The Adaptive Regulation Model (ARM): A Mechanistic Framework for State-Dependent Behavioral Access

The Adaptive Regulation Model (ARM) is a mechanistic framework that posits that human behavior is constrained by moment-to-moment regulatory capacity and temporal availability before conscious deliberation. The model specifies a pre-behavioral processing window in which neural systems compete for expression under conditions shaped by physiological load, capacity, and time pressure. ARM integrates findings from neuroscience, stress physiology, and learning theory to formalize how regulatory state determines which responses are neurologically accessible at the moment of action selection. Increasing regulatory load is predicted to narrow the processing window and bias behavior toward faster, previously reinforced responses, while regulatory stabilization preserves access to goal-aligned alternatives. The framework operationalizes its core constructs—regulatory load, processing-window width, and behavioral accessibility—using observable variables such as response latency, persistence of error correction, and nonlinear transitions under increasing demand. The manuscript also outlines a proposed experimental approach, including the High-Load Temporal Constraint (HLTC) protocol, to examine state-dependent behavioral access. ARM is presented as a constraint-based scaffold rather than a comprehensive theory of behavior and is intended to support future empirical research, clinical translation, and interdisciplinary investigation of behavior under pressure.