From Satiation to Allostasis: Toward a Resource-Based Framework for Reversal Triggers in Reversal Theory

Author contact: yan.yang.research [at] proton.me This note proposes the following original research ideas: 1. A theoretical linkage between Apter’s Reversal Theory and Barrett’s allostasis-based framework, suggesting that reversal triggers in RT (e.g., satiation, frustration, contingent events) may reflect adaptive shifts within a longer-range predictive body resource budgeting system. 2. A proposal that such reversal dynamics might, in future work, be formally operationalized. Potential directions for operationalization are briefly outlined, including: o How some of the reversal triggers described by Apter can be reinterpreted in terms of body resource budgeting, offering inspirations for future modeling using multimodal data such as behavioral, self-report, and physiological; o A contextualized data collection strategy—grounded in RT and phenomenological theory—embedding RT scales into interactive platforms, enabling time-extended sampling of subjective states alongside behavioral dynamics. o A breakdown of possible data collection environments by platform characteristics—such as sensing richness, degree of immersion, and social interactivity. 3. A distinction between two classes of industrial application scenarios: constraint-bound systems (e.g., search engines) and sensor-rich environments (e.g., smart homes or mixed-reality platforms). 4. The possibility that measurement disturbance (Dirac, 1958), in light of quantum-like models of qualia (Tsuchiya et al., 2025), may provide a new angle for explaining reversal triggers in Reversal Theory. This note was inspired in part by informal discussions following Models of Consciousness 6 (Sapporo, Japan), but all theoretical proposals are independently developed by the author. These ideas are shared here in early form to publicly establish authorship and intellectual priority. © 2025 Yan Yang. Please do not reuse, extend, or cite these ideas without appropriate attribution.