Do Subjective Mood Ratings Covary with Spectral Power EEG Characteristics? Exploratory Analysis

Abstract

Introduction

Mood is a persistent affective state of low or moderate arousal that is not induced or triggered by a specific stimulus or event. Because of its stimulus independence, the neural correlates of mood are studied using the resting-state paradigm. In the following research we have focused on resting state (RS) EEG. There are two main ways of investigating this topic: linking subjective reports to brain activity [1], or investigating brain activity by inferring subjective experience from the tasks chosen for the experiment [2]. Some researchers [1] concluded that spectral power is an important indicator of arousal independent of mood valence, but others [2] described methods to classify the valence of felt emotions based on gamma activity. 

To improve on previous findings, we used a mood questionnaire to assess the valence of the current mood. We were therefore interested in how spectral power EEG characteristics covaried with participants' subjectively reported valence of mood.

Method

Seventy-two psychology students (11 males, 61 females) aged 18-25 years (mean age = 19) were recruited for this study. To track differences in mood during the experiment, RS EEG was measured at three time points: before the task (RS1), after the task (RS2), and after guided relaxation (RS3). Between RS1 and RS2, participants completed tasks designed to investigate the influence of cognitive control on emotional regulation. This task was not related to the present research and will not be discussed further. To assess mood, participants completed a 12-item Scale of Positive and Negative Experiences (SPANE) after each RS measurement.

Results and Further Research

First, we analysed the brain and subjective data separately. Initial results showed lower spectral power at all frequencies in the frontal lobe and greater power in alpha activity at RS1 than at subsequent time points. Subjects reported more positive than negative subjective mood states at RS1 and after guided relaxation (RS3). After the task (RS2), however, subjects reported more negative than positive mood states. The next step in the analysis will be to correlate the two sets of data.

As the SPANE questionnaire only assesses the valence of mood numerically, we should include more detailed first-person data on the subjective experience of mood in the future research. This could be done with phenomenological interviews after training subjects in phenomenological introspection.

References

[1] M. Wyczesany, J. Kaiser and A. M. Coenen, “Subjective mood estimation co-varies with spectral power EEG characteristics”, Acta Neurobiologiae Experimentalis, vol. 68, no. 2, pp. 180-92, 2008.

[2] T. M. Li, H. C. Chao, and J. Zhang, “Emotion classification based on Brain Wave: A survey,” Human-centric Computing and Information Sciences, vol. 9, no. 1, 2019.