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Review
. 2021 Aug 30;2021(2):niab023.
doi: 10.1093/nc/niab023. eCollection 2021.

Consciousness and complexity: a consilience of evidence

Affiliations
Review

Consciousness and complexity: a consilience of evidence

Simone Sarasso et al. Neurosci Conscious. .

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.

Keywords: anesthesia; coma; information; integration; sleep.

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Conflict of interest statement

None declared.

Figures

Figure 1.
Figure 1.
Relevant examples of brain complexity measures as a reliable index of the state of consciousness
Figure 2.
Figure 2.
Literature on complexity-related measures
Figure 3.
Figure 3.
Schematic representation of the first strategy for estimating the repertoire of brain states (topological differentiation)
Figure 4.
Figure 4.
Schematic representation of the second strategy for estimating the repertoire of brain states (temporal differentiation)
Figure 5.
Figure 5.
Schematic representation of the mixed strategy for estimating the repertoire of brain states
Figure 6.
Figure 6.
A perturbational approach to brain complexity

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