Neurons exploit stochastic growth to rapidly and economically build dense radially oriented dendritic arbors.

ABSTRACT: Dendrites grow by stochastic branching, elongation, and retraction. A key question is whether such a mechanism is sufficient to form highly branched dendritic morphologies. Alternatively, are signals from other cells or is the topological hierarchy of the growing network necessary for dendrite geometry? To answer these questions, we developed a mean-field model in which branch dynamics is isotropic and homogenous (i.e., no extrinsic instruction) and depends only on the average lengths and densities of branches. Branching is modeled as density-dependent nucleation so there are no tree structures and no network topology. Despite its simplicity, the model predicted several key morphological properties of class IV Drosophila sensory dendrites, including the exponential distribution of branch l

SUBMITTER: Ouyang X 

PROVIDER: S-EPMC11888375 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature