
Domain-general ability underlies complex object ensemble processing.
Author(s) -
Ting-Yun Chang,
Isabel Gauthier
Publication year - 2022
Publication title -
journal of experimental psychology. general
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 2.521
H-Index - 161
eISSN - 1939-2222
pISSN - 0096-3445
DOI - 10.1037/xge0001110
Subject(s) - coding (social sciences) , artificial intelligence , computer science , domain (mathematical analysis) , object (grammar) , cognitive neuroscience of visual object recognition , orientation (vector space) , representation (politics) , pattern recognition (psychology) , psychology , natural language processing , mathematics , statistics , mathematical analysis , geometry , politics , political science , law
When seeing groups of objects, various features can be extracted to form an ensemble representation, including low-level features such as orientation and higher-level features like facial expression. Past research proposed distinct abilities for ensemble coding of high-level versus low-level visual features, but the only complex objects used were faces. Here, we examine evidence for a shared ability supporting ensemble representations for complex objects from different object categories. In 2 experiments, participants completed an ensemble mean judgment task for an array of 4 objects, including planes and birds (Experiment 1) or cars and birds (Experiment 2). We also measured and controlled for domain-specific recognition ability. Across the 2 experiments, performance on ensemble judgments with different objects were correlated, even after controlled for domain-specific recognition abilities. These findings provide the strongest evidence to date of a domain-general ability involved in complex object ensemble coding. (PsycInfo Database Record (c) 2022 APA, all rights reserved).