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Information integration, Granger causality and measuring conscious level.

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If you have a question about this talk, please contact Mikail Rubinov.

A key challenge in the neuroscience of consciousness is to develop theoretically grounded and practically applicable quantitative measures sensitive to conscious level. Such measures should be high for vivid alert conscious wakefulness, and low for unconscious states such as dreamless sleep, coma and general anaesthesia. I begin by motivating the hypothesis that, given the basic structure of conscious experience, conscious level must somehow correlate with the extent to which underlying neural dynamics are simultaneously generating and integrating information. I will then talk about two groups of proposed measures based on this hypothesis: (i) measures of integrated information, which reflect the extent to which the information generated by the whole system exceeds that generated by its parts; (ii) measures of causal density, which use Granger causality to quantify the overall causal interactivity in the system. I will compare and contrast the two groups of measures, both in their conception and in their properties in simulation, and discuss their merits and shortcomings, in theory and in practice. I then present some preliminary empirical tests of the theory from steady-state electrophysiological data: EEG data from subjects undergoing general anaesthesia and intracranial depth electrode data recorded during deep sleep and wakeful resting.

This talk is part of the Brain Mapping Unit Networks Meeting and the Cambridge Connectome Consortium series.

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