The Italian Famous Face Test (IT-FFT): Normative data from neurotypical individuals and an assessment of its sensitivity in Autism Spectrum Disorder (ASD)

Author:

Ventura Martina1,Caffò Alessandro Oronzo2,Manippa Valerio2,Cicinelli Giovanni3,Nobile Emanuela3,Keller Roberto3,Rivolta Davide2

Affiliation:

1. Western Sydney University

2. University of Bari Aldo Moro

3. Local Health Unit ASL Città di Torino

Abstract

Abstract

The faces we see in daily life exist on a continuum of familiarity, ranging from personally familiar to famous to unfamiliar faces. Thus, when assessing face recognition abilities, adequate evaluation measures should be employed to discriminate between each of these processes and their relative impairments. We here developed the Italian Famous Face Test (IT-FFT), a novel assessment tool for famous face recognition in typical and clinical populations. Normative data on a large sample (N = 436) of Italian neurotypical individuals (NT) were collected, assessing both familiarity (d-prime) and recognition accuracy. Next, we investigated the IT-FFA’s validity on a neurodevelopmental condition, autism spectrum disorder (ASD), often associated with face recognition deficits. Results showed ASDs’ difficulties in face recognition and in their ability to discriminate between famous and non-famous faces. Furthermore, this study explored whether both NTs and ASDs possess insights into their overall face recognition skills by correlating the Prosopagnosia Index-20 (PI-20) with the IT-FFT; a negative correlation between these measures in both groups suggests that even ASDs have insight into their (weaker) face recognition skills. Overall, our study provides the first online-based Italian test for famous faces (IT-FFT), demonstrates its sensitivity in detecting face difficulties in ASDs, and suggests spared face-related metacognitive skills in ASD.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3