CAN WE MEASURE CONSCIOUSNESS WITH EEG COMPLEXITIES?
GU Fanji, Xin Meng, Enhua Shen, CAI Zhijie
International Journal of Bifurcation and Chaos March 1, 2003 DOI: 10.1142/s0218127403006893 (opens in new tab)
Summary
AI-generated from the abstractComplexity measures of EEG signals, including approximate entropy and a new measure, decrease in order from rest with eyes open, eyes closed, light sleep, deep sleep, and during epileptic seizures. Averaged mutual information between EEG channels increases significantly during seizures but shows no significant difference among resting with eyes open or closed, light sleep, or deep sleep. The complexity measures appear promising for distinguishing consciousness levels, while mutual information does not.
Study at a glance
| Characteristics | Observational study Peer reviewed |
|---|---|
| Population | Human subjects |
| Key finding | EEG complexity measures decrease with decreasing consciousness levels and during epileptic seizures, while averaged mutual information increases only during seizures. |
Abstract
Several complexity measures, especially approximate entropy (ApEn) and a new defined complexity measure [Formula: see text], of EEG signals or the ones of the mutual information transmission between different channels of EEGs were calculated to distinguish different consciousness levels for different brain functional states. All of the measures decreased with the following order of brain states: rest with eyes open, eyes closed, light sleep and deep sleep. They decreased during epileptic seizures. On the contrary, the averaged mutual information between different channels increased significantly during the epileptic seizure; there is no significant difference among the averaged mutual information for the subject resting with eyes open, closed, being in light sleep and in deep sleep. Thus, the former indexes seem to be promising candidates to characterize different consciousness levels, while the latter seems not.