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

## TL;DR

This study identifies EEG biomarkers that change with motion speed, offering a new way to assess dynamic visual acuity using brain activity.

## Contribution

The study introduces Hjorth activity as a novel speed-sensitive EEG biomarker for dynamic visual acuity.

## Key findings

- Hjorth activity and Tsallis entropy showed consistent monotonic trends with motion speed.
- Hjorth activity had the strongest univariate correlation with speed (r = 0.88).
- TRCA-weighted features contributed significantly in a multivariate Lasso regression model.

## Abstract

Background: Dynamic visual acuity (DVA) is functionally distinct from static visual acuity (SVA), though SVA is often used clinically as a reference. Methods: 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. Results: Hjorth activity and Tsallis entropy showed consistent monotonic trends with respect to speed. Hjorth activity exhibited the strongest univariate correlation (r = 0.88, p < 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. Conclusion: 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.