Resting-state EEG alterations and cognitive impairment in atrial fibrillation: insights into neural biomarkers and functional connectivity

Min-Qiang Bao; Li Cao; Yi-Nong Chen; Guo-Liang Gao; Zhi-Yong Lu; Jie Wang; Shuang-Shuang Chen; Xiao-Ning Sheng; Yu Wang

doi:10.3389/fneur.2025.1583715

Resting-state EEG alterations and cognitive impairment in atrial fibrillation: insights into neural biomarkers and functional connectivity

Front Neurol. 2025 Jun 19:16:1583715. doi: 10.3389/fneur.2025.1583715. eCollection 2025.

Authors

Min-Qiang Bao^#^{1

2}, Li Cao^#³, Yi-Nong Chen¹, Guo-Liang Gao⁴, Zhi-Yong Lu⁵, Jie Wang¹, Shuang-Shuang Chen¹, Xiao-Ning Sheng¹, Yu Wang²

Affiliations

¹ Department of Neurology, The Affiliated Xuancheng Hospital of Wannan Medical College, Xuancheng, China.
² Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
³ Department of Electrocardiogram, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
⁴ Department of Electrocardiogram, The Affiliated Xuancheng Hospital of Wannan Medical College, Xuancheng, China.
⁵ Department of Cardiovascular Medicine, The Affiliated Xuancheng Hospital of Wannan Medical College, Xuancheng, China.

^# Contributed equally.

Abstract

Aims: Atrial fibrillation (AF) is associated with cognitive decline, but the role of electroencephalography (EEG) in assessing cognitive dysfunction in AF patients is underexplored.

Objective: This study investigated the relationship between resting-state EEG patterns and cognitive impairment in AF patients.

Methods: We recruited 120 participants from the Affiliated Xuancheng Hospital, China (January 2023 to January 2024), categorizing them into healthy controls and AF patients. Resting-state EEG metrics, including power spectral density (PSD), functional connectivity (FC), cross-frequency coupling (CFC), and sample entropy (EnSA), were analyzed alongside the Montreal Cognitive Assessment (MoCA) scores. Mediation analysis explored EEG's role in the AF-cognitive decline relationship.

Results: AF patients had significantly lower MoCA scores. PSD analysis showed increased δ and θ and decreased α and β activity. FC was reduced in the α and β bands but increased in localized θ and γ bands. CFC analysis revealed elevated θ-β and θ-γ phase-amplitude coupling (PAC), reduced β-γ PAC, and lower EnSA. EEG metrics were significantly correlated with MoCA scores, with θ-β PAC mediating cognitive decline.

Conclusion: AF patients exhibit distinctive EEG changes, with θ-β PAC mediating cognitive impairment, suggesting the potential of resting-state EEG for cognitive assessment in AF patients.

Keywords: atrial fibrillation; cognitive dysfunction; cross-frequency coupling; functional connectivity; power spectral density; resting-state EEG; sample entropy.