Disrupting Feedback Processing Interferes with Rule-based but Not Information-integration Category Learning

Overview

Journal Mem Cognit

Specialty Psychology

Date 2004 Oct 14

PMID 15478752

Citations 60

Authors

W Todd Maddox

F Gregory Ashby

A David Ing

Alan D Pickering

Affiliations

Soon will be listed here.

Abstract

The effect of a sequentially presented memory scanning task on rule-based and information-integration category learning was investigated. On each trial in the short feedback-processing time condition, memory scanning immediately followed categorization. On each trial in the long feedback-processing time condition, categorization was followed by a 2.5-sec delay and then memory scanning. In the control condition, no memory scanning was required. Rule-based category learning was significantly worse in the short feedback-processing time condition than in the long feedback-processing time condition or control condition, whereas information-integration category learning was equivalent across conditions. In the rule-based condition, a smaller proportion of observers learned the task in the short feedback-processing time condition, and those who learned took longer to reach the performance criterion than did those in the long feedback-processing time or control condition. No differences were observed in the information integration task. These results provide support for a multiple-systems approach to category learning and argue against the validity of single-system approaches.

Citing Articles

Distribution-dependent representations in auditory category learning and generalization.

Gan Z, Zheng L, Wang S, Feng G Front Psychol. 2023; 14:1132570.

PMID: 37829077 PMC: 10566369. DOI: 10.3389/fpsyg.2023.1132570.

Strategy inference during learning via cognitive activity-based credit assignment models.

James A, Reynaud-Bouret P, Mezzadri G, Sargolini F, Bethus I, Muzy A Sci Rep. 2023; 13(1):9408.

PMID: 37296163 PMC: 10256696. DOI: 10.1038/s41598-023-33604-2.

Stable, flexible, common, and distinct behaviors support rule-based and information-integration category learning.

Roark C, Chandrasekaran B NPJ Sci Learn. 2023; 8(1):14.

PMID: 37179364 PMC: 10183008. DOI: 10.1038/s41539-023-00163-0.

A role for the medial temporal lobes in category learning.

Wang Y, Ashby F Learn Mem. 2020; 27(10):441-450.

PMID: 32934097 PMC: 7497113. DOI: 10.1101/lm.051995.120.

Multiple object-tracking isolates feedback-specific load in attention and learning.

Tullo D, Perico C, Faubert J, Bertone A J Vis. 2020; 20(5):9.

PMID: 32441736 PMC: 7409588. DOI: 10.1167/jov.20.5.9.

References

Willingham D, Nissen M, Bullemer P . On the development of procedural knowledge. J Exp Psychol Learn Mem Cogn. 1989; 15(6):1047-60. DOI: 10.1037//0278-7393.15.6.1047. View

Ashby F, Turken A, Waldron E . A neuropsychological theory of multiple systems in category learning. Psychol Rev. 1998; 105(3):442-81. DOI: 10.1037/0033-295x.105.3.442. View

Waldron E, Ashby F . The effects of concurrent task interference on category learning: evidence for multiple category learning systems. Psychon Bull Rev. 2001; 8(1):168-76. DOI: 10.3758/bf03196154. View

Brainard D . The Psychophysics Toolbox. Spat Vis. 1997; 10(4):433-6. View

Reber P, Squire L . Parallel brain systems for learning with and without awareness. Learn Mem. 1994; 1(4):217-29. View

Nosofsky R, Johansen M . Exemplar-based accounts of "multiple-system" phenomena in perceptual categorization. Psychon Bull Rev. 2000; 7(3):375-402. View

Maddox W, Ashby F, Bohil C . Delayed feedback effects on rule-based and information-integration category learning. J Exp Psychol Learn Mem Cogn. 2003; 29(4):650-62. DOI: 10.1037/0278-7393.29.4.650. View

Smith E, Patalano A, Jonides J . Alternative strategies of categorization. Cognition. 1998; 65(2-3):167-96. DOI: 10.1016/s0010-0277(97)00043-7. View

Ashby F, Ell S, Waldron E . Procedural learning in perceptual categorization. Mem Cognit. 2004; 31(7):1114-25. DOI: 10.3758/bf03196132. View

10.

Ashby F, Maddox W, Bohil C . Observational versus feedback training in rule-based and information-integration category learning. Mem Cognit. 2002; 30(5):666-77. DOI: 10.3758/bf03196423. View

11.

Erickson M, Kruschke J . Rules and exemplars in category learning. J Exp Psychol Gen. 1998; 127(2):107-40. DOI: 10.1037//0096-3445.127.2.107. View

12.

Ashby F, Noble S, Filoteo J, Waldron E, Ell S . Category learning deficits in Parkinson's disease. Neuropsychology. 2003; 17(1):115-24. View

13.

Willingham D . A neuropsychological theory of motor skill learning. Psychol Rev. 1998; 105(3):558-84. DOI: 10.1037/0033-295x.105.3.558. View

14.

Pickering A . New approaches to the study of amnesic patients: what can a neurofunctional philosophy and neural network methods offer?. Memory. 1997; 5(1-2):255-300. DOI: 10.1080/741941146. View

15.

Maddox W, Bohil C, Ing A . Evidence for a procedural-learning-based system in perceptual category learning. Psychon Bull Rev. 2005; 11(5):945-52. DOI: 10.3758/bf03196726. View

16.

Ashby F, Waldron E . On the nature of implicit categorization. Psychon Bull Rev. 2002; 6(3):363-78. DOI: 10.3758/bf03210826. View

17.

Ashby F, Gott R . Decision rules in the perception and categorization of multidimensional stimuli. J Exp Psychol Learn Mem Cogn. 1988; 14(1):33-53. DOI: 10.1037//0278-7393.14.1.33. View

18.

Ashby F, Ell S . The neurobiology of human category learning. Trends Cogn Sci. 2001; 5(5):204-210. DOI: 10.1016/s1364-6613(00)01624-7. View