Motivational Subdomains in Neurodevelopmental Disorders: A Heuristic Circuit Framework for Translational Validation

Neurodevelopmental disorders such as attention-deficit/hyperactivity disorder, autism spectrum disorder, and schizophrenia are classically defined by cognitive and sensorimotor impairments. However, dysregulated motivation is a core but underrecognized feature of these conditions with significant implications for quality of life. We present a heuristic hypothesis-generating framework that distinguishes two interacting and partially dissociable subdomains of motivation: self-initiated motivation, defined as goal-directed behavior that arises in the absence of immediate external prompting, and stimulus-driven motivation, defined as responses elicited by environmental cues or physiological states. Unlike traditional distinctions such as intrinsic versus extrinsic motivation or the liking-wanting dichotomy, this framework emphasizes the initiation of motivated action as its organizing axis, focusing on whether behaviors are generated internally or triggered by external stimuli rather than on reward valuation or hedonic impact. These subdomains are implemented by overlapping, dynamically interacting neural circuits that follow relatively distinct developmental trajectories and may exhibit differential sensitivity to early-life adversity. Our model provides a transdiagnostic conceptual scaffold that bridges categorical diagnoses and aligns with the Research Domain Criteria Motivation Systems framework. We focus on disorders with early-emerging circuit vulnerability and developmental onset, while recognizing that the framework is applicable more broadly across psychiatric conditions. Rather than offering a definitive nosology, the model supports mechanistic phenotyping, hypothesis-driven experimental design, and translational inference across neurodevelopmental disorders. To illustrate its translational utility, we highlight behavioral assays in animal models that differentially engage each subdomain and propose circuit-informed, testable strategies to guide future intervention development.