C. Navona

AN AUTOMATIC METHOD FOR THE RECOGNITION AND CLASSIFICATION OF THE A-PHASES OF THE CYCLIC ALTERNATING PATTERN

OBJECTIVES The aim of this research has been to introduce an automatic method, simple from the mathematical and computational points of view, for the recognition and classification of the A-phases of the cyclic alternating pattern. METHODS The automatic method was based on the computation of 5 descriptors, which were derived from the EEG signal and were able to provide a meaningful data reduction. Each of them corresponded to a different frequency band. RESULTS The computation of these descriptors, followed by the introduction of two suitable thresholds and of simple criteria for logical discrimination, provided results which were in good agreement with those obtained with visual analysis. The method was versatile and could be applied to the study of other important microstructure phenomena by means of very small adaptations. CONCLUSIONS The simplicity of the method leads to a better understanding and a more precise definition of the visual criteria for the recognition and classification of the microstructure phenomena.

A simple method for the quantitative description of sleep microstructure

A simple method for the quantitative description of sleep microstructure is proposed. This method is based on the computation of descriptors which provide a normalized measure of how the amplitude of the activity in a frequency band differs, at a given instant, from its background. The use of these descriptors makes it possible to identify epochs of transient increase in band activity, to measure their length, and to measure the time distance between two successive epochs.

A study of the interhemispheric correlation during sleep in elderly subjects.

The interhemispheric relationship during sleep in elderly subjects was studied throughout the night by a minute-by-minute computation of two linear correlation coefficients between right and left EEG activities. One of these coefficients (Xδ) related to the 1–4-Hz band activity, and the other (Xσ) to the 12.5–14.5-Hz band activity. For five of the six subjects examined, it was found that the rapid-eyemovement (REM) mean values of both coefficients were significantly different from the nonrapid-eye-movement (NREM) values. A comparison between this elderly group and a control group of young subjects, examined previously, did not reveal any significant shift, either for the REM or for the NREM mean values of the coefficients.

Significance of Automatically Detected Word Recurrences in Dream Associations

Verbal data files including dream reports and associations with the report items were subjected to automatic analysis aiming at the recognition of word recurrences. The research was based on the following assumptions: the associations can provide information about the dream sources; the recognition of word recurrences in text files can be a useful tool for the study of dreaming; the identification of links between different dream sources can provide an interesting insight into the phenomenon of dreaming. The principal result obtained was that word recurrences often evidence possible significant links between dream sources. A number of the possible links evidenced by the automatic analysis not only escaped the subjects notice, but might also be unexpected for an analyzer not assisted by a computer.