Task-Based EEG Neurofeedback Enhances Training Effects in Dynamic Visual Search.

Dynamic visual search is essential for efficient performance in high-demand perceptual and operational environments. However, effectively improving such a higher-order cognitive ability remains challenging. Although conventional training approaches based on repeated practice can enhance visual search performance, their effectiveness tends to reach a ceiling, thereby constraining further development. To address this limitation, the present study developed a task-based EEG neurofeedback (NF) paradigm by integrating parietal beta upregulation training into the moving object discrimination (MOD) paradigm, a dynamic visual search task. We then conducted well-designed training procedures with 88 healthy participants randomly assigned to the NF group (task-based NF training), the Sham group (sham-feedback training), and the Control group (no training). Results showed that (i) the NF group exhibited significantly greater increases in parietal beta power both within and across training sessions, compared to the Sham group; and (ii) the NF group achieved significantly greater reductions in response time (RT) during the MOD task compared to both the Sham and Control groups. The enhanced training effects likely resulted from the direct modulation of task-relevant neural activity and the promotion of sustained attentional engagement during task execution through parietal beta upregulation. Overall, these findings underscore the utility of task-based NF in facilitating more effective training in cognitively demanding contexts and provide a promising framework for developing high-efficiency, domain-specific training interventions. Nevertheless, the present findings should be interpreted with caution due to the absence of a conventional practice-based training comparison and limited participant diversity.