Modeling dendritic geometry and the development of nerve connections

Van Pelt, J., Van Ooyen, A., and Uylings, H. B. M. (2001). In: De Schutter, E., ed. Computational Neuroscience: Realistic Modeling for Experimentalists. Boca Raton: CRC Press, pp. 179-208. [Full text: PDF]

Abstract

The two models described in this chapter focus on the development of neuronal geometry and interneuronal connectivity. The first model, for dendritic geometry, is based on a stochastic description of elongation and branching during neurite outgrowth. This model allows the user to generate random trees by means of computer simulations. Using optimized parameters for particular neuron types, the geometrical properties of these models can be made to correspond with those of the experimentally observed dendrites. The second model, for the development of nerve connections, describes competition for neurotrophic factors. This model is formulated in terms of differential equations, which can be studied analytically and numerically using well-known tools for nonlinear system analysis.