Aurina Arnatkevičiūtė

This study investigates the role of DUSP6 in ADHD by generating DUSP6 knockouts in iPSC-derived dopaminergic neurons, finding increased dopamine secretion and transcriptomic changes linked to neurodevelopment and psychiatric disorders.

The paper benchmarks overlapping community detection methods on human connectomes, finding OSLOM best identifies overlapping structures and reveals hierarchical cortical organization.

This study profiles transcriptomes of dopaminergic neurons from ADHD and neurotypical iPSCs, identifying DEGs overlapping with ADHD GWAS results and suggesting delayed neuronal maturation.

The paper investigates the cortical, genetic, and molecular dissociation of three attention networks using multimodal neuroimaging and finds that gene expression co-varies with activation maps but neurotransmitter receptor distributions do not align with the networks.

This study evaluates how different diffusion MRI processing pipelines affect the identification of connectome hubs in humans, finding significant variability in hub location and connectivity based on processing choices.

The paper identifies new cortical gene expression components linked to neurodevelopment and finds associations with autism and schizophrenia across multiple data types.

This paper characterizes individualized cortical shape asymmetries using MRI data, finding they are more informative for individual identification than size-based measures.

This study develops a model to capture wiring cost and topological complexity in human brain connectivity but finds models struggle to capture spatial embedding.

The paper develops the abagen toolbox to standardize imaging transcriptomics workflows and shows that methodological variability significantly affects research outcomes using the Allen Human Brain Atlas.

This study shows that regional transcriptional heterogeneity in excitatory and inhibitory receptor gene expression improves the accuracy of models of brain functional connectivity and supports complex neuronal dynamics.

This study identifies genetic influences on hub connectivity in the human connectome using diffusion-weighted imaging in twins and transcriptomic data.

The paper identifies and addresses statistical biases in gene-set enrichment analysis of brain-wide transcriptomic data, introducing new null models to reduce false positives.

This study evaluates how different preprocessing steps affect motion-related contamination in diffusion MRI structural connectivity estimates, finding that specific motion correction methods significantly reduce cross-subject correlations between motion and connectivity strength.

The paper identifies Core and Matrix thalamic sub-populations and links them to spatio-temporal cortical connectivity gradients using fMRI and calcium-binding protein data.

This study shows that individual differences in haemoglobin levels affect BOLD fMRI functional connectivity and its relationship with cognition, with sex-specific patterns observed.

This study investigates how changes in wakefulness affect behavioural and neural markers of conscious awareness in humans.

The paper shows that fMRI timescales correlate with structural connectivity strength in humans, mirroring findings in mice.

This paper outlines a seven-step pipeline for integrating brain-wide gene expression and neuroimaging data and evaluates how processing choices affect results.

The paper shows that hub neurons in the C. elegans connectome have tightly coupled gene expression, which is linked to their role as command interneurons regulating locomotion.