To establish an automated preprocessing pipeline for EEG data that enhances patient-friendly protocols and defines the minimum data needed for stable quantitative EEG features in Rett syndrome (RTT).
Key Findings:
The correction-based pipeline retained 95.0% of data compared to 28.4% with the rejection-based workflow (p < 0.001), indicating a significant improvement in data retention.
Stable power estimates were achieved after 19–34 epochs (76–136 s), with implications for clinical practice.
No significant difference in minimum stabilization threshold was found between RTT and typically developing (TD) controls, although RTT exhibited higher intrinsic signal instability, which may impact clinical interpretations.
Interpretation:
The proposed pipeline allows for approximately 3 minutes of raw resting-state EEG to yield stable and clinically meaningful spectral features in children with RTT.
Limitations:
The study primarily focuses on a specific age range (1-18 years) and may not generalize to all age groups, potentially limiting applicability.
The findings are based on a multisite study, which may introduce variability in data collection and processing, affecting the robustness of the conclusions.
Conclusion:
The findings support shorter EEG acquisition times and provide a reproducible framework for data sufficiency in multisite neurodevelopmental studies, paving the way for future research in RTT.
