Abstract
The way in which dendrites spread within neural tissue determines the resulting circuit connectivity and computation. However, a general theory describing the dynamics of this growth process does not exist. Here we obtain the first time-lapse reconstructions of neurons in living fly larvae over the entirety of their developmental stages. We show that these neurons expand in a remarkably regular stretching process that conserves their shape. Newly available space is filled optimally, a direct consequence of constraining the total amount of dendritic cable. We derive a mathematical model that predicts one time point from the previous and use this model to predict dendrite morphology of other cell types and species. In summary, we formulate a novel theory of dendrite growth based on detailed developmental experimental data that optimises wiring and space filling and serves as a basis to better understand aspects of coverage and connectivity for neural circuit formation.
In brief We derive a detailed mathematical model that describes long-term time-lapse data of growing dendrites; it optimises total wiring and space-filling.
Dendrite growth iterations guarantee optimal wiring at each iteration.
Optimal wiring guarantees optimal space filling.
The growth rule from fly predicts dendrites of other cell types and species.
Fly neurons stretch-and-fill target area with precise scaling relations.
Phase transition of growth process between fly embryo and larval stages.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵* cuntz{at}fias.uni-frankfurt.de
