2011
DOI: 10.1162/neco_a_00075
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Bayes-Optimal Chemotaxis

Abstract: Chemotaxis plays a crucial role in many biological processes, including nervous system development. However, fundamental physical constraints limit the ability of a small sensing device such as a cell or growth cone to detect an external chemical gradient. One of these is the stochastic nature of receptor binding, leading to a constantly fluctuating binding pattern across the cell's array of receptors. This is analogous to the uncertainty in sensory information often encountered by the brain at the systems lev… Show more

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Cited by 21 publications
(20 citation statements)
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References 56 publications
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“…[This is similar to the observation that a small difference of two large numbers always has a larger relative error than either of the two numbers, and so one is frequently cautioned against making such subtractions in scientific computing (43).] This decrease has been observed in many systems (12,13,22,(44)(45)(46)(47) and typically attributed to receptor saturation, whereas our analysis suggests that it is present even for linear systems. Indeed, high-affinity EGF receptors (K D ≈ 300 pM) generally constitute ∼ 10% of the total receptor pool, and low-affinity receptors (K D ≈ 2 nM) constitute the remaining ∼ 90% (48).…”
Section: Resultscontrasting
confidence: 42%
“…[This is similar to the observation that a small difference of two large numbers always has a larger relative error than either of the two numbers, and so one is frequently cautioned against making such subtractions in scientific computing (43).] This decrease has been observed in many systems (12,13,22,(44)(45)(46)(47) and typically attributed to receptor saturation, whereas our analysis suggests that it is present even for linear systems. Indeed, high-affinity EGF receptors (K D ≈ 300 pM) generally constitute ∼ 10% of the total receptor pool, and low-affinity receptors (K D ≈ 2 nM) constitute the remaining ∼ 90% (48).…”
Section: Resultscontrasting
confidence: 42%
“…The previous works we built on (Mortimer et al, 2009(Mortimer et al, , 2011Hu et al, 2011aHu et al, , 2011bBaba et al, 2012) derived the posterior distribution of the gradient by assuming a uniform distribution of receptors on the sensing device, and a large enough number of receptors such that the Gaussian approximation holds for the magnitude and the direction of the gradient. In contrast, we use the mutual information instead of Fisher information, which makes our approach more suitable to analyse the case of a finite or small number of receptors (thousands or fewer).…”
Section: Discussionmentioning
confidence: 99%
“…A powerful approach for analysing such problems is to consider the optimal statistical inference that an ideal observer would perform (Andrews and Iglesias, 2007;Mortimer et al, 2009;Fuller et al, 2010;Hu et al, 2010Hu et al, , 2011aMortimer et al, 2011). This involves combining available information with prior assumptions.…”
Section: Introductionmentioning
confidence: 99%
“…The previous works we built on [95,[97][98][99]230] derived the posterior distribution of the gradient by assuming a uniform distribution of receptors on the sensing device, and a large enough number of receptors such that the Gaussian approximation holds for the magnitude and the direction of the gradient. In contrast, we use the mutual information instead of Fisher information, which makes our approach more suitable to analyse the case of a finite or small number of receptors (thousands or fewer).…”
Section: Discussionmentioning
confidence: 99%