spacer gif spacer gif spacer gif spacer gif spacer gif
 QUICK SEARCH:   [advanced]


spacer gif
     Home     Help     Feedback     Subscriptions     Archive     Search    

The fully linked HTML version of this article has now been published.
Development ePress online publication date 21 Sep 2005
doi: 10.1242/dev.02029


This Article
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
dev.02029v1
132/20/4545    most recent
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Xu, J.
Right arrow Articles by Goodhill, G. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Xu, J.
Right arrow Articles by Goodhill, G. J.
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Research article

Adaptation is not required to explain the long-term response of axons to molecular gradients


Jun Xu, William J. Rosoff, Jeffrey S. Urbach, and Geoffrey J. Goodhill*
* Author for correspondence (e-mail: g.goodhill{at}uq.edu.au)

It has been suggested that growth cones navigating through the developing nervous system might display adaptation, so that their response to gradient signals is conserved over wide variations in ligand concentration. Recently however, a new chemotaxis assay that allows the effect of gradient parameters on axonal trajectories to be finely varied has revealed a decline in gradient sensitivity on either side of an optimal concentration. We show that this behavior can be quantitatively reproduced with a computational model of axonal chemotaxis that does not employ explicit adaptation. Two crucial components of this model required to reproduce the observed sensitivity are spatial and temporal averaging. These can be interpreted as corresponding, respectively, to the spatial spread of signaling effects downstream from receptor binding, and to the finite time over which these signaling effects decay. For spatial averaging, the model predicts that an effective range of roughly one-third of the extent of the growth cone is optimal for detecting small gradient signals. For temporal decay, a timescale of about 3 minutes is required for the model to reproduce the experimentally observed sensitivity.


Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?


This article has been cited by other articles:


Home page
Proc. Natl. Acad. Sci. USAHome page
D. Mortimer, J. Feldner, T. Vaughan, I. Vetter, Z. Pujic, W. J. Rosoff, K. Burrage, P. Dayan, L. J. Richards, and G. J. Goodhill
From the Cover: A Bayesian model predicts the response of axons to molecular gradients
PNAS, June 23, 2009; 106(25): 10296 - 10301.
[Abstract] [Full Text] [PDF]


Home page
DevelopmentHome page
A. C. von Philipsborn, S. Lang, J. Loeschinger, A. Bernard, C. David, D. Lehnert, F. Bonhoeffer, and M. Bastmeyer
Growth cone navigation in substrate-bound ephrin gradients
Development, July 1, 2006; 133(13): 2487 - 2495.
[Abstract] [Full Text] [PDF]




© The Company of Biologists Ltd 2005