symptoms out of the three subtypes. Transcriptomic analysis revealed that GABAergic parvalbumin and glutamatergic intratelencephalic-projecting neurons were key cell types differentiating subtypes. These findings suggest the existence of distinct ASD neuroanatomical subtypes defined by regional morphometric similarity, each linked to unique behavioral, functional, and transcriptomic profiles. Morphometric dissimilarity in association regions may serve as a neural signature for ASD subtypes characterized by more severe clinical manifestations.

2026-01-31

NeuroImage (publié)

Threading the needle: Practical considerations for merging theory-driven computational psychiatry with data-driven analytics to enhance precision health at scale

Annie Cheng

Anna Konova

Albert Powers

Philip Corlett

Ifat Levy

Xiaosi Gu

Quentin Huys

Helen Pushkarskya

Sarah Fineberg

Tobias Hauser

Ilan Harpaz-Rotem

Theresa Babuscio

Lisa Nichols

Yize Zhao

Manu Sharma

Daniella Meeker

Hua Xu

Robb B. Rutledge

Godfrey D. Pearlson … (voir 2 de plus)

Christopher Pittenger

Sarah W. Yip

The rapidly evolving field of computational psychiatry enables quantification of specific cognitive processes, and their underlying mechanis… (voir plus)ms, in a translational and potentially scalable manner, using a combination of data collection via mechanistically informed behavioral tasks and theory-driven mathematical modeling. In parallel, transdiagnostic, dimensional approaches to psychiatric diagnostics, such as RDoC and HiTOP, seek to facilitate links between clinical research and real-world clinical reality, which rarely respects traditional diagnostic boundaries. These two approaches are seldom combined. In addition, while most psychiatric disorders are defined by their longitudinal course, our ability to predict symptom trajectories and tailor treatments to the individual remains limited, in part due to a dearth of longitudinal data collected using assessments sensitive to individual change over time. To address these gaps, the recently launched 'Individually Measured Phenotypes to Advance Computational Translation at Yale' (IMPACT-Y) study is collecting longitudinal data from a transdiagnostic cohort of 2400 individuals, using a combination of 'traditional' clinical research methods (e.g., health records, standardized assessments) and more novel computational approaches (e.g., behavioral tasks with demonstrated sensitivity to latent constructs and to within-person change, spoken narrative data). Here, we discuss unique challenges and opportunities in study design and analysis considerations of IMPACT-Y. Incorporating both theory- and data-driven analytics, we hope that IMPACT-Y will provide an unprecedented resource for characterizing longitudinal trajectories of core computational psychiatry constructs (e.g., reward learning) within and between individuals, for parsing heterogeneity beyond traditional diagnostic categories, and for linking inter- and intra-individual clinical variability to underlying mechanisms.

2026-01-31

Biological Psychiatry: Cognitive Neuroscience and Neuroimaging (publié)

Genetic and Causal Insights Into White Matter Hyperintensities Across the Brain‐Body Axis

Manpreet Singh

Kimia Shafighi

Flavie E. Detcheverry

Gabrielle Dagasso

Fanta Dabo

Ikrame Housni

Sridar Narayanan

Nils D. Forkert

Sarah A Gagliano Taliun

AmanPreet Badhwar

White matter hyperintensities (WMHs), visible as bright regions on T2‐weighted FLAIR MRI, are frequent with age and elevated in Alzheimer'… (voir plus)s disease (AD). Representing axonal damage, demyelination, and edema, WMHs are driven by vascular mechanisms, including endothelial dysfunction and impaired cerebrovascular autoregulation. WMHs also exhibit strong heritability (55–73%), with overlapping genetic pathways shared with AD. Emerging evidence suggests systemic factors across the brain‐body axis influence WMHs, yet these contributions and their genetic overlap with AD remain underexplored. Our study investigated genetic underpinnings specific to WMHs and those shared with AD by assessing partitioned heritability of WMHs and AD across the brain‐body axis with SNP level tissue‐ and cell‐specific annotations; identifying genes associated with WMHs and AD through integration of gene expression data, establishing causal links between SNP‐level findings and imaging‐derived phenotypes (IDPs), particularly structural variations in regional brain volumes. Partitioned heritability was assessed using stratified‐linkage disequilibrium score regression (sLDSC) on GWAS summary statistics ( N = 3 WMH studies; N = 6 AD studies) using human A1) tissue level annotations ( N = 10) and A2) continuous cell‐specific annotations ( N = 64). MAGMA and FUSION analyses highlighted genes associated with WMH and AD for further bioinformatics analysis (using human protein atlas (HPA) and STRING database). MACAW (Vigneshwaran et al, 2024) modeled causal relationships between WMH‐associated SNPs (from FUMA analysis) and IDPs ( N = 172), leveraging directed acyclic graphs to evaluate genetic effects while controlling for confounders (Figure 2). Tissue‐specific analysis revealed significant enrichment of WMH‐associated SNPs in the CNS, liver, cardiovascular system, and kidneys, while AD‐associated SNPs were enriched in the CNS, connective bone, liver, and immune tissues. (Figure 1). Cell‐specific analysis identified vascular endothelial cells as enriched across WMH‐enriched tissues. MAGMA analysis, combined with HPA analysis, corroborated sLDSC tissue‐level findings. MAGMA and FUSION analyses highlighted genes associated with WMHs ( N = 39 and 69) and AD ( N = 291 and 193). MACAW linked WMH‐associated SNP to 172 IDPs, consistently impacting WM hypointensities and regional brain volumes (e.g., left inferior temporal volume). Our findings highlight systemic multi‐tissue contributions (CNS, liver, cardiovascular system, and kidneys) to WMHs, driven by vascular endothelial dysfunction and shared AD genetics, with SNPs across the body also affecting brain imaging derived phenotypes.

2026-01-06

Alzheimer's & Dementia (publié)