Measuring early-stage attentional bias towards food images using saccade trajectory deviations

被引:0
|
作者
Qin Chen
Shisang Peng
Changlin Luo
Xiangling Zhuang
Guojie Ma
机构
[1] Shaanxi Normal University,Shaanxi Key Laboratory of Behavior and Cognitive Neuroscience, School of Psychology
[2] Chinese Academy of Sciences (CAS),Institute of Psychology
来源
Current Psychology | 2023年 / 42卷
关键词
Restrained eaters; Saccade curvature; Attentional bias; Goal conflict;
D O I
暂无
中图分类号
学科分类号
摘要
Food-related attentional bias has been studied for many years, yet the time course of attentional bias is not well characterized. Probe detection and Stroop paradigms are commonly utilized to examine food-related attentional bias, however, these methods are relatively rough in reflecting attentional processing. Thus, we used a modified food-house task combined with eye-tracking to investigate restrained and unrestrained eaters’ food-related attentional bias in different time courses. Saccade trajectory deviations and fixation durations were collected as eye movement measures to examine unconscious detection bias in the early stage of attentional processing and conscious maintenance bias in the later stage. An approach-avoidance conflict towards low-calorie food cues was found in restrained eaters, showing that food-related attentional bias changes with the different time courses. The saccade curvature demonstrated an early-stage attentional bias towards low-calorie foods in restrained eaters, whereas fixation measurements suggested a later-stage attentional avoidance of low-calorie foods in restrained eaters. The processing accumulation of food cues in human consciousness can probably explain the results. With the increase of the priming effect of high-calorie foods, attentional bias towards low-calorie foods disappears. In this study, saccade curvature was confirmed to be useful for directly revealing early-stage unconscious food-related attentional processing, and the role of time courses in attention allocation was also demonstrated.
引用
收藏
页码:29838 / 29850
页数:12
相关论文
共 28 条
  • [1] Measuring early-stage attentional bias towards food images using saccade trajectory deviations
    Chen, Qin
    Peng, Shisang
    Luo, Changlin
    Zhuang, Xiangling
    Ma, Guojie
    CURRENT PSYCHOLOGY, 2023, 42 (34) : 29838 - 29850
  • [2] Saccade trajectory deviations and inhibition-of-return: Measuring the amount of attentional processing
    Theeuwes, Jan
    Van der Stigchel, Stefan
    VISION RESEARCH, 2009, 49 (10) : 1307 - 1315
  • [3] Towards visualising early-stage osteonecrosis using intraoperative imaging modalities
    Liu, Mingxu
    Martin-Gomez, Alejandro
    Oni, Julius K.
    Mears, Simon C.
    Armand, Mehran
    COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION, 2023, 11 (04): : 1234 - 1242
  • [4] The feasibility of measuring fatigability in early-stage Parkinson's disease using functional MRI
    Xing, Y.
    Bajaj, N.
    Schwarz, S. T.
    Auer, D. P.
    MOVEMENT DISORDERS, 2016, 31 : S429 - S429
  • [5] Early-stage atherosclerosis detection using deep learning over carotid ultrasound images
    Menchon-Lara, Rosa-Maria
    Sancho-Gomez, Jose-Luis
    Bueno-Crespo, Andres
    APPLIED SOFT COMPUTING, 2016, 49 : 616 - 628
  • [6] Measuring attentional bias to food cues in young children using a visual search task: An eye-tracking study
    Brand, John
    Masterson, Travis D.
    Emond, Jennifer A.
    Lansigan, Reina
    Gilbert-Diamond, Diane
    APPETITE, 2020, 148
  • [7] Robust Bayesian Analysis of Early-Stage Parkinson's Disease Progression Using DaTscan Images
    Zhou, Yuan
    Tinaz, Sule
    Tagare, Hemant D.
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2021, 40 (02) : 549 - 561
  • [8] Early-Stage Cervical Cancerous Cell Detection from Cervix Images Using YOLOv5
    Ontor, Md Zahid Hasan
    Ali, Md Mamun
    Ahmed, Kawsar
    Bui, Francis M.
    Al-Zahrani, Fahad Ahmed
    Mahmud, S. M. Hasan
    Azam, Sami
    CMC-COMPUTERS MATERIALS & CONTINUA, 2023, 74 (02): : 3727 - 3741
  • [9] A novel machine learning based technique for classification of early-stage Alzheimer's disease using brain images
    Hazarika, Ruhul Amin
    Kandar, Debdatta
    Maji, Arnab Kumar
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 83 (8) : 24277 - 24299
  • [10] A novel machine learning based technique for classification of early-stage Alzheimer’s disease using brain images
    Ruhul Amin Hazarika
    Debdatta Kandar
    Arnab Kumar Maji
    Multimedia Tools and Applications, 2024, 83 : 24277 - 24299