EEG coherence during subjectively-rated psychological state variations



Publication Details

McCabe, L., Johnstone, S., Watts, A., Jiang, H., Sun, L. & Zhang, D. (2020). EEG coherence during subjectively-rated psychological state variations. International Journal of Psychophysiology, 158 380-388.


2020 Elsevier B.V. Background: Neurofeedback training aims to develop awareness and control of psychological states in order to self-regulate brain activity and while used widely therapeutically, important questions remain unanswered. Central to these aims is an assumed association between the live EEG-based feedback and the subjective experience of a psychological state. To date, there is little evidence to support this relationship. Previous studies examining the association between an EEG index and subjective experience have explored only the presence or absence of the state, or merely assumed state variations. The current study aims to examine this association by considering how different levels of a psychological state (i.e., attention) are reflected in EEG coherence. Methods: Our approach aims to allow comparisons of EEG coherence between psychological states (attention vs. rest), and also within subjectively-rated levels of a psychological state (attention) through a purpose-designed questionnaire. Thirty healthy adult participants performed a resting eyes-open (REO) and attention modulation task, while 28 channels of EEG were recorded. Levels within the psychological state were subjectively-attested by participants on a trial-by-trial basis. Results: The main analyses examined the effect of subjectively-rated attention levels (SRALs) on EEG coherence, with results suggesting that high and low SRALs may be represented by: 1) different levels of alpha and theta coherence at anterior and posterior electrodes of the frontal lobe bilaterally, and 2) different levels of alpha coherence between central and parietal lobes, also bilaterally. Discussion: These findings provide partial, preliminary evidence for EEG correlates of SRALs. These findings may have implications for understanding underlying mechanisms of NFT, which is an underdeveloped area.

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