Speed-Sensitive EEG Biomarkers in a Motion Tracking Paradigm: Implications for Dynamic Visual Acuity Research

<b>Background:</b> Dynamic visual acuity (DVA) is functionally distinct from static visual acuity (SVA), though SVA is often used clinically as a reference. <b>Methods:</b> To identify EEG biomarkers for DVA, we presented participants with a high-contrast checkerboard moving horizontally at speeds ranging from 4°/s to 30°/s, engaging motion-sensitive pathways while preserving spatial detail. Six EEG features-ERPs (N200 and P300), TRCA, Hjorth activity, mean curve length, and Tsallis entropy-were extracted from eight occipito-parietal channels and evaluated for speed sensitivity. <b>Results:</b> Hjorth activity and Tsallis entropy showed consistent monotonic trends with respect to speed. Hjorth activity exhibited the strongest univariate correlation (r = 0.88, <i>p</i> < 0.05). In a Lasso regression model using all speed-sensitive features, the predicted speed correlated with actual speed at r = 0.588, with TRCA-weighted features retained for their multivariate contribution. Notably, Hjorth activity peaked at PO7/PO8 (3.558 and 1.478 µV² at 30°/s), aligning with V5/MT+ activation. <b>Conclusion:</b> Given its high sensitivity, neuroanatomical plausibility, and simplicity, Hjorth activity is recommended as a primary candidate for EEG-based DVA biomarker development. This study provides a foundation for objective neurophysiological evaluation of dynamic vision.