习惯化系统的最小图案

Matthew Smart, Stanislav Y. Shvartsman, Martin Mönnigmann
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引用次数: 0

摘要

从动物到细胞生物的生命系统中都普遍存在习惯化现象,即动态系统对重复刺激的反应逐渐减弱,而当停止刺激时,这种反应最终会恢复。尽管这种现象普遍存在,但这种基本学习形式的通用机制仍未得到很好的界定。我们从对阶跃输入做出适应性反应的系统的前人研究中汲取灵感,从非线性动力学的角度研究了习得。这种方法使我们能够将习惯化的经典特征形式化,这些特征已在不同生物体和刺激情景中得到实验验证。我们利用这一框架来研究能够产生习惯化的独特动力学回路。特别是,我们表明,记忆变量的驱动线性动力学与作用于输入和输出的静态非线性可以以数学上可解释的方式实现众多特征。这项研究为理解这种原始学习行为的动力学基础奠定了基础,并为识别生物系统中的习惯化电路提供了蓝图。
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Minimal motifs for habituating systems
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.
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