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 Video

Updated: Jun 27, 2026

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
08:31

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome

Published on: July 31, 2016

Model comparison for automatic characterization and classification of average ERPs using visual oddball paradigm.

A C Merzagora1, M Butti, R Polikar

  • 1School of Biomedical Engineering, Science and Health Systems, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA. a.merzagora@drexel.edu

Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology
|December 9, 2008
PubMed
Summary
This summary is machine-generated.

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

Assessment of Cyclic Alternating Pattern of sleep during late pregnancy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Comfort assessment in outdoor spaces supported by dynamic environmental monitoring: A comparison between different travel conditions.

The Science of the total environment·2025
Same author

Role of the EEG Theta Network During Software Production: A Connectivity Study.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2023
Same author

Selecting a pre-processing pipeline for the analysis of EEG event-related rhythms modulation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2022
Same author

Levodopa-dependent differences in the non-oscillatory activity of the subthalamic nucleus.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2022
Same author

Action Observation Therapy Before Sleep Hours: An EEG Study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2022

Automated classifiers can accurately identify event-related potentials (ERPs) for attentional processes. Using P300 features with non-linear classifiers like SVM offers optimal performance.

Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience
  • Psychophysiology

Background:

  • Investigating attentional processes often relies on analyzing event-related potentials (ERPs).
  • Automated classification methods offer potential for objective and efficient analysis of ERP data.
  • Identifying optimal features and models is crucial for accurate computer-assisted ERP analysis.

Purpose of the Study:

  • To evaluate the efficacy of automated classifiers in identifying target categorization responses from averaged ERPs.
  • To determine the most effective features and classification models for computer-assisted investigation of attentional processes.
  • To explore the potential of automated ERP analysis for clinical applications.

Main Methods:

  • ERPs were recorded during a target categorization task.

More Related Videos

Quantification of Visual Feature Selectivity of the Optokinetic Reflex in Mice
09:28

Quantification of Visual Feature Selectivity of the Optokinetic Reflex in Mice

Published on: June 23, 2023

Related Experiment Videos

Last Updated: Jun 27, 2026

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
08:31

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome

Published on: July 31, 2016

Quantification of Visual Feature Selectivity of the Optokinetic Reflex in Mice
09:28

Quantification of Visual Feature Selectivity of the Optokinetic Reflex in Mice

Published on: June 23, 2023

  • Automated classification compared average target ERPs versus average non-target ERPs.
  • Features from P300 and N200 components were extracted to train six classifiers: Euclidean classifier (EC), Mahalanobis discriminant (MD), quadratic classifier (QC), Fisher linear discriminant (FLD), multi-layer perceptron neural network (MLP), and support vector machine (SVM).

    • Main Results:

    • The quadratic classifier (QC), multi-layer perceptron (MLP), and support vector machine (SVM) achieved the highest classification performance (accuracy: 91-92%; sensitivity: 85-86%; specificity: 95-99%).
    • Optimal performance was achieved using feature vectors extracted from P300 components recorded at multiple sites.
    • Non-linear and non-parametric classifiers generally outperformed linear classifiers; N200 features did not significantly improve classification beyond P300 features.

    Conclusions:

    • Automatic characterization and classification of average target and non-target ERPs are feasible.
    • P300 features from multiple sites trained with non-linear classifiers are recommended for optimal classification.
    • Automated ERP analysis offers an objective approach for diagnosing abnormalities and monitoring attentional processes in clinical populations.