Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Sleep-Wake Cycles01:24

Sleep-Wake Cycles

2.7K
Sleep is an essential physiological process vital to maintaining overall well-being. The reticular activating system (RAS), a network of neurons in the brainstem, regulates wakefulness and sleep. While it may seem passive, sleep consists of distinct cycles, each with its unique characteristics and functions. Two key sleep phases are non-rapid eye movement (NREM) and  rapid eye movement (REM).
NREM Sleep
NREM sleep comprises four progressive stages that seamlessly merge:
2.7K
Understanding Sleep01:11

Understanding Sleep

1.4K
Sleep, an essential biological state, involves significant reductions in physical activity, sensory awareness, and interaction with the environment. This complex physiological process is primarily regulated by specific brain regions, notably the hypothalamus and pons, which govern the sleep-wake cycle or circadian rhythm.
The circadian rhythm, a nearly 24-hour cycle, is deeply influenced by environmental light cues. Light exposure directly affects the hypothalamus, which in turn regulates...
1.4K
Stages of Sleep01:22

Stages of Sleep

1.3K
Sleep progresses through distinct stages, each characterized by specific brain wave patterns and physiological responses ranging from wakefulness to stages of non-rapid eye movement, known as non-REM, to rapid eye movement, referred to as REM. Understanding these stages helps in recognizing how sleep supports various bodily and cognitive functions.
Before sleep begins, in wakefulness, the brain exhibits primarily beta waves, which are high in frequency and low in amplitude, indicating alertness...
1.3K
REM Sleep Behavior Disorder01:15

REM Sleep Behavior Disorder

1.4K
REM Sleep Behavior Disorder (RBD) is a sleep disorder characterized by the absence of muscle paralysis that normally occurs during the REM phase of sleep. This absence allows individuals to physically act out their dreams, which are often vivid and disturbing. Common behaviors exhibited during episodes include kicking, punching, and yelling. These actions can be dangerous, potentially leading to injuries for the person with RBD or their bed partner.
RBD is significantly associated with...
1.4K
Substance Use Disorders Affecting Sleep01:24

Substance Use Disorders Affecting Sleep

398
Substance use disorders involve a pattern of using drugs more extensively than intended and continuing use despite harmful consequences. This includes legal substances like alcohol and nicotine, as well as illegal drugs. These disorders often involve both physical and psychological dependence, reflecting compulsive use of substances that significantly alter thoughts, feelings, and behaviors, contributing to a major public health issue.
Understanding the concepts of physical dependence,...
398

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Learn how to interpret and use intracranial EEG findings.

Epileptic disorders : international epilepsy journal with videotape·2023
Same author

Targeted density electrode placement achieves high concordance with traditional high-density EEG for electrical source imaging in epilepsy.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2023
Same author

Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy.

Epilepsy & behavior : E&B·2023
Same author

Data on the design optimization, indoor characterization and outdoor testing of GaAs/Bifacial Si heterojunction four-terminal photovoltaic systems.

Data in brief·2022
Same author

Interictal sleep recordings during presurgical evaluation: Bidirectional perspectives on sleep related network functioning.

Revue neurologique·2022
Same author

[Sleep disorders in patients with a neurocognitive disorder].

L'Encephale·2021
Same journal

Translational profiling of Drd2-expressing populations reveals molecular heterogeneity of dentate gyrus mossy cells along the dorsoventral axis.

eNeuro·2026
Same journal

Movement Disorder Patients with Depression have Altered Corticostriatal Alpha-Beta Power Response to Reward and Loss.

eNeuro·2026
Same journal

Ocular speech tracking persists in blindness, but its dynamics and oculo-cerebral connectivity depend on visual status.

eNeuro·2026
Same journal

Emergent multidien cycles from partial circadian synchrony.

eNeuro·2026
Same journal

Adolescent social isolation induces persistent impairments in emotional discrimination and helping behavior.

eNeuro·2026
Same journal

Increased Ih Current Is Associated with Reduced Hippocampal CA1 Excitability in a Mouse Model of Multiple Sclerosis.

eNeuro·2026
See all related articles

Related Experiment Video

Updated: Jan 15, 2026

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice
10:56

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice

Published on: August 2, 2017

10.5K

Rhythms and Background (RnB): The Spectroscopy of Sleep Recordings.

J Dubé1,2, M Foti3, S Jaffard4

  • 1Department of Psychology, Université de Montréal, Montreal, Quebec H3C 1J7, Canada.

Eneuro
|January 13, 2026
PubMed
Summary
This summary is machine-generated.

We introduce Rhythms & Background (RnB), a new wavelet method to separate brain rhythms from background noise in sleep EEG data. This improves analysis of sleep oscillations and their role in memory and brain function.

Keywords:
EEGNREM sleeparrhythmic activitybrain rhythmsphase–amplitude couplingspectral analysis

More Related Videos

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data
04:13

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data

Published on: November 13, 2019

12.8K
Multi-Modal Home Sleep Monitoring in Older Adults
07:40

Multi-Modal Home Sleep Monitoring in Older Adults

Published on: January 26, 2019

8.1K

Related Experiment Videos

Last Updated: Jan 15, 2026

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice
10:56

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice

Published on: August 2, 2017

10.5K
Computer-based Multitaper Spectrogram Program for Electroencephalographic Data
04:13

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data

Published on: November 13, 2019

12.8K
Multi-Modal Home Sleep Monitoring in Older Adults
07:40

Multi-Modal Home Sleep Monitoring in Older Adults

Published on: January 26, 2019

8.1K

Area of Science:

  • Neuroscience
  • Signal Processing
  • Computational Biology

Background:

  • Non-rapid eye movement (NREM) sleep involves complex brain oscillations crucial for memory consolidation.
  • Existing spectral analysis methods struggle to separate rhythmic brain activity from arrhythmic background noise in the time domain.
  • This limitation hinders accurate analysis of instantaneous oscillatory properties and their functional roles during sleep.

Purpose of the Study:

  • To introduce a novel wavelet-based methodology, Rhythms & Background (RnB), for denoising time-series electrophysiological data.
  • To enable the extraction of purely rhythmic time series, overcoming limitations of current spectral analysis techniques.
  • To enhance time-domain analyses of sleep rhythms and their interactions.

Main Methods:

  • Developed the Rhythms & Background (RnB) algorithm, a wavelet-based approach for time-series denoising.
  • Validated RnB using simulations to assess its accuracy in estimating spectral profiles under various arrhythmic conditions.
  • Applied RnB to intracranial EEG sleep recordings to analyze NREM sleep rhythms.

Main Results:

  • Simulations confirmed RnB's robust performance in accurately estimating spectral profiles of oscillations amidst arrhythmic interference.
  • Application to EEG data revealed improved spectral and time-domain representations of NREM sleep rhythms.
  • RnB significantly enhanced the assessment of phase-amplitude coupling between NREM oscillations compared to traditional methods.

Conclusions:

  • RnB offers a substantial methodological advancement for analyzing sleep oscillations, providing greater precision in time-domain studies.
  • This method disentangles rhythmic brain activity from background noise, offering clearer insights into cerebral oscillatory processes during sleep.
  • RnB has broad applications in neuroscience research, including the study of brain connectivity, oscillatory dynamics, and clinical populations with altered arrhythmic activity.