Hyper-scanning and hyper-pursuit define eye movement biomarkers of anxiety disorders

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.

Authors

Institutions

Publication Details

Journal
The British Journal of Psychiatry
Published
2026-04-27
DOI
https://doi.org/10.1192/bjp.2026.10626
Citations
1
Primary Topic
Neural and Behavioral Psychology Studies
Type
article
Field-Weighted Citation Impact
21.28

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hyper-scanning and hyper-pursuit define eye movement biomarkers of anxiety disorders

D Zhang, HaiChun Liu, Y C Li, HuiRu Cui et al.
1 citations
The British Journal of Psychiatry
Neural and Behavioral Psychology Studies
21.28
article

Hyper-scanning and hyper-pursuit define eye movement biomarkers of anxiety disorders

D Zhang, HaiChun Liu, Y C Li, HuiRu Cui, Yangyang Xu, Wensi Zheng, Yawen Hong, Tianhong Zhang, Yi-Xiang Wang, JinYang Zhao, Yanyan Wei, Lihua Xu, Xu Liu
article en
1 citations

Abstract

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.

The British Journal of Psychiatry
Shanghai Jiao Tong University (CN), Shanghai Mental Health Center (CN), Children's Hospital of Fudan University (CN), Tianjin haihe hospital (CN)
Shanghai Municipal Health Commission
Quality Education
Openalex Percentile: Top 1%
Neural and Behavioral Psychology Studies
21.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.