Assessing and conceptualizing frontal EEG asymmetry: An updated primer on recording, processing, analyzing, and interpreting frontal alpha asymmetry

Ezra E. Smith, Samantha J. Reznik, Jennifer L. Stewart, John J.B. Allen

Research output: Research - peer-reviewArticle

  • 4 Citations

Abstract

Frontal electroencephalographic (EEG) alpha asymmetry is widely researched in studies of emotion, motivation, and psychopathology, yet it is a metric that has been quantified and analyzed using diverse procedures, and diversity in procedures muddles cross-study interpretation. The aim of this article is to provide an updated tutorial for EEG alpha asymmetry recording, processing, analysis, and interpretation, with an eye towards improving consistency of results across studies. First, a brief background in alpha asymmetry findings is provided. Then, some guidelines for recording, processing, and analyzing alpha asymmetry are presented with an emphasis on the creation of asymmetry scores, referencing choices, and artifact removal. Processing steps are explained in detail, and references to MATLAB-based toolboxes that are helpful for creating and investigating alpha asymmetry are noted. Then, conceptual challenges and interpretative issues are reviewed, including a discussion of alpha asymmetry as a mediator/moderator of emotion and psychopathology. Finally, the effects of two automated component-based artifact correction algorithms—MARA and ADJUST—on frontal alpha asymmetry are evaluated.

LanguageEnglish (US)
Pages98-114
Number of pages17
JournalInternational Journal of Psychophysiology
Volume111
DOIs
StatePublished - Jan 1 2017

Fingerprint

Psychopathology
Artifacts
Emotions
Motivation
Guidelines

Keywords

  • Frontal EEG asymmetry
  • ICA artifact correction
  • Signal processing
  • Statistical models

ASJC Scopus subject areas

  • Neuroscience(all)
  • Neuropsychology and Physiological Psychology
  • Physiology (medical)

Cite this

Assessing and conceptualizing frontal EEG asymmetry : An updated primer on recording, processing, analyzing, and interpreting frontal alpha asymmetry. / Smith, Ezra E.; Reznik, Samantha J.; Stewart, Jennifer L.; Allen, John J.B.

In: International Journal of Psychophysiology, Vol. 111, 01.01.2017, p. 98-114.

Research output: Research - peer-reviewArticle

@article{dfd703bac3714a618abe579419d9e270,
title = "Assessing and conceptualizing frontal EEG asymmetry: An updated primer on recording, processing, analyzing, and interpreting frontal alpha asymmetry",
abstract = "Frontal electroencephalographic (EEG) alpha asymmetry is widely researched in studies of emotion, motivation, and psychopathology, yet it is a metric that has been quantified and analyzed using diverse procedures, and diversity in procedures muddles cross-study interpretation. The aim of this article is to provide an updated tutorial for EEG alpha asymmetry recording, processing, analysis, and interpretation, with an eye towards improving consistency of results across studies. First, a brief background in alpha asymmetry findings is provided. Then, some guidelines for recording, processing, and analyzing alpha asymmetry are presented with an emphasis on the creation of asymmetry scores, referencing choices, and artifact removal. Processing steps are explained in detail, and references to MATLAB-based toolboxes that are helpful for creating and investigating alpha asymmetry are noted. Then, conceptual challenges and interpretative issues are reviewed, including a discussion of alpha asymmetry as a mediator/moderator of emotion and psychopathology. Finally, the effects of two automated component-based artifact correction algorithms—MARA and ADJUST—on frontal alpha asymmetry are evaluated.",
keywords = "Frontal EEG asymmetry, ICA artifact correction, Signal processing, Statistical models",
author = "Smith, {Ezra E.} and Reznik, {Samantha J.} and Stewart, {Jennifer L.} and Allen, {John J.B.}",
year = "2017",
month = "1",
doi = "10.1016/j.ijpsycho.2016.11.005",
volume = "111",
pages = "98--114",
journal = "International Journal of Psychophysiology",
issn = "0167-8760",
publisher = "Elsevier",

}

TY - JOUR

T1 - Assessing and conceptualizing frontal EEG asymmetry

T2 - International Journal of Psychophysiology

AU - Smith,Ezra E.

AU - Reznik,Samantha J.

AU - Stewart,Jennifer L.

AU - Allen,John J.B.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Frontal electroencephalographic (EEG) alpha asymmetry is widely researched in studies of emotion, motivation, and psychopathology, yet it is a metric that has been quantified and analyzed using diverse procedures, and diversity in procedures muddles cross-study interpretation. The aim of this article is to provide an updated tutorial for EEG alpha asymmetry recording, processing, analysis, and interpretation, with an eye towards improving consistency of results across studies. First, a brief background in alpha asymmetry findings is provided. Then, some guidelines for recording, processing, and analyzing alpha asymmetry are presented with an emphasis on the creation of asymmetry scores, referencing choices, and artifact removal. Processing steps are explained in detail, and references to MATLAB-based toolboxes that are helpful for creating and investigating alpha asymmetry are noted. Then, conceptual challenges and interpretative issues are reviewed, including a discussion of alpha asymmetry as a mediator/moderator of emotion and psychopathology. Finally, the effects of two automated component-based artifact correction algorithms—MARA and ADJUST—on frontal alpha asymmetry are evaluated.

AB - Frontal electroencephalographic (EEG) alpha asymmetry is widely researched in studies of emotion, motivation, and psychopathology, yet it is a metric that has been quantified and analyzed using diverse procedures, and diversity in procedures muddles cross-study interpretation. The aim of this article is to provide an updated tutorial for EEG alpha asymmetry recording, processing, analysis, and interpretation, with an eye towards improving consistency of results across studies. First, a brief background in alpha asymmetry findings is provided. Then, some guidelines for recording, processing, and analyzing alpha asymmetry are presented with an emphasis on the creation of asymmetry scores, referencing choices, and artifact removal. Processing steps are explained in detail, and references to MATLAB-based toolboxes that are helpful for creating and investigating alpha asymmetry are noted. Then, conceptual challenges and interpretative issues are reviewed, including a discussion of alpha asymmetry as a mediator/moderator of emotion and psychopathology. Finally, the effects of two automated component-based artifact correction algorithms—MARA and ADJUST—on frontal alpha asymmetry are evaluated.

KW - Frontal EEG asymmetry

KW - ICA artifact correction

KW - Signal processing

KW - Statistical models

UR - http://www.scopus.com/inward/record.url?scp=85007392053&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85007392053&partnerID=8YFLogxK

U2 - 10.1016/j.ijpsycho.2016.11.005

DO - 10.1016/j.ijpsycho.2016.11.005

M3 - Article

VL - 111

SP - 98

EP - 114

JO - International Journal of Psychophysiology

JF - International Journal of Psychophysiology

SN - 0167-8760

ER -