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Integrated Information Theory (IIT) is an audacious attempt to pin down theabstract, phenomenological experiences of consciousness into a rigorous,mathematical framework. We show that IIT's stance in regards to neuronal noiseis inconsistent with experimental data demonstrating that neuronal noise in thebrain plays a critical role in learning, visual recognition, and evencategorical representation. IIT predicts that entropy due to noise will reducethe information integration of a physical system, which is inconsistent withexperimental data demonstrating that decision-related noise is a necessarycondition for learning and visual recognition tasks. IIT must therefore bereformulated to accommodate experimental evidence showing both the successesand failures of noise.

A Neuronal Noise Critique of Integrated Information Theory