Minimal motifs for habituating systems

• 成果类型: Article
• 署名作者: Smart, Matthew; Shvartsman, Stanislav Y.; Gershman, Samuel J.
• 署名单位: Simons Foundation; Flatiron Institute; Princeton University; Princeton University; Ruhr University Bochum
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-11816
• DOI: 10.1073/pnas.2409330121
• 发表日期: 2024-10-08
• 关键词: perfect adaptation; single-cell; MODEL; sensitization; homeostasis

摘要

Habituation-a phenomenon in which a dynamical system exhibits a diminishing response to repeated stimulations that eventually recovers when the stimulus is withheld-is universally observed in living systems from animals to unicellular organisms. Despite its prevalence, generic mechanisms for this fundamental form of learning remain poorly defined. Drawing inspiration from prior work on systems that respond adaptively to step inputs, we study habituation from a nonlinear dynamics perspective. This approach enables us to formalize classical hallmarks of habituation that have been experimentally identified in diverse organisms and stimulus scenarios. We use this framework to investigate distinct dynamical circuits capable of habituation. In particular, we show that driven linear dynamics of a memory variable with static nonlinearities acting at the input and output can implement numerous hallmarks in a mathematically interpretable manner. This work establishes a foundation for understanding the dynamical substrates of this primitive learning behavior and offers a blueprint for the identification of habituating circuits in biological systems.