Unlabelled: STUDY OBJECTIVIES: several studies have investigated slow wave sleep EEG parameters, including slow-wave activity (SWA) in relation to somnambulism, but results have been both inconsistent and contradictory. The first goal of the present study was to conduct a quantitative analysis of sleepwalkers' sleep EEG by studying fluctuations in spectral power for delta (1-4 Hz) and slow delta (0.5-1 Hz) before the onset of somnambulistic episodes. A secondary aim was to detect slow-wave oscillations to examine changes in their amplitude and density prior to behavioral episodes.
Participants: twenty-two adult sleepwalkers were investigated polysomnographically following 25 h of sleep deprivation.
Results: analysis of patients' sleep EEG over the 200 sec prior to the episodes' onset revealed that the episodes were not preceded by a gradual increase in spectral power for either delta or slow delta over frontal, central, or parietal leads. However, time course comparisons revealed significant changes in the density of slow-wave oscillations as well as in very slow oscillations with significant increases occurring during the final 20 sec immediately preceding episode onset.
Conclusions: the specificity of these sleep EEG parameters for the occurrence and diagnosis of NREM parasomnias remains to be determined.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2954701 | PMC |
http://dx.doi.org/10.1093/sleep/33.11.1511 | DOI Listing |
MethodsX
June 2025
Medical College of Wisconsin, Department of Neurosurgery, 8701 Watertown Plank Road, Milwaukee, WI, 53226.
Electrographic recording of brain activity through either surface electrodes (electroencephalography, EEG) or implanted electrodes (electrocorticography, ECOG) are valuable research tools in neuroscience across many disciplines, including epilepsy, sleep science and more. Research techniques to perform recordings in rodents are wide-ranging and often require custom parts that may not be readily available. Moreover, the information required to connect individual components is often limited and can therefore be challenging to implement.
View Article and Find Full Text PDFCell
December 2024
Center for Translational Neuromedicine, University of Copenhagen, 2200 Copenhagen N, Denmark; Center for Translational Neuromedicine, University of Rochester, Rochester, NY 14627, USA. Electronic address:
As the brain transitions from wakefulness to sleep, processing of external information diminishes while restorative processes, such as glymphatic removal of waste products, are activated. Yet, it is not known what drives brain clearance during sleep. We here employed an array of technologies and identified tightly synchronized oscillations in norepinephrine, cerebral blood volume, and cerebrospinal fluid (CSF) as the strongest predictors of glymphatic clearance during NREM sleep.
View Article and Find Full Text PDFBrain Dev
January 2025
Department of Pediatric Neurology, Okayama University Hospital and Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
Introduction: Epileptic encephalopathy (EE) is a serious clinical issue that manifests as part of developmental and epileptic encephalopathy (DEE), particularly in childhood epilepsy. In EE, neurocognitive functions and behavior are impaired by intense epileptiform electroencephalogram (EEG) activity. Hypotheses of pathophysiological mechanisms behind EE are reviewed to contribute to an effective solution for EE.
View Article and Find Full Text PDFPulsating blood vessels push fluid into and out of the brains of slumbering mice.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Sorbonne Université, Paris Brain Institute (ICM), INSERM, CNRS, UMR-1127, Mov'It, DreamTeam, Paris, France.
Background: Spectral power of slow rhythms in resting-state EEG increases along Alzheimer's disease (AD) continuum. Besides, recent studies have revealed 1) the importance of analyzing the aperiodic component of an EEG power spectrum and 2) the intrusions of sleep-like slow waves identifiable in wake EEG of animals and young adults. Importantly, the occurrence of these wake slow waves is known i) to increase after sleep deprivation, ii) to be associated with markers of sleepiness, and iii) to predict behavioral errors at different tasks.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!