Integrated information theory (IIT) and the testability of the silent neuron predictions.

Abstract

Integrated information theory (IIT) makes two predictions about the role of inactive neurons in consciousness. According to the silent brain (SB) prediction, rendering all active neurons inactive ("silent") in the physical substrate of consciousness (the "main complex") does not eliminate the presence of consciousness, because the neurons are still able to spike. According to the disabled neuron (DN) prediction, rendering a subset of silent neurons in the main complex no longer able to spike ("disabled") can impact the qualitative character of experiences "nonconventionally" associated with those neurons. Bartlett (2022) argues that these predictions are untestable, because evidence for either prediction would imply that the testing conditions were not met. In this paper, we provide a detailed analysis of both silent neuron predictions, showing how they can in fact be tested. For the SB case, we clarify how a neural mechanism outside of the main complex can yield the required report of consciousness while maintaining the SB state. For the DN case, we distinguish between two ways of explaining how a neural mechanism could casually interact with the main complex: an IIT-inspired "dispositionalist" explanation, and a more conventional "actualist" explanation. Drawing on the work of Imre Lakatos, we conclude with a discussion of how the distinction between the two explanations sheds light on why it is so difficult to resolve theoretical disputes about consciousness. Despite these difficulties, we provide a framework that can lead to concrete progress for consciousness science.