Conscious experience corresponds to information encoded in coarse-grained neural states, such as the firing patterns of neuronal populations, rather than in the noisy activity of individual neurons or in macro-level interactions like interpersonal communication. The authors introduce Information Closure Theory of Consciousness (ICT), which hypothesizes that conscious processes form non-trivial informational closure (NTIC) with respect to the environment at certain coarse-grained levels. This closure confines conscious experience to those levels. ICT provides quantitative definitions of conscious content and conscious level, offering explanations and predictions for various consciousness phenomena and reconciling issues in existing theories.
Consciousness may have evolved because it enables organisms to internally generate representations of events not tied to current sensory input, using generative models built through sensory-motor interactions. This capacity for information generation supports intention, imagination, planning, short-term memory, attention, curiosity, and creativity, all of which contribute to non-reflexive, flexible behavior. The hypothesis aligns with predictive coding, where top-down predictions correspond to information generation, and with empirical evidence that recurrent feedback activations are linked to consciousness while feedforward processing alone occurs without conscious experience. Thus, consciousness provides a biological advantage by allowing internal simulations that endow organisms with intelligent, adaptive behavior.