Study reveals mechanical basis of decision-making in slime molds
Researchers studying the slime mold Physarum polycephalum found that its decision-making process relies on rhythmic muscle-like contractions that redistribute internal mass, rather than neural processing. When confined by blue light, the organism explores its environment by extending protrusions aligned with contraction waves, eventually settling on the most efficient contraction pattern for escape. The findings demonstrate how decentralized biological systems can make adaptive decisions through mechanical processes alone.
A new study published on arXiv examined how the single-celled slime mold Physarum polycephalum makes decisions without a brain or nervous system. Researchers confined the organism within blue-light-defined polygonal shapes and tracked how it explored and eventually escaped. They discovered that the slime mold's decision-making relies on peristaltic contractions—rhythmic waves similar to muscle contractions—that drive internal flows and redistribute mass throughout the organism. During exploration, the organism extends protrusions in various directions aligned with these contraction waves, but only gradually settles on the contraction mode most efficient for transport and escape. The study reveals that harsh environmental constraints trigger optimal behavior through a time-dependent reorganization of flow patterns, providing insights into how decentralized systems without centralized neural organization can process environmental information and generate adaptive responses.
What's missing
The study does not discuss potential applications of these findings to artificial decision-making systems or biomimetic engineering, nor does it compare the efficiency of the slime mold's mechanical decision-making to neural systems quantitatively.
What different sources said
- arXiv physicsCenter
Decision-making in light-trapped slime molds involves active mechanical processes
Related
Genetic Drift, Not Selection, Drives Rapid Feather Color Evolution in Island Bird Radiation
A new study of an island bird radiation found that rapid evolution of feather coloration is driven primarily by genetic drift in small populations rather than sexual or ecological selection. The research integrated whole-genome data with detailed plumage measurements across complete species sampling to test whether signaling trait evolution correlates with speciation rates. The findings suggest that neutral demographic processes play a central role in generating phenotypic diversity during island radiations, challenging assumptions about the mechanisms driving rapid evolution.
New AI Model Improves Prediction of Therapeutic Peptide Function from Protein Sequences
Researchers developed a lightweight CNN classifier that predicts whether peptide sequences have therapeutic properties, trained on a database of 54,655 peptides across 48 functional categories. The model uses a novel negative sampling strategy to reduce false positive rates from over 60% in previous approaches to 2.1%. This advancement could accelerate drug discovery by enabling faster computational screening of peptide candidates before expensive experimental testing.
Study Shows Different Metabolic Stress Models Produce Distinct Effects on Human Neuronal Networks
Researchers tested three common in vitro metabolic stress models on human-derived neuronal networks and found each produced different patterns of neuronal activity and cell damage. The models tested were hypoxia alone, oxygen-glucose deprivation (OGD), and hypoxia combined with glutamate exposure. The findings suggest that choice of experimental model significantly affects results and that combining electrophysiological and structural analyses is important for accurately assessing metabolic stress in stroke research.