Minimal motifs for habituating systems

TL;DR

This paper explores the fundamental mechanisms of habituation in living systems using nonlinear dynamics, proposing a mathematical framework that captures key features and offers insights into the circuits underlying this primitive form of learning.

Contribution

It introduces a formal nonlinear dynamics model for habituation, providing a theoretical foundation and blueprint for identifying habituating circuits in biological systems.

Findings

Linear driven dynamics with static nonlinearities can replicate habituation hallmarks

The framework formalizes classical habituation features in a mathematically interpretable way

Provides a basis for future identification of habituating circuits in biology

Abstract

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.