Geometrical factors determining dendritic domain intersection between neurons: a modeling study.

Abstract

Modeling the structural basis of neuronal connectivity has advanced our understanding of organization and function of the nervous system. Research has focused on predicting synaptic connectivity from the geometry of intersecting axonal and dendritic trees. We extended this framework to examine how the dendritic domains of neighbouring neurons intersect, aiming to understand how shared afferences and projection system topography arise. We studied intersections in pairs of ventral tegmental area (VTA) dopaminergic neurons (n = 15; 105 pairs), as if in their actual brain locations, using intersection of their 3D convex hulls polyhedra (CHPs) as proxies of domain intersection. Proximity increased intersection probability, but substantial data spreading suggested additional factors. We hypothesized that similarities in domain volume, orientation, somatic eccentricity, and shape increase intersection too. After independently normalizing each factor based on a common value or structural principle, we found that eccentricity homogenization most strongly increased intersection and model accuracy. Combining normalization of two or more factors further enhanced both metrics, though effects were factor dependent; simultaneous normalization of eccentricity and shape produced the greatest increases. We replicated the analysis with nigral dopaminergic neurons and found eccentricity to be the strongest determinant of intersection. This result held when systematically spacing CHPs and when using α-shapes for closer representation of dendritic architecture. Interestingly, VTA CHP pairs intersected more than nigral pairs at equal distances, suggesting greater geometrical heterogeneity in the latter. These findings suggest that differences in neuronal geometry contribute to segregated connectivity in topographically arranged neural circuits.