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Jakub Kopal

Alumni

Publications

Using rare genetic mutations to revisit structural brain asymmetry
Kuldeep Kumar
Kimia Shafighi
Claudia Modenato
Clara A. Moreau
Martineau Jean-Louis
Charles-Olivier Martin
Zohra Saci
Nadine Younis
Élise Douard
Khadije Jizi
Alexis Beauchamp-Chatel
Leila Kushan
Ana I. Silva
Marianne B. M. van den Bree
David E. J. Linden
Michael J. Owen
Jeremy Hall … (see 10 more)
Sarah Lippé
Bogdan Draganski
Ida E. Sønderby
Ole A. Andreassen
David C. Glahn
Paul M. Thompson
Carrie E. Bearden
Robert Zatorre
Sébastien Jacquemont
Asymmetry between the left and right brain is a key feature of brain organization. Hemispheric functional specialization underlies some of t… (see more)he most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variant studies, which typically exert small effects on brain phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We quantitatively dissected the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior mapping highlights the consequences of genetically controlled brain lateralization on human-defining cognitive traits.
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.
Rare CNVs and phenome-wide profiling highlight brain structural divergence and phenotypical convergence
Kuldeep Kumar
Claudia Modenato
Clara Moreau
Sandra Martin‐Brevet
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.
Bringing language to dynamic brain states: the default network dominates neural responses to evolving movie stories
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.
Bringing language to dynamic brain states: the default network dominates neural responses to evolving movie stories
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.
Endorsing Complexity Through Diversity: Computational Psychiatry Meets Big Data Analytics