Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut.
JAMA Psychiatry. 2023 Oct 1;80(10):1026-1036. doi: 10.1001/jamapsychiatry.2023.2105.
Face processing is foundational to human social cognition, is central to the hallmark features of autism spectrum disorder (ASD), and shapes neural systems and social behavior. Highly efficient and specialized, the face processing system is sensitive to inversion, demonstrated by reduced accuracy in recognition and altered neural response to inverted faces. Understanding at which mechanistic level the autistic face processing system may be particularly different, as measured by the face inversion effect, will improve overall understanding of brain functioning in autism.
To synthesize data from the extant literature to determine differences of the face processing system in ASD, as measured by the face inversion effect, across multiple mechanistic levels.
Systematic searches were conducted in the MEDLINE, Embase, Web of Science, and PubMed databases from inception to August 11, 2022.
Original research that reported performance-based measures of face recognition to upright and inverted faces in ASD and neurotypical samples were included for quantitative synthesis. All studies were screened by at least 2 reviewers.
This systematic review and meta-analysis was conducted according to the 2020 Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Multiple effect sizes were extracted from studies to maximize information gain and statistical precision and used a random-effects, multilevel modeling framework to account for statistical dependencies within study samples.
Effect sizes were calculated as a standardized mean change score between ASD and neurotypical samples (ie, Hedges g). The primary outcome measure was performance difference between upright and inverted faces during face recognition tasks. Measurement modality, psychological construct, recognition demand, sample age, sample sex distribution, and study quality assessment scores were assessed as moderators.
Of 1768 screened articles, 122 effect sizes from 38 empirical articles representing data from 1764 individual participants (899 ASD individuals and 865 neurotypical individuals) were included in the meta-analysis. Overall, face recognition performance differences between upright and inverted faces were reduced in autistic individuals compared with neurotypical individuals (g = -0.41; SE = 0.11; 95% credible interval [CrI], -0.63 to -0.18). However, there was considerable heterogeneity among effect sizes, which were explored with moderator analysis. The attenuated face inversion effect in autistic individuals was more prominent in emotion compared with identity recognition (b = 0.46; SE = 0.26; 95% CrI, -0.08 to 0.95) and in behavioral compared with electrophysiological measures (b = 0.23; SE = 0.24; 95% CrI, -0.25 to 0.70).
This study found that on average, face recognition in autism is less impacted by inversion. These findings suggest less specialization or expertise of the face processing system in autism, particularly in recognizing emotion from faces as measured in behavioral paradigms.
面部处理是人类社会认知的基础,是自闭症谱系障碍(ASD)的标志性特征的核心,并且塑造了神经系统和社会行为。面部处理系统非常高效和专门化,对面部反转敏感,表现在识别准确性降低和对反转面部的神经反应改变。了解自闭症患者的面部处理系统在何种机制水平上可能存在特别不同,这可以通过面部反转效应来衡量,这将提高对自闭症大脑功能的整体理解。
综合现有文献中的数据,确定 ASD 患者的面部处理系统在多个机制水平上的差异,这可以通过面部反转效应来衡量。
从 2022 年 8 月 11 日开始,在 MEDLINE、Embase、Web of Science 和 PubMed 数据库中进行了系统性搜索。
纳入了报告 ASD 和神经典型样本中识别直立和倒置面孔的基于表现的面部识别测量的原始研究进行定量综合。所有研究均由至少两名评审员进行筛选。
本系统评价和荟萃分析根据 2020 年系统评价和荟萃分析的首选报告项目(PRISMA)报告准则进行。从研究中提取了多个效应大小,以最大程度地获取信息增益和统计精度,并使用随机效应、多层次建模框架来解释研究样本内的统计依赖性。
效应大小计算为 ASD 和神经典型样本之间的识别任务中直立和倒置面孔之间的标准化平均变化分数(即 Hedges g)。主要结果是在识别任务中,直立和倒置面孔之间的识别表现差异。评估了测量方式、心理结构、识别需求、样本年龄、样本性别分布和研究质量评估分数作为调节因素。
在筛选出的 1768 篇文章中,有 122 个来自 38 篇实证文章的效应大小,代表了来自 1764 名个体参与者(899 名 ASD 个体和 865 名神经典型个体)的数据,被纳入荟萃分析。总体而言,与神经典型个体相比,自闭症患者在识别直立和倒置面孔时的表现差异较小(g = -0.41;SE = 0.11;95%可信区间[CrI],-0.63 至 -0.18)。然而,效应大小之间存在很大的异质性,这通过调节分析进行了探讨。与身份识别相比,自闭症患者的面部反转效应减弱在情绪识别中更为明显(b = 0.46;SE = 0.26;95% CrI,-0.08 至 0.95),而在行为测量中比在电生理测量中更为明显(b = 0.23;SE = 0.24;95% CrI,-0.25 至 0.70)。
本研究发现,自闭症患者的面部识别平均而言受反转的影响较小。这些发现表明,自闭症患者的面部处理系统专业化或专业程度较低,特别是在行为范式中识别面部表情时。