Exploring Alpha and Theta Activity in Depression: A Combined Surface EEG and LORETA Study of Cortical and Subcortical Networks
DOI:
https://doi.org/10.15540/nr.12.2.89Keywords:
depression, qEEG, alpha and theta oscillations, hippocampus-amygdala network, frontotemporal areaAbstract
Introduction. Depression is a common mental health condition characterized by disrupted neural activity in cortical and subcortical networks involved in emotion and memory. While alpha and theta oscillations have been linked to depression, their specific roles in symptom domains remain unclear. This study examines these relationships using quantitative EEG (qEEG) and low-resolution electromagnetic tomography analysis (LORETA). Methods. Fifty-eight adults with depression underwent resting-state, eyes-closed qEEG. Absolute power and coherence of alpha (8–12 Hz) and theta (4–8 Hz) bands were analyzed across 19 scalp electrodes and hippocampal and amygdala regions using LORETA. Depressive symptom severity was assessed using the Beck Depression Inventory-II (BDI-II). Statistical analyses evaluated associations between EEG parameters and symptom scores. Results. Alpha coherence between the left hippocampus and amygdala negatively correlated with somatic symptoms (r = −0.298, p = .027), explaining 26% of variance in total BDI-II scores. Increased theta coherence in the right frontotemporal network was associated with reductions in affective and somatic symptoms. Conclusions. The findings identify neural oscillatory patterns within hippocampal-amygdala and frontotemporal networks as potential biomarkers for depressive symptoms, providing insights into novel therapeutic targets.
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