Conditioning as a route to stereotyped behavior in growing populations

TL;DR

This paper demonstrates that conditioning through stochastic resets can induce ordered, reliable multi-step behaviors in growing populations without detailed molecular control, relying only on timing constraints.

Contribution

It introduces a model showing how conditioning via resets creates hierarchical order in populations, offering a minimal alternative to molecular error correction.

Findings

Resets impose hierarchical temporal order without specific control.

Fastest-growing populations are inherently more ordered under certain conditions.

Save points enable scaling of conditioning to complex processes.

Abstract

Biological systems perform complex multi-step processes in a reproducible way despite underlying stochasticity. The standard explanation is micromanagement by molecular machinery that recognizes and corrects specific errors. Here we study conditioning, a qualitatively different strategy in which attempts failing a coarse criterion are destroyed and do not leave a physical record. The surviving, i.e., conditioned, ensemble is narrower and therefore more ordered. We model conditioning through stochastic resets in a ''socks-before-shoes'' model of a growing population, where $n$ actions must be completed in any order to replicate and any replication attempt not finished by a threshold time is discarded. We find that resets impose hierarchical temporal ordering of the $n$ actions without microscopic control over which action happens when. When disorder carries a sufficient time penalty, this ordering is free: the fastest-growing population is automatically the most ordered, with no direct selection for order required. Save points, at which verified progress is preserved across resets, allow conditioning to scale to complex multi-step processes. Conditioning provides a minimal route to reliable behavior, requiring only a clock rather than molecular machinery that recognizes specific errors. For the right class of processes, it pays for itself.