Non-linear recurrence analysis of NREM human sleep microstructure discloses deterministic oscillation patterns related to sleep stage transitions and sleep maintenance.

L. Priano, F. Saccomandi, A. Mauro, C. Guiot

Research output: Contribution to journalArticle

Abstract

Sleep is a dynamic process aimed at obtaining the required neurophysiological states at certain times, according to circadian and homeostatic needs and despite external or internal interfering stimuli. In this context, peculiar transient synchronized EEG patterns (TSEP) are supposed to play the main role in the building up of EEG synchronization and in the flexible adaptation against perturbations Our study aimed at disclosing and quantifying attractor driven, hidden periodicity or, conversely, chaotic oscillation patterns in the series of these TSEP related to sleep stage transitions and sleep maintenance. At first we devised a multistep algorithm, able to capture TSEP from EEG during sleep in 10 healthy volunteers. The time series of TSEP were then analyzed according to the Recurrence Plot (RP). TSEP series showed to form a pseudo-periodic series which becomes progressively denser and more stable until steady slow wave NREM sleep is reached, but looses stability just before REM sleep starts. This suggests that deterministic oscillatory patterns maybe adequate descriptors of the balance between homeostatic needs for NREM sleep and REM sleep pressure, supported by different cortical neuronal populations interactions.

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Sleep Stages
Nonlinear analysis
Electroencephalography
Sleep
Maintenance
Recurrence
Microstructure
REM Sleep
Sleep-Wake Transition Disorders
Periodicity
Healthy Volunteers
Time series
Synchronization
Pressure
Population

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

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title = "Non-linear recurrence analysis of NREM human sleep microstructure discloses deterministic oscillation patterns related to sleep stage transitions and sleep maintenance.",
abstract = "Sleep is a dynamic process aimed at obtaining the required neurophysiological states at certain times, according to circadian and homeostatic needs and despite external or internal interfering stimuli. In this context, peculiar transient synchronized EEG patterns (TSEP) are supposed to play the main role in the building up of EEG synchronization and in the flexible adaptation against perturbations Our study aimed at disclosing and quantifying attractor driven, hidden periodicity or, conversely, chaotic oscillation patterns in the series of these TSEP related to sleep stage transitions and sleep maintenance. At first we devised a multistep algorithm, able to capture TSEP from EEG during sleep in 10 healthy volunteers. The time series of TSEP were then analyzed according to the Recurrence Plot (RP). TSEP series showed to form a pseudo-periodic series which becomes progressively denser and more stable until steady slow wave NREM sleep is reached, but looses stability just before REM sleep starts. This suggests that deterministic oscillatory patterns maybe adequate descriptors of the balance between homeostatic needs for NREM sleep and REM sleep pressure, supported by different cortical neuronal populations interactions.",
author = "L. Priano and F. Saccomandi and A. Mauro and C. Guiot",
year = "2010",
language = "English",
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T1 - Non-linear recurrence analysis of NREM human sleep microstructure discloses deterministic oscillation patterns related to sleep stage transitions and sleep maintenance.

AU - Priano, L.

AU - Saccomandi, F.

AU - Mauro, A.

AU - Guiot, C.

PY - 2010

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N2 - Sleep is a dynamic process aimed at obtaining the required neurophysiological states at certain times, according to circadian and homeostatic needs and despite external or internal interfering stimuli. In this context, peculiar transient synchronized EEG patterns (TSEP) are supposed to play the main role in the building up of EEG synchronization and in the flexible adaptation against perturbations Our study aimed at disclosing and quantifying attractor driven, hidden periodicity or, conversely, chaotic oscillation patterns in the series of these TSEP related to sleep stage transitions and sleep maintenance. At first we devised a multistep algorithm, able to capture TSEP from EEG during sleep in 10 healthy volunteers. The time series of TSEP were then analyzed according to the Recurrence Plot (RP). TSEP series showed to form a pseudo-periodic series which becomes progressively denser and more stable until steady slow wave NREM sleep is reached, but looses stability just before REM sleep starts. This suggests that deterministic oscillatory patterns maybe adequate descriptors of the balance between homeostatic needs for NREM sleep and REM sleep pressure, supported by different cortical neuronal populations interactions.

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