Emergent dynamics in slime mold networks

Slime molds are composed of simple units that aggregate into networks that exhibit sophisticated emergent responses. These networks operate as smart biological materials, and strongly rely on mechanical interactions to adapt dynamically to the environment. While the microscale features are well understood, emergent intelligence at the macroscale remains a challenge. In this paper, we present a novel computational model, validated with experiments, to elucidate the nonlinear mechanical interactions underlying the synchronized morphological response of the slime mold Physarum polycephalum. We model the growth and reshaping of the network with an integrated phase-field approach and the internal flow as a diffusion–advection process through a poroelastic cytoplasm. The internal flow redistributes nutrients and free Ca^2＋, which interacts with the synchronized pulsation of the network. Our study demonstrates that this nonlinear interplay – between the mechanics of the cytoplasm, the pulsation amplitude, and flow velocity – is responsible for the adaptive patterns observed in experiments. Our model reproduces the consolidation of optimized vein structures from amorphous layers, captures optimized redistribution morphologies, and explains inter- and intraspecies behaviors observed in the laboratory. Our results indicate a path for developing active soft materials that exhibit decentralized intelligence and superior adaptivity to the medium.