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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:

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Related Experiment Video

Updated: Apr 18, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

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Developmental and aging changes in brain network switching dynamics revealed by EEG phase synchronization.

Dionysios Perdikis^1,2, Rita Sleimen-Malkoun³, Viktor Müller⁴

¹Aix-Marseille Univ, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France.

Plos Computational Biology

|April 16, 2026

Summary

Neural variability changes across the lifespan, with brain activity becoming less complex with age. Young adults show the most diverse brain network dynamics, suggesting a critical period for brain adaptability.

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Last Updated: Apr 18, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

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Published on: May 7, 2014

Cortical Source Analysis of High-Density EEG Recordings in Children

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Published on: June 30, 2014

EEG Mu Rhythm in Typical and Atypical Development

EEG Mu Rhythm in Typical and Atypical Development

Published on: April 9, 2014

Area of Science:

Neuroscience
Cognitive Science
Computational Biology

Background:

Adaptive behavior relies on brain activity variability across scales.
Understanding lifespan changes in neural variability is crucial for neurocognitive aging models.
Current models lack mechanistic insights into developmental and aging trajectories of brain dynamics.

Purpose of the Study:

To characterize lifespan changes in neural variability using electroencephalography (EEG) and computational modeling.
To investigate how EEG amplitude, entropy, and phase synchrony evolve from childhood to older adulthood.
To develop a mechanistic model explaining age-related alterations in brain network dynamics.

Main Methods:

Analyzed high-density EEG data from 111 healthy individuals (ages 9-75) at rest and during auditory oddball tasks.
Extracted scale-dependent EEG fluctuation measures (amplitude, entropy) and phase-synchrony networks (2-20 Hz).
Employed partial least squares decomposition and fitted a phase-oscillator model constrained by the human connectome.

Main Results:

Identified two lifespan trajectories: monotonic decline in slow-frequency power/variance/complexity with age, and an inverted U-trend in phase-synchrony reconfiguration dynamics.
Young adults exhibited slowest, most diverse synchrony switching (2-6 Hz), contrasting with children and older adults' faster, stereotyped dynamics.
A metastable coupling regime in the phase-oscillator model reproduced young adults' heterogeneous synchrony, while weaker/stronger coupling mimicked children/older adults.

Conclusions:

Brain development and aging significantly alter EEG phase synchronization switching dynamics.
Stationary and transient aspects of neural variability are differentially sculpted across the lifespan.
Time-resolved phase-synchrony metrics serve as sensitive, mechanistically grounded markers of neurocognitive status throughout life.