caa a22 4500 605541930 CHVBK 20210128100919.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s10071-015-0895-8 doi (NATIONALLICENCE)springer-10.1007/s10071-015-0895-8 Feature- versus rule-based generalization in rats, pigeons and humans [Elektronische Daten] [Elisa Maes, Guido De Filippo, Angus Inkster, Stephen Lea, Jan De Houwer, Rudi D'Hooge, Tom Beckers, Andy Wills] Humans can spontaneously create rules that allow them to efficiently generalize what they have learned to novel situations. An enduring question is whether rule-based generalization is uniquely human or whether other animals can also abstract rules and apply them to novel situations. In recent years, there have been a number of high-profile claims that animals such as rats can learn rules. Most of those claims are quite weak because it is possible to demonstrate that simple associative systems (which do not learn rules) can account for the behavior in those tasks. Using a procedure that allows us to clearly distinguish feature-based from rule-based generalization (the Shanks-Darby procedure), we demonstrate that adult humans show rule-based generalization in this task, while generalization in rats and pigeons was based on featural overlap between stimuli. In brief, when learning that a stimulus made of two components ("AB”) predicts a different outcome than its elements ("A” and "B”), people spontaneously abstract an opposites rule and apply it to new stimuli (e.g., knowing that "C” and "D” predict one outcome, they will predict that "CD” predicts the opposite outcome). Rats and pigeons show the reverse behavior—they generalize what they have learned, but on the basis of similarity (e.g., "CD” is similar to "C” and "D”, so the same outcome is predicted for the compound stimulus as for the components). Genuinely rule-based behavior is observed in humans, but not in rats and pigeons, in the current procedure. The Author(s), 2015 Rats nationallicence Pigeons nationallicence Humans nationallicence Generalization nationallicence Rule-based nationallicence Associative models nationallicence Maes Elisa KU Leuven, Tiensestraat 102, Box 3712, 3000, Leuven, Belgium aut De Filippo Guido Università di Bologna, Via Zamboni 33, 40126, Bologna, Italy aut Inkster Angus Plymouth University, Drake Circus, PL4 8AA, Plymouth, UK aut Lea Stephen Washington Singer Laboratories, University of Exeter, EX4 4QG, Exeter, UK aut De Houwer Jan Ghent University, Henri Dunantlaan 2, 9000, Ghent, Belgium aut D'Hooge Rudi KU Leuven, Tiensestraat 102, Box 3714, 3000, Leuven, Belgium aut Beckers Tom KU Leuven, Tiensestraat 102, Box 3712, 3000, Leuven, Belgium aut Wills Andy Plymouth University, Drake Circus, PL4 8AA, Plymouth, UK aut Animal Cognition Springer Berlin Heidelberg 18/6(2015-11-01), 1267-1284 1435-9448 18:6<1267 2015 18 10071 https://doi.org/10.1007/s10071-015-0895-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10071-015-0895-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Maes Elisa KU Leuven, Tiensestraat 102, Box 3712, 3000, Leuven, Belgium aut NATIONALLICENCE 700 1- De Filippo Guido Università di Bologna, Via Zamboni 33, 40126, Bologna, Italy aut NATIONALLICENCE 700 1- Inkster Angus Plymouth University, Drake Circus, PL4 8AA, Plymouth, UK aut NATIONALLICENCE 700 1- Lea Stephen Washington Singer Laboratories, University of Exeter, EX4 4QG, Exeter, UK aut NATIONALLICENCE 700 1- De Houwer Jan Ghent University, Henri Dunantlaan 2, 9000, Ghent, Belgium aut NATIONALLICENCE 700 1- D'Hooge Rudi KU Leuven, Tiensestraat 102, Box 3714, 3000, Leuven, Belgium aut NATIONALLICENCE 700 1- Beckers Tom KU Leuven, Tiensestraat 102, Box 3712, 3000, Leuven, Belgium aut NATIONALLICENCE 700 1- Wills Andy Plymouth University, Drake Circus, PL4 8AA, Plymouth, UK aut NATIONALLICENCE 773 0- Animal Cognition Springer Berlin Heidelberg 18/6(2015-11-01), 1267-1284 1435-9448 18:6<1267 2015 18 10071