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Title: On the relation between complex brain activity and consciousness
Author: Schartner, Michael Manfred
ISNI:       0000 0004 6061 7969
Awarding Body: University of Sussex
Current Institution: University of Sussex
Date of Award: 2017
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Why does it feel like something to be awake? I.e. how is consciousness generated by the body, the brain in particular? Seeking to map phenomenological properties of any first person experience to neural activity patterns, theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, all brain regions are to a certain extent connected and there is diversity in the interactions. In support of this, Casali et al. (2013) have used EEG and transcranial magnetic stimulation to show extensively that brain response activity to direct perturbation is the more diverse across regions and time, the higher the level of consciousness. The spatio-temporal diversity of the response signal is quantified by a single index, the perturbational complexity index (PCI), using a Lempel-Ziv compression algorithm. Motivated by this result, and given that spontaneous neural signals are easier to obtain than response signals to perturbation, this thesis proposes measures - based on Lempel-Ziv compression and entropy - to quantify spontaneous neural signal diversity across channels and observations. Our measures' sensitivity and specificity to conscious level is demonstrated by re-analysing resting state scalp EEG during propofol-induced anaesthesia and depth electrode recordings during sleep stages, resulting in consistently higher scores for subjects that are awake than being in propofol-induced anaesthesia or non-rapid eye movement sleep. In addition we demonstrate that our measures score higher for states induced by psychedelic substances by re-analysing resting state magnetoencephalography (MEG) data. We further explore in computer simulation how our measures and PCI behave as a function of connectivity of coupled oscillators, informing models of brain mechanisms associated with the loss of consciousness. While our measures may be weaker than PCI in terms of specificity and sensitivity to conscious level, they are quick and easy to compute and applicable to readily available resting state data. This thesis provides strong evidence that cortical signal diversity is a hallmark of consciousness, as predicted by integrated information and complexity theories of consciousness.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QP0351 Neurophysiology and neuropsychology