A mathematical model of embodied consciousness

Area of Science:

• Cognitive Science
• Neuroscience
• Artificial Intelligence
• Mathematical Psychology

Background:

• Current models of consciousness lack a unified mathematical framework.
• Understanding the computational role of consciousness in perception and action is crucial.
• Embodied cognition emphasizes the role of the body and sensory-motor interactions in shaping conscious experience.

Purpose of the Study:

• To introduce the Projective Consciousness Model (PCM), a novel mathematical model for embodied consciousness.
• To explain how projective geometry and active inference shape the spatial field of consciousness (FoC).
• To demonstrate how the PCM accounts for subjective experience, perception-action dynamics, and psychological phenomena.

Main Methods:

• Developed a mathematical model based on projective geometry and active inference.
• Hypothesized that the field of consciousness (FoC) is structured by projective frames.
• Modeled consciousness as a resilience maximization algorithm using projective perspective-taking and imagination.

Main Results:

• The PCM integrates multisensory evidence and prior beliefs within projective frames.
• Free energy minimization, driven by expectation violations, controls perspective-taking and action switching.
• The model explains subjective spatial experience, perception-action distinctions, and phenomena like bistable figures and VR illusions.

Conclusions:

• The PCM provides a computational account of consciousness, linking phenomenology to function.
• Consciousness, via projective transformations, offers computational advantages for escaping local minima.
• The model suggests testable hypotheses for neuroscience, AI design, and formal psychology.