Through the Looking Glass: A Study of EEG Data Using Aperiodic Components Analysis

Authors

Daniel C. Whitney, Brigham Young University
Dawson Hedges, Brigham Young University

Keywords

EEG data, aperiodic components analysis, ACA, serial sevens, pop-out recognition

College

Family, Home, and Social Sciences

Department

Psychology

Abstract

In the past, it has been difficult to distinguish between different tasks of cognition using conventional statistical and graphical methods of EEG analysis. Aperiodic components analysis (ACA) offers a new, innovative approach to time series data analysis – a rubric under which EEG data analysis falls – and should allow the differentiation between simple tasks of cognition.

Recommended Citation

Whitney, Daniel C. and Hedges, Dawson (2013) "Through the Looking Glass: A Study of EEG Data Using Aperiodic Components Analysis," Journal of Undergraduate Research: Vol. 2013: Iss. 1, Article 465.
Available at: https://scholarsarchive.byu.edu/jur/vol2013/iss1/465