Sabaghypour S, Navi FFT, Basiri N, Shakibaei F, Zirak N. Differential roles of brain oscillations in numerical processing: evidence from resting-state EEG and mental number line.
Front Hum Neurosci 2024;
18:1357900. [PMID:
38974482 PMCID:
PMC11224460 DOI:
10.3389/fnhum.2024.1357900]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 06/11/2024] [Indexed: 07/09/2024] Open
Abstract
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.
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