Adaptive Regulation Model (ARM): A Neurobehavioral Framework of State-Dependent Behavior with the High-Load Temporal Constraint Protocol

The Adaptive Regulation Model (ARM) proposes that behavioral control is constrained by moment-to-moment regulatory capacity rather than by intention or executive choice alone. The framework identifies a pre-behavioral processing window in which neural systems compete for expression under conditions determined by physiological load, temporal pressure, and available stabilization. As regulatory load increases, the processing window narrows, biasing behavior toward rapid, previously reinforced responses and reducing access to goal-aligned alternatives. This produces predictable nonlinear transitions between deliberate and automatic behavior, as evidenced by changes in response latency, persistence, and error-correction capacity. Version 3 introduces the High-Load Temporal Constraint (HLTC) protocol, an experimental paradigm designed to measure state-dependent behavioral availability in real time using synchronized bilateral motor engagement and controlled load escalation. The protocol operationalizes regulatory capacity as a measurable threshold at which voluntary rule-guided behavior becomes unavailable. ARM is presented as a constraint-based mechanistic scaffold designed to generate falsifiable predictions and to support laboratory, clinical, and interdisciplinary investigations of behavior under pressure.