Sabaghypour Saied, Navi Farhad Farkhondeh Tale, Basiri Nooshin, Shakibaei Fereshteh, Zirak Negin
Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran.
Safahan Institute of Higher Education, Isfahan, Iran.
Front Hum Neurosci. 2024 Jun 21;18:1357900. doi: 10.3389/fnhum.2024.1357900. eCollection 2024.
Recent works point to the importance of emotions in special-numerical associations. There remains a notable gap in understanding the electrophysiological underpinnings of such associations. Exploring resting-state (rs) EEG, particularly in frontal regions, could elucidate emotional aspects, while other EEG measures might offer insights into the cognitive dimensions correlating with behavioral performance. The present work investigated the relationship between rs-EEG measures (emotional and cognitive traits) and performance in the mental number line (MNL). EEG activity in theta (3-7 Hz), alpha (8-12 Hz, further subdivided into low-alpha and high-alpha), sensorimotor rhythm (SMR, 13-15 Hz), beta (16-25 Hz), and high-beta/gamma (28-40 Hz) bands was assessed. 76 university students participated in the study, undergoing EEG recordings at rest before engaging in a computerized number-to-position (CNP) task. Analysis revealed significant associations between frontal asymmetry, specific EEG frequencies, and MNL performance metrics (i.e., mean direction bias, mean absolute error, and mean reaction time). Notably, theta and beta asymmetries correlated with direction bias, while alpha peak frequency (APF) and beta activity related to absolute errors in numerical estimation. Moreover, the study identified significant correlations between relative amplitude indices (i.e., theta/beta ratio, theta/SMR ratio) and both absolute errors and reaction times (RTs). Our findings offer novel insights into the emotional and cognitive aspects of EEG patterns and their links to MNL performance.
近期的研究指出了情绪在特殊数字关联中的重要性。在理解此类关联的电生理基础方面，仍存在显著差距。探索静息态（rs）脑电图，尤其是额叶区域的脑电图，可能会阐明情绪方面的问题，而其他脑电图测量方法可能会提供与行为表现相关的认知维度的见解。本研究调查了rs-脑电图测量（情绪和认知特征）与心理数字线（MNL）表现之间的关系。评估了theta（3 - 7Hz）、alpha（8 - 12Hz，进一步细分为低alpha和高alpha）、感觉运动节律（SMR，13 - 15Hz）、beta（16 - 25Hz）和高beta/伽马（28 - 40Hz）频段的脑电图活动。76名大学生参与了该研究，在进行计算机化数字到位置（CNP）任务之前进行了静息状态下的脑电图记录。分析揭示了额叶不对称性、特定脑电图频率与MNL表现指标（即平均方向偏差、平均绝对误差和平均反应时间）之间的显著关联。值得注意的是，theta和beta不对称性与方向偏差相关，而alpha峰值频率（APF）和beta活动与数字估计中的绝对误差相关。此外，该研究还发现相对振幅指数（即theta/beta比率、theta/SMR比率）与绝对误差和反应时间（RTs）之间存在显著相关性。我们的研究结果为脑电图模式的情绪和认知方面及其与MNL表现的联系提供了新的见解。
