Geometrical factors determining dendritic domain intersection between neurons: a modeling study
Abstract
Overlap between dendritic trees of neighboring neurons is a feature of nervous systems. Overlap allows neurons to share common afferences and defines the topography of the circuit they belong to. Proximity is also a requirement for dendritic communication, including dendro-dendritic synaptic contacts. We simulated overlap dynamics between pairs of ventral tegmental area dopamine neurons, a population characterized by diverse and extensive dendritic domains. Using each neuron’s 3D convex hull (CH) as a proxy for dendritic domain size and shape, we examined intersection versus cell-to-cell distance curves for 210 pairs of neurons, and found that decay dynamics were diverse and complex, indicating that intersection between real dendritic domains does not comply with spherical or isotropic shape assumptions. We re-examined intersection dynamics for the same 210 pairs, but this time with either: a) a normalized volume corresponding to the average volume of all CHs, b) normalized shapes, using an average CH shape, or CHs from neurons exhibiting average dendritic distribution, isotropy or morphology, or c) a normalized cell body position, which we artificially placed in each CHs’ centroid. All three interventions significantly increased pair intersection and simplified decay dynamics, yet shape normalization had the strongest influence. Critically, shape uniformity was also the most relevant factor for increased dendritic domain pair intersection using the neurons’ original brain position and distances. We applied this experimental approach to other populations using reconstructions from<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="http://neuromorpho.org">neuromorpho.org</ext-link>database and found that shape and intersection dynamics were cell-type dependent. We conclude that intersection between neurons is not only maximized by proximity, but that individual-specific dendritic domain geometries have a profound impact too. The results predict that one biological solution for circuits requiring selective connectivity is to exhibit greater heterogeneity in size, cell body location, and especially shape, among their constituent neuronal elements.
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