Resting-State EEG Alterations of Practice-Related Spectral Activity and Connectivity Patterns in Depression

Abstract

Background: Depression presents with altered energy regulation and neural plasticity. Previous electroencephalography (EEG) studies showed that practice in learning tasks increases power in beta range (13-30 Hz) in healthy subjects but not in those with impaired plasticity. Here, we ascertain whether depression presents with alterations of spectral activity and connectivity before and after a learning task.

Methods: We used publicly available resting-state EEG recordings (64 electrodes) from 122 subjects. Based on Beck Depression Inventory (BDI) scores, they were assigned to either a high BDI (hBDI, BDI > 13, N = 46) or a control (CTL, BDI < 7, N = 75) group. We analyzed spectral activity, theta-beta, and theta-gamma phase-amplitude coupling (PAC) of EEG recorded at rest before and after a learning task.

Results: At baseline, compared to CTL, hBDI exhibited greater power in beta over fronto-parietal regions and in gamma over the right parieto-occipital area. At post task, power increased in all frequency ranges only in CTL. Theta-beta and theta-gamma PAC were greater in hBDI at baseline but not after the task.

Conclusions: The lack of substantial post-task growth of beta power in depressed subjects likely represents power saturation due to greater baseline values. We speculate that inhibitory/excitatory imbalance, altered plasticity mechanisms, and energy dysregulation present in depression may contribute to this phenomenon.

Keywords: EEG oscillations; beta frequency; depression; energy; fractal dynamics; gamma frequency; phase–amplitude coupling; plasticity; resting-state EEG.

Figure 1

Scalp topographies displaying the t-values for group comparisons (hBDI vs. CLT) before the task, at baseline for the original, oscillatory, and fractal components for each frequency band. White dots indicate electrodes with significant group differences after cluster correction for multiple comparisons.

Figure 2

EEG Power-Law Exponent (PLE) for the hBDI group (orange) and CTL group (green) before (A) and after the task (B), with individual data points, box plots, and density plots to visualize data distribution. Topographic plots depict the t-values of cluster-based permutation statistics (right). Electrodes within significant clusters are represented as white dots.

Figure 3

Group differences (hBDI vs. CTL) for theta–beta (A) and theta–gamma (B) PAC. Topographic plots depict the results of cluster-based permutation t-statistics. PRE, in the top line, represents the group comparison at baseline, before task performance. POST (bottom line) refers to group comparison after the task execution. White dots represent electrodes within significant clusters.

Figure 4

Scalp topographical t-maps of group comparisons (hBDI vs. CLT) in the post-task resting-state EEG for the original, oscillatory, and fractal components. White dots indicate electrodes with significant group differences after cluster correction for multiple comparisons.

Figure 5

Scalp topographical t-values maps for post-pre task comparisons (post-task vs. pre-task EEG) in the CTL (A) and hBDI (B) groups. Results for the original, oscillatory, and fractal components are presented for each frequency band. White dots indicate electrodes with significant group differences after cluster correction for multiple comparisons.

Figure 6

Post-task/pre-task differences for theta–beta (A) and theta–gamma (B) PAC in the CTL (first line) and hBDI (bottom line) groups. Topographic plots depict the results of cluster-based permutation t-statistics. White dots represent electrodes within significant clusters.