https://doi.org/10.1140/epjs/s11734-024-01348-3
Regular Article
Recurrency time entropy of brain wave rhythms as an indicator of performance on visual search tasks in schoolchildren
Baltic Center for Neurotechnology and Artificial Intelligence, Immanuel Kant Baltic Federal University, 14 Alexander Nevsky Street, 236016, Kaliningrad, Russia
Received:
12
August
2024
Accepted:
16
September
2024
Published online:
2
October
2024
This study demonstrates that the entropy of brain rhythms in the alpha and beta ranges serves as a significant indicator of the efficiency of visual information processing. We employed the method of recurrent quantitative analysis to estimate the recurrency tIme entropy across various EEG frequency ranges and conducted a correlation analysis to identify significant relationships between entropy and reaction time. EEG signals were collected from children aged 8–11 years while they performed visual search tasks. Our results indicate that higher entropy is associated with more efficient visual information processing.
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