Modular Maximization Theory: A functional account of economic behavior in laboratory animal models with applications to drug-seeking behavior

Abstract

Substance abuse research depends on precise and sensitive assessments of reinforcer efficacy in animal models. However, conventional methods often lack theoretical rigor and specificity to support these assessments. To address these gaps, the Modular Maximization Theory (MMT) is introduced as a comprehensive framework for understanding instrumental behavior. Like earlier maximization theories, MMT posits that behavior is distributed across alternatives to maximize utility over time. This concept is structured through five foundational postulates that define alternative actions and rules for choosing between them as budget constraints and utility functions. A key innovation of MMT is its incorporation of reinforcer utilization—encompassing both consummatory and post-consummatory activities—into the budget-constraint function. A model of ratio-schedule performance is developed under the assumption that utilization is proportional to demand, with utility represented as an additive power function of reinforcer magnitude. This model, termed PURSPU (Proportional Utilization, Ratio Schedule, Power Utility), effectively explains how reinforcer magnitude, response effort, non-contingent reinforcement, and income influence demand curves, behavior-output functions, dose-response relationships, and progressive-ratio breakpoints, while accounting for rate-dependent effects. The model also offers novel insights into choice behavior, including concurrent-schedule performance, income dependency, and delay discounting, as well as post-reinforcement pauses and run rates. Variations in budget constraints and utility functions are proposed as alternative models. Potential theoretical advancements, more targeted assessments of drug abuse liability, and the broader role of MMT in understanding human drug abuse are explored.