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Speed-Sensitive EEG Biomarkers in a Motion Tracking Paradigm: Implications for Dynamic Visual Acuity Research
Zejin Li1, Guanghua Xu1,2,3,4, Hui Li1
1School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710061, China.
Brain Sciences
|February 27, 2026
Summary
Hjorth activity, an EEG measure, shows strong correlation with dynamic visual acuity (DVA) speed. This finding supports its potential as a reliable biomarker for evaluating dynamic vision objectively.
Area of Science:
- Neuroscience
- Ophthalmology
- Biomedical Engineering
Background:
- Dynamic visual acuity (DVA) assessment is crucial, yet often relies on static visual acuity (SVA) as a proxy.
- Distinct neural pathways underlie DVA, necessitating specific biomarkers for accurate evaluation.
- Current clinical practices often overlook the functional differences between static and dynamic vision.
Purpose of the Study:
- To identify electroencephalography (EEG) biomarkers sensitive to varying speeds of dynamic visual stimuli.
- To evaluate the correlation between specific EEG features and horizontal motion speeds (4°/s to 30°/s).
- To establish a foundation for objective neurophysiological assessment of dynamic vision.
Main Methods:
- Participants viewed a high-contrast checkerboard moving horizontally at controlled speeds.
- Six EEG features (ERPs, TRCA, Hjorth activity, mean curve length, Tsallis entropy) were extracted from occipito-parietal channels.
- Speed sensitivity of EEG features was analyzed using univariate correlation and Lasso regression.
Main Results:
- Hjorth activity and Tsallis entropy demonstrated consistent monotonic trends with increasing speed.
- Hjorth activity showed the strongest univariate correlation with speed (r = 0.88, p < 0.05).
- A Lasso regression model predicted actual speed with r = 0.588, retaining TRCA-weighted features.
Conclusions:
- Hjorth activity is a highly sensitive, neuroanatomically plausible, and simple EEG biomarker candidate for DVA.
- The study supports Hjorth activity for developing objective EEG-based DVA assessment tools.
- Findings pave the way for improved neurophysiological evaluation of dynamic visual performance.
