Information Transfer During Food Choice in the Slime Mold Physarum polycephalum

FRONTIERS IN ECOLOGY AND EVOLUTION(2019)

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摘要
Throughout evolution, living systems have developed mechanisms to make adaptive decisions in the face of complex and changing environmental conditions. Most organisms make such decisions despite lacking a neural architecture. This is the case of the acellular slime mold Physarum polycephalum that has demonstrated remarkable information processing and problem-solving abilities. Previous studies suggest that the membrane of P. polycephalum plays an important role in integrating and processing information leading to the selection of a resource to exploit. The cyclical contraction-relaxation pattern of the membrane changes with the local quality of the environment, and individual contractile regions within a P. polycephalum can entrain neighboring regions, providing a potential mechanism for information processing and propagation. In this study, we use an information-theoretic tool, transfer entropy, to study the flow of information in single tubule segments of P. polycephalum in a binary choice between two food sources. We test P. polycephalum tubules in two food choice conditions, where the two available options are either symmetric in their nutrient concentrations or with one more concentrated in nutrients than the other (i.e., asymmetric). We measure the contractile pattern of the P. polycephalum membrane and use these data to explore the direction and amount of information transfer along the tubule as a function of the cell's final decision. We find that the direction of information transfer is different in the two experimental conditions, and the amount of information transferred is inversely proportional to the distance between different contractile regions. Our results show that regions playing a leading role in information transfer changes with the decision-making challenges faced by P. polycephalum.
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关键词
slime mold,protist,Physarumpolycephalum,non-neuronal,decision-making,food choice,information theory,transfer entropy
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