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

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 Misic

Boris C. Bernhardt

W. Dale Stevens

Felipe De Brigard

Prantik Kundu

Gary R. Turner … (voir 2 de plus)

R. Nathan Spreng

Montreal Neurological

The intrinsic functional organization of the brain changes into older adulthood. Age differences are observed at multiple spatial scales, fr… (voir plus)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.

2022-01-27

Cerebral Cortex (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)

Meta-topologies define distinct anatomical classes of brain tumors linked to histology and survival

Julius M. Kernbach

Daniel Delev

Georg Neuloh

Hans Clusmann

Simon B. Eickhoff

Victor E. Staartjes

Flavio Vasella

Michael Weller

Luca Regli

Carlo Serra

Niklaus Krayenbühl

Kevin Akeret

Abstract Background The current WHO classification integrates histological and molecular features of brain tumors. The aim of this study was… (voir plus) to identify generalizable topological patterns with the potential to add an anatomical dimension to the classification of brain tumors. Methods We applied non-negative matrix factorization as an unsupervised pattern discovery strategy to the fine-grained topographic tumor profiles of 936 patients with primary and secondary brain tumors. From the anatomical features alone, this machine learning algorithm enabled the extraction of latent topological tumor patterns, termed meta-topologies . The optimal parts-based representation was automatically determined in 10,000 split-half iterations. We further characterized each meta-topology’s unique histopathologic profile and survival probability, thus linking important biological and clinical information to the underlying anatomical patterns Results In primary brain tumors, six meta-topologies were extracted, each detailing a transpallial pattern with distinct parenchymal and ventricular compositions. We identified one infratentorial, one allopallial, three neopallial (parieto-occipital, frontal, temporal) and one unisegmental meta-topology. Each meta-topology mapped to distinct histopathologic and molecular profiles. The unisegmental meta-topology showed the strongest anatomical-clinical link demonstrating a survival advantage in histologically identical tumors. Brain metastases separated to an infra- and supratentorial meta-topology with anatomical patterns highlighting their affinity to the cortico-subcortical boundary of arterial watershed areas. Conclusions Using a novel data-driven approach, we identified generalizable topological patterns in both primary and secondary brain tumors Differences in the histopathologic profiles and prognosis of these anatomical tumor classes provide insights into the heterogeneity of tumor biology and might add to personalized clinical decision making.

2021-12-31

Brain and Spine (publié)

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… (voir plus) 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.

2021-12-31

(publié)

www.semanticscholar.org

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 Misic

Boris C Bernhardt

W. Dale Stevens

Felipe De Brigard

Prantik Kundu

Richard S. Gary

Gary R. Turner … (voir 1 de plus)

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.

2021-12-31

(publié)

www.semanticscholar.org

Adapting to the COVID‐19 pandemic in cohort studies: Validation of online assessments of cognition and neuropsychiatric symptoms in an aging population

Firoza Z Lussier

Stijn Servaes

Min Su Kang

Gleb Bezgin

Mira Chamoun

Jenna Stevenson

Nesrine Rahmouni

Alyssa Stevenson

Tharick A. Pascoal

Suzanne King

Serge Gauthier

Pedro Rosa‐Neto

The occurrence of the COVID‐19 pandemic has had a significant impact on cohort studies, particularly those whose subjects are at higher ri… (voir plus)sk of developing complications from the virus. As such, assessment methods must be adapted to minimize COVID‐19 exposure risk. The TRIAD (Translational Biomarkers of Aging and Dementia) cohort assessed N=292 individuals during initial COVID‐19 lockdown measures by telephone interview to rate cognition, neuropsychiatric symptoms, and impact of the pandemic. To increase speed and efficiency of data collection, we aim to follow these individuals by means of online survey. Here, we present a validation of our online assessment tools by comparing data obtained through both methods (phone interview and online survey) in the same subjects.

2021-12-30

Alzheimer's & Dementia (publié)

Tau‐PET is associated with knowledge of COVID‐19, COVID‐19‐related distress, and change in sleep quality during the pandemic

Firoza Z Lussier

Stijn Servaes

Min Su Kang

Gleb Bezgin

Mira Chamoun

Jenna Stevenson

Nesrine Rahmouni

Alyssa Stevenson

Tharick A. Pascoal

Suzanne King

Guillaume Elgbeili

Serge Gauthier

Pedro Rosa‐Neto

While the global COVID‐19 pandemic has hindered many human research operations, it has allowed for the investigation of novel scientific q… (voir plus)uestions. Particularly, the effects of the pandemic and its resulting social isolation on elderly individuals and their association with Alzheimer’s disease biomarkers remains a broad and open question. Here, we sought to investigate whether knowledge of COVID‐19, pandemic‐related distress, and changes in sleep quality were associated with in vivo tau deposition in an AD‐enriched cohort.

2021-12-30

Alzheimer's & Dementia (publié)

Recovery after stroke: the severely impaired are a distinct group

Anna K. Bonkhoff

Thomas Hope

Adrian G. Guggisberg

Rachel L. Hawe

Sean P. Dukelow

François Chollet

David J. Lin

Christian Grefkes

Howard Bowman

Our work highlights the benefit of simultaneously modelling recovery of severely-to-non-severely impaired patients and demonstrates both sha… (voir plus)red and distinct recovery patterns. Our findings provide evidence that the severe/non-severe subdivision in recovery modelling is not an artefact of previous confounds. The presented out-of-sample prediction performance may serve as benchmark to evaluate promising biomarkers of stroke recovery.

2021-12-21

Journal of Neurology Neurosurgery & Psychiatry (publié)

Cognitive health mediates the effect of hippocampal volume on COVID‐19‒related knowledge or anxiety change during the COVID‐19 pandemic

Min Su Kang

Julie Ottoy

Stijn Servaes

Firoza Z Lussier

Gleb Bezgin

Mira Chamoun

Jenna Stevenson

Suzanne King

Serge Gauthier

Pedro Rosa‐Neto

Our finding highlights the poorer knowledge of COVID19 and related risks in individuals with cognitive/memory impairments; the CDRSOB, indic… (voir plus)ative of cognitive health, significantly mediated the effect of hippocampal volume on the rate of change in anxiety or knowledge on COVID19 in our cohort. This study urges for a more effective strategy and policy about informing and educating the individual with cognitive/memory impairment on COVID19 and related risks.

2021-11-30

Alzheimer's & Dementia (publié)

Tau‐load in the lingual gyrus impacts anxiety levels during the COVID‐19 pandemic in participants of longitudinal observational studies in aging

Stijn Servaes

Firoza Z Lussier

Gleb Bezgin

Yi‐Ting Wang

Jenna Stevenson

Cécile Tissot

Guillaume Elgbeili

Jaime Fernandez Arias

Joseph Therriault

Andréa Lessa Benedet

Mira Chamoun

Tharick A. Pascoal

Suzanne King

Serge Gauthier

Pedro Rosa‐Neto

By obtaining a better grasp on the impact of the COVID‐19 pandemic on individuals with cognitive impairment, this knowledge could be used … (voir plus)to improve the delivery of information to this particular group. We aimed to assess the relationship between tau deposition and the change in anxiety levels, before and during the pandemic. We hypothesized that since the pandemic, higher tau loads would lower the change in anxiety. Furthermore, we expected these anxiety levels not to be associated with COVID‐19 related stress in participants with cognitive decline. 63 participants of the Translational Biomarker of Aging and Dementia (TRIAD) cohort (cognitively healthy, N=38; cognitively impaired, N=25, of which 7 had dementia due to Alzheimer’s disease), were assessed to evaluate their individual change in anxiety levels (GAD‐7). This was done at three different timepoints, of which the latest fell during the COVID‐19 lockdown period. Two rates of change, one before and one during the pandemic, were determined using the following definition: (next timepoint – current timepoint)/time difference. In addition, at the latest timepoint, subjective stress due to COVID‐19 was measured using the Montreal Assessment of Stress related to COVID‐19 (MASC). To assess the levels of tau, standard uptake value ratios (SUVR) from previously obtained [18F]MK‐6240 PET‐scans were used. [18F]MK‐6240 tracer binding in the lingual gyrus was negatively associated with the rate of change in GAD‐7 scores after correcting for age, sex, years of education and the presence of APOE ε4, but only in cognitively impaired individuals during the pandemic (fig 1A). In addition, the GAD‐7 score at the latest timepoint was associated with stress related to COVID‐19, but only in cognitively healthy individuals (fig 1B and 1C). The presence of tau in the lingual gyrus negatively affected the rate of change in GAD‐7 scores during the COVID‐19 pandemic in individuals with cognitive impairment. This could indicate that information pertaining to the pandemic does not reach these individuals in an efficient manner. The missing association between COVID‐19 induced stress and the latest GAD‐7 scores in these individuals is a further indication of this.

2021-11-30

Alzheimer's & Dementia (inconnu)

Loneliness is linked to specific subregional alterations in hippocampus-default network co-variation

Chris Zajner

R. Nathan Spreng

Social interaction complexity makes humans unique. But in times of social deprivation this strength risks to expose important vulnerabilitie… (voir plus)s. Human social neuroscience studies have placed a premium on the default network (DN). In contrast, hippocampus (HC) subfields have been intensely studied in rodents and monkeys. To bridge these two literatures, we here quantified how DN subregions systematically co-vary with specific HC subfields in the context of subjective social isolation (i.e., loneliness). By co-decomposition using structural brain scans of ∼40,000 UK Biobank participants, loneliness was specially linked to midline subregions in the uncovered DN patterns. These association cortex signatures coincided with concomitant HC patterns implicating especially CA1 and molecular layer. These patterns also showed a strong affiliation with the fornix white-matter tract and the nucleus accumbens. In addition, separable signatures of structural HC-DN co-variation had distinct associations with the genetic predisposition for loneliness at the population level.

2021-11-23

Journal of Neurophysiology (publié)

The meaning of significant mean group differences for biomarker discovery

Eva Loth

Jumana Ahmad

Chris Chatham

Beatriz López

Ben Carter

Daisy Crawley

Bethany Oakley

Hannah Hayward

Jennifer Cooke

Antonia San José Cáceres

Emily Jones

Tony Charman

Christian Beckmann

Thomas Bourgeron

Roberto Toro

Jan Buitelaar

Declan Murphy

Guillaume Dumas

Over the past decade, biomarker discovery has become a key goal in psychiatry to aid in the more reliable diagnosis and prognosis of heterog… (voir plus)eneous psychiatric conditions and the development of tailored therapies. Nevertheless, the prevailing statistical approach is still the mean group comparison between “cases” and “controls,” which tends to ignore within-group variability. In this educational article, we used empirical data simulations to investigate how effect size, sample size, and the shape of distributions impact the interpretation of mean group differences for biomarker discovery. We then applied these statistical criteria to evaluate biomarker discovery in one area of psychiatric research—autism research. Across the most influential areas of autism research, effect size estimates ranged from small (d = 0.21, anatomical structure) to medium (d = 0.36 electrophysiology, d = 0.5, eye-tracking) to large (d = 1.1 theory of mind). We show that in normal distributions, this translates to approximately 45% to 63% of cases performing within 1 standard deviation (SD) of the typical range, i.e., they do not have a deficit/atypicality in a statistical sense. For a measure to have diagnostic utility as defined by 80% sensitivity and 80% specificity, Cohen’s d of 1.66 is required, with still 40% of cases falling within 1 SD. However, in both normal and nonnormal distributions, 1 (skewness) or 2 (platykurtic, bimodal) biologically plausible subgroups may exist despite small or even nonsignificant mean group differences. This conclusion drastically contrasts the way mean group differences are frequently reported. Over 95% of studies omitted the “on average” when summarising their findings in their abstracts (“autistic people have deficits in X”), which can be misleading as it implies that the group-level difference applies to all individuals in that group. We outline practical approaches and steps for researchers to explore mean group comparisons for the discovery of stratification biomarkers.

2021-10-31

PLoS Computational Biology (publié)