Quantifying Emotional States Using Neurochemical Indices: A Theoretical Framework
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This paper proposes a theoretical model to scale emotions based on quantifiable neurochemical levels—primarily dopamine, serotonin, oxytocin, endorphins, and cortisol. By analyzing the relative interaction and balance among these neurochemical agents, we derive a composite metric, termed the Emotional Potency Quotient (EPQ), capable of representing emotional valence and intensity on a multidimensional scale.The framework introduces five key components of emotional experience—physiological arousal, subjective intensity, cognitive disruption, behavioral influence, and duration—and integrates them with known neurochemical correlates. This creates a structured, semi-quantitative formula to describe affective states and transitions.We believe this model holds promise in applications ranging from mental health diagnostics and AI-human interaction to wearable affective computing and neurofeedback therapies. This paper aims to initiate an interdisciplinary dialogue between neuroscience, psychology, computational modeling, and emotional theory.
