Evidence map›Paper›PMID 19541606›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2009

Bayesian model predicts the response of axons to molecular gradients.

Duncan Mortimer, Julia Feldner, Timothy Vaughan, Irina Vetter, Zac Pujic, William J Rosoff, Kevin Burrage, Peter Dayan, Linda J Richards, Geoffrey J Goodhill

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed.

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  8. Stem cell colony interspacing effect on differentiation to neural cells.Journal of tissue engineering and regenerative medicine · 2018
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  11. Axon growth regulation by a bistable molecular switch.Proceedings. Biological sciences · 2018
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Duncan MortimerQueensland Brain Institute, The University of Queensland, St Lucia, QLD 4072, Australia.
Julia Feldner
Timothy Vaughan
Irina Vetter
Zac Pujic
William J Rosoff
Kevin Burrage
Peter Dayan
Linda J Richards
Geoffrey J Goodhill

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 steepness and absolute concentration. Third, we confirm this prediction quantitatively by performing the first systematic experimental analysis of how axonal response varies with both these quantities. These experiments demonstrate a degree of sensitivity much higher than previously reported for any chemotacting system. Together, these results reveal both the quantitative constraints that must be satisfied for effective axonal guidance and the computational principles that may be used by the underlying signal transduction pathways, and allow predictions for the degree of response of axons to gradients in a wide variety of in vivo and in vitro settings.

Indexed as

Models, NeurologicalNeurogenesisAnimalsAxonsBayes TheoremNerve Growth FactorRatsNerve Growth Factor

Identifiers

PMID19541606
PMCPMC2700145

What OpenQuestion holds

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Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.