Subjective awareness may arise because the brain builds a simplified, incomplete model of its own attention—an 'attention schema.' This incompleteness prevents us from fully understanding how consciousness emerges, which relates to the 'hard problem' of consciousness. Using a mathematical model grounded in classical topology, the paper demonstrates that a complete representation of attention is impossible for any system, human or machine, that monitors its own attention. The argument shows that attention streams cannot be faithfully represented internally, supporting the core claim of Attention Schema Theory: the brain's self-model of attention is necessarily incomplete.
Consciousness is modeled as a spatial field structured by projective geometry and controlled by active inference. The Projective Consciousness Model (PCM) combines sensory evidence with prior beliefs, selecting points of view and perspectives according to preferences. Violations of expectation are encoded as free energy, and minimizing free energy drives perspective taking, switching between perception, imagination, and action. Consciousness functions as an algorithm maximizing resilience by using projective perspective taking to escape local free energy minima. The model accounts for spatial phenomenology, distinctions between perception, imagination, and action, affective processes in intentionality, bistable figure dynamics, and body swap illusions. It relates phenomenology to function, suggesting computational advantages of consciousness and generating neurophenomenological hypotheses.
Evolution has selected for inherently unstable biological systems—such as blood pressure, immune responses, and gene expression—that can react swiftly to changing threats or opportunities, but these systems require strict regulation to avoid fatal consequences. Consciousness similarly demands high rates of metabolic free energy to both operate and regulate its underlying machinery, with the stream of consciousness and its boundaries being continually reconstructed in response to dynamic circumstances. The authors develop necessary conditions models using the Data Rate Theorem, which links control and information theories for inherently unstable systems. The synergy between conscious action and its regulation explains the ten-fold higher metabolic energy consumption in human neural tissue and implies a culturally modulated connection between sleep disorders and certain psychopathologies.