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ORIGINAL RESEARCH article

Front. Neurosci.
Sec. Translational Neuroscience
Volume 18 - 2024 | doi: 10.3389/fnins.2024.1482849
This article is part of the Research Topic Mechanism of Neural Oscillations and Their Relationship with Multiple Cognitive Functions and Mental Disorders View all 10 articles

Eye Movement Characteristics of Emotional Face Recognizing Task (EFRT) in Patients with Mild to Moderate Depression

Provisionally accepted
Qian Yang Qian Yang 1Qiuli Yang Qiuli Yang 1*Yanan Zhao Yanan Zhao 1*Hao Wang Hao Wang 1*Yanyan Fu Yanyan Fu 1*Han Zhang Han Zhang 2*Xinyi Xie Xinyi Xie 1*Yanran Sun Yanran Sun 3*Jian Du Jian Du 1*
  • 1 China Academy of Chinese Medical Sciences, Beijing, China
  • 2 Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
  • 3 Jiangxi University of Chinese Medicine, Nanchang, China

The final, formatted version of the article will be published soon.

    Depression is a complex affective disorder characterized by high prevalence and severe impact, commonly presenting with cognitive impairment. The objective diagnosis of depression lacks precise standards. This study investigates eye movement characteristics during emotional face recognition task (EFRT) in depressive patients to provide empirical support for objective diagnosis. Methods: We recruited 43 patients with depression (Depressive patients, DP) from a psychiatric hospital and 44 healthy participants (Healthy Control, HC) online. All participants completed an EFRT comprising 120 trials. Each trial presented a gray screen for 800ms followed by a stimulus image for judgment. Emotions were categorized as positive, neutral, or negative. Eye movement trajectories were recorded throughout the task. Latency of First Fixation (LFF), Latency of First Fixation for Eye AOI, and Latency of First Fixation for Mouth AOI were used as representative indicators of early attention, Proportion of Eye AOI, and Proportion of Mouth AOI as measures of intermediate attention, Accuracy (ACC) and Reaction Time (RT) as behavioral indicators of late-stage attention. In this study, these metrics were employed to explore the differences between patients with depression and healthy individuals.Results: Compared to healthy participants, individuals with depression exhibit longer first fixation latencies on the eyes and mouth during the early attention stage of emotional face recognition, indicating an avoidance tendency toward key facial recognition cues. In the mid-to-late attention stages, depressive individuals show an increased fixation ratio on the eyes and a decreased fixation ratio on the mouth, along with lower accuracy and longer response times. These findings suggest that, relative to healthy individuals, individuals with depression have deficits in facial recognition.This study identified distinct attention patterns and cognitive deficits in emotional face recognition among individuals with depression compared to healthy individuals, providing an attention-based approach for exploring potential clinical diagnostic markers for depression.

    Keywords: EYE MOVEMENT, Depression, AOI, Emotional facial expression recognition, cognitive deficit

    Received: 18 Aug 2024; Accepted: 28 Oct 2024.

    Copyright: © 2024 Yang, Yang, Zhao, Wang, Fu, Zhang, Xie, Sun and Du. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Qiuli Yang, China Academy of Chinese Medical Sciences, Beijing, China
    Yanan Zhao, China Academy of Chinese Medical Sciences, Beijing, China
    Hao Wang, China Academy of Chinese Medical Sciences, Beijing, China
    Yanyan Fu, China Academy of Chinese Medical Sciences, Beijing, China
    Han Zhang, Shandong University of Traditional Chinese Medicine, Jinan, 250355, Shandong Province, China
    Xinyi Xie, China Academy of Chinese Medical Sciences, Beijing, China
    Yanran Sun, Jiangxi University of Chinese Medicine, Nanchang, China
    Jian Du, China Academy of Chinese Medical Sciences, Beijing, China

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