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

Correlations between psychiatric diagnosis and some quantitative EEG variables.

C Shagass, J J Straumanis, D A Overton

    Neuropsychobiology
    |January 1, 1979
    PubMed
    Summary

    Electroencephalography (EEG) analysis revealed distinct patterns in psychiatric patients compared to controls. Resting EEG revealed differences in amplitude and frequency, particularly in chronic schizophrenics and neurotics.

    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

    Electromyographic studies of muscular tension in psychiatric patients under stress.

    Journal of clinical and experimental psychopathology·2014
    Same author

    An attempt to correlate the occipital alpha frequency of the electroencephalogram with performance on a mental ability test.

    Journal of experimental psychology·2010
    Same author

    Inadequacies of self-report data for exclusion criteria detection in marihuana research: an empirical case for multi-method direct examination screening.

    Journal of addictive diseases·2000
    Same author

    Validation of volume measurements in esophageal pseudotumors using 3D endoluminal ultrasound.

    Ultrasound in medicine & biology·2000
    Same author

    Topographic quantitative EEG sequelae of chronic marihuana use: a replication using medically and psychiatrically screened normal subjects.

    Drug and alcohol dependence·1999
    Same author

    Creation and first 20 years of the society for the stimulus properties of drugs (SSPD).

    Pharmacology, biochemistry, and behavior·1999

    Area of Science:

    • Neuroscience
    • Psychiatry
    • Quantitative Electroencephalography (qEEG)

    Background:

    • Quantitative analysis of resting electroencephalograms (EEGs) is crucial for understanding brain activity.
    • Previous research suggests potential differences in EEG patterns between psychiatric populations and healthy individuals.

    Purpose of the Study:

    • To investigate quantitative differences in left parietal resting EEGs between psychiatric inpatients and nonpatient controls.
    • To identify specific EEG markers associated with different psychiatric conditions, including schizophrenia and neurosis.

    Main Methods:

    • Applied quantitative analysis methods to resting EEG data from 48 controls and 90 psychiatric inpatients.
    • Matched patient and control groups for age and sex to minimize confounding variables.

    Related Experiment Videos

  • Analyzed mean frequency, frequency variability, and mean amplitude of EEG signals.

    • Main Results:

    • The total patient group exhibited lower mean frequency and greater frequency variability than controls.
    • Chronic schizophrenics showed higher mean amplitude and lower mean frequency compared to controls, with female patients contributing significantly to amplitude differences.
    • Nonpsychotic patients displayed intermediate EEG profiles between chronic schizophrenics and controls.
    • Neurotic patients demonstrated greater mean amplitudes and less frequency variability than controls.

    Conclusions:

    • Resting EEG quantitative analysis reveals significant differences in brain electrical activity between psychiatric patients and controls.
    • Specific patterns of EEG amplitude and frequency variability may serve as potential biomarkers for conditions like schizophrenia and neurosis.
    • Further research is warranted to explore the diagnostic and prognostic utility of these EEG findings in psychiatry.