Dual-System Cognition as Curvature Dynamics: A Recursive Informational Perspective on Human Behavior and Nudging

Human cognition often departs from classical models of rationality, giving rise to systematic biases, framing effects, and emotionally weighted decisions. While dual-process and behavioral economic theories have offered descriptive accounts of these patterns, they lack a unified, mechanistic framework to explain the internal dynamics of thought. Here, we extend the Recursive Informational Curvature (RIC) model, a theoretical construct we previously developed to characterize cognition as a dynamic trajectory within a symbolic manifold shaped by recursive gain (λ) and symbolic entropy (H). In this extended formulation, mental states, ranging from intuitive responses to reflective control, are modeled as curvature phases that emerge or collapse based on the balance of entropy and recursion.We apply this framework to reinterpret foundational constructs, including System 1/2 cognition, prospect theory, the endowment effect, cognitive biases, nudging, and cultural schema formation. Within RIC, biases are not logical failures but curvature-specific instabilities in symbolic space. Nudges, in turn, are understood as interventions that reshape informational flow geometrically rather than through explicit persuasion.RIC generates empirically testable predictions for neuroscience (e.g., curvature-related EEG/fMRI dynamics), behavior (e.g., entropy-modulated decision trajectories), and cognition (e.g., recursive language structures). It also suggests practical applications in education, therapy, interface design, and behavioral policy.As a unifying theory of mind and behavior, RIC reframes cognition as symbolic geometry, connecting decision science, recursive structure, and meaning. It offers a coherent explanatory model of how the mind bends, stabilizes, and deviates within the recursive topology of information.