Masaki Yamachiyo

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. Here, we show that a system composed of particles, which move and are modified based upon the particle transformation that contains the relationship between the parts and the whole, can emulate the network formed by Physarum. This system balances the exploration-exploitation trade-off and shows a scale-free sub-domain. By decreasing the number of particles, our model, VP-S, can emulate the Physarum adaptive network as it is attracted to a food stimulus. By increasing the number of particles, our model, VP-D, can emulate the pattern of a growing Physarum. The patterns produced by our model were compared with those of the Physarum pattern quantitatively, which showed that both patterns balance exploration with exploitation. This model should have a wide applicability to study biological collective phenomena in general.

Multi-scaled adaptability in motility and pattern formation of the Physarum plasmodium

The plasmodium of Physarum polycephalum is a unicellular and multinuclear giant amoeba that has macroscopic size, and by this particular nature the organism is attracting a lot of attention in the research fields such as systems science, nature-inspired bio-computing and swarm behavioural study. In this paper, we investigated how the plasmodium generates new motility and morphology, and found that there are allometric relationships between the cell volume and morphology, and between cell size and cell motility. We further discuss how these relationships are realised, and these relationships are deeply connected to the organisms benefit of being a large-scale unicellular organism.

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. We demonstrated that the network pattern mimicking the Kanizsa illusion can be produced by an asynchronous automata-fashioned model of the foraging slime mold and by the real plasmodia of P. polycephalum. Because the protoplasm of the plasmodium is transported depending on both local and global computation, it may contain differentiation-integration processes. In this sense, we can extend the idea of perception and computation.

Physarum plasmodium perceives ambiguous stimulus as either attractant or repellent

We demonstrate that plasmodium of Physarum polycephalum perceives an ambiguous stimulus made from oatmeal and KCl as it is either attractant or repellent. While there is no intermediate behavior of being attracted and avoiding a stimulus, each plasmodium makes a decision whether a given stimulus is either attractant or repellent evenly. We propose a model explaining why the plasmodium either covers a stimulus perfectly or avoids a stimulus without entering a stimulus. The model is based on a rough set analysis. We propose that the plasmodium has two perception models with respect to attractant and repellent. These two models conflict with each other. Due to the composition of two models, the effect of one of the models can be evoked and the effect of another model is suppressed.