Attention to Detail Predicts Better Verbal Analogy Performance
Year: 2014
Type: article
Abstract: Attention to Detail Predicts Better Verbal Analogy Performance Jessica L. Irwin Dept. of Psychology, Wayne State University, 5057 Woodward Ave., Detroit, MI 48202 USA Lara L. Jones Dept. of Psychology, Wayne State University, 5057 Woodward Ave., Detroit, MI 48202 USA Matthew J. Kmiecik Dept. of Psychology, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA Nash Unsworth Dept. of Psychology, University of Oregon, Eugene, OR 97403 USA Robert G. Morrison Dept. of Psychology, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA Abstract: Prior studies have found equivalent or even better performance on Raven’s Progressive Matrices tasks for those with autism spectrum disorders (ASD) in comparison to normal controls (e.g., Chen, Planche, & Lemonnier, 2010; Mottron, 2009). We investigated the extent to which subscales of the Autism-Spectrum Quotient would predict better performance on a verbal analogy task in a non-clinical sample of young adults. For each analogy stem, (OAK : TREE :: SPOON : participants had to choose between the correct answer (SILVERWARE) and one distracter, which was either high (FORK) or low (DRAWER) in salience. Controlling for sex and individual differences in working memory, better attention to detail predicted higher accuracies for the analogies with low but not high salient distracters. Thus, attention to detail facilitates recognizing analogical relations but only when there is not also a need to inhibit the superficial similarity of a high salient distracter.
Authors: Jessica L. Irwin, Lara L. Jones, Matthew J. Kmiecik, Nash Unsworth, Robert Morrison
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2406546859