Papers on axon guidance available

[Geoff Goodhill]

Dear Connectionists,

The following two recent papers may be of interest to readers of this
list. They can be downloaded from

http://cns.georgetown.edu/~geoff/pubs.html

Rosoff, W.J., Urbach, J.S., Esrick, M., McAllister, R.G., Richards,
L.J. & Goodhill, G.J. (2004).
A new chemotaxis assay shows the extreme sensitivity of axons to
molecular gradients.
Nature Neuroscience, 7, 678-682.

Goodhill, G.J., Gu, M. & Urbach, J.S. (2004).
Predicting axonal response to molecular gradients with a computational 
model of filopodial dynamics.
Neural Computation, in press.

Abstracts are appended below.

Sincerely,

Geoff 

Geoffrey J Goodhill, PhD
Department of Neuroscience 
Georgetown University Medical Center
3900 Reservoir Road NW, Washington DC 20007
Email: geoff at georgetown.edu
Homepage: cns.georgetown.edu

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A new chemotaxis assay shows the extreme sensitivity of axons to
molecular gradients.

Axonal chemotaxis is believed to play a key role in wiring up the
developing and regenerating nervous system, but little is known about
how axons actually respond to molecular gradients. We report a new
quantitative assay that allows the long-term response of axons to
gradients of known and controllable shape to be examined in a
three-dimensional gel. Using this assay we show that axons may be
nature's most sensitive gradient detectors, but that this
sensitivity exists only within a narrow range of ligand
concentrations.  This assay should also be applicable to other
biological processes controlled by molecular gradients, such as cell
migration and morphogenesis.

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Predicting axonal response to molecular gradients with a computational
model of filopodial dynamics.

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.