Natalí Barros-Zulaica

The paper explains neuronal network architecture through spatial continuity and validates it with a stochastic algorithm matching reference data.

The paper investigates how human neuronal morphology influences synaptic connectivity complexity and shows that human neuron shapes lead to more complex connectomes compared to rodents.

This study builds a detailed computational model of the human neocortex and compares it to a rat model, revealing differences in cell density, branching complexity, and synaptic connectivity.

The paper presents a large-scale biophysically detailed model of somatosensory cortex to simulate and validate cortical dynamics and experimental results.

The paper compares dendritic architecture in human and mice neuronal networks, finding that human pyramidal cells have greater dendritic complexity, contributing to increased network complexity despite lower neuron density.

The paper estimates the size of the readily-releasable vesicle pool (NRRP) at synaptic connections in the neocortex, finding values between two to three for L5-TTPC connections and suggesting multi-vesicular release is common.