Consciousness and complexity: a consilience of evidence

Summary

A compelling consilience reveals complexity measures consistently mark Consciousness across diverse states like sleep and anesthesia. This convergence, spanning two decades of Psychology and Cognitive science, highlights robust Neural dynamics and brain function. Different methods, from EEG and Brain-Computer Interfaces to Functional Brain Connectivity Studies, leverage Data science to confirm these reliable markers. This systematic review clarifies this positive trend, offering a unified framework for future Epistemology in Cognitive psychology and Computer science, reflecting a positive, empirical approach to understanding the mind.

Abstract

Abstract Over the last years, a surge of empirical studies converged on complexity-related measures as reliable markers of consciousness across many different conditions, such as sleep, anesthesia, hallucinatory states, coma, and related disorders. Most of these measures were independently proposed by researchers endorsing disparate frameworks and employing different methods and techniques. Since this body of evidence has not been systematically reviewed and coherently organized so far, this positive trend has remained somewhat below the radar. The aim of this paper is to make this consilience of evidence in the science of consciousness explicit. We start with a systematic assessment of the growing literature on complexity-related measures and identify their common denominator, tracing it back to core theoretical principles and predictions put forward more than 20 years ago. In doing this, we highlight a consistent trajectory spanning two decades of consciousness research and provide a provisional taxonomy of the present literature. Finally, we consider all of the above as a positive ground to approach new questions and devise future experiments that may help consolidate and further develop a promising field where empirical research on consciousness appears to have, so far, naturally converged.

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