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Global‐Before‐Basic Object Categorization in Connectionist Networks and 2‐Month‐Old Infants
Author(s) -
Quinn Paul C.,
Johnson Mark H.
Publication year - 2000
Publication title -
infancy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 69
eISSN - 1532-7078
pISSN - 1525-0008
DOI - 10.1207/s15327078in0101_04
Subject(s) - connectionism , categorization , novelty , psychology , representation (politics) , object (grammar) , perception , concept learning , preference , cognitive psychology , artificial neural network , artificial intelligence , cognitive science , computer science , mathematics , social psychology , statistics , neuroscience , politics , political science , law
A 3‐layered backpropagation connectionist network, configured as an autoassociator, learned to form global (e.g., mammal) before basic‐level (e.g., cat) category representations from perceptual input. To test the predicted global‐to‐basic order of category learning of the network, 2‐month‐olds were administered the familiarization/novelty‐preference procedure and examined for representation of global and basic‐level categories. Infants formed a global category representation for mammals that excluded furniture but not a basic‐level representation for cats that excluded elephants, rabbits, or dogs. The empirical results are consistent with the global‐to‐basic learning sequence observed in the network simulations.