Danilo Bzdok

Why AI Models Hallucinate and How to Fix Them

A tab representation of the Pre trained CLIP Vision Transformer

October 8, 2025

Praneet Suresh

Jack Stanley

Danilo Bzdok

Sonia Joseph

Luca Scimeca

Using LLMs to better understand autism diagnosis

March 25, 2025

Jack Stanley

Danilo Bzdok

Towards Precision Medicine: Understanding Inference and Prediction Divergence in Biomedicine

September 8, 2020

Danilo Bzdok

Publications

Generative lesion pattern decomposition of cognitive impairment after stroke

Anna K. Bonkhoff

Jae-Sung Lim

Hee-Joon Bae

Nick A. Weaver

Hugo J. Kuijf

J. Matthijs Biesbroek

Natalia S. Rost

Cognitive impairment is a frequent and disabling sequela of stroke. There is however incomplete understanding of how lesion topographies in … (see more)the left and right cerebral hemisphere brain interact to cause distinct cognitive deficits. We integrated machine learning and Bayesian hierarchical modelling to enable a hemisphere-aware analysis of 1080 acute ischaemic stroke patients with deep profiling ∼3 months after stroke. We show the relevance of the left hemisphere in the prediction of language and memory assessments and relevance of the right hemisphere in the prediction of visuospatial functioning. Global cognitive impairments were equally well predicted by lesion topographies from both sides. Damage to the hippocampal and occipital regions on the left was particularly informative about lost naming and memory functions, while damage to these regions on the right was linked to lost visuospatial functioning. Global cognitive impairment was predominantly linked to lesioned tissue in the supramarginal and angular gyrus, the post-central gyrus as well as the lateral occipital and opercular cortices of the left hemisphere. Hence, our analysis strategy uncovered that lesion patterns with unique hemispheric distributions are characteristic of how cognitive capacity is lost due to ischaemic brain tissue damage.

2021-03-31

Brain Communications (published)

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 … (see 2 more)

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… (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.

2021-03-30

bioRxiv (preprint)

Fasting alters the gut microbiome reducing blood pressure and body weight in metabolic syndrome patients

András Maifeld

Hendrik Bartolomaeus

Ulrike Löber

Ellen G. Avery

Nico Steckhan

Lajos Markó

Nicola Wilck

Ibrahim Hamad

Urša Šušnjar

Anja Mähler

Christoph Hohmann

Chia-Yu Chen

Holger Cramer

Gustav Dobos

Till Robin Lesker

Till Strowig

Ralf Dechend

Markus Kleinewietfeld

Andreas Michalsen … (see 2 more)

Dominik N. Müller

Sofia K. Forslund

Abstract Periods of fasting and refeeding may reduce cardiometabolic risk elevated by Western diet. We show that in hypertensive metabolic s… (see more)yndrome (MetS) patients (n=35), a 5-day fast followed by a modified DASH diet (Dietary Approach to Stop Hypertension) reduced systolic blood pressure (SBP), antihypertensive medication need, and body-mass index (BMI) at three months post intervention compared to a modified DASH diet alone (n=36). Fasting altered the gut microbiome, impacting bacterial taxa and gene modules associated with short-chain fatty acid production. Cross-system analyses revealed a positive correlation of circulating mucosa-associated invariant T (MAIT) cells, non-classical monocytes and CD4+ effector T cells with SBP. Furthermore, regulatory T cells (Tregs) positively correlated with BMI and weight. Machine learning could predict sustained SBP-responsiveness within the fasting group from baseline immunome data, identifying CD8+ effector T cells, Th17 cells and Tregs as important contributors to the model. The high-resolution multi-omics data highlights fasting as a promising non-pharmacological intervention in MetS.

2021-03-29

Nature Communications (published)

Loneliness and Neurocognitive Aging

R. Nathan Spreng

2021-03-28

Advances in Geriatric Medicine and Research (published)

Mapping gene transcription and neurocognition across human neocortex

Justine Y. Hansen

Ross D. Markello

Jacob W. Vogel

Jakob Seidlitz

Bratislav Misic

2021-03-24

Nature Human Behaviour (published)

Functional specialization within the inferior parietal lobes across cognitive domains

Ole Numssen

Gesa Hartwigsen

The inferior parietal lobe (IPL) is a key neural substrate underlying diverse mental processes, from basic attention to language and social … (see more)cognition, that define human interactions. Its putative domain-global role appears to tie into poorly understood differences between cognitive domains in both hemispheres. Across attentional, semantic, and social cognitive tasks, our study explored functional specialization within the IPL. The task specificity of IPL subregion activity was substantiated by distinct predictive signatures identified by multivariate pattern-learning algorithms. Moreover, the left and right IPL exerted domain-specific modulation of effective connectivity among their subregions. Task-evoked functional interactions of the anterior and posterior IPL subregions involved recruitment of distributed cortical partners. While anterior IPL subregions were engaged in strongly lateralized coupling links, both posterior subregions showed more symmetric coupling patterns across hemispheres. Our collective results shed light on how under-appreciated hemispheric specialization in the IPL supports some of the most distinctive human mental capacities.

2021-03-01

eLife (published)

The neural correlates of ongoing conscious thought

Jonathan Smallwood

Adam Turnbull

Hao-Ting Wang

Nerissa S.P. Ho

Giulia L. Poerio

Theodoros Karapanagiotidis

Delali Konu

Brontë Mckeown

Meichao Zhang

Charlotte Murphy

Deniz Vatansever

Mahiko Konishi

Robert Leech

Paul Seli

Jonathan W. Schooler

Boris C Bernhardt

Daniel S. Margulies

Elizabeth Jefferies

2021-01-31

iScience (published)

Author response: Functional specialization within the inferior parietal lobes across cognitive domains

Ole Numssen

Gesa Hartwigsen

2021-01-20

(published)

Deep learning identifies partially overlapping subnetworks in the human social brain

Hannah Kiesow

R. Nathan Spreng

Avram J. Holmes

Mallar Chakravarty

Andre Marquand

B.T. Thomas Yeo

2021-01-13

Communications Biology (published)

Signal diffusion along connectome gradients and inter-hub routing differentially contribute to dynamic human brain function

Bo-yong Park

Reinder Vos de Wael

Casey Paquola

Sara Larivière

Oualid Benkarim

Jessica Royer

Shahin Tavakol

Raul R. Cruces

Qiongling Li

Sofie L. Valk

Daniel S. Margulies

Bratislav Misic

Jonathan Smallwood

Boris C. Bernhardt

2020-12-31

NeuroImage (published)

Functional idiosyncrasy has a shared topography with group-level connectivity alterations in autism

Oualid Benkarim

Casey Paquola

Bo-yong Park

Seok-Jun Hong

Jessica Royer

Reinder Vos de Wael

Sara Larivière

Sofie Valk

Laurent Mottron

Boris Bernhardt

Autism spectrum disorder (ASD) is commonly understood as a network disorder, yet case-control analyses against typically-developing controls… (see more) (TD) have yielded somewhat inconsistent patterns of results. The current work was centered on a novel approach to profile functional network idiosyncrasy, the inter-individual variability in the association between functional network organization and brain anatomy, and we tested the hypothesis that idiosyncrasy contributes to connectivity alterations in ASD. Studying functional network idiosyncrasy in a multi-centric dataset with 157 ASD and 172 TD, our approach revealed higher idiosyncrasy in ASD in the default mode, somatomotor and attention networks together with reduced idiosyncrasy in the lateral temporal lobe. Idiosyncrasy was found to increase with age in both ASD and TD, and was significantly correlated with symptom severity in the former group. Association analysis with structural and molecular brain features indicated that patterns of functional network idiosyncrasy were not correlated with ASD-related cortical thickness alterations, but closely with the spatial expression patterns of intracortical ASD risk genes. In line with our main hypothesis, we could demonstrate that idiosyncrasy indeed plays a strong role in the manifestation of connectivity alterations that are measurable with conventional case-control designs and may, thus, be a principal driver of inconsistency in the autism connectomics literature. These findings support important interactions between the heterogeneity of individuals with an autism diagnosis and group-level functional signatures, and help to consolidate prior research findings on the highly variable nature of the functional connectome in ASD. Our study promotes idiosyncrasy as a potential individualized diagnostic marker of atypical brain network development.

2020-12-17

bioRxiv (preprint)

Historical and cross-disciplinary trends in the biological and social sciences reveal an accelerating adoption of advanced analytics

Taylor Bolt

Jason S. Nomi

Lucina Q. Uddin

Methods for data analysis in the biomedical, life and social sciences are developing at a rapid pace. At the same time, there is increasing … (see more)concern that education in quantitative methods is failing to adequately prepare students for contemporary research. These trends have led to calls for educational reform to undergraduate and graduate quantitative research method curricula. We argue that such reform should be based on data-driven insights into within- and cross-disciplinary use of research methods. Our survey of peer-reviewed literature screened ∼3.5 million openly available research articles to monitor the cross-disciplinary usage of research methods in the past decade. We applied data-driven text-mining analyses to the methods and materials section of a large subset of this corpus to identify method trends shared across disciplines, as well as those unique to each discipline. As a whole, usage of T -test, analysis of variance, and other classical regression-based methods has declined in the published literature over the past 10 years. Machine-learning approaches, such as artificial neural networks, have seen a significant increase in the total share of scientific publications. We find unique groupings of research methods associated with each biomedical, life and social science discipline, such as the use of structural equation modeling in psychology, survival models in oncology, and manifold learning in ecology. We discuss the implications of these findings for education in statistics and research methods, as well as within- and cross-disciplinary collaboration.

2020-12-02

bioRxiv (preprint)