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Consciousness as an Emergent Phenomenon: A Tale of Different Levels of Description.

Ramón Guevara, Diego M. Mateos, Jose Luis Perez Velazquez

Entropy (Basel, Switzerland) August 22, 2020 DOI: 10.3390/e22090921 (opens in new tab)

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AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Keywords Quantum biology Consciousness Brain connectivity Brain dynamics Neural synchronization
Key points Proposes that consciousness can emerge not only from large-scale brain networks but also from subcellular networks exhibiting nontrivial quantum phenomena, with the essential feature being strong correlations and an optimal point where complexity and energy dissipation are maximized while free energy is minimized, expressed either by maximization of information content in large-scale functional networks or by optimal efficiency through the quantum "Goldilock effect."

Abstract

One of the biggest queries in cognitive sciences is the emergence of consciousness from matter. Modern neurobiological theories of consciousness propose that conscious experience is the result of interactions between large-scale neuronal networks in the brain, traditionally described within the realm of classical physics. Here, we propose a generalized connectionist framework in which the emergence of "conscious networks" is not exclusive of large brain areas, but can be identified in subcellular networks exhibiting nontrivial quantum phenomena. The essential feature of such networks is the existence of strong correlations in the system (classical or quantum coherence) and the presence of an optimal point at which the system's complexity and energy dissipation are maximized, whereas free-energy is minimized. This is expressed either by maximization of the information content in large scale functional networks or by achieving optimal efficiency through the quantum Goldilock effect.

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