EEG synchronization signatures for decoding attentional states during continuous force control

Results revealed that the mind-wandering state was characterized by increased alpha power (8-10 Hz) over frontal-posterior regions and reduced occurrence of high alpha-theta harmonic ratios. It also exhibited increased functional connectivity within sensorimotor networks and decreased mutual information between frontal EEG activity and force errors. Support vector machine classifiers for the binary attentional-state classification, utilizing combined spectral power and synchronization features, achieved 75.53% within-participant and 71.57% cross-participant accuracy, outperforming single-feature models. These findings highlight EEG synchronization signatures of mind wandering and demonstrate their feasibility for decoding attentional states during the force control task. This work may provide a foundation for future exploration of haptic-based neurofeedback systems, which could potentially complement existing visual and auditory modalities in applications such as neurocognitive rehabilitation or skilled motor training.