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 Experiment Videos

Nonlinearity in human resting, eyes-closed EEG: an in-depth case study.

W S Pritchard1, C J Stam

  • 1Psychophysiology Laboratory, Bowman Gray Technical Center, R.J. Reynolds Tobacco Company, Winston-Salem, NC 27102, USA. pritchw@rjrt.com.

Acta Neurobiologiae Experimentalis
|April 19, 2000
PubMed
Summary

Linear analysis of human electroencephalogram (EEG) is efficient. While some nonlinearity was detected in alpha rhythms, it was trivial, with linear models explaining most variance.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Reliability and state-dependency of EEG connectivity, complexity and network characteristics.

Scientific reports·2025
Same author

Comparing individual and group-level simulated neurophysiological brain connectivity using the Jansen and Rit neural mass model.

Network neuroscience (Cambridge, Mass.)·2023
Same author

The influence of very preterm birth on adolescent EEG connectivity, network organization and long-term outcome.

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

Network Hyperexcitability in Early Alzheimer's Disease: Is Functional Connectivity a Potential Biomarker?

Brain topography·2023
Same author

Macroscale EEG characteristics in antipsychotic-naïve patients with first-episode psychosis and healthy controls.

Schizophrenia (Heidelberg, Germany)·2023
Same author

Minimum spanning tree analysis of brain networks: A systematic review of network size effects, sensitivity for neuropsychiatric pathology, and disorder specificity.

Network neuroscience (Cambridge, Mass.)·2022

Area of Science:

  • Neuroscience
  • Signal Processing

Background:

  • Linear methods for electroencephalogram (EEG) analysis are well-established and computationally efficient.
  • Understanding nonlinearity in EEG is crucial for comprehending the brain's oscillatory activity.

Purpose of the Study:

  • To investigate the presence and significance of nonlinearity in human EEG.
  • To compare the efficacy of linear versus nonlinear modeling approaches for EEG data.

Main Methods:

  • Utilized a linear summary measure as a control for comparison.
  • Analyzed normal, resting, eyes-closed EEG data from a single participant.
  • Applied both linear and nonlinear modeling techniques to assess data variance.

Main Results:

Related Experiment Videos

  • Failed to reject the null hypothesis of a stationary linear-Gaussian process for the overall EEG.
  • Detected significant evidence of nonlinearity at occipital sites (O1, O2) associated with alpha rhythm.
  • Nonlinear structure was deemed trivial, with linear models explaining over 94% of the variance.

    • Conclusions:

    • The detected nonlinearity in human EEG alpha rhythms appears minimal and does not significantly improve upon linear modeling.
    • Findings suggest that linear models are largely sufficient for analyzing typical resting-state EEG, despite localized nonlinearities.