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Does integrated information theory make testable predictions about the role of silent neurons in consciousness?

Gary Bartlett

Neuroscience of Consciousness 2022 DOI: 10.1093/nc/niac015 (opens in new tab)

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AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Keywords Consciousness Integrated information theory Neural activity Predictions Testability
Key points Argues that the disabling prediction and the silent brain prediction derived from integrated information theory are not testable, because the test conditions themselves preclude interpreting a subject's response as evidence of consciousness.

Abstract

Tononi et al. claim that their integrated information theory of consciousness makes testable predictions. This article discusses two of the more startling predictions, which follow from the theory's claim that conscious experiences are generated by inactive as well as active neurons. The first prediction is that a subject's conscious experience at a time can be affected by the disabling of neurons that were already inactive at that time. The second is that even if a subject's entire brain is "silent," meaning that all of its neurons are inactive (but not disabled), the subject can still have a conscious experience. A few authors have noted the implausibility of these predictions-which I call the disabling prediction and the silent brain prediction-but none have considered whether they are testable. In this article, I argue that they are not. In order to make this case, I first try to clarify the distinction between active, inactive (i.e. silent), and inactivated (i.e. disabled) neurons. With this clarification in place, I show that, even putting aside practical difficulties, it is impossible to set up a valid test of either the disabling prediction or the silent brain prediction. The conditions of the tests themselves are conditions under which a response from the subject could not reasonably be interpreted as evidence of consciousness or change in consciousness.

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