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Adaptive Responses Limited by Intrinsic Noise.

Shankar P, Nishikawa M, Shibata T - PLoS ONE (2015)

Bottom Line: Such adaptive responses are effective for a wide dynamic range of sensing and perception of temporal change in stimulus.We also identify the condition that yields the upper limit of response for both network motifs.These results may explain the reason of why nFBL seems to be more abundant in nature for the implementation of adaption systems.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematical and Life Sciences, Hiroshima University, Higashi-Hiroshima, Japan; Laboratory for Physical Biology, RIKEN Quantitative Biology Center, Kobe, Japan.

ABSTRACT
Sensory systems have mechanisms to respond to the external environment and adapt to them. Such adaptive responses are effective for a wide dynamic range of sensing and perception of temporal change in stimulus. However, noise generated by the adaptation system itself as well as extrinsic noise in sensory inputs may impose a limit on the ability of adaptation systems. The relation between response and noise is well understood for equilibrium systems in the form of fluctuation response relation. However, the relation for nonequilibrium systems, including adaptive systems, are poorly understood. Here, we systematically explore such a relation between response and fluctuation in adaptation systems. We study the two network motifs, incoherent feedforward loops (iFFL) and negative feedback loops (nFBL), that can achieve perfect adaptation. We find that the response magnitude in adaption systems is limited by its intrinsic noise, implying that higher response would have higher noise component as well. Comparing the relation of response and noise in iFFL and nFBL, we show that whereas iFFL exhibits adaptation over a wider parameter range, nFBL offers higher response to noise ratio than iFFL. We also identify the condition that yields the upper limit of response for both network motifs. These results may explain the reason of why nFBL seems to be more abundant in nature for the implementation of adaption systems.

No MeSH data available.


Related in: MedlinePlus

The dependence of gain and noise on the ratio of eigenvalues.The joint histograms of the Fano factor f and ratio χ of eigenvalues (A, C), and the gain g and χ (B, D) for iFFL (A, B) and nFBL (C, D), for the parameters with perfect adaptation. For nFBL, the non-oscillatory case is considered. The colors indicate the log of histogram of the density of points, as explained in Fig 3. The dashed line in (B) shows .
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pone.0136095.g005: The dependence of gain and noise on the ratio of eigenvalues.The joint histograms of the Fano factor f and ratio χ of eigenvalues (A, C), and the gain g and χ (B, D) for iFFL (A, B) and nFBL (C, D), for the parameters with perfect adaptation. For nFBL, the non-oscillatory case is considered. The colors indicate the log of histogram of the density of points, as explained in Fig 3. The dashed line in (B) shows .

Mentions: We verified this dependence on χ numerically, as shown in Fig 5(A) and 5(B). As χ decreases, both gain and noise approach to unity, reaching the equality. In contrast, as χ increases, the gain systematically decreases as according to Eq (22), while the Fano factor f is maintained around unity or larger than unity for many parameter sets (Fig 5(A)) independent of χ, because the noise contribution from the reactions of A is independent of χ. As a result, the deviation between noise and gain increases with a larger value in Eq (26).


Adaptive Responses Limited by Intrinsic Noise.

Shankar P, Nishikawa M, Shibata T - PLoS ONE (2015)

The dependence of gain and noise on the ratio of eigenvalues.The joint histograms of the Fano factor f and ratio χ of eigenvalues (A, C), and the gain g and χ (B, D) for iFFL (A, B) and nFBL (C, D), for the parameters with perfect adaptation. For nFBL, the non-oscillatory case is considered. The colors indicate the log of histogram of the density of points, as explained in Fig 3. The dashed line in (B) shows .
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4549281&req=5

pone.0136095.g005: The dependence of gain and noise on the ratio of eigenvalues.The joint histograms of the Fano factor f and ratio χ of eigenvalues (A, C), and the gain g and χ (B, D) for iFFL (A, B) and nFBL (C, D), for the parameters with perfect adaptation. For nFBL, the non-oscillatory case is considered. The colors indicate the log of histogram of the density of points, as explained in Fig 3. The dashed line in (B) shows .
Mentions: We verified this dependence on χ numerically, as shown in Fig 5(A) and 5(B). As χ decreases, both gain and noise approach to unity, reaching the equality. In contrast, as χ increases, the gain systematically decreases as according to Eq (22), while the Fano factor f is maintained around unity or larger than unity for many parameter sets (Fig 5(A)) independent of χ, because the noise contribution from the reactions of A is independent of χ. As a result, the deviation between noise and gain increases with a larger value in Eq (26).

Bottom Line: Such adaptive responses are effective for a wide dynamic range of sensing and perception of temporal change in stimulus.We also identify the condition that yields the upper limit of response for both network motifs.These results may explain the reason of why nFBL seems to be more abundant in nature for the implementation of adaption systems.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematical and Life Sciences, Hiroshima University, Higashi-Hiroshima, Japan; Laboratory for Physical Biology, RIKEN Quantitative Biology Center, Kobe, Japan.

ABSTRACT
Sensory systems have mechanisms to respond to the external environment and adapt to them. Such adaptive responses are effective for a wide dynamic range of sensing and perception of temporal change in stimulus. However, noise generated by the adaptation system itself as well as extrinsic noise in sensory inputs may impose a limit on the ability of adaptation systems. The relation between response and noise is well understood for equilibrium systems in the form of fluctuation response relation. However, the relation for nonequilibrium systems, including adaptive systems, are poorly understood. Here, we systematically explore such a relation between response and fluctuation in adaptation systems. We study the two network motifs, incoherent feedforward loops (iFFL) and negative feedback loops (nFBL), that can achieve perfect adaptation. We find that the response magnitude in adaption systems is limited by its intrinsic noise, implying that higher response would have higher noise component as well. Comparing the relation of response and noise in iFFL and nFBL, we show that whereas iFFL exhibits adaptation over a wider parameter range, nFBL offers higher response to noise ratio than iFFL. We also identify the condition that yields the upper limit of response for both network motifs. These results may explain the reason of why nFBL seems to be more abundant in nature for the implementation of adaption systems.

No MeSH data available.


Related in: MedlinePlus