title: Predictable internal brain dynamics in EEG and its relation to conscious states.
abstract: Consciousness is a complex and multi-faceted phenomenon defying scientific explanation. Part of the reason why this is the case is due to its subjective nature. In our previous computational experiments, to avoid such a subjective trap, we took a strategy to investigate objective necessary conditions of consciousness. Our basic hypothesis was that predictive internal dynamics serves as such a condition. This is in line with theories of consciousness that treat retention (memory), protention (anticipation), and primary impression as the tripartite temporal structure of consciousness. To test our hypothesis, we analyzed publicly available sleep and awake electroencephalogram (EEG) data. Our results show that EEG signals from awake or rapid eye movement (REM) sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS). Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis. The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics.
authors.affiliation: Department of Computer Science and Engineering, Texas A&M University College Station, TX, USA.
authors.forename: Jaewook
authors.initials: J
authors.lastname: Yoo
authors.affiliation: Department of Electrical and Computer Engineering, Kettering University Flint, MI, USA.
authors.forename: Jaerock
authors.initials: J
authors.lastname: Kwon
authors.affiliation: Department of Computer Science and Engineering, Texas A&M University College Station, TX, USA.
authors.forename: Yoonsuck
authors.initials: Y
authors.lastname: Choe
keywords: EEG; consciousness; neuroevolution; predictable dynamics; sleep