Information generation as a functional basis of consciousness.

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.

Study at a glance

Abstract

What is the biological advantage of having consciousness? Functions of consciousness have been elusive due to the subjective nature of consciousness and ample empirical evidence showing the presence of many nonconscious cognitive performances in the human brain. Drawing upon empirical literature, here, we propose that a core function of consciousness be the ability to internally generate representations of events possibly detached from the current sensory input. Such representations are constructed by generative models learned through sensory-motor interactions with the environment. We argue that the ability to generate information underlies a variety of cognitive functions associated with consciousness such as intention, imagination, planning, short-term memory, attention, curiosity, and creativity, all of which contribute to non-reflexive behavior. According to this view, consciousness emerged in evolution when organisms gained the ability to perform internal simulations using internal models, which endowed them with flexible intelligent behavior. To illustrate the notion of information generation, we take variational autoencoders (VAEs) as an analogy and show that information generation corresponds the decoding (or decompression) part of VAEs. In biological brains, we propose that information generation corresponds to top-down predictions in the predictive coding framework. This is compatible with empirical observations that recurrent feedback activations are linked with consciousness whereas feedforward processing alone seems to occur without evoking conscious experience. Taken together, the information generation hypothesis captures many aspects of existing ideas about potential functions of consciousness and provides new perspectives on the functional roles of consciousness.