BACKGROUND: Anxiety disorders are highly prevalent yet lack objective biomarkers. Whereas threat-related attentional biases are well documented, less is known about broader eye movement alterations that may characterise anxiety. AIMS: To characterise multi-paradigm eye movement profiles in anxiety disorders and evaluate their potential as behavioural markers for disorder differentiation. METHOD: Eye movements were recorded in 91 patients with anxiety disorders, 118 with depressive disorders and 98 healthy controls during free viewing of neutral-stimuli, smooth-pursuit and fixation-stability tasks. Principal component analysis was applied to derive latent eye movement dimensions, which were then tested for group differences, associations with symptom severity and classification performance. RESULTS: Compared with both patients with depression and healthy controls, patients with anxiety disorders exhibited hyper-scanning during free viewing, characterised by increased saccade frequency and path length, and hyper-pursuit during smooth pursuit, reflected in increased velocity gain, fewer intrusive saccades and more catch-up saccades. Principal component analysis identified six latent components, among which active visual exploration, pupillary arousal and smooth-pursuit control demonstrated robust group differences. Machine learning models trained on 6 components yielded areas under the receiver operating characteristic curve of 0.82 for anxiety versus healthy controls, 0.83 for depression versus healthy controls and 0.61 for anxiety versus depression. CONCLUSIONS: Hyper-scanning and hyper-pursuit emerge as defining eye movement signatures of anxiety, linking core mechanisms of vigilance and prediction with measurable behavioural markers. These insights position eye-tracking as a promising behavioural modality for mechanism-informed differentiation across affective disorders.
Zhang et al. (Mon,) studied this question.