Panic disorder is a common acute anxiety disorder characterized by sudden panic attacks that severely impact patients’daily lives. In recent years, electroencephalogram (EEG) and event-related potentials (ERP) techniques have played a crucial role in elucidating the neural mechanisms underlying this condition. Resting-state EEG studies have demonstrated abnormalities such as frontal alpha asymmetry, altered EEG microstates and impaired functional brain network connectivity in patients with panic disorder. Meanwhile, ERP investigations using paradigms such as Oddball, Go/NoGo, Stroop and Flanker have revealed deficits in cognitive functions including attentional allocation, inhibitory control and error monitoring. However, existing research is limited by methodological heterogeneity, small sample sizes and a lack of longitudinal designs. Future studies should focus on establishing standardized protocols, promoting multi-center collaborations with larger samples and incorporating advanced techniques such as high-density EEG, source localization, machine learning and longitudinal studies. This integrated approach is critical to identifying reliable neuroelectrophysiological biomarkers for the early diagnosis and personalized treatment of panic disorder.