| Abstract | Axonogenesis is the growth and differentiation of axonal processes by the developing neuron. Studies in vivo and in vitro have demonstrated that ethanol disrupts axonogenesis. Current studies use time lapse microscopy of live embryonic rat hippocampal neurons growing in cell culture to study the dynamics of axonal growth and its disruption by ethanol. Thus far we can analyze axonal trajectory data based on cells growing in an undisturbed environment. Due to the noisy nature of the data we develop filtering algorithms to smoothen out the paths while maintaining the underlying dynamics of the axonal growth process. We analyze the new paths and propose a model for growth cone kinematics during axonogenesis without a gradient field. We propose a general model that can be extended to accommodate steering effects, a consequence of adding gradients. We present a simple renewal process with the aim of reproducing certain path behaviors of the growth cone. Future development will include angle variability and gradients effects. |
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