Running title:Mechanical force sensing underlies Physarum aneural cognition
AbstractThe unicellular protist Physarum polycephalum is an important emerging model for understanding how aneural organisms process information toward adaptive behavior. Here, we reveal that Physarum can use mechanosensation to reliably make decisions about distant objects its environment, preferentially growing in the direction of heavier, substrate-deforming but chemically-inert masses. This long-range mass-sensing is abolished by gentle rhythmic mechanical disruption, changing substrate stiffness, or addition of a mechanosensitive transient receptor potential channel inhibitor. Computational modeling revealed that Physarum may perform this calculation by sensing the fraction of its growth perimeter that is distorted above a threshold straina fundamentally novel method of mechanosensation. Together, these data identify a surprising behavioral preference relying on biomechanical features and not nutritional content, and characterize a new example of an aneural organism that exploits physics to make decisions about growth and form.
Highlights The aneural Physarum makes behavioral decisions by control of its morphology It has a preference for larger masses, which it can detect at long range This effect is mediated by mechanosensing, not requiring chemical attractants Machine learning reveals that it surveys environment and makes decision in < 4 hours A biophysical model reveals how its pulsations enable long-distance mapping of environmental features A defining feature of any living organism is its ability to select actions that maximize utility in diverse environments (Barandiaran and Moreno, 2006). Decision-making is a process that is well-characterized in behavioral studies of human and other vertebrate species possessing nervous systems. Increasingly, it is also recognized as a fundamental capability whose evolutionary roots extend to the most basal forms on the tree of life (Baluška and Levin, 2016;Lyon, 2006Lyon, , 2015. Even unicellular organisms, including bacteria, have been studied as computational systems that collect information from their environment and use it to guide subsequent behaviors (Balazsi et al.