Time-frequency analysis methods and their application in developmental EEG data

EEG provides a rich measure of brain activity that can be characterized as neuronal oscillations. However, most developmental EEG work to date has focused on analyzing EEG data as Event-Related Potentials (ERPs) or power based on the Fourier transform. While these measures have been productive, they...

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Bibliographic Details
Published inDevelopmental cognitive neuroscience Vol. 54; p. 101067
Main Authors Morales, Santiago, Bowers, Maureen E.
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier Ltd 01.04.2022
Elsevier
Subjects
EEG
Electroencephalography - methods
ERPs
Evoked Potentials - physiology
Humans
Neural oscillations
Original Research
Power
Time frequency
ERPs
Neural oscillations
Time frequency
EEG
Power
Online AccessGet full text
ISSN1878-9293
1878-9307
1878-9307
DOI10.1016/j.dcn.2022.101067

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Summary:EEG provides a rich measure of brain activity that can be characterized as neuronal oscillations. However, most developmental EEG work to date has focused on analyzing EEG data as Event-Related Potentials (ERPs) or power based on the Fourier transform. While these measures have been productive, they do not leverage all the information contained within the EEG signal. Namely, ERP analyses ignore non-phase-locked signals and Fourier-based power analyses ignore temporal information. Time-frequency analyses can better characterize the oscillations contained in the EEG data. By separating power and phase information across different frequencies, time-frequency measures provide a closer interpretation of the neurophysiological mechanisms, facilitate translation across neurophysiology disciplines, and capture processes not observed by ERP or Fourier-based analyses (e.g., connectivity). Despite their unique contributions, a literature review of this journal reveals that time-frequency analyses of EEG are yet to be embraced by the developmental cognitive neuroscience field. This manuscript presents a conceptual introduction to time-frequency analyses for developmental researchers. To facilitate the use of time-frequency analyses, we include a tutorial of accessible scripts, based on Cohen (2014), to calculate time-frequency power (signal strength), inter-trial phase synchrony (signal consistency), and two types of phase-based connectivity (inter-channel phase synchrony and weighted phase lag index).
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Both authors contributed equally to this manuscript.
ISSN:1878-9293
1878-9307
1878-9307
DOI:10.1016/j.dcn.2022.101067