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The Consciousness States in the Light of Neuroscience

Stanisław Radoń

Annales Universitatis Mariae Curie-Skłodowska sectio J – Paedagogia-Psychologia August 20, 2018 DOI: 10.17951/j.2018.31.1.75-95 (opens in new tab)

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Characteristics Review Longitudinal Peer reviewed
Key findings Argues that deviations in the brain's small-world network structure, especially Default Mode Network activity, track changes in consciousness across coma, vegetative state, minimal consciousness, and meditation, with each state showing distinct connectivity and spectral patterns. Proposes that advanced spectral metrics could have clinical diagnostic, therapeutic, and prognostic value, and calls for further neuroimaging research.

Abstract

The human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity (optimal organization of different brain network associated with rapid information propagation, minimal wiring costs, as well as a balance between local processing and global integration) in which activity of Default Mode Network play important role in different states of consciousness. The small-world structure deviation reflects genuine changes in levels of consciousness: 1) coma state: increased activity of precuneus and posterior cingulate cortex and domination alpha band over theta and delta band connected with low activity of alpha, theta, and delta band, 2) vegetative state: increased connectivity in Default Mode Network and increased power in delta, theta, beta, and low alpha band, 3) state of minimal consciousness: decreased activation of the Default Mode Network during tasks, domination alpha band over theta and delta band connected with high activity of alpha, theta, and delta band, 4) meditation state: reorganization of central and peripheral elements of the brain network, changes in quantity, quality, orientation of longitudinal (antero-posterior) and transverse (right-left) edges, and its frequency of activity, increased longitudinal integration and hemispherical synchronization. Future neuroimaging investigations are needed. Especially the new sophisticated spectral metrics could be potentially effective in clinical setting and have diagnostic, therapeutic and prognostic relevance.

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