Bayesian model predicts the response of axons to molecular gradients.

@article{Mortimer2009BayesianMP,
  title={Bayesian model predicts the response of axons to molecular gradients.},
  author={Duncan Mortimer and Julia Feldner and Timothy E Vaughan and Irina Vetter and Zac Pujic and William J. Rosoff and Kevin Burrage and Peter Dayan and Linda J. Richards and Geoffrey J. Goodhill},
  journal={Proceedings of the National Academy of Sciences of the United States of America},
  year={2009},
  volume={106 25},
  pages={10296-301}
}
Axon guidance by molecular gradients plays a crucial role in wiring up the nervous system. However, the mechanisms axons use to detect gradients are largely unknown. We first develop a Bayesian "ideal observer" analysis of gradient detection by axons, based on the hypothesis that a principal constraint on gradient detection is intrinsic receptor binding noise. Second, from this model, we derive an equation predicting how the degree of response of an axon to a gradient should vary with gradient… CONTINUE READING

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