Natural Computing and Beyond

This book contains the joint proceedings of the Winter School of Hakodate (WSH) 2011 held in Hakodate, Japan, March 15–16, 2011, and the 6th International Workshop on Natural Computing (6th IWNC) held in Tokyo, Japan, March 28–30, 2012, organized by the Special Interest Group of Natural Computing (SIG-NAC), the Japanese Society for Artificial Intelligence (JSAI). This volume compiles refereed contributions to various aspects of natural computing, ranging from computing with slime mold, artificial chemistry, eco-physics, and synthetic biology, to computational aesthetics

Flow-Induced Channel Formation in the Cytoplasm of Motile Cells

A model is presented to explain the development of flow channels within the cytoplasm of the plasmodium of the giant amoeba Physarum polycephalum. The formation of channels is related to the development of a self-organizing tubular network in large cells. Experiments indicate that the flow of cytoplasm is involved in the development and organization of these networks, and the mathematical model proposed here is motivated by recent experiments involving the observation of development of flow channel in small cells. A model of pressure-driven flow through a polymer network is presented in which the rate of flow increases the rate of depolymerization. Numerical solutions and asymptotic analysis of the model in one spatial dimension show that under very general assumptions this model predicts the formation of channels in response to flow

Automated analysis of Physarum network structure and dynamics

We evaluate different ridge-enhancement and segmentation methods to automatically extract the network architecture from time-series of Physarum plasmodia withdrawing from an arena via a single exit. Whilst all methods gave reasonable results, judged by precision-recall analysis against a ground-truth skeleton, the mean phase angle (Feature Type) from intensity-independent, phase-congruency edge enhancement and watershed segmentation was the most robust to variation in threshold parameters. The resultant single pixel-wide segmented skeleton was converted to a graph representation as a set of weighted adjacency matrices containing the physical dimensions of each vein, and the inter-vein regions. We encapsulate the complete image processing and network analysis pipeline in a downloadable software package, and provide an extensive set of metrics that characterise the network structure, including hierarchical loop decomposition to analyse the nested structure of the developing network. In addition, the change in volume for each vein and intervening plasmodial sheet was used to predict the net flow across the network. The scaling relationships between predicted current, speed and shear force with vein radius were consistent with predictions from Murray's law. This work was presented at PhysNet 2015

Fluid-filled Soft-bodied Amoeboid Robot Inspired by Plasmodium of True Slime Mold

This paper presents a fluid-filled soft-bodied amoeboid robot inspired by plasmodium of true slime mold. The significant features of this robot are twofold: (1) the robot has fluid circuit (i.e., cylinders and nylon tubes filled with fluid) and truly soft and deformable body stemming from Real-time Tunable Springs (RTSs), the former seals protoplasm to induce global physical interaction between the body parts and the latter is used for elastic actuators; and (2) a fully decentralized control using coupled oscillators with completely local sensory feedback mechanism is realized by exploiting the global physical interaction between the body parts stemming from the fluid circuit. The experimental results show that this robot exhibits adaptive locomotion without relying on any hierarchical structure. The results obtained are expected to shed new light on design scheme for autonomous decentralized control systems

Pattern formation of reaction-diffusion system having self-determined flow in the amoeboid organism of Physarum plasmodium

The amoeboid organism, the plasmodium of Physarum polycephalum, behaves on the basis of spatio-temporal pattern formation by local contraction-oscillators. This biological system can be regarded as a reaction-diffusion system which has spatial interaction by active flow of protoplasmic sol in the cell. Paying attention to the physiological evidence that the flow is determined by contraction pattern in the plasmodium, a reaction-diffusion system having self-determined flow arises. Such a coupling of reaction-diffusion-advection is a characteristic of the biological system, and is expected to relate with control mechanism of amoeboid behaviours. Hence, we have studied effects of the self-determined flow on pattern formation of simple reaction-diffusion systems. By weakly nonlinear analysis near a trivial solution, the envelope dynamics follows the complex Ginzburg-Landau type equation just after bifurcation occurs at finite wave number. The flow term affects the nonlinear term of the equation through the critical wave number squared. Contrary to this, wave number isn't explicitly effective with lack of flow or constant flow. Thus, spatial size of pattern is especially important for regulating pattern formation in the plasmodium. On the other hand, the flow term is negligible in the vicinity of bifurcation at infinitely small wave number, and therefore the pattern formation by simple reaction-diffusion will also hold. A physiological role of pattern formation as above is discussed.Comment: REVTeX, one column, 7 pages, no figur

Flow rate driven by peristaltic movement in plasmodial tube of Physarum polycephalum

We report a theoretical analysis of protoplasmic streaming driven by peristaltic movement in an elastic tube of an amoeba-like organism. The plasmodium of Physarum polycephalum, a true slime mold, is a large amoeboid organism that adopts a sheet-like form with a tubular network. The network extends throughout the plasmodium and enables the transport and circulation of chemical signals and nutrients. This tubular flow is driven by periodically propagating waves of active contraction of the tube cortex, a process known as peristaltic movement. We derive the relationship between the phase velocity of the contraction wave and the flow rate, and we discuss the physiological implications of this relationship