A Neurocomputational Account of Consciousness: The Goal-Aligning Representation Internal Manipulation Theory (GARIM)

Consciousness, a central element of human cognition, has been studied with multiple scientific approaches spanning neuroscience, psychology, artificial intelligence and robotics. Unfortunately, poor integration between these fields limits a full and clear understanding of consciousness. Here we contribute to improving this integration by proposing, within a neurocomputational framework, the `Goal-Aligning Representations Internal Manipulation' (GARIM) theory of consciousness. The central idea of the GARIM theory is that consciousness supports the active manipulation of goal-relevant internal representations (e.g., world states, objects, and action sequences), making them more aligned with the goals pursued. These manipulations allow the conscious agent to internally produce the knowledge it lacks to cope with novel conditions and goals, increasing the flexibility of goal-directed behaviour. The manipulation of representations is supported by four neuro-functional macro-systems (hierarchical perceptual working memories, abstract working memory, internal manipulator, motivational systems) that operate through a set of computational manipulation operations (abstraction, specification, decomposition, composition). The theory also presents the concept of `GARIM agency', proposing that subjective conscious experience derives from the ability of agents to generate and control a vivid internally simulated reality. Furthermore, the theory highlights the criticalities of the experimental investigation of consciousness, suggesting a new approach to testing consciousness in biological and artificial agents. Finally, the GARIM theory can benefit technological fields such as machine learning and autonomous robotics (e.g., the manipulation processes proposed by the theory could be linked to the operations performed by systems based on transformers).