Integrated information and predictive processing theories of consciousness: An adversarial collaborative review

Three major theories of consciousness—Integrated Information Theory, Neurorepresentationalism, and Active Inference—are compared and contrasted in the context of a structured adversarial collaboration designed to test their competing predictions. The review presents each theory's core claims, the phenomena they explain, their explanatory styles, and methodological strategies. It outlines key hypotheses to be tested across multi-site experiments, discusses observations that would support or challenge each theory, and describes how data from disparate experiments can be formally integrated to provide a quantitative measure of evidential support. The work also offers meta-scientific insights into adversarial collaboration and theory-testing.

Study at a glance

Abstract

As neuroscientific theories of consciousness continue to proliferate, the need to assess their similarities and differences - as well as their predictive and explanatory power - becomes ever more pressing. Recently, a number of structured adversarial collaborations have been devised to test the competing predictions of several candidate theories of consciousness. In this review, we compare and contrast three theories being investigated in one such adversarial collaboration: Integrated Information Theory, Neurorepresentationalism, and Active Inference. We begin by presenting the core claims of each theory, before comparing them in terms of the phenomena they seek to explain, the sorts of explanations they avail, and the methodological strategies they endorse. We then consider some of the inherent challenges of theory-testing, and how adversarial collaboration addresses some of these difficulties. The stage is then set for the empirical work to come: first, we outline the key hypotheses to be tested across a series of multi-site experiments; second, we discuss the kinds of observations that would support or challenge each theory; third, we consider how these theories might assimilate or accommodate such observations. Finally, we show how data harvested across disparate experiments (and their replicates) may be formally integrated to provide a quantitative measure of the evidential support accrued under each theory. Besides orienting the reader to the theoretical foundations of our collaboration, this review aims to provide valuable meta-scientific insights into the mechanics of adversarial collaboration and theory-testing in general - including the way theories may be evaluated in terms of the scientific progress they deliver.