Functional Roles of Yuragi in Biosystems View Full Text


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Chapter Info

DATE

2020-11-25

AUTHORS

Toshio Yanagida , Tsutomu Murata

ABSTRACT

What are the underlying principles that explain how complex biosystems work in such a remarkably energy-saving and flexible manner? In this chapter we explore this question based on our research of muscle and brain, both of which are typically complex biosystems. Our state-of-the-art imaging technology of direct observation of individual molecular motor motion has revealed the surprising fact that muscle contraction is produced by utilizing the Brownian motion of molecular motors in a very skillful manner. This indicates that the muscle can utilize thermal fluctuations of molecules in an effective way, such that the energy efficiency of muscle is extremely high compared to artificial energy conversion systems. Although the research methods are quite different, we have also observed analogous findings in human brain function. Our research on human visual recognition showed that the time taken for recognizing a difficult figure follows the same exponential function as the “Arrhenius equation,” which describes how the rate of a chemical reaction is driven by thermal fluctuation. This finding, as well as our related modeling, strongly supports the idea that stochastic activity, possibly resting-level spontaneous activity, may also help make human recognition flexible and energy saving. Based on these findings, we would argue that fluctuations in biosystems, both thermal fluctuation of motor molecules in muscle and stochastic activity of neurons in the brain, play an essential role in flexible and energy-saving functioning. To emphasize these positive aspects of fluctuations in biosystems, we would propose the concept of “Yuragi,” which is a word of Japanese origin with the meaning of fluctuations for flexible adaptation to the environment. We would suggest that the utilization of Yuragi is one of the principles for efficiency and flexibility of biosystems. More... »

PAGES

31-47

Book

TITLE

Fluctuation-Induced Network Control and Learning

ISBN

978-981-33-4975-9
978-981-33-4976-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-981-33-4976-6_2

DOI

http://dx.doi.org/10.1007/978-981-33-4976-6_2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1136441671


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