Aurina Arnatkevičiūtė

TL;DR: These analyses have revealed that spatial patterning of gene expression and neuronal connectivity are closely linked, following broad spatial gradients that track regional variations in microcircuitry, inter-regional connectivity, and functional specialisation.

TL;DR: It is found that centrality measures are generally positively correlated to each other, the strength of these correlations varies across networks, and network modularity plays a key role in driving these cross-network variations.

TL;DR: It is demonstrated that thalamocortical connectivity recapitulates large-scale, low-dimensional connectivity gradients within the cerebral cortex and the Core-Matrix architecture of the thalamus is important for understanding network topology in a manner that supports dynamic integration of signals distributed across the brain.

TL;DR: A key role is identified for E:I heterogeneity in generating complex neuronal dynamics and the viability of using transcriptional data to constrain models of large-scale brain function is demonstrated.

TL;DR: It is found that an approach to motion correction that includes outlier replacement and within-slice volume correction led to a dramatic reduction in cross-subject correlations between head motion and structural connectivity strength, and that motion contamination is more severe when quantifying connectivity strength using mean tract fractional anisotropy rather than streamline count.