EEG synchronization signatures for decoding attentional states during continuous force control

Zheng, Yilei; Wang, Qiaoxiu; Tong, Qianqian; Tian, Bohao; Su, Peng; Xu, Yonghong; Wang, Dangxiao; Wang, Dangxiao · 2025 · DOAJ

DOI: 10.3389/fnins.2025.1654827

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Summary

This study investigates the neural signatures of mind wandering (MW) during continuous visuo-haptic force control, a task modality that remains underexplored compared to visual or auditory paradigms. While MW is known to impair performance in skilled activities like surgery or robotic manipulation, the specific EEG synchronization features associated with attentional lapses in haptic tasks are poorly understood. The authors aimed to identify whether cross-frequency coupling, functional connectivity, and neural-behavioral synchronization could serve as robust biomarkers for decoding attentional states, potentially enabling future haptic-based neurofeedback systems. The researchers employed a novel continuous force control task where nine healthy male participants tracked a dynamically varying target force using a haptic device while scalp EEG was recorded. Attentional states were labeled using the thought-probe method; participants rated their focus on a 0–100 scale at random intervals, allowing the classification of trials preceding probes as either on-task or mind-wandering. The analysis focused on three seconds of data preceding each probe. Feature extraction included spectral power, alpha-theta cross-frequency coupling ratios, functional connectivity measured via Phase Locking Value (PLV), and neural-behavioral synchronization quantified by mutual information between frontal EEG activity and force errors. Support vector machine classifiers were then trained to distinguish between attentional states using these features. Results indicated distinct synchronization signatures for mind wandering. The MW state was characterized by increased alpha power (8–10 Hz) over frontal-posterior regions and a reduced occurrence of high alpha-theta harmonic ratios, suggesting disrupted cross-frequency synchronization. Additionally, MW exhibited increased functional connectivity within sensorimotor networks and decreased mutual information between frontal EEG activity and force errors, indicating a decoupling of neural activity from behavioral output. When combined, spectral power and synchronization features achieved a classification accuracy of 75.53% within participants and 71.57% across participants, outperforming models relying on single feature types. These findings demonstrate that EEG synchronization metrics provide unique and complementary information for detecting attentional fluctuations during continuous motor tasks. By establishing reliable neural markers for mind wandering in a haptic context, this work addresses a critical gap in the literature and lays the groundwork for developing haptic neurofeedback systems. Such systems could complement existing visual and auditory approaches in applications ranging from neurocognitive rehabilitation to skilled motor training, offering a more ecologically valid method for monitoring and enhancing sustained attention.

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• mind wandering