The Projective Consciousness Model (PCM) combines a projective geometric model of the perspectival structure of conscious experience with a variational free-energy minimization model of active inference, explaining how consciousness serves a cybernetic function: modulating cognitive and affective dynamics to control embodied agents. Projective transformations link geometry and inference, integrating perception, emotion, memory, reasoning, and perspectival imagination to optimize behavior, resilience, and preference satisfaction. The PCM makes empirical predictions, fits a neurocomputational framework, and accounts for pre-reflective self-consciousness, the first-person perspective, the sense of ownership, and social self-consciousness. The authors argue it offers the most complete theory to date of phenomenal selfhood.
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.