When more is less: Feedback effects in perceptual category learning
CognitionPublished 4 May 2008Open access
W. Todd Maddox, Bradley C. Love, Brian D. Glass, J. Vincent Filoteo
Citations86
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
An examination of the distinct neural circuits that subserve rule- based and information-integration category learning leads to the counterintuitive prediction that full feedback should facilitate rule-based learning but should also hinder information-Integration learning.
Abstract
Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether their response was correct or incorrect, but are not informed of the correct category assignment. With full feedback subjects are informed of the correctness of their response and are also informed of the correct category assignment. An examination of the distinct neural circuits that subserve rule-based and information-integration category learning leads to the counterintuitive prediction that full feedback should facilitate rule-based learning but should also hinder information-integration learning. This prediction was supported in the experiment reported below. The implications of these results for theories of learning are discussed.
Keywords
PsychologyNeuroscience
ScienceA Neural Substrate of Prediction and Reward
9,610 Citations1997Wolfram Schultz, Peter Dayan +1 more
Findings in this work indicate that dopaminergic neurons in the primate whose fluctuating output apparently signals changes or errors in the predictions of future salient and rewarding events can be understood through quantitative theories of adaptive optimizing control.
Journal of Experimental Psychology GeneralAttention, similarity, and the identification-categorization relationship.
2,225 Citations1986Robert M. Nosofsky
A unified quantitative approach to modeling subjects' identification and categorization of multidimensional perceptual stimuli is proposed and tested and some support was gained for the hypothesis that subjects distribute attention among component dimensions so as to optimize categorization performance.
Journal of NeuroscienceA framework for mesencephalic dopamine systems based on predictive Hebbian learning
2,114 Citations1996P. Read Montague, Peter Dayan +1 more
A theoretical framework is developed that shows how mesencephalic dopamine systems could distribute to their targets a signal that represents information about future expectations and shows that, through a simple influence on synaptic plasticity, fluctuations in dopamine release can act to change the predictions in an appropriate manner.
Psychological ReviewA neuropsychological theory of multiple systems in category learning.
1,212 Citations1998F. Gregory Ashby, Leola A. Alfonso-Reese +2 more
A neuropsychological theory is proposed that assumes category learning is a competition between separate verbal and implicit categorization systems and that the anterior cingulate and prefrontal cortices are critical to the verbal system.
Brain Research ReviewsThe role of dopamine in locomotor activity and learning
856 Citations1983Richard J Beninger
It is suggested that the biological substrate of DA-mediated incentive learning is a heterosynaptic facilitation of muscarinic cholinergic synapses, which has important clinical implications since it has been suggested that DA hyperfunctioning underlies the development of schizophrenia.
Psychological ReviewSUSTAIN: A Network Model of Category Learning.
804 Citations2004Bradley C. Love, Douglas L. Medin +1 more
SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.
Psychological ReviewRule-plus-exception model of classification learning.
793 Citations1994Robert M. Nosofsky, Thomas J. Palmeri +1 more
The authors propose a rule-plus-exception model (RULEX) of classification learning, which accounts for numerous fundamental classification phenomena, including prototype and specific exemplar effects, sensitivity to correlational information, difficulty of learning linearly separables versus nonlinearly separable categories, selective attention effects, and difficulty oflearning concepts with rules of differing complexity.
Proceedings of the National Academy of SciencesModulation of competing memory systems by distraction
600 Citations2006Karin Foerde, Barbara J. Knowlton +1 more
Results from functional neuroimaging are presented showing that the presence of a demanding secondary task during learning modulates the degree to which subjects solve a problem using either declarative memory or habit learning, and suggest that the absence of distraction can bias this competition.
Journal of Experimental Psychology GeneralRules and exemplars in category learning.
560 Citations1998Michael A. Erickson, John K. Kruschke
2 experiments are presented that show evidence of both rule induction and exemplar encoding as well as a connectionist model, ATRIUM, that specifies a mechanism for combining rule-and- exemplar-based representation.
Journal of NeuroscienceThe Roles of the Caudate Nucleus in Human Classification Learning
414 Citations2005Carol A. Seger, Corinna M. Cincotta
Activity associated with successful learning was localized in the body and tail of the caudate and putamen; this activity increased as the stimulus-outcome contingencies were learned, and hippocampal activity was associated with receiving positive feedback but not with correct classification.
Journal of Experimental Psychology Learning Memory and CognitionDelayed feedback effects on rule-based and information-integration category learning.
314 Citations2003W. Todd Maddox, F. Gregory Ashby +1 more
Support for a multiple-systems approach to category learning is provided and the validity of single-system approaches is argued against.
Psychonomic Bulletin & ReviewThe effects of concurrent task interference on category learning: Evidence for multiple category learning systems
293 Citations2001Elliott M. Waldron, F. Gregory Ashby
Participants learned simple and complex category structures under typical single-task conditions and when performing a simultaneous numerical Stroop task to support the hypothesis that category learning is mediated by multiple learning systems.
Psychological ReviewA neurobiological theory of automaticity in perceptual categorization.
291 Citations2007F. Gregory Ashby, John M. Ennis +1 more
A biologically detailed computational model is described of how categorization judgments become automatic in tasks that depend on procedural learning, showing that the model accounts for some classic single-cell recording and behavioral results.
Journal of NeurophysiologyHuman Midbrain Sensitivity to Cognitive Feedback and Uncertainty During Classification Learning
270 Citations2004Adam R. Aron, Daphna Shohamy +4 more
Midbrain activity was significantly different for negative versus positive feedback and was reliably correlated with the degree of uncertainty as well as with activity in MDS target regions, consistent with a broader characterization of this network.
Memory & CognitionDual-task interference in perceptual category learning
235 Citations2006Dagmar Zeithamová, W. Todd Maddox
The results support the notion of at least two systems of category learning: a hypothesis-testing system that seeks verbalizable rules and relies on working memory and selective attention, and an implicit system that is procedural-learning based and is essentially automatic.
Cerebral CortexNeural Correlates of Rule-Based and Information-Integration Visual Category Learning
225 Citations2006Emi Nomura, W. Todd Maddox +6 more
Functional neuroimaging was used to assess activity in medial temporal lobe and posterior regions of the caudate systems during category-learning tasks with category structures designed to afford either RB or II learning.
Cerebral CortexDynamics of Frontal, Striatal, and Hippocampal Systems during Rule Learning
220 Citations2005Carol A. Seger
Interactions between frontal, striatal, and hippocampal systems during a rule-learning task showed antagonistic patterns of activity: Activation in the anterior hippocampus decreased, whereas caudate activity increased.
Memory & CognitionObservational versus feedback training in rule-based and information-integration category learning
213 Citations2002F. Gregory Ashby, W. Todd Maddox +1 more
There was an overall advantage for feedback training over observational training, but most importantly, type of training interacted strongly with type of category structure, and people were less likely to use suboptimal rule-based strategies.
Current Directions in Psychological ScienceThe Simplicity Principle in Human Concept Learning
193 Citations2003Jacob Feldman
CognitionIndividual differences in category learning: Sometimes less working memory capacity is better than more
170 Citations2007Marci S. DeCaro, Robin D. Thomas +1 more
The positive relation commonly seen between individual differences in working memory and performance can not only be absent, but reversed, and a comprehensive understanding of skill learning requires considering the demands of the tasks being performed and the cognitive abilities of the performer.
Life SciencesMesencephalic dopaminergic unit activity in the behaviorally conditioned rat
169 Citations1981Joseph D. Miller, Manjit K. Sanghera +1 more
It is indicated that some DA cells change their firing pattern following behaviorally relevant stimuli, and that the incidence of spontaneously active DA neurons is low in the awake rat.
Journal of Experimental Psychology Learning Memory and CognitionDelayed Feedback Disrupts the Procedural-Learning System but Not the Hypothesis-Testing System in Perceptual Category Learning.
164 Citations2005W. Todd Maddox, A. David Ing
A strong performance decrement for information-integration but not rule-based category learning under delayed feedback was revealed that was due to an increase in the number of observers using hypothesis-testing strategies to solve the information- integration task, and lower accuracy rates for the few observers using information-Integration strategies.
Journal of Cognitive NeuroscienceDissociating Explicit and Implicit Category Knowledge with fMRI
164 Citations2003Paul J. Reber, Darren R. Gitelman +2 more
Neuroimaging of healthy volunteers identified separate neural systems supporting the expression of category knowledge depending on whether the learning mode was intentional or incidental, and differences in brain activity indicate differing representations of category Knowledge.
Memory & CognitionDisrupting feedback processing interferes with rule-based but not information-integration category learning
153 Citations2004W. Todd Maddox, F. Gregory Ashby +2 more
The effect of a sequentially presented memory scanning task on rule-based and informationintegration category learning was investigated and support for a multiple-systems approach to category learning is provided and the validity of single-system approaches is argued.
Elsevier eBooksA Theory of the Striatum
151 Citations1993
This work proposes a model of the striatal function as a field of inhibitory domains and its implications for brain models and psychological theory, and discusses the role of reinforcement learning in neural nets and reward-mediated learning.
Cognitive Affective & Behavioral NeuroscienceModels in search of a brain
94 Citations2007Bradley C. Love, Todd M. Gureckis
This case is made by relating an existing cognitive model of category learning to a learning circuit involving the hippocampus, perirhinal, and prefrontal cortices, and it is argued that the proper targets for localization are well-specified cognitive models.
Memory & CognitionThe role of visuospatial and verbal working memory in perceptual category learning
83 Citations2007Dagmar Zeithamová, W. Todd Maddox
NeuroreportCortical and subcortical brain regions involved in rule-based category learning
80 Citations2005J. Vincent Filoteo, W. Todd Maddox +5 more
Results indicated that left frontal and parietal regions were differentially activated in those participants who learned the task as compared to those who did not, consistent with theories suggesting that a frontal-striatal circuit is involved in rule-based category learning.
Journal of Neural TransmissionDopaminergic contribution to cognitive sequence learning
23 Citations2007Orsolya Nagy, Ogúz Kelemen +5 more
A significant negative relationship between errors in the feedback-guided training phase of the sequence learning task and the plasma HVA level was revealed, suggesting that dopamine plays a special role in feedback- guided cognitive sequence learning.