Resolution-aware spectral parameterization reveals robust context-dependent aperiodic EEG dynamics during real-world table tennis
Mobile EEG can link neuroimaging to natural behavior, but effects recorded during movement, and sport in particular, are difficult to interpret because neural activity overlaps with signals from movement, muscle activity, and cable movement artifacts. We analyzed the OpenNeuro Real World Table Tennis dataset to test whether peri-hit spectral activity could be analyzed and how it differed between…
A new study utilizing mobile EEG technology has revealed context-dependent aperiodic dynamics in EEG signals during real-world table tennis. Researchers analyzed data from 25 participants who underwent EEG, noise-layer, EMG, and motion recordings, then examined peri-hit spectral activity during pre-hit, impact, and post-hit windows.
By removing trial-level root mean square artifacts from noise-layer, EMG, and miscellaneous channels, the researchers were able to model spectral power as an aperiodic component plus periodic peaks. They found that residualized alpha and beta power were lower for ball-machine play compared to human-opponent play, particularly in the pre-hit posterior alpha region.
A notable context difference emerged, with ball-machine play showing a higher aperiodic exponent over posterior and parietal sensors, indicating a steeper broadband spectral slope.
Further analysis confirmed that posterior post-hit EEG means differed between the two conditions, with 0.451 for human-opponent play and 0.606 for ball-machine play. Despite using various specifications, a focal parietal effect remained consistent. The findings support the use of artifact-informed, resolution-aware spectral analysis as a reliable method for detecting spectral differences between naturalistic visuomotor contexts, suggesting that EEG may offer valuable insights into the cognitive and physiological processes activated by different practice environments.
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