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

Circadian Rhythms and Gene Regulation02:19

Circadian Rhythms and Gene Regulation

4.7K
The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent...
4.7K
Sleep-Wake Cycles01:24

Sleep-Wake Cycles

3.3K
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:
3.3K

You might also read

Related Articles

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

Sort by
Same author

Deltas' and Spindles' Cross-Area Synchronization and Ripple Subtypes.

Sleep·2026
Same author

EEG microstates reveal distinct network dynamics in lucid and non-lucid REM sleep.

Consciousness and cognition·2026
Same author

An Increase in C-Reactive Protein Levels during Antidepressant Treatment as a Candidate Marker for Treatment Nonresponse in Major Depressive Disorder.

Neuropsychobiology·2026
Same author

The Young Adult Sleep model: an evolving causal loop diagram of mental health dynamics.

BMC medicine·2026
Same author

Cheating hypnos: can polyphasic sleep schedules reduce the need for sleep?

Sleep·2026
Same author

<i>Wearanize+</i>: a multimodal dataset for evaluating wearable technologies in sleep research.

Sleep advances : a journal of the Sleep Research Society·2026
Same journal

The causal efficacy of consciousness: a neuroscientific analysis and explanation.

Frontiers in human neuroscience·2026
Same journal

Temporal-oscillatory entrainment: a multi-timescale framework for rhythmic coordination from neural to social frequencies.

Frontiers in human neuroscience·2026
Same journal

Role of AQP4 in ameliorating heat stress-induced cellular injury in a cell line model through active heat acclimation.

Frontiers in human neuroscience·2026
Same journal

Correction: Cognitive state monitoring for neuroadaptive information visualization.

Frontiers in human neuroscience·2026
Same journal

The synthetic self-hypothesis: dopaminergic redirection through self-face recognition in stuttering therapy.

Frontiers in human neuroscience·2026
Same journal

A randomised, placebo-controlled, triple-blind clinical trial to investigate the efficacy of <i>Ginkgo biloba</i> extract EGb 761<sup>®</sup> in cognitive impairment associated with post COVID-19 syndrome-the EGb COCOS protocol.

Frontiers in human neuroscience·2026
See all related articles

Related Experiment Video

Updated: Mar 29, 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

10.7K

Automatic Sleep Spindle Detection and Genetic Influence Estimation Using Continuous Wavelet Transform.

Marek Adamczyk1, Lisa Genzel2, Martin Dresler3

  • 1Max Planck Institute of Psychiatry Munich, Germany.

Frontiers in Human Neuroscience
|December 5, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a new algorithm for detecting sleep spindles, crucial for neuroplasticity and memory. The findings highlight a significant genetic influence on slow sleep spindle traits.

Keywords:
EEGautomatic detectionheritabilitysleep spindletwins

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

13.0K
Author Spotlight: IntelliSleepScorer &#8212; A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research
04:54

Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research

Published on: November 8, 2024

1.1K

Related Experiment Videos

Last Updated: Mar 29, 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

10.7K
Computer-based Multitaper Spectrogram Program for Electroencephalographic Data
04:13

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data

Published on: November 13, 2019

13.0K
Author Spotlight: IntelliSleepScorer &#8212; A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research
04:54

Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research

Published on: November 8, 2024

1.1K

Area of Science:

  • Neuroscience
  • Sleep Science
  • Genetics

Background:

  • Sleep spindles, a type of non-rapid eye movement (NREM) sleep oscillation, are increasingly recognized for their role in neuroplasticity.
  • Previous research suggests distinct functions for fast and slow sleep spindles in memory processing.

Purpose of the Study:

  • To develop and validate a novel algorithm for detecting sleep spindles using continuous wavelet transform (CWT).
  • To investigate the genetic underpinnings of slow and fast sleep spindle characteristics.

Main Methods:

  • A new sleep spindle detection algorithm was developed, employing CWT and individualized frequency band adjustments for slow and fast spindles.
  • The algorithm was validated against human scoring and the SIESTA detector using 18 nap recordings.
  • The algorithm was applied to datasets on memory consolidation and twin studies (monozygotic and dizygotic).

Main Results:

  • The developed algorithm demonstrated good agreement with human scorers (kappa=0.45) and the SIESTA detector (kappa=0.62).
  • The algorithm confirmed a correlation between spindle density and declarative memory consolidation.
  • Analysis revealed substantial genetic influence on slow spindle parameters, a weaker effect on fast spindles, and no significant genetic effect on fast spindle density or number during stage 2 sleep.

Conclusions:

  • The novel CWT-based algorithm provides a reliable method for sleep spindle detection.
  • Sleep spindle characteristics, particularly slow spindles, are significantly influenced by genetic factors.