The unfolding argument: Why IIT and other causal structure theories cannot explain consciousness.

Theories that identify consciousness with specific causal structures in the brain, such as those requiring feedback loops, are either false or unscientific. Using theorems from computation theory, the authors demonstrate that causal structure theories—including Information Integration Theory (IIT) and Recurrent Processing Theory (RPT)—cannot be empirically tested because any causal structure can be realized by systems that lack consciousness. This undermines the claim that feedforward systems are never conscious and feedback systems always are. The argument suggests that consciousness research should focus instead on functional explanations, such as global workspace or higher-order theories, which are compatible with diverse neural implementations.

Study at a glance

Abstract

How can we explain consciousness? This question has become a vibrant topic of neuroscience research in recent decades. A large body of empirical results has been accumulated, and many theories have been proposed. Certain theories suggest that consciousness should be explained in terms of brain functions, such as accessing information in a global workspace, applying higher order to lower order representations, or predictive coding. These functions could be realized by a variety of patterns of brain connectivity. Other theories, such as Information Integration Theory (IIT) and Recurrent Processing Theory (RPT), identify causal structure with consciousness. For example, according to these theories, feedforward systems are never conscious, and feedback systems always are. Here, using theorems from the theory of computation, we show that causal structure theories are either false or outside the realm of science.