Local Diameter Fully Constrains Dendritic Size in Basal but not Apical Trees of CA1 Pyramidal Neurons

Abstract

Computational modeling of dendritic morphology is a powerful tool for quantitatively describing complex geometrical relationships, uncovering principles of dendritic development, and synthesizing virtual neurons to systematically investigate cellular biophysics and network dynamics. A feature common to many morphological models is a dependence of the branching probability on local diameter. Previous models of this type have been able to recreate a wide variety of dendritic morphologies. However, these diameter-dependent models have so far failed to properly constrain branching when applied to hippocampal CA1 pyramidal cells, leading to explosive growth. Here we present a simple modification of this basic approach, in which all parameter sampling, not just bifurcation probability, depends on branch diameter. This added constraint prevents explosive growth in both apical and basal trees of simulated CA1 neurons, yielding arborizations with average numbers and patterns of bifurcations extremely close to those observed in real cells. However, simulated apical trees are much more varied in size than the corresponding real dendrites. We show that, in this model, the excessive variability of simulated trees is a direct consequence of the natural variability of diameter changes at and between bifurcations observed in apical, but not basal, dendrites. Conversely, some aspects of branch distribution were better matched by virtual apical trees than by virtual basal trees. Dendritic morphometrics related to spatial position, such as path distance from the soma or branch order, may be necessary to fully constrain CA1 apical tree size and basal branching pattern.

Models and Simulation of 3D Neuronal Dendritic Trees Using Bayesian Networks

“…A number of stages have been described during neuron development, and different parts might have different morphologies and be regulated by different factors (Donohue and Ascoli 2005a). Making a distinction between segments at different centrifugal orders is useful for identifying context-specific interactions.…”

“…As far as we know, this is the first time that such a multivariate test has been used to evaluate the joint probability distribution over a set of variables that describe dendritic morphology. Usually, univariate statistical tests that compare each variable independently are used (Lindsay et al 2007;Torben-Nielsen et al 2008b), or plots are visually inspected to evaluate bivariate or conditional densities (Donohue and Ascoli 2005a;Koene et al 2009). More complex evaluation methods are still needed in order to accurately compare dendritic morphology.…”

Successes and Rewards in Sharing Digital Reconstructions of Neuronal Morphology

“…This approach was also applied to the description of Purkinje cells and further compared to a different simulation scheme in which subsequent phases of branch attachment were implemented in parallel over an entire population of cells (Ascoli et al 2001). A simplified version of the diameter-based strategy was later extended to CA1 pyramidal cells, with different success for separate dendritic regions: tree size was better captured in basal than in apical trees, but the opposite held for topological asymmetry (Donohue and Ascoli 2005b). …”

L-Measure: a web-accessible tool for the analysis, comparison and search of digital reconstructions of neuronal morphologies

“…LM is also employed for the extraction of parameter distributions from experimental data required for resampling by stochastic computational simulations to generate virtual neurons 23 . Similarly, LM is often used to investigate the quality and limitations of these models by comparing their emergent morphological properties with the original experimental data 24 .…”