arXiv subjects

Shinya Kuroda

Publications and source records attributed to Shinya Kuroda.

4 recordsLinked to original sources

arXiv2019

Robustness against additional noise in cellular information transmission

Fluctuations in intracellular reactions (intrinsic noise) reduce the information transmitted from an extracellular input to a cellular response. However, recent studies have demonstrated that the decrease in the transmitted information with respect to extracellular input fluctuations (extrinsic noise) is smaller when the intrinsic noise is larger. Therefore, it has been suggested that robustness against extrinsic noise increases with the level of the intrinsic noise. We call this phenomenon intrinsic noise-induced robustness (INIR). As previous studies on this phenomenon have focused on complex biochemical reactions, the relation between INIR and the input--output of a system is unclear. Moreover, the mechanism of INIR remains elusive. In this paper, we address these questions by analyzing simple models. We first analyze a model in which the input--output relation is linear. We show that the robustness against extrinsic noise increases with the intrinsic noise, confirming the INIR phenomenon. Moreover, the robustness against the extrinsic noise is more strongly dependent on the intrinsic noise when the variance of the intrinsic noise is larger than that of the input distribution. Next, we analyze a threshold model in which the output depends on whether the input exceeds the threshold. When the threshold is equal to the mean of the input, INIR is realized, but when the threshold is much larger than the mean, the threshold model exhibits stochastic resonance, and INIR is not always apparent. The robustness against extrinsic noise and the transmitted information can be traded off against one another in the linear model and the threshold model without stochastic resonance, whereas they can be simultaneously increased in the threshold model with stochastic resonance.

q-bio.MN↗

arXiv2016

Small-volume effect enables the spine robust, sensitive and efficient information transfer

Why is the spine of a neuron so small that only small numbers of molecules can exist and reactions inevitably become stochastic? Despite such noisy conditions, we previously showed that the spine exhibits robust, sensitive and efficient features of information transfer using probability of Ca$^{2+}$ increase; however, their mechanisms remains unknown. Here we show that the small-volume effect enables robust, sensitive and efficient information transfer in the spine volume, but not in the cell volume. In the spine volume, intrinsic noise in reactions becomes larger than extrinsic noise of input, making robust information transfer against input fluctuation. Stochastic facilitation of Ca$^{2+}$ increase occurs in the spine volume, making higher sensitivity to lower intensity of input. Volume-dependency of information transfer enables efficient information transfer per input in the spine volume. Thus, we propose that the small-volume effect is the functional reasons why the spine has to be so small.

q-bio.SC↗

arXiv2014

Stochasticity in Ca$^{2+}$ increase in spines enables robust and sensitive information coding

A dendritic spine is a very small structure (~0.1 μm$^3$) of a neuron that processes input timing information. Why are spines so small? Here, we provide functional reasons; the size of spines is optimal for information coding. Spines code input timing information by the probability of Ca$^{2+}$ increases, which makes robust and sensitive information coding possible. We created a stochastic simulation model of input timing-dependent Ca$^{2+}$ increases in a cerebellar Purkinje cell's spine. Spines used probability coding of Ca$^{2+}$ increases rather than amplitude coding for input timing detection via stochastic facilitation by utilizing the small number of molecules in a spine volume, where information per volume appeared optimal. Probability coding of Ca$^{2+}$ increases in a spine volume was more robust against input fluctuation and more sensitive to input numbers than amplitude coding of Ca$^{2+}$ increases in a cell volume. Thus, stochasticity is a strategy by which neurons robustly and sensitively code information.

q-bio.MN↗

arXiv2006

A mass conserved reaction-diffusion system captures properties of cell polarity

Various molecules exclusively accumulate at the front or back of migrating eukaryotic cells in response to a shallow gradient of extracellular signals. Directional sensing and signal amplification highlight the essential properties in the migrating cells, known as cell polarity. In addition to these, such properties of cell polarity involve unique determination of migrating direction (uniqueness of axis) and localized gradient sensing at the front edge (localization of sensitivity), both of which may be required for smooth migration. Here we provide the mass conservation system based on the reaction-diffusion system with two components, where the mass of the two components is always conserved. Using two models belonging to this mass conservation system, we demonstrate through both numerical simulation and analytical approximations that the spatial pattern with a single peak (uniqueness of axis) can be generally observed and that the existent peak senses a gradient of parameters at the peak position, which guides the movement of the peak. We extended this system with multiple components, and we developed a multiple-component model in which cross-talk between members of the Rho family of small GTPases is involved. This model also exhibits the essential properties of the two models with two components. Thus, the mass conservation system shows properties similar to those of cell polarity, such as uniqueness of axis and localization of sensitivity, in addition to directional sensing and signal amplification.

q-bio.CB↗