Application of Subjective Information Theory to Dream Interpretation: The P-D-S Cognitive Architecture

Subjective experience emerges when a cognitive system actively participates in synthesizing information, especially under profound sensory deprivation. The P-D-S (Field-Disturbance-Subjective filter) architecture describes this process, integrating dream phenomenology and computational neurobiology. Sleep functions as an autopoietic mechanism generating subjective reality from endogenous neural noise. A heuristic space of cognitive states is introduced, along with an algorithmic metaphor of tensor synthesis and a principle of consciousness dynamics: maximization of affective resonance. The modal independence of information content is argued through dreams in congenitally blind individuals. The theory supports a computational architecture for artificial intelligence (PDS-Net) and complements the Predictive Processing paradigm.

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Abstract

The present work represents a theoretical development and interdisciplinary synthesis of concepts describing the processes of information synthesis in cognitive systems operating under conditions of profound sensory deprivation. The research is based on the "Field - Disturbance - Subjective filter" (P-D-S) conceptual architecture, which postulates that subjective experience is an emergent event requiring the active participation of the observer's cognitive-affective apparatus. The P-D-S model is integrated with dream phenomenology and contemporary computational neurobiology. Sleep is viewed as an autopoietic process of generating subjective reality based on endogenous neural noise. The paper introduces a heuristic space of cognitive states, develops an algorithmic metaphor of tensor synthesis, and formulates the basic principle of consciousness dynamics—the maximization of affective resonance. Special attention is given to the "problem of inter-mode decoding" and the phenomenology of dreams in the congenitally blind as an argument for the modal independence of information content. In the applied aspect, the theory lays the foundation for an artificial intelligence computational architecture (PDS-Net) and demonstrates methodological complementarity to the Predictive Processing paradigm.