Optimizing computation of overnight decline in delta power: Evidence for slower rate of decline in delta power in insomnia patients

Objective: To determine the best of commonly used methods for computing the rate of decline in non rapid eye movement (NREM) sleep EEG delta power overnight (Delta Decline) in terms of vulnerability to missing data and to evaluate whether this rate is slower in insomnia patients than healthy controls (HC). Methods: Fifty-one insomnia patients and 53 HC underwent 6 nights of polysomnography. Four methods for estimating Delta Decline were compared (exponential and linear best-fit functions using NREM (1) episode mean, (2) peak, and (3) total delta power and (4) delta power for all available NREM epochs). The best method was applied to compare groups on linear and exponential rates of Delta Decline. Results: Best-fit models using all available NREM epochs were significantly less vulnerable to deviation due to missing data than other methods. Insomnia patients displayed significantly slower linear and exponential Delta Decline than HC. Conclusions: Computing Delta Decline using all available NREM epochs was the best of the methods studied for minimizing the effects of missing data. Insomnia patients display slower Delta Decline, which is not explained by differences in total sleep time or wake after sleep onset. Significance: This study supports using all available NREM epochs in Delta Decline computation and suggests a slower rate in insomnia. (c) 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Automated summary

The study found that using all available NREM epochs in computing Delta Decline is the best method for minimizing the effects of missing data. Insomnia patients displayed slower Delta Decline rates compared to healthy controls, suggesting a potential indicator of insomnia.