Pure awareness, entropy, and the foundation of perception
Jonas Mago, Shamil Chandaria, Mark Miller, Ruben Laukkonen
July 21, 2025 preprint DOI: 10.31234/osf.io/c7naw_v2 (opens in new tab) via OpenAlex
Summary
AI-generated from the abstractMinimal phenomenal experiences—states of consciousness with very little content—can be modeled as arising when precision weighting shifts to lower levels of a hierarchical inferential system, producing a perceptual state with increased entropy and reduced complexity. Awareness of this simplified state is maintained through epistemic depth, the reflexive sharing of the organism's reality model with itself, so that a reflexive knowing of the empty field of experience remains. The paper proposes an in silico simulation to test the relationship between precision distribution and entropy, which could generate synthetic EEG data to empirically validate the framework.
Study at a glance
| Characteristics | Theoretical or philosophical paper |
|---|---|
| Keywords | Perception Foundation evidence Psychology Political science Philosophy |
| Key finding | Proposes that Minimal Phenomenal Experiences arise when precision weighting shifts to lower levels of a hierarchical inferential system, leading to increased entropy and reduced complexity, while awareness is maintained through epistemic depth. |
Abstract
Minimal Phenomenal Experiences (MPEs) represent states of consciousness reduced to their most fundamental elements, posing a unique challenge and opportunity for modeling consciousness. This paper introduces a novel computational framework based on Bayesian and active inference to model MPEs. We propose that MPEs arise when precision weighting shifts predominantly to the lower levels of a hierarchical inferential system, leading to a perceptual state characterized by increased entropy and reduced complexity. Crucially, awareness of this simplified state is main- tained through epistemic depth: The reflexive sharing of the organism’s reality model with itself. Therefore, although the contents of consciousness are exceptionally quiet, a reflexive knowing of the empty field of experience remains. We then propose an in silico simulation to test the relation- ship between precision distribution and entropy, outlining how this model could generate synthetic EEG data to empirically validate the theoretical framework. By advancing our understanding of pure awareness through this computational approach, we provide a foundation for future research into the mechanisms underlying various altered states of consciousness, contributing to a more comprehensive understanding of the full spectrum of conscious experience.