Collapse of local circuit integrated information Φ during NREM sleep

Abstract

Abstract Clarifying the mechanisms underlying the emergence of consciousness remains a fundamental challenge in modern neuroscience. Integrated Information Theory (IIT) provides a mathematical framework derived from the phenomenological properties of consciousness as its axioms. IIT proposes that consciousness is identical to a system’s intrinsic cause-effect information structure, quantified by integrated information Φ. While IIT predicts that the Φ of a neuronal system should decrease during the loss of consciousness, this hypothesis has remained untested at the neural circuit level. The present study provides empirical support for this IIT prediction. It was found that Φ within local circuits decreases during non-rapid eye movement (NREM) sleep compared to wakefulness and REM sleep, regardless of cortical laminar structure or brain regions, and even after controlling for firing rates. The reduction in Φ was particularly pronounced during OFF-periods, when neural activity is collectively suppressed. These results align with IIT’s framework, suggesting that the loss of consciousness corresponds to a collapse of integrated information within local circuits that cannot be explained solely by changes in individual system elements (such as overall firing rates). The findings provide empirical support for IIT as a mathematical theory aiming to explain conscious experiences.