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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

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Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
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EEG microstates associated with intra- and inter-subject alpha variability.

Pierpaolo Croce1, Angelica Quercia1, Sergio Costa1

  • 1Department of Neuroscience, Imaging and Clinical Sciences,"G. d'Annunzio" University of Chieti-Pescara, Chieti-Pescara, Italy.

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|February 14, 2020
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Summary

Posterior alpha rhythm variations influence brain microstate dynamics, affecting sensory processing and cognition. Increased alpha oscillations correlate with visual system microstates and alter executive attention and task-negative network activity.

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

  • Neuroscience
  • Cognitive Science
  • Brain Activity Analysis

Background:

  • Posterior alpha rhythm (8-12 Hz) variations impact sensory processing and cognitive functions.
  • Electroencephalography (EEG) reveals brain activity through microstates (40-120 ms), reflecting synchronized neural activity and scalp potential topographies.
  • Microstate dynamics may indicate transitions between global brain states, potentially mediated by alpha activity and selective cortical inhibition.

Purpose of the Study:

  • To investigate the intra-subject and inter-subject relationship between electroencephalography (EEG) microstate features and alpha band activity.
  • To determine if observed microstate parameter variations are specific to the alpha band or also occur with other frequency bands (theta, beta) and global field power.

Main Methods:

  • Acquired high-density EEG signals from 29 healthy subjects during a 10-minute eyes-closed rest period.
  • Classified EEG signal epochs into four groups based on occipital alpha power.
  • Calculated and compared microstate metrics (duration, coverage, frequency) across groups, and performed correlations between alpha power and microstate metrics.

Main Results:

  • Increased metrics of microstates associated with the visual system were observed with higher intra-subject alpha oscillation amplitude.
  • Lower coverage of microstates linked to the executive attention network and higher frequency of microstates linked to the task-negative network were found with increased alpha power.
  • Modulation effects of broad-band EEG power on microstate metrics were observed, indicating these effects are not exclusive to the alpha band.

Conclusions:

  • Posterior alpha level acts as a regulatory mechanism, dynamically interacting with other frequency bands.
  • This alpha-mediated regulation is responsible for switching between active brain areas.
  • Observed microstate dynamics reflect the interplay between alpha oscillations and global brain state transitions.