Eye tracking provides insights into social processing deficits in autism spectrum disorder (ASD), especially in conjunction with dynamic, naturalistic free-viewing stimuli. However, the question remains whether gaze characteristics, such as preference for specific facial features, can be considered a stable individual trait, particularly in those with ASD. If so, how much data are needed for consistent estimations? To address these questions, we assessed the stability and robustness of gaze preference for facial features as incremental amounts of movie data were introduced for analysis. We trained an artificial neural network to create an object-based segmentation of naturalistic movie clips (14 s each, 7410 frames total). Thirty-three high-functioning individuals with ASD and 36 age- and IQ-equated typically developing individuals (age range: 12–30 years) viewed 22 Hollywood movie clips, each depicting a social interaction. As we evaluated combinations of one, three, five, eight, and 11 movie clips, gaze dwell times on core facial features became increasingly stable at within-subject, within-group, and between-group levels. Using a number of movie clips deemed sufficient by our analysis, we found that individuals with ASD displayed significantly less face-centered gaze (centralized on the nose; p < 0.001) but did not significantly differ from typically developing participants in eye or mouth looking times. Our findings validate gaze preference for specific facial features as a stable individual trait and highlight the possibility of misinterpretation with insufficient data. Additionally, we propose the use of a machine learning approach to stimuli segmentation to quickly and flexibly prepare dynamic stimuli for analysis.

中文翻译：

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将面部特征观看偏好视为自闭症谱系障碍中稳定的个体特征

眼动追踪可以深入了解自闭症谱系障碍 (ASD) 的社会处理缺陷，尤其是与动态、自然的自由观看刺激相结合。然而，问题仍然是注视特征（例如对特定面部特征的偏好）是否可以被视为稳定的个体特征，特别是对于自闭症谱系障碍患者。如果是这样，需要多少数据才能进行一致的估计？为了解决这些问题，随着引入增量电影数据进行分析，我们评估了面部特征的注视偏好的稳定性和鲁棒性。我们训练了一个人工神经网络来创建基于对象的自然电影剪辑分割（每个 14 秒，总共 7410 帧）。33 名患有 ASD 的高功能个体和 36 名年龄和智商相当的典型发育个体（年龄范围：12-30 岁）观看了 22 个好莱坞电影片段，每个片段都描述了一次社交互动。当我们评估 1 个、3 个、5 个、8 个和 11 个影片剪辑的组合时，核心面部特征上的注视停留时间在受试者内、组内和组间水平上变得越来越稳定。使用我们分析认为足够的一些电影剪辑，我们发现患有自闭症谱系障碍的人表现出明显较少的以面部为中心的凝视（集中在鼻子上；集中在鼻子上；p  < 0.001），但在眼睛或嘴巴的注视时间方面与典型发育参与者没有显着差异。我们的研究结果证实了对特定面部特征的注视偏好是一种稳定的个体特征，并强调了数据不足时产生误解的可能性。此外，我们建议使用机器学习方法进行刺激分割，以快速灵活地准备动态刺激进行分析。