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Predicting Axonal Response to Molecular Gradients with a Computational Model of Filopodial Dynamics

geoff{at}georgetown.edu, Department of Neuroscience, Georgetown University Medical Center, Washington, D.C. 20007, U.S.A.

Ming Gu

gu{at}klab.caltech.edu, Computation and Neural Systems, California Institute of Technology Pasadena, CA 91125, USA

Jeffrey S. Urbach

urbach{at}physics.georgetown.edu, Department of Physics, Georgetown University, Washington, D.C. 20057, U.S.A.

Axons are often guided to their targets in the developing nervous system by attractive or repulsive molecular concentration gradients. We propose a computational model for gradient sensing and directed movement of the growth cone mediated by filopodia. We show that relatively simple mechanisms are sufficient to generate realistic trajectories for both the short-term response of axons to steep gradients and the long-term response of axons to shallow gradients. The model makes testable predictions for axonal response to attractive and repulsive gradients of different concentrations and steepness, the size of the intracellular amplification of the gradient signal, and the differences in intracellular signaling required for repulsive versus attractive turning.

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