This study aims to explore the temporal dynamics of brain networks involved in self-generated affective states, specifically focusing on modulating these states in both positive and negative valences. The overarching goal is to contribute to a deeper understanding of the neurodynamic patterns associated with affective regulation, potentially informing the development of biomarkers for therapeutic interventions in mood and anxiety disorders.
Utilizing EEG microstate analysis during self-generated affective states, we investigated the temporal dynamics of five distinct microstates across different conditions, including baseline resting state and self-generated states of positive valence (e.g., awe, contentment) and negative valence (e.g., anger, fear).
The study revealed noteworthy modulations in microstate dynamics during affective states. Additionally, valence-specific mechanisms of spontaneous affective regulation were identified. Negative valence affective states were characterized by the heightened presence of attention-associated microstates and reduced occurrence of salience-related microstates during negative valence states. In contrast, positive valence affective states manifested a prevalence of microstates related to visual/autobiographical memory and a reduced presence of auditory/language-associated microstates compared to both baseline and negative valence states.
This study contributes to the field by employing EEG microstate analysis to discern the temporal dynamics of brain networks involved in self-generated affective states. Insights from this research carry significant implications for understanding neurodynamic patterns in affective regulation. The identification of valence-specific modulations and mechanisms has potential applications in developing biomarkers for mood and anxiety disorders, offering novel avenues for therapeutic interventions.