Literature DB >> 22746952

The effect of feedback delay and feedback type on perceptual category learning: the limits of multiple systems.

John C Dunn1, Ben R Newell, Michael L Kalish.   

Abstract

Evidence that learning rule-based (RB) and information-integration (II) category structures can be dissociated across different experimental variables has been used to support the view that such learning is supported by multiple learning systems. Across 4 experiments, we examined the effects of 2 variables, the delay between response and feedback and the informativeness of feedback, which had previously been shown to dissociate learning of the 2 types of category structure. Our aim was twofold: first, to determine whether these dissociations meet the more stringent inferential criteria of state-trace analysis and, second, to determine the conditions under which they can be observed. Experiment 1 confirmed that a mask-filled feedback delay dissociated the learning of RB and II category structures with minimally informative (yes/no) feedback and also met the state-trace criteria for the involvement of multiple latent variables. Experiment 2 showed that this effect is eliminated when a less similar, fixed pattern mask is presented in the interval between response and feedback. Experiment 3 showed that the selective effect of feedback delay on II learning is reduced with fully informative feedback (in which the correct category is specified after an incorrect response) and that feedback type did not dissociate RB and II learning. Experiment 4 extended the results of Experiment 2, showing that the differential effect of feedback delay is eliminated when a fixed pattern mask is used. These results pose important challenges to models of category learning, and we discuss their implications for multiple learning system models and their alternatives. 2012 APA, all rights reserved

Mesh:

Year:  2012        PMID: 22746952     DOI: 10.1037/a0027867

Source DB:  PubMed          Journal:  J Exp Psychol Learn Mem Cogn        ISSN: 0278-7393            Impact factor:   3.051


  20 in total

1.  Category-Induced Transfer of Visual Perceptual Learning.

Authors:  Qingleng Tan; Zhiyan Wang; Yuka Sasaki; Takeo Watanabe
Journal:  Curr Biol       Date:  2019-03-28       Impact factor: 10.834

Review 2.  Visual category learning: Navigating the intersection of rules and similarity.

Authors:  Gregory I Hughes; Ayanna K Thomas
Journal:  Psychon Bull Rev       Date:  2021-01-19

3.  Generalization of category knowledge and dimensional categorization in humans (Homo sapiens) and nonhuman primates (Macaca mulatta).

Authors:  J David Smith; Alexandria C Zakrzewski; Jennifer J R Johnston; Jessica L Roeder; Joseph Boomer; F Gregory Ashby; Barbara A Church
Journal:  J Exp Psychol Anim Learn Cogn       Date:  2015-07-13       Impact factor: 2.478

Review 4.  Multiple stages of learning in perceptual categorization: evidence and neurocomputational theory.

Authors:  George Cantwell; Matthew J Crossley; F Gregory Ashby
Journal:  Psychon Bull Rev       Date:  2015-12

5.  Comparing the effects of positive and negative feedback in information-integration category learning.

Authors:  Michael Freedberg; Brian Glass; J Vincent Filoteo; Eliot Hazeltine; W Todd Maddox
Journal:  Mem Cognit       Date:  2017-01

Review 6.  Is state-trace analysis an appropriate tool for assessing the number of cognitive systems?

Authors:  F Gregory Ashby
Journal:  Psychon Bull Rev       Date:  2014-08

7.  The role of feedback contingency in perceptual category learning.

Authors:  F Gregory Ashby; Lauren E Vucovich
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2016-05-05       Impact factor: 3.051

8.  The role of differential outcomes-based feedback on procedural memory.

Authors:  Víctor Martínez-Pérez; Luis J Fuentes; Guillermo Campoy
Journal:  Psychol Res       Date:  2019-08-05

9.  Task and distribution sampling affect auditory category learning.

Authors:  Casey L Roark; Lori L Holt
Journal:  Atten Percept Psychophys       Date:  2018-10       Impact factor: 2.199

10.  Dissociations between rule-based and information-integration categorization are not caused by differences in task difficulty.

Authors:  F Gregory Ashby; J David Smith; Luke A Rosedahl
Journal:  Mem Cognit       Date:  2020-05
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