Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Brain Waves

Brain Waves

Brain waves are electrical signals generated by the neurons in the brain, which are regularly monitored to measure mental activities. Brain waves and their frequency ranges can be measured using an electroencephalogram or EEG. There are four main types of brain waves, each with distinct characteristics:

You might also read

Related Articles

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

Sort by

Same author

From womb to words: the sex-specific interplay of fetal sex hormones and maternal mood on infant language development.

Frontiers in endocrinology·2026

Same author

COLLEMBOT: AI-based counting of Collembola for OECD 232 Tests.

Environmental toxicology and chemistry·2026

Same author

Convergent transcriptomic and connectomic controllers of information integration and its anaesthetic breakdown across mammalian brains.

Nature human behaviour·2026

Same author

Continuous sleep tracking in digital CBT-I: Efficacy and insights from a naturalistic-environment study.

International journal of clinical and health psychology : IJCHP·2026

Same author

Exploring the bidirectional within-subject relationship between sleep and affective wellbeing: Insights from an intensive longitudinal study.

International journal of clinical and health psychology : IJCHP·2025

Same author

Sleep-Related Factors in Shift Workers: A Cross-Sectional Cohort Pilot Study to Inform Online Group Therapy for Insomnia.

International journal of environmental research and public health·2025

Same journal

Neuropsychological, biological, and electrophysiological outcomes of gamma-tACS in MCI-AD: A case series.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2026

Same journal

Enhanced broad-band intermuscular coherence in myoclonus: a targeted characterization study.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2026

Same journal

Perturbing the vestibular cortex with transcranial oscillatory currents uncovers early postural alterations in Parkinson's disease.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2026

Same journal

F-waves in primary lateral sclerosis: a window into spinal motoneuron hyperexcitability.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2026

Same journal

When the algorithm disagrees: managing AI-generated 'second opinions' in clinical neurophysiology.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2026

Same journal

Cervical nerve root contribution to diaphragm motor innervation revisited via intraoperative clinical and neurophysiological observations.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 31, 2026

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

EEG entropy measures indicate decrease of cortical information processing in Disorders of Consciousness.

Alexander Thul¹, Julia Lechinger², Johann Donis³

¹Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Germany; Department of Anesthesiology, Klinikum rechts der Isar, Technische Universität München, Germany.

Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology

|October 21, 2015

Summary

This summary is machine-generated.

Electroencephalography (EEG) entropy analysis can differentiate disorders of consciousness (DoC) by measuring brain activity. This method reveals reduced information processing and impaired connectivity in patients with Minimally-Conscious-State (MCS) and Unresponsive-Wakefulness-Syndrome (UWS).

Keywords:

Disorders of consciousness Electroencephalography Information theory Non-linear analysis Own-name paradigm Permutation entropy Symbolic transfer entropy

More Related Videos

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Published on: May 10, 2017

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Published on: June 15, 2018

Related Experiment Videos

Last Updated: Mar 31, 2026

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Published on: May 10, 2017

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Published on: June 15, 2018

Area of Science:

Neuroscience
Clinical Neurology
Biomedical Engineering

Background:

Clinical assessments for Disorders of Consciousness (DoC) are limited by motor disabilities.
Objective measures of brain activity are needed to assess reduced consciousness.

Purpose of the Study:

To evaluate electroencephalography (EEG) entropy analysis for objectifying patients' conditions of reduced consciousness.
To differentiate between Minimally-Conscious-State (MCS) and Unresponsive-Wakefulness-Syndrome (UWS) using EEG measures.

Main Methods:

Analyzed permutation entropy (PeEn) and symbolic transfer entropy (STEn) from 18 scalp EEG channels.
Compared 15 severely brain-damaged patients (MCS/UWS) with 24 healthy controls.
Utilized a modified active own-name paradigm to assess active instruction following.

Main Results:

Reduced local information content (PeEn) in patient EEGs, most pronounced in UWS.
Altered directed information flow (STEn) indicating impaired feedback connectivity in patients.
Differences in entropy measures during auditory stimulation, showing reduced processing in MCS and UWS.

Conclusions:

Local EEG information content and flow are affected in DoC.
EEG entropy analysis can differentiate patient groups within DoC.
Cortical information capacity and feedback transfer are potential neural correlates of consciousness.