Posterior Cortex Isolation Enhances Detection of Alpha Desynchronization During Sustained Attention

St. Clair, N; Mahajan, S; Leung, C; Srinivas, C; Oushana, L; Dewan, N; Zhou, F · 2025 · Crossref

DOI: 10.1101/2025.11.17.688558

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Summary

This study investigates whether isolating posterior cortical regions enhances the detection of alpha-band desynchronization, a neural marker associated with mental fatigue and sustained attention. While alpha oscillations (8–12 Hz) are established indicators of cortical engagement, their specific dynamics during sustained attention remain abstract. The authors hypothesized that focusing on posterior cortex activity would provide greater resolution and reproducibility in detecting alpha power decreases over time, compared to whole-brain averaging. The researchers analyzed electroencephalography (EEG) data from 109 healthy adult participants sourced from the open-source PhysioNet EEG Motor Movement/Imagery Dataset (EEGMMIDB). The study utilized a within-subjects design, analyzing one-minute eyes-closed resting-state recordings to establish a stable baseline with minimal motor or cognitive confounds. Data processing was conducted using the Brainwave EEG OpenLab framework. Raw signals were band-pass filtered (0.5–30 Hz), notch-filtered at 60 Hz, and re-referenced to the common average. The recordings were segmented into 2-second epochs, and power spectral density was computed using Welch’s method. Alpha-band power was extracted and averaged across posterior electrodes (P–, PO–, O–, Iz–). To assess temporal changes, the first ten epochs were defined as the "early" block and the final ten as the "late" block. Paired-sample t-tests compared log-transformed alpha power between these blocks. The results demonstrated a significant decrease in alpha power from the early to late blocks, indicating alpha desynchronization. When analyzing the whole brain, the mean decrease was −0.052 log₁₀ units (p = 0.0334). However, isolating posterior electrodes yielded a stronger effect size and higher statistical significance, with a mean decrease of −0.076 ± 0.019 log₁₀ units (p = 0.0001). Topographic maps confirmed that this desynchronization was localized primarily to posterior regions. Individual subject trajectories showed consistent negative shifts in posterior alpha power over time. The authors note that this desynchronization reflects a shift from a resting, synchronized state to one of increased cortical activation and mental fatigue. The study concludes that isolating the posterior cortex significantly enhances the sensitivity and resolution of detecting alpha desynchronization associated with sustained attention. These findings support the role of thalamo-posterior cortical loops in generating alpha waves and validate the use of open-source datasets and reproducible pipelines for fatigue research. The authors acknowledge limitations, including the lack of subjective fatigue measures and the potential influence of spontaneous visual imagery during eyes-closed rest. Future work should apply this methodology to task-based datasets, such as the Psychomotor Vigilance Task, to further validate alpha desynchronization as a robust marker of mental fatigue.

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• neuro workload indices

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• Empirical Findings: physiological data