What is the origin of behaviour? Although typically associated with a nervous system, simple organisms also show complex behaviours. Among them, the slime mold Physarum polycephalum, a giant single cell, is ideally suited to study emergence of behaviour. Here, we show how locomotion and morphological adaptation behaviour emerge from self-organized patterns of rhythmic contractions of the actomyosin lining of the tubes making up the network-shaped organism. We quantify the spatio-temporal contraction dynamics by decomposing experimentally recorded contraction patterns into spatial contraction modes. Notably, we find a continuous spectrum of modes, as opposed to a few dominant modes. Our data suggests that the continuous spectrum of modes allows for dynamic transitions between a plethora of specific behaviours with transitions marked by highly irregular contraction states. By mapping specific behaviours to states of active contractions, we provide the basis to understand behaviour’s complexity as a function of biomechanical dynamics.

What is the origin of behavior? Although typically associated with a nervous system, simple life forms also show complex behavior - thus serving as a model to study how behaviors emerge. Among them, the slime mold Physarum polycephalum, growing as a single giant cell, is renowned for its sophisticated behavior. Here, we show how locomotion and morphological adaptation behavior emerge from self-organized patterns of rhythmic contractions of the actomyosin lining of the tubes making up the network-shaped organism. We quantify the spatio-temporal contraction dynamics by decomposing experimentally recorded contraction patterns into spatial contraction modes. Surprisingly, we find a continuous spectrum of modes, as opposed to few dominant modes. Over time, activation of modes along this continuous spectrum is highly dynamic, resulting in contraction patterns of varying regularity. We show that regular patterns are associated with stereotyped behavior by triggering a behavioral response with a food stimulus. Furthermore, we demonstrate that the continuous spectrum of modes and the existence of irregular contraction patterns persist in specimens with a morphology as simple as a single tube. Our data suggests that the continuous spectrum of modes allows for dynamic transitions between a plethora of specific behaviors with transitions marked by highly irregular contraction states. By mapping specific behaviors to states of active contractions, we provide the basis to understand behavior's complexity as a function of biomechanical dynamics. This perspective will likely stimulate bio-inspired design of soft robots with a similarly rich behavioral repertoire as P. polycephalum.

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Every interaction of a living organism with its environment involves the placement of a bet. Armed with partial knowledge about a stochastic world, the organism must decide its next step or near-term strategy, an act that implicitly or explicitly involves the assumption of a model of the world. Better information about environmental statistics can improve the bet quality, but in practice resources for information gathering are always limited. We argue that theories of optimal inference dictate that "complex" models are harder to infer with bounded information and lead to larger prediction errors. Thus, we propose a principle of "playing it safe" where, given finite information gathering capacity, biological systems should be biased towards simpler models of the world, and thereby to less risky betting strategies. In the framework of Bayesian inference, we show that there is an optimally safe adaptation strategy determined by the Bayesian prior. We then demonstrate that, in the context of stochastic phenotypic switching by bacteria, implementation of our principle of "playing it safe" increases fitness (population growth rate) of the bacterial collective. We suggest that the principle applies broadly to problems of adaptation, learning and evolution, and illuminates the types of environments in which organisms are able to thrive.

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