Electrophysiological Evidence of Local Sleep During Yoga Nidra Practice

We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

An English language self-assessment Morningness-Eveningness questionnaire is presented and evaluated against individual differences in the circadian vatiation of oral temperature. 48 subjects falling into Morning, Evening and Intermediate type categories regularly took their temperature. Circadian peak time were identified from the smoothed temperature curves of each subject. Results showed that Morning types and a significantly earlier peak time than Evening types and tended to have a higher daytime temperature and lower post peak temperature. The Intermediate type had temperatures between those of the other groups. Although no significant differences in sleep lengths were found between the three types, Morning types retired and arose significantly earlier than Evening types. Whilst these time significatly correlated with peak time, the questionnaire showed a higher peak time correlation. Although sleep habits are an important déterminant of peak time there are other contibutory factors, and these appear to be partly covered by the questionnaire. Although the questionnaire appears to be valid, further evaluation using a wider subject population is required.