Sarah Bate, Emma Portch, Rachel J Bennetts, Benjamin A Parris
{"title":"A taxometric analysis of developmental prosopagnosia: Evidence for a categorically distinct impairment.","authors":"Sarah Bate, Emma Portch, Rachel J Bennetts, Benjamin A Parris","doi":"10.1016/j.cortex.2024.10.021","DOIUrl":null,"url":null,"abstract":"<p><p>Poor performance on cognitive assessment tasks may indicate a selective 'impairment'. However, it is unclear whether such difficulties separate the individual from the general population qualitatively (i.e., they form a discrete group) or quantitatively (i.e., they represent the lower end of a continuous distribution). Taxometric methods address this question but have rarely been applied to cognitive disorders. This study examined the latent structure of developmental prosopagnosia (DP) - a relatively selective deficit in face recognition that occurs in the absence of neurological injury. Multiple taxometric procedures were applied to dominant diagnostic indices of face recognition ability across two independent datasets. All analyses supported a categorical outcome, even for mild cases of DP, suggesting that it is a qualitatively distinct condition. This finding has significant implications for our understanding of DP given it has traditionally been viewed as a continuous impairment. In particular, existing (arbitrary) diagnostic cut-offs may be too conservative, underestimating prevalence rates and prohibiting big-data approaches to theoretical study. More broadly, these conclusions support application of the taxometric method to many other cognitive processes where weaknesses are predominantly assumed to reside on a continuous distribution.</p>","PeriodicalId":10758,"journal":{"name":"Cortex","volume":"183 ","pages":"131-145"},"PeriodicalIF":3.2000,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cortex","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1016/j.cortex.2024.10.021","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Poor performance on cognitive assessment tasks may indicate a selective 'impairment'. However, it is unclear whether such difficulties separate the individual from the general population qualitatively (i.e., they form a discrete group) or quantitatively (i.e., they represent the lower end of a continuous distribution). Taxometric methods address this question but have rarely been applied to cognitive disorders. This study examined the latent structure of developmental prosopagnosia (DP) - a relatively selective deficit in face recognition that occurs in the absence of neurological injury. Multiple taxometric procedures were applied to dominant diagnostic indices of face recognition ability across two independent datasets. All analyses supported a categorical outcome, even for mild cases of DP, suggesting that it is a qualitatively distinct condition. This finding has significant implications for our understanding of DP given it has traditionally been viewed as a continuous impairment. In particular, existing (arbitrary) diagnostic cut-offs may be too conservative, underestimating prevalence rates and prohibiting big-data approaches to theoretical study. More broadly, these conclusions support application of the taxometric method to many other cognitive processes where weaknesses are predominantly assumed to reside on a continuous distribution.
期刊介绍:
CORTEX is an international journal devoted to the study of cognition and of the relationship between the nervous system and mental processes, particularly as these are reflected in the behaviour of patients with acquired brain lesions, normal volunteers, children with typical and atypical development, and in the activation of brain regions and systems as recorded by functional neuroimaging techniques. It was founded in 1964 by Ennio De Renzi.