Skirmantas Janušonis

This study shows that developing serotonergic axons follow pre-existing serotonergic pathways, supporting the epiphytic guidance hypothesis.

This study uses high-resolution holotomography to visualize serotonergic axon growth dynamics in mouse embryos, revealing stochastic motion patterns and providing data for computational modeling.

The paper models serotonergic fiber organization in the Pacific angelshark brain using supercomputing simulations of fractional Brownian motion, showing stochastic processes can reproduce observed fiber density patterns.

The paper qualitatively describes individually-tagged serotonergic axons in mouse telencephalic regions using Brainbow labeling and confocal microscopy.

The paper develops an experimental platform for analyzing single serotonergic fibers in the mouse brain using stochastic modeling and transgenic visualization techniques.

The paper uses a supercomputing simulation of fractional Brownian motion to predict serotonergic axon distribution in a 3D mouse brain model, showing qualitative similarity to actual densities.

This study uses high-resolution imaging to analyze the spatiotemporal behavior of single serotonergic axons in vitro, revealing their stochastic geometry and morphology.

The paper proposes a dropout algorithm inspired by serotonergic fibers' anomalous diffusion, suggesting potential biological analogies for regularization in ANNs.

The paper models serotonergic axon distributions using reflected Fractional Brownian Motion and shows it approximates real brain fiber densities.