Modeling and analysis of axonogenesis: Random spatial network perspective

Yanthe E. Pearson, Donald A. Drew

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Data from time lapse microscopy of live embryonic rat hippocampal neurons growing in cell culture are used to study the dynamics of axonal growth.1 We analyze axonal trajectory data based on cells growing in a homogeneous medium. Due to the noisy nature of the data we develop filtering algorithms to smoothen out the paths while maintaining the underlying dynamics of the axon growth process. We analyze the new paths and propose a model for growth cone kinematics during axonogenesis without a gradient field. In this work we present a simple renewal process with the aim of reproducing certain path behaviors of the growth cone. Future development will include, renewal process simulation, and gradients eects.

Original languageEnglish (US)
Title of host publicationFrontiers of Applied and Computational Mathematics
Subtitle of host publicationNew Jersey Institute of Technology, USA, 19 - 21 May 2008
PublisherWorld Scientific Publishing Co.
Pages137-145
Number of pages9
ISBN (Electronic)9789812835291
ISBN (Print)9789812835284
DOIs
StatePublished - Jan 1 2008

Keywords

  • Axonogenesis
  • Random spatial networks
  • Stochastic dierential equations

ASJC Scopus subject areas

  • Mathematics(all)
  • Physics and Astronomy(all)

Fingerprint Dive into the research topics of 'Modeling and analysis of axonogenesis: Random spatial network perspective'. Together they form a unique fingerprint.

Cite this