Age-Related Changes in Action Observation EEG Response and Its Effect on BCI Performance
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| Názov: | Age-Related Changes in Action Observation EEG Response and Its Effect on BCI Performance |
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| Autori: | Fukang Zeng, Xingyu Wen, Hongmei Tang, Guiyu Hu, Wensheng Hou, Xin Zhang |
| Zdroj: | IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 33, Pp 1805-1816 (2025) |
| Informácie o vydavateľovi: | Institute of Electrical and Electronics Engineers (IEEE), 2025. |
| Rok vydania: | 2025 |
| Predmety: | brain computer interface (BCI), age, Medical technology, Therapeutics. Pharmacology, RM1-950, R855-855.5, electrocorticography (EEG), Action observation (AO), rehabilitation |
| Popis: | Action observation-based brain-computer interface (AO-BCI) can simultaneously elicit steady-state motion visual evoked potential in the occipital region and sensorimotor rhythm in the sensorimotor region, demonstrating substantial potential in neuro-rehabilitation applications. While current AO-BCI research primarily focuses on the younger population, this study conducted a comparative investigation of age-related differences in EEG response to the AO-BCI by enrolling 18 older and 18 younger subjects. We employed task discriminant component analysis (TDCA) to decode observed actions and performed comprehensive analyses of prefrontal EEG responses, i.e. approximate entropy (ApEn), sample entropy (SamEn), and rhythm power ratios (RPR), and the whole-brain functional network. Regression analyses were subsequently conducted to analyze the effects on the classification accuracy. Results revealed significantly diminished TDCA accuracy in older subjects (77.01% ± 14.67%) compared to younger subjects (87.22% ± 15.22%). Age-dependent EEG responses emerged across multiple dimensions: 1) Prefrontal ApEn, SamEn, and RPR exhibited distinct aging patterns; 2) Brain network analysis uncovered significant intergroup differences in α and β band connectivity strength; 3) θ band network topology demonstrated reduced prefrontal nodal degree along with enhanced global efficiency in older subjects. Regression analysis identified a robust inverse relationship between the β/θ RPR during stimulation and overall accuracy. And the β/θ RPR and the β band ApEn might be the main factor that causing individual differences in the identification accuracy in older and younger subjects, respectively. This study provides novel insights into age-related neuro-mechanisms in AO-BCI, establishing quantitative relationships between specific EEG features and BCI performance. These findings would offer guidelines for optimizing AO-BCI in rehabilitation. |
| Druh dokumentu: | Article |
| ISSN: | 1558-0210 1534-4320 |
| DOI: | 10.1109/tnsre.2025.3566371 |
| Prístupová URL adresa: | https://pubmed.ncbi.nlm.nih.gov/40315092 https://doaj.org/article/fb38fd5106984b8a9519268a67c76d23 |
| Rights: | CC BY |
| Prístupové číslo: | edsair.doi.dedup.....e57d6aefa644e44a640958d89cd0545c |
| Databáza: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstrakt: | Action observation-based brain-computer interface (AO-BCI) can simultaneously elicit steady-state motion visual evoked potential in the occipital region and sensorimotor rhythm in the sensorimotor region, demonstrating substantial potential in neuro-rehabilitation applications. While current AO-BCI research primarily focuses on the younger population, this study conducted a comparative investigation of age-related differences in EEG response to the AO-BCI by enrolling 18 older and 18 younger subjects. We employed task discriminant component analysis (TDCA) to decode observed actions and performed comprehensive analyses of prefrontal EEG responses, i.e. approximate entropy (ApEn), sample entropy (SamEn), and rhythm power ratios (RPR), and the whole-brain functional network. Regression analyses were subsequently conducted to analyze the effects on the classification accuracy. Results revealed significantly diminished TDCA accuracy in older subjects (77.01% ± 14.67%) compared to younger subjects (87.22% ± 15.22%). Age-dependent EEG responses emerged across multiple dimensions: 1) Prefrontal ApEn, SamEn, and RPR exhibited distinct aging patterns; 2) Brain network analysis uncovered significant intergroup differences in α and β band connectivity strength; 3) θ band network topology demonstrated reduced prefrontal nodal degree along with enhanced global efficiency in older subjects. Regression analysis identified a robust inverse relationship between the β/θ RPR during stimulation and overall accuracy. And the β/θ RPR and the β band ApEn might be the main factor that causing individual differences in the identification accuracy in older and younger subjects, respectively. This study provides novel insights into age-related neuro-mechanisms in AO-BCI, establishing quantitative relationships between specific EEG features and BCI performance. These findings would offer guidelines for optimizing AO-BCI in rehabilitation. |
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| ISSN: | 15580210 15344320 |
| DOI: | 10.1109/tnsre.2025.3566371 |