Power-law scaling behavior of A-phase events during sleep: Normal and pathologic conditions. (March 2020)

• Record Type: Journal Article
• Authors: Mendez, Martin O.; Murguía, J.S.; Alba, Alfonso; Arce-Guevara, V.E.; González-Aguilar, H.; Guerrero-Mora, Guillermina
• Is Part Of: Biomedical signal processing and control. Volume 57(2020)
• Publication Date: 2020-03
• Subjects: Cyclic alternating pattern -- DFA -- CAP -- Self-affine process -- Long-range dependence; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2019.101757
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: The A-phase occurrence during sleep presents a statistical fractal structure. The fractal structure of A-phase dynamics is similar during pathologic and normal sleep. The scaling exponent of the A-phase dynamics could be a complementary index to the CAP-rate index. Abstract: Objective: A-phases are short-time cortical events during sleep that repeatedly disrupt the basal fluctuations of electrical brain activity. They are the basic units of the cyclic alternating pattern (CAP), which is related to the instability and consolidation of the sleep process. The main purpose of this study is to evaluate the temporal occurrence of A-phases (TOAP) under normal and pathologic sleep conditions. Methods: To derive a quantitative description of TOAP, we have applied detrended fluctuation analysis (DFA), to unveil scale-free behavior from non-stationary time series. Data from sleep recordings of 15 healthy subjects (H), 37 with nocturnal frontal lobe epilepsy (NFLE), 9 with periodic leg movement (PLM), and 22 with REM Sleep Behavior Disorder (RBD) from the Physionet database were used. TOAP was computed from binary time series constructed from A-phase annotations, where symbols 1 and −1, represent the presence or absence of an A-phase, respectively. These time series were analyzed through DFA and characterized by the scaling exponent. Results: In all cases, numerical results show evidence that a statistical fractal structure is embedded in TOAP, where persistent scaling behavior is observed with scaling exponent close to 1. Conclusion: The sleep process maintains a similar structure from the A-phase perspective despite of internal or external factors that could affect the sleep process, suggesting that sleep may be a resilient process. Significance: The scaling exponent of the A-phase occurrence provides new information about the sleep process that may have clinical relevance and complementary to standard clinical indices such as the CAP-rate.