A Computational Model of Minimal Phenomenal Experience (MPE)

Abstract

Minimal phenomenal experience (MPE), or "pure consciousness," represents a fundamental form of conscious experience characterised by reflexive meta-awareness and the absence of many features of regular phenomenology. It has been described as e.g. non-conceptual, atemporal, non-egoic and aperspectival. This paper aims to develop a computational model of MPE using the mathematics of variational free energy minimization derived from the free energy principle (FEP). I employ a computational neurophenomenology approach, formalising key phenomenological features of MPE within the active inference framework. The model incorporates parametric depth, allowing for higher-order inferences about generative model parameters. I relate specific model parameterisations to reported MPE qualities such as meta-awareness, equanimity, effortlessness, and non-conceptuality. The proposed model suggests that MPE arises when an agent achieves very low free energy through self-directed awareness and modulation of their generative model, particularly by emphasising awareness of awareness itself. The model predicts elements of MPE phenomenology including a sense of effortlessness, timelessness, and the potential for a "zero-person perspective”. The implementation details for a simulation of the proposed model are outlined, as well as directions for empirical validation.