Emergent memory in cell-like active systems
- 1Laboratoire Jean Perrin, CNRS/Sorbonne Université, Paris, France
Abstract
Active systems across scales, ranging from molecular machines to human crowds, are usually modeled as assemblies of self-propelled particles driven by internally generated forces. However, these models often assume memoryless dynamics. Here, guided by the example of living cells, which have recently been shown to display multi-timescale memory effects, we introduce a minimal theoretical framework that incorporates internal state dynamics and environmental sensing into overdamped active particle models of cell migration. We show that when the self-propulsion depends on internal variables with their own complex dynamics–modulated by local environmental cues– environmental memory spontaneously emerges and gives rise to new classes of behaviours. These include memory-induced responses, adaptable localization in complex landscapes, suppression of motility-induced phase separation, and enhanced jamming transitions. Our results demonstrate how minimal information processing capabilities, intrinsic to nonequilibrium agents with internal states like living cells, can profoundly influence both individual and collective behaviours. This framework bridges cell-scale activity and large-scale intelligent motion in cell assemblies, and opens the way to the quantitative analysis and design of systems ranging from synthetic colloids to biological collectives and robotic swarms.
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BibTeX
@article{besse2026emergent,
title = {{Emergent memory in cell-like active systems}},
author = {M. Besse and R. Voituriez},
journal = {Nature Communications},
year = {2026},
month = sep,
doi = {10.1038/s41467-026-77681-z},
url = {https://doi.org/10.1038/s41467-026-77681-z},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Emergent memory in cell-like active systems
AU - M. Besse
AU - R. Voituriez
PY - 2026
DA - 2026/09/25
JO - Nature Communications
DO - 10.1038/s41467-026-77681-z
UR - https://doi.org/10.1038/s41467-026-77681-z
AB - Active systems across scales, ranging from molecular machines to human crowds, are usually modeled as assemblies of self-propelled particles driven by internally generated forces. However, these models often assume memoryless dynamics. Here, guided by the example of living cells, which have recently been shown to display multi-timescale memory effects, we introduce a minimal theoretical framework that incorporates internal state dynamics and environmental sensing into overdamped active particle models of cell migration. We show that when the self-propulsion depends on internal variables with their own complex dynamics–modulated by local environmental cues– environmental memory spontaneously emerges and gives rise to new classes of behaviours. These include memory-induced responses, adaptable localization in complex landscapes, suppression of motility-induced phase separation, and enhanced jamming transitions. Our results demonstrate how minimal information processing capabilities, intrinsic to nonequilibrium agents with internal states like living cells, can profoundly influence both individual and collective behaviours. This framework bridges cell-scale activity and large-scale intelligent motion in cell assemblies, and opens the way to the quantitative analysis and design of systems ranging from synthetic colloids to biological collectives and robotic swarms.
SN - 2041-1723
ER -