Mechanosensation Mediates Long‐Range Spatial Decision‐Making in an Aneural Organism

Abstract

The unicellular protist Physarum polycephalum is an important emerging model for understanding how aneural organisms process information toward adaptive behavior. Here, it is revealed that Physarum can use mechanosensation to reliably make decisions about distant objects in its environment, preferentially growing in the direction of heavier, substratedeforming, but chemically inert masses. This long-range sensing is abolished by gentle rhythmic mechanical disruption, changing substrate stiffness, or the addition of an inhibitor of mechanosensitive transient receptor potential channels. Additionally, it is demonstrated that Physarum does not respond to the absolute magnitude of strain. Computational modeling reveales that Physarum may perform this calculation by sensing the fraction of its perimeter that is distorted above a threshold substrate strain-a fundamentally novel method of mechanosensation. Using its body as both a distributed sensor array and computational substrate, this aneural organism leverages its unique morphology to make long-range decisions. Together, these data identify a surprising behavioral preference relying on biomechanical features and quantitatively characterize how the Physarum exploits physics to adaptively regulate its growth and shape.

Darwin’s Agential Materials: evolutionary implications of multi-scale competency in developmental biology

“…Cells and their components have many competencies for adaptive behavior when navigating physiological, metabolic, and transcriptional spaces [86]. Examples include the ability of gene-regulatory networks and chemical pathways to learn from experience [87][88][89], for transcriptional machinery to rapidly adjust to compensate for entirely novel physiological stressors [90], and for unicellular slime molds to explore their environment at a distance and make decisions using memory and comparison of alternatives [91][92][93][94][95].…”

Behavioural changes in slime moulds over time

“…Indeed, since the seminal contribution of Toshiyuki Nakagaki and colleagues more than 20 years ago [33], P. polycephalum has become an essential model organism for studying problem-solving in non-neural systems [32][33][34][35][36][37]. Past experiments have shown that acellular slime moulds can find the shortest path in a maze [33,38], build optimized networks to connect several food sources [34], anticipate events [39], learn to ignore irrelevant stimuli [40,41], encode memory in their environment [42] or in their morphology [43], interact with their congeners [21,44], optimize nutrient intake [28,45], make optimal decisions [27,29,46], etc. Physarum polycephalum's behaviour relies on its self-organized internal architecture, which consists of a transport network of interconnected tubes [47].…”

“…Physarum polycephalum can migrate at a speed of up to few millimetres per hour through the interplay of intracellular flow, adhesion and rhythmic contractions of the tubes [48][49][50]. The frequency and the amplitude of the contractions depend on external stimuli, and, as a result, P. polycephalum is capable of altering its shape and motion as a function of a variety of external stimuli such as chemicals [51][52][53], light [54], temperature [55][56][57], humidity [44], gravity [58] or substrate distortion [46].…”

Hydrophobic Barriers for Directing Physarum polycephalum Propulsion and Navigation

“…To understand the intelligence and decision-making capabilities of P.polycephalum, various experimental studies have been conducted to control the movement of P.polycephalum. ,, As one of the methodological examples of P.polycephalum guidance, organism was placed in a dish and exposed to a light source at a specific area . The organism was able to navigate toward the light source, demonstrating its ability to sense and respond to light.…”