A new set of composite, non-redundant electroencephalogram measures of non-rapid eye movement sleep based on the power law scaling of the Fourier spectrum

Abstract

26A novel method for deriving composite, non-redundant measures of non-rapid eye 27 movement (NREM) sleep electroencephalogram (EEG) is developed on the basis of the 28 power law scaling of the Fourier spectra. Measures derived are the spectral intercept, the 29 slope (spectral exponent), as well as the maximal whitened spectral peak amplitude and 30 frequency in the sleep spindle range. As a proof of concept, we apply these measures on a 31 large sleep EEG dataset (N = 175; 81 females; age range: 17-60 years) with previously 32 demonstrated effects of age, sex and intelligence. As predicted, aging is associated with 33 decreased overall spectral slopes (increased exponents) and whitened spectral peak 34 amplitudes in the spindle frequency range. In addition, age associates with decreased sleep 35 spindle spectral peak frequencies in the frontal region. Women were characterized by higher 36 spectral intercepts and higher spectral peak frequencies in the sleep spindle range. No sex 37 differences in whitened spectral peak amplitudes of the sleep spindle range were found. 38 Intelligence correlated positively with whitened spectral peak amplitudes of the spindle 39 frequency range in women, but not in men. Last, age-related increases in spectral exponents 40 did not differ in subjects with average and high intelligence. Our findings replicate and 41 complete previous reports in the literature, indicating that the number of variables describing 42 NREM sleep EEG can be effectively reduced in order to overcome redundancy and Type I 43 statistical errors in future electrophysiological studies of sleep. 44 45 46 47 48 Given the tight reciprocal relationship between sleep and wakefulness, the objective 49 description of the complex neural activity patterns characterizing human sleep is of utmost 50 importance in understanding the several facets of brain function, like sex differences, aging 51 and cognitive abilities. Current approaches are either exclusively based on visual impressions 52 expressed in graded levels of sleep depth (W, N1, N2, N3, REM), whereas computerized 53quantitative methods provide an almost infinite number of potential metrics, suffering from 54 significant redundancy and arbitrariness. Our current approach relies on the assumptions that 55 the spontaneous human brain activity as reflected by the scalp-derived electroencephalogram 56 (EEG) are characterized by coloured noise-like properties. That is, the contribution of 57 different frequencies to the power spectrum of the signal are best described by power law 58 functions with negative exponents. In addition, we assume, that stages N2-N3 are further 59 characterized by additional non-random (non-noise like, sinusoidal) activity patterns, which 60 are emerging at specific frequencies, called sleep spindles (9-18 Hz). By relying on these 61 assumptions we were able to effectively reduce 191 spectral measures to 4: (1) the spectral 62 intercept reflecting the overall amplitude of the signal, (2) the spectral slope reflecting the 63 constan...

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“…We calculated Rüger area global significance as follows: 1/3 of the descriptive significances at p=.05/3 =.017 AND/OR half of descriptive significances at p=.05/2=.025. In this study, we considered data Rüger area significant under the "AND” condition (65, 66).…”