Noise-induced bistability in a simple mutual inhibition system.

In this study, we study noise-induced bistability in a simple bivariate mutual inhibition system with slow fluctuating responses to external signals. We give a general condition that the marginal stationary probability density of one of the two variables experiences a transition from a unimodal shape to a bimodal one. We show that the transition occurs even when the stationary probability density of the response to external signals is monotone.

Biased Lévy-walk pattern in the exploratory behavior of the Physarum plasmodium.

The plasmodium of Physarum polycephalum is a unicellular and multinuclear giant amoeba. The plasmodium has the ability to sense and adapt to many kinds of environmental stimuli, and its optimization behavior in closed spaces has been analyzed extensively. However, few studies have tested the behavior of the plasmodium in an open spaces, despite the biological importance of the adaptability of biological entities in such conditions.

A machine learning model with human cognitive biases capable of learning from small and biased datasets.

Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning.

Kanizsa illusory contours appearing in the plasmodium pattern of Physarum polycephalum.

The plasmodium of Physarum polycephalum is often used in the implementation of non-linear computation to solve optimization problems, and this organismal feature was not used in this analysis to compute perception and/or sensation in humans. In this paper, we focused on the Kanizsa illusion, which is a well-known visual illusion resulting from the differentiation-integration of the visual field, and compared the illusion with the adaptive network in the plasmodium of P. polycephalum.

An adaptive and robust biological network based on the vacant-particle transportation model.

A living system reveals local computing by referring to a whole system beyond the exploration-exploitation dilemma. The slime mold, Physarum polycephalum, uses protoplasmic flow to change its own outer shape, which yields the boundary condition and forms an adaptive and robust network. This observation suggests that the whole Physarum can be represented as a local protoplasmic flow system.

A model of network formation by Physarum plasmodium: interplay between cell mobility and morphogenesis.

The plasmodium of Physarum polycephalum has attracted much attention due its intelligent adaptive behavior. In this study, we constructed a model of the organism and attempted to simulate its locomotion and morphogenetic behavior. By modifying our previous model, we were able to get closer to the actual behavior.

Minimal model of a cell connecting amoebic motion and adaptive transport networks.

A cell is a minimal self-sustaining system that can move and compute. Previous work has shown that a unicellular slime mold, Physarum, can be utilized as a biological computer based on cytoplasmic flow encapsulated by a membrane. Although the interplay between the modification of the boundary of a cell and the cytoplasmic flow surrounded by the boundary plays a key role in Physarum computing, no model of a cell has been developed to describe this interplay.

Class-specific binding of two aminoacyl-tRNA synthetases to annexin, a Ca2+- and phospholipid-binding protein.

Annexins are a family of Ca2+/phospholipid-binding proteins that have diverse functions. To understand the function of annexin in Physarum polycephalum, we searched for its binding proteins. Here we demonstrate the presence of two novel annexin-binding proteins.