Jakub Kopal

F66. FROM GENE TO COGNITION: MAPPING THE EFFECTS OF GENOMIC DELETIONS AND DUPLICATIONS ON COGNITIVE ABILITY

Sayeh Kazem

Kuldeep Kumar

Thomas Renne

Martineau Jean-Louis

Zohra Saci

Laura Almasy

David Glahn

Guy Wolf

Guillaume Dumas

Sébastien Jacquemont

2023-09-30

European Neuropsychopharmacology (publié)

doi.org

The default network dominates neural responses to evolving movie stories

Enning Yang

Filip Milisav

Jakub Kopal

Avram J. Holmes

Georgios D. Mitsis

Bratislav Misic

Emily S. Finn

Danilo Bzdok

Neuroscientific studies exploring real-world dynamic perception often overlook the influence of continuous changes in narrative content. In … (voir plus)our research, we utilize machine learning tools for natural language processing to examine the relationship between movie narratives and neural responses. By analyzing over 50,000 brain images of participants watching Forrest Gump from the studyforrest dataset, we find distinct brain states that capture unique semantic aspects of the unfolding story. The default network, associated with semantic information integration, is the most engaged during movie watching. Furthermore, we identify two mechanisms that underlie how the default network liaises with the amygdala and hippocampus. Our findings demonstrate effective approaches to understanding neural processes in everyday situations and their relation to conscious awareness.

2023-07-13

Nature Communications (publié)

doi.org

The end game: respecting major sources of population diversity

Jakub Kopal

Lucina Q. Uddin

Danilo Bzdok

Human neuroscience is enjoying burgeoning population data resources: large-scale cohorts with thousands of participant profiles of gene expr… (voir plus)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 (publié)

doi.org

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

Jakub Kopal

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 … (voir 12 de plus)

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

Danilo Bzdok

Copy number variations (CNVs) are rare genomic deletions and duplications that can affect brain and behaviour. Previous reports of CNV pleio… (voir plus)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 (inconnu)

doi.org

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

Enning Yang

Filip Milisav

Jakub Kopal

Avram J. Holmes

Georgios D. Mitsis

Bratislav Misic

Emily S. Finn

Danilo Bzdok

Naturalistic neuroscience opened the door to new insights into neural circuits that serve real-world dynamic perception. Such studies have o… (voir plus)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 (publié)

doi.org

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

Enning Yang

Filip Milisav

Jakub Kopal

Avram J. Holmes

Georgios D. Mitsis

Bratislav Misic

Emily S. Finn

Danilo Bzdok

Naturalistic neuroscience opened the door to new insights into neural circuits that serve real-world dynamic perception. Such studies have o… (voir plus)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 (publié)

doi.org

Endorsing Complexity Through Diversity: Computational Psychiatry Meets Big Data Analytics

Jakub Kopal

Danilo Bzdok

2022-08-04

Biological Psychiatry (inconnu)

doi.org