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

Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease

Andrea I. Luppi

S. Parker Singleton

Justine Y. Hansen

Amy Kuceyeski

Richard F. Betzel

Bratislav Misic

Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain’s network architect… (see more)ure. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic engine. We also systematically incorporate neurotransmitter receptor density maps (18 receptors and transporters) and disease-related cortical abnormality maps (11 neurodegenerative, psychiatric and neurodevelopmental diseases; N = 17 000 patients, N = 22 000 controls). Integrating large-scale multimodal neuroimaging data from functional MRI, diffusion tractography, cortical morphometry, and positron emission tomography, we simulate how anatomically-guided transitions between cognitive states can be reshaped by pharmacological or pathological perturbation. Our results provide a comprehensive look-up table charting how brain network organisation and chemoarchitecture interact to manifest different cognitive topographies. This computational framework establishes a principled foundation for systematically identifying novel ways to promote selective transitions between desired cognitive topographies.

2023-03-16

bioRxiv (preprint)

Investigating the neural correlates of affective mentalizing and their association with general intelligence in patients with schizophrenia

Wladimir Tantchik

Melissa J. Green

Yann Quidé

Susanne Erk

Sebastian Mohnke

Carolin Wackerhagen

Nina Romanczuk-Seiferth

Heike Tost

Kristina Schwarz

Carolin Moessnang

Andreas Meyer-Lindenberg

Andreas Heinz

Henrik Walter

2023-03-12

Schizophrenia Research (unknown)

A cognitive fingerprint in human random number generation

Marc-Andre Schulz

Sebastian Baier

Benjamin Timmermann

Karsten Witt

Most work in the neurosciences collapses data from multiple subjects to obtain robust statistical results. This research agenda ignores t… (see more)hat even in healthy subjects brain structure and function are known to be highly variable. Recently, Finn and colleagues showed that the brain's functional organisation is unique to each individual and can yield human-specific connectome fingerprints. This raises the question whether unique functional brain architecture may reflect a unique implementation of cognitive processes and problem solving - i.e. "Can we identify single individuals based on how they think?". The present study addresses the general question of interindividual differences in the specific context of human random number generation. We analyzed the deployment of recurrent patterns in the pseudorandom sequences to develop an identification scheme based on subject-specific volatility patterns. We demonstrate that individuals can be reliably identified based on how they how they generate randomness patterns alone. We moreover show that this phenomenon is driven by individual preference and inhibition of patterns, together forming a cognitive fingerprint.

2023-03-06

Charité - Universitätsmedizin Berlin (published)

The end game: respecting major sources of population diversity

Lucina Q. Uddin

Human neuroscience is enjoying burgeoning population data resources: large-scale cohorts with thousands of participant profiles of gene expr… (see more)ession, brain scanning and sociodemographic measures. The depth of phenotyping puts us in a better position than ever to fully embrace major sources of population diversity as effects of interest to illuminate mechanisms underlying brain health.

2023-03-02

Nature Methods (published)

Rare CNVs and phenome-wide profiling highlight brain structural divergence and phenotypical convergence

Kuldeep Kumar

Karin Saltoun

Claudia Modenato

Clara Moreau

Sandra Martin‐Brevet

Guillaume Huguet

Martineau Jean‐Louis

Charles-Olivier Martin

Zohra Saci

Nadine Younis

Petra Tamer

Élise Douard

Anne Maillard

Borja Rodríguez‐Herreros

Aurélie Pain

Sonia Richetin

Leila Kushan

Ana Isabel Silva

Marianne van den Bree … (see 12 more)

David E.J. Linden

Michael J. Owen

Jeremy Hall

Sarah Lippé

Bogdan Draganski

Ida E. Sønderby

Ole A. Andreassen

David C. Glahn

Paul M. Thompson

Carrie E. Bearden

Sébastien Jacquemont

Copy number variations (CNVs) are rare genomic deletions and duplications that can affect brain and behaviour. Previous reports of CNV pleio… (see more)tropy imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, existing studies have primarily examined single CNV loci in small clinical cohorts. It remains unknown, for example, how distinct CNVs escalate vulnerability for the same developmental and psychiatric disorders. Here we quantitatively dissect the associations between brain organization and behavioural differentiation across 8 key CNVs. In 534 CNV carriers, we explored CNV-specific brain morphology patterns. CNVs were characteristic of disparate morphological changes involving multiple large-scale networks. We extensively annotated these CNV-associated patterns with ~1,000 lifestyle indicators through the UK Biobank resource. The resulting phenotypic profiles largely overlap and have body-wide implications, including the cardiovascular, endocrine, skeletal and nervous systems. Our population-level investigation established brain structural divergences and phenotypical convergences of CNVs, with direct relevance to major brain disorders.

2023-03-01

Nature Human Behaviour (unknown)

Social isolation is linked to classical risk factors of Alzheimer's disease-related dementias

Kimia Shafighi

Sylvia Villeneuve

Pedro Rosa Neto

AmanPreet Badhwar

Judes Poirier

Vaibhav Sharma

Yasser Iturria Medina

Patricia P. Silveira

Laurette Dubé

David Glahn

Alzheimer’s disease and related dementias is a major public health burden–compounding over upcoming years due to longevity. Recently, cl… (see more)inical evidence hinted at the experience of social isolation in expediting dementia onset. In 502,506 UK Biobank participants and 30,097 participants from the Canadian Longitudinal Study of Aging, we revisited traditional risk factors for developing dementia in the context of loneliness and lacking social support. Across these measures of subjective and objective social deprivation, we have identified strong links between individuals’ social capital and various indicators of Alzheimer’s disease and related dementias risk, which replicated across both population cohorts. The quality and quantity of daily social encounters had deep connections with key aetiopathological factors, which represent 1) personal habits and lifestyle factors, 2) physical health, 3) mental health, and 4) societal and external factors. Our population-scale assessment suggest that social lifestyle determinants are linked to most neurodegeneration risk factors, highlighting them as promising targets for preventive clinical action.

2023-01-31

PLOS ONE (published)

Disentangling poststroke cognitive deficits and their neuroanatomical correlates through combined multivariable and multioutcome lesion‐symptom mapping

Nick A. Weaver

Muhammad Hasnain Mamdani

Jae‐Sung Lim

Johannes Matthijs Biesbroek

Geert Jan Biessels

Irene M. C. Huenges Wajer

Yeonwook Kang

Beom Joon Kim

Byung‐Chul Lee

Keon‐Joo Lee

Kyung‐Ho Yu

Hee‐Joon Bae

Hugo J. Kuijf

Studies in patients with brain lesions play a fundamental role in unraveling the brain's functional anatomy. Lesion‐symptom mapping (LSM) … (see more)techniques can relate lesion location to cognitive performance. However, a limitation of current LSM approaches is that they can only evaluate one cognitive outcome at a time, without considering interdependencies between different cognitive tests. To overcome this challenge, we implemented canonical correlation analysis (CCA) as combined multivariable and multioutcome LSM approach. We performed a proof‐of‐concept study on 1075 patients with acute ischemic stroke to explore whether addition of CCA to a multivariable single‐outcome LSM approach (support vector regression) could identify infarct locations associated with deficits in three well‐defined verbal memory functions (encoding, consolidation, retrieval) based on four verbal memory subscores derived from the Seoul Verbal Learning Test (immediate recall, delayed recall, recognition, learning ability). We evaluated whether CCA could extract cognitive score patterns that matched prior knowledge of these verbal memory functions, and if these patterns could be linked to more specific infarct locations than through single‐outcome LSM alone. Two of the canonical modes identified with CCA showed distinct cognitive patterns that matched prior knowledge on encoding and consolidation. In addition, CCA revealed that each canonical mode was linked to a distinct infarct pattern, while with multivariable single‐outcome LSM individual verbal memory subscores were associated with largely overlapping patterns. In conclusion, our findings demonstrate that CCA can complement single‐outcome LSM techniques to help disentangle cognitive functions and their neuroanatomical correlates.

2023-01-19

Human Brain Mapping (published)

Adaptive Network Interactions in Cognition After Stimulation-Induced Inferior Parietal Lobe Inhibition

Kathleen Williams

Ole Numssen

Gesa Hartwigsen

2022-12-31

Brain Stimulation (unknown)

Bringing language to dynamic brain states: the default network dominates neural responses to evolving movie stories

Enning Yang

Filip Milisav

Avram J. Holmes

Georgios D. Mitsis

Bratislav Misic

Emily S. Finn

Naturalistic neuroscience opened the door to new insights into neural circuits that serve real-world dynamic perception. Such studies have o… (see more)ften neglected the rich texture of the movie narrative itself, but semantic content can be used to contextualize the induced neural responses. Here, we translated natural language processing tools from machine learning to characterize brain states estimated from hidden Markov models. Our analytical strategy allowed pitting shallow unimodal against the deep associative brain network layers in explaining how semantic content of the movie links to observed neural activity. Pooling information across >53,000 brain image time points watching Forrest Gump, we could show that distinct dynamic brain states capture unique semantic facets along the unfolding movie narrative. The spatiotemporal dynamics of brain states explicitly captured subject-level responses throughout the brain network hierarchy. Across all analyses, the default network was most intimately linked to semantic information integration, and this neural system switched online for longest durations during movie watching. Further, we identified and described two mechanisms of how the default network liaises dynamically with microanatomically defined subregion partners: the amygdala and the hippocampus. Our study thus unlocks the potential of natural language processing to explore neural processes in everyday life situations that engage key aspects of conscious awareness.

2022-12-31

McGill University (published)

Bringing language to dynamic brain states: the default network dominates neural responses to evolving movie stories

Enning Yang

Filip Milisav

Avram J. Holmes

Georgios D. Mitsis

Bratislav Misic

Emily S. Finn

2022-12-31

McGill University (published)

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

Gary R. Turner

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.

2022-12-31

(published)

www.semanticscholar.org

Home alone: A population neuroscience investigation of brain morphology substrates

MaryAnn Noonan

Chris Zajner

As a social species, ready exchange with peers is a pivotal asset - our “social capital”. Yet, single-person households have come to per… (see more)vade metropolitan cities worldwide, with unknown consequences in the long run. Here, we systematically explore the morphological manifestations associated with singular living in ∼40,000 UK Biobank participants. The uncovered population-level signature spotlights the highly associative default mode network, in addition to findings such as in the amygdala central, cortical and corticoamygdaloid nuclei groups, as well as the hippocampal fimbria and dentate gyrus. Sex-stratified analyses revealed male-specific neural substrates, including somatomotor, saliency and visual systems, while female-specific neural substrates centred on the dorsomedial prefrontal cortex. In line with our demographic profiling results, the discovered neural imprint of living alone is potentially linked to alcohol and tobacco consumption, anxiety, sleep quality as well as daily TV watching. The secular trend for solitary living will require new answers from public-health decision makers.

2022-12-31

NeuroImage (published)