Xu Yuting, Yamashita Ayumu, Uno Kyuto, Kawashima Tomoya, Amano Kaoru
Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan.
Department of Psychological Science, College of Informatics and Human Communication, Kanazawa Institute of Technology, Kanazawa, Japan.
Psychophysiology. 2025 Mar;62(3):e70028. doi: 10.1111/psyp.70028.
Alpha oscillations are associated with various cognitive functions. However, the determinants of alpha power variation remain ambiguous, primarily due to its inconsistent associations with autonomic responses and subjective states under different experimental conditions. To thoroughly examine the correlations between alpha power variation and these factors, we implemented a range of experimental conditions, encompassing attentional and emotional tasks, as well as a resting-state. In addition to the electroencephalogram data, we gathered a suite of autonomic response measurements and subjective ratings. We employed multiple linear regression analysis, utilizing autonomic responses and subjective reports as predictors of alpha power. We also subtracted the aperiodic components for better estimation of the power of periodic alpha oscillations. Our results from two separately conducted experiments robustly demonstrated that the combined use of autonomic response measurements and subjective ratings effectively predicted the parietal-occipital periodic alpha power variation across a range of conditions. These predictions were supported by leave-one-participant-out cross-validation and cross-experiment validation, confirming that multiple linear relationships can be generalized to new participants. This study demonstrates the links of alpha power variations with autonomic responses and subjective states, suggesting that during investigations of the cognitive functions of alpha oscillations, it is important to consider the potential influences of autonomic responses and subjective states on alpha oscillations.
阿尔法振荡与多种认知功能相关。然而，阿尔法功率变化的决定因素仍不明确，主要是因为在不同实验条件下，它与自主反应和主观状态的关联并不一致。为了全面研究阿尔法功率变化与这些因素之间的相关性，我们实施了一系列实验条件，包括注意力和情绪任务，以及静息状态。除了脑电图数据，我们还收集了一系列自主反应测量数据和主观评分。我们采用多元线性回归分析，将自主反应和主观报告作为阿尔法功率的预测指标。我们还减去了非周期性成分，以便更好地估计周期性阿尔法振荡的功率。我们分别进行的两个实验结果有力地表明，自主反应测量和主观评分的联合使用能够有效预测一系列条件下顶枕部周期性阿尔法功率的变化。这些预测得到了留一参与者交叉验证和跨实验验证的支持，证实了多元线性关系可以推广到新的参与者。这项研究证明了阿尔法功率变化与自主反应和主观状态之间的联系，表明在研究阿尔法振荡的认知功能时，考虑自主反应和主观状态对阿尔法振荡的潜在影响非常重要。
