Formalizing Falsification of Causal Structure Theories for Consciousness Across Computational Hierarchies

There is currently a global, multimillion-dollar effort to experimentally confirm or falsify neuroscience's preeminent theory of consciousness: Integrated Information Theory (IIT). Yet, recent theoretical work suggests major epistemic concerns regarding the validity of IIT and all so-called "causal structure theories". In particular, causal structure theories are based on the assumption that consciousness supervenes on a particular causal structure, despite the fact that different causal structures can lead to the same input-output behavior and global functionality. This, in turn, leads to epistemic problems when it comes to the ability to falsify such a theory - if two systems are functionally identical, what remains to justify a difference in subjective experience? Here, we ground these abstract epistemic problems in a concrete example of functionally indistinguishable systems with different causal architectures. Our example comes in the form of an isomorphic feed-forward decomposition ("unfolding") of a simple electronic tollbooth, which we use to demonstrate a clear falsification of causal structure theories such as IIT. We conclude with a brief discussion regarding the level of formal description at which a candidate measure of consciousness must operate if it is to be considered scientific.