The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
A model for Pavlovian learning: Variations in the effectiveness of conditioned but not of unconditioned stimuli.
Abstract
Several formal models of excitatory classical conditioning are reviewed. It is suggested that a central problem for all of them is the explanation of cases in which learning does not occur in spite of the fact that the conditioned stimulus is a signal for the reinforcer. We propose a new model that deals with this problem by specifying that certain procedures cause a conditioned stimulus (CS) to lose effectiveness; in particular, we argue that a CS will lose associability when its consequences are accurately predicted. In contrast to other current models, the effectiveness of the reinforcer remains constant throughout conditioning. The second part of the article presents a reformulation of the nature of the learning produced by inhibitory-conditioning procedures and a discussion of the way in which such learning can be accommodated within the model outlined for excitatory learning. A recent review of classical conditioning (Dickinson & Mackintosh, 1978) suggests that the underlying associative process is "responsible for organisms learning about the relationships between events, enabling them to build up an associative representation of the causal structure of their environment" (p. 588). According to this view the occurrence of a conditioned response (CR) as a result of the pairing of a conditioned stimulus (CS) and an unconditioned stimulus (US) is regarded as being merely an index of the formation of some internal representation of the relationship between CS and US. The first task of a theory of classical conditioning becomes that of This work was supported by grants from the United Kingdom Science and Medical Research Councils. We have made free use of many suggestions, especially concerning inhibitory learning, made by A. Dickinson. We thank him and also C. Adams, P. Bailey, S. Channel!, N. Mackintosh, and E. Macphail for their comments on earlier versions of this article. Requests for reprints should be sent to John Pearce,
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“according to at least one venerable theory of associative learning, the Pearce-Hall model of Pavlovian learning (Pearce & Hall, 1980), attention paid to cues that predict a reinforcer should decline as the reinforcer becomes better and better predicted during extended conditioning.”
From Context, attention, and the switch between habit and goal-direction in behavior (2021) · cites this paper as Pearce & Hall, 1980
In the citing paper
“The attention explanation given above is based on a well-known theory of attention and its role in Pavlovian learning (Pearce & Hall, 1980).”
From Context, attention, and the switch between habit and goal-direction in behavior (2021) · cites this paper as Pearce & Hall, 1980
Citations
Cites
Shiffrin, R. M., & Schneider, W. (1977) · Psychological Review · doi:10.1037/0033-295x.84.2.127 · Cited by 7,335
Rescorla, R. A. (1972) · Medical Entomology and Zoology · Cited by 7,268
Controlled and automatic human information processing: I. Detection, search, and attention.
Schneider, W., & Shiffrin, R. M. (1977) · Psychological Review · doi:10.1037/0033-295x.84.1.1 · Cited by 5,902
Lane, S. D. (2016) · Routledge eBooks · doi:10.4324/9781315506173-8 · Cited by 4,707
Classical conditioning II: Current research and theory.
Black, A. H., & Prokasy, W. F. (1972) · Appleton-Century-Crofts eBooks · Cited by 4,449
A theory of attention: Variations in the associability of stimuli with reinforcement
Mackintosh, N. J. (1975) · Psychological Review · doi:10.1037/h0076778 · Cited by 2,733
The Psychology of Animal Learning
Hill, W. F., & Mackintosh, N. J. (1976) · The American Journal of Psychology · doi:10.2307/1421765 · Cited by 2,397
Controlled and automatic human information processing: I
Schneider, W. E., & Shiffrin, R. M. (1977) · Cited by 2,228
Punishment and aversive behavior
Campbell, B. A., & Church, R. M. (1969) · Appleton-Century-Crofts eBooks · Cited by 1,989
Predictability, surprise, attention, and conditioning
Kamin, L. J. (1967) · NASA Technical Reports Server (NASA) · Cited by 1,483
Cited by
Sorted by citations
Items 301–400 of 1,010
A neural network for information seeking
White, J. K., Bromberg-Martin, E. S., Heilbronner, S. R., Zhang, K., Pai, J., Haber, S. N., & Monosov, I. E. (2019) · Nature Communications · doi:10.1038/s41467-019-13135-z · Cited by 129
Carìa, A., Sitaram, R., & Birbaumer, N. (2011) · The Neuroscientist · doi:10.1177/1073858411407205 · Cited by 138
O’Doherty, J. P. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.03.027 · Cited by 136
A retrieved context model of the emotional modulation of memory.
Talmi, D., Lohnas, L. J., & Daw, N. D. (2019) · Psychological Review · doi:10.1037/rev0000132 · Cited by 140
Beyond dichotomies in reinforcement learning
Collins, A. G. E., & Cockburn, J. (2020) · Nature reviews. Neuroscience · doi:10.1038/s41583-020-0355-6 · Cited by 147
Divjak, D. (2019) · Elsevier eBooks · doi:10.1016/b978-0-323-95504-1.01134-0 · Cited by 135
Contextual control of human fear associations in a renewal paradigm
Effting, M., & Kindt, M. (2007) · Behaviour Research and Therapy · doi:10.1016/j.brat.2007.02.011 · Cited by 128
Episodic Memory Encoding Interferes with Reward Learning and Decreases Striatal Prediction Errors
Wimmer, G. E., Braun, E. K., Daw, N. D., & Shohamy, D. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.0204-14.2014 · Cited by 134
Neural Basis of Motivational and Cognitive Control
Mars, R., Sallet, J., Mfs., R., & Yeung, N. (2011) · The MIT Press eBooks · doi:10.7551/mitpress/9780262016438.001.0001 · Cited by 128
The exponential learning equation as a function of successful trials results in sigmoid performance
Leibowitz, N., Baum, B., Enden, G., & Karniel, A. (2010) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2010.01.006 · Cited by 128
Beitel, R. E., Schreiner, C. E., Cheung, S. W., Wang, X., & Merzenich, M. M. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1334187100 · Cited by 129
Moustafa, A. A., Gilbertson, M. W., Orr, S. P., Herzallah, M. M., Servatius, R. J., & Myers, C. E. (2012) · Brain and Cognition · doi:10.1016/j.bandc.2012.10.005 · Cited by 134
Is predictability salient? A study of attentional capture by auditory patterns
Southwell, R. V., Anna, B., Cécile, G., Barascud, N., Friston, K. J., & Maria Chait, A. (2017) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2016.0105 · Cited by 128
Charpentier, C. J., Iigaya, K., & O’Doherty, J. P. (2020) · Neuron · doi:10.1016/j.neuron.2020.02.028 · Cited by 132
Batesian, quasi-Batesian or Müllerian mimicry? Theory and data in mimicry Research
Speed, M. P. (1999) · Evolutionary Ecology · doi:10.1023/a:1010871106763 · Cited by 127
Making predictions in a changing world—inference, uncertainty, and learning
O’Reilly, J. X. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00105 · Cited by 124
Reacquisition following extinction in appetitive conditioning
Ricker, S. T., & Bouton, M. E. (1996) · Animal Learning & Behavior · doi:10.3758/bf03199014 · Cited by 126
The Origins and Organization of Vertebrate Pavlovian ConditioningPreprint
Fanselow, M., & Wassum, K. (2015) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a021717 · Cited by 132
Mechanisms of renewal after the extinction of instrumental behavior.
Todd, T. P. (2013) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/a0032236 · Cited by 125
Occasion setting: A neural network approach.
Schmajuk, N. A., Lamoureux, J. A., & Holland, P. C. (1998) · Psychological Review · doi:10.1037/0033-295x.105.1.3 · Cited by 125
A Search for Context-Stimulus Associations in Latent Inhibition
Hall, G., & Minor, H. (1984) · The Quarterly Journal of Experimental Psychology Section B · doi:10.1080/14640748408402200 · Cited by 125
Self-citationDaly, H. B., & Daly, J. T. (1982) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.111.4.441 · Cited by 123
Grossberg, S. (1984) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.1984.tb23523.x · Cited by 123
Real-time attentional models for classical conditioning and the hippocampus
Schmajuk, N. A., & Moore, J. W. (1985) · Physiological Psychology · doi:10.3758/bf03326534 · Cited by 125
Craske, M. (2015) · Verhaltenstherapie · doi:10.1159/000381574 · Cited by 124
Prefrontal Cortex Predicts State Switches during Reversal Learning
Bartolo, R., & Averbeck, B. B. (2020) · Neuron · doi:10.1016/j.neuron.2020.03.024 · Cited by 132
Killcross, S., Dickinson, A., & Robbins, T. W. (1994) · Psychopharmacology · doi:10.1007/bf02244771 · Cited by 123
Thalamic reticular nucleus activation reflects attentional gating during classical conditioning
McAlonan, K., Brown, V. J., & Bowman, E. M. (2000) · The Journal of Neuroscience · doi:10.1523/jneurosci.20-23-08897.2000 · Cited by 122
Generalization versus contextualization in automatic evaluation.
Gawronski, B., Rydell, R. J., Vervliet, B., & Houwer, J. D. (2010) · Journal of Experimental Psychology General · doi:10.1037/a0020315 · Cited by 124
Tool-use and instrumental learning in the Eurasian jay (Garrulus glandarius)
Cheke, L. G., Bird, C. D., & Clayton, N. S. (2011) · Animal Cognition · doi:10.1007/s10071-011-0379-4 · Cited by 122
Structuring Memory Through Inference‐Based Event Segmentation
Shin, Y. S., & DuBrow, S. (2020) · Topics in Cognitive Science · doi:10.1111/tops.12505 · Cited by 135
Systems-level integration of interval timing and reaction time
MacDonald, C. J., & Meck, W. H. (2004) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2004.09.007 · Cited by 123
Functional Connectivity between Amygdala and Cingulate Cortex for Adaptive Aversive Learning
Klavir, O., Genud-Gabai, R., & Paz, R. (2013) · Neuron · doi:10.1016/j.neuron.2013.09.035 · Cited by 128
When does social learning become cultural learning?
Heyes, C. M. (2015) · Developmental Science · doi:10.1111/desc.12350 · Cited by 130
Visual search in schizophrenia: latent inhibition and novel pop-out effects
Lubow, R. E., Kaplan, O., Abramovich, P., Rudnick, A., & Laor, N. (2000) · Schizophrenia Research · doi:10.1016/s0920-9964(99)00188-7 · Cited by 122
Context Specificity of Excitation and Inhibition in Ambiguous Stimuli
Nelson, J. B. (2002) · Learning and Motivation · doi:10.1006/lmot.2001.1112 · Cited by 120
Recovery from blocking achieved by extinguishing the blocking CS
Blaisdell, A. P., Gunther, L. M., & Miller, R. R. (1999) · Animal Learning & Behavior · doi:10.3758/bf03199432 · Cited by 118
Dorsal tegmental dopamine neurons gate associative learning of fear
Groessl, F., Munsch, T., Meis, S., Griessner, J., Kaczanowska, J., Pliota, P., Kargl, D., Badurek, S., Kraitsy, K., Rassoulpour, A., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0174-5 · Cited by 118
Weiner, I., & Arad, M. (2009) · Behavioural Brain Research · doi:10.1016/j.bbr.2009.05.004 · Cited by 119
Predicting danger: The nature, consequences, and neural mechanisms of predictive fear learningPreprint
McNally, G. P., & Westbrook, R. F. (2006) · Learning & Memory · doi:10.1101/lm.196606 · Cited by 124
Dopamine Modulates Adaptive Prediction Error Coding in the Human Midbrain and Striatum
Diederen, K. M. J., Ziauddeen, H., Vestergaard, M. D., Spencer, T., Schultz, W., & Fletcher, P. C. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.1979-16.2016 · Cited by 110
Rapid dopamine dynamics in the accumbens core and shell Learning and action
Saddoris, M. P. (2012) · Frontiers in Bioscience-Elite · doi:10.2741/e615 · Cited by 118
Mesolimbic dopamine adapts the rate of learning from action
Coddington, L. T., Lindo, S. E., & Dudman, J. T. (2023) · Nature · doi:10.1038/s41586-022-05614-z · Cited by 123
Carelli, R. M., Wolske, M., & West, M. O. (1997) · The Journal of Neuroscience · doi:10.1523/jneurosci.17-05-01804.1997 · Cited by 114
Functionally Segregated Neural Substrates for Arbitrary Audiovisual Paired-Association Learning
Tanabe, H. C., Honda, M., & Sadato, N. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.0636-05.2005 · Cited by 116
Psychological and neural mechanisms of experimental extinction: A selective review
Delamater, A. R., & Westbrook, R. F. (2013) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2013.09.016 · Cited by 120
Cue-Evoked Dopamine Promotes Conditioned Responding during Learning
Morrens, J., Aydın, Ç., van Rensburg, A. J., Rabell, J. E., & Haesler, S. (2020) · Neuron · doi:10.1016/j.neuron.2020.01.012 · Cited by 124
Effects of amygdala central nucleus lesions on blocking and unblocking.
Holland, P. C., & Gallagher, M. (1993) · Behavioral Neuroscience · doi:10.1037//0735-7044.107.2.235 · Cited by 117
Alexander, W. H., & Brown, J. W. (2015) · Neural Computation · doi:10.1162/neco_a_00779 · Cited by 119
The neural signature of escalating frustration in humans
Yu, R., Mobbs, D., Seymour, B., Rowe, J. B., & Calder, A. J. (2014) · Cortex · doi:10.1016/j.cortex.2014.02.013 · Cited by 122
Frequency in Language: Memory, Attention and Learning
Divjak, D. (2019) · doi:10.1017/9781316084410 · Cited by 115
The Aging Hippocampus: Navigating Between Rat and Human Experiments
Driscoll, I. F., & Sutherland, R. J. (2005) · Reviews in the Neurosciences · doi:10.1515/revneuro.2005.16.2.87 · Cited by 117
Expectancy violations promote learning in young children
Stahl, A. E., & Feigenson, L. (2017) · Cognition · doi:10.1016/j.cognition.2017.02.008 · Cited by 115
Reinforcement accounts for transitive inference performance
Wynne, C. D. L. (1995) · Animal Learning & Behavior · doi:10.3758/bf03199936 · Cited by 114
The Olfactory Memory of the Honeybee Apis Mellifera:II. Blocking Between Odorants in Binary Mixtures
Smith, B. H., & Cobey, S. (1994) · Journal of Experimental Biology · doi:10.1242/jeb.195.1.91 · Cited by 114
Stimulus coding in human associative learning: Flexible representations of parts and wholes
Melchers, K. G., Shanks, D. R., & Lachnit, H. (2007) · Behavioural Processes · doi:10.1016/j.beproc.2007.09.013 · Cited by 115
Associative Fear Learning Enhances Sparse Network Coding in Primary Sensory Cortex
Gdalyahu, A., Tring, E., Polack, P., Gruver, R., Golshani, P., Fanselow, M. S., Silva, A. J., & Trachtenberg, J. T. (2012) · Neuron · doi:10.1016/j.neuron.2012.04.035 · Cited by 112
Wills, A. J., Lavric, A., Croft, G., & Hodgson, T. L. (2007) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2007.19.5.843 · Cited by 118
Aversive Learning Modulates Cortical Representations of Object Categories
Dunsmoor, J. E., Kragel, P. A., Martin, A. D., & LaBar, K. S. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht138 · Cited by 117
Trial and intertrial durations in Pavlovian conditioning: Issues of learning and performance.
Lattal, K. M. (1999) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/0097-7403.25.4.433 · Cited by 112
The passionate scientist: emotion in scientific cognition
Thagard, P. R. (2002) · Cambridge University Press eBooks · doi:10.1017/cbo9780511613517.013 · Cited by 115
Chandra, S., Hosler, J. S., & Smith, B. H. (2000) · Journal of comparative psychology · doi:10.1037/0735-7036.114.1.86 · Cited by 112
The amygdala: securing pleasure and avoiding pain
Fernando, A. B. P., Murray, J. E., & Milton, A. L. (2013) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2013.00190 · Cited by 119
Retrosplenial cortex and its role in cue-specific learning and memory
Todd, T. P., Fournier, D. I., & Bucci, D. J. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.04.016 · Cited by 110
Influence of a beacon on spatial learning based on the shape of the test environment.
Pearce, J. M., Ward-Robinson, J., Good, M. A., Fussell, C., & Aydin, A. (2001) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/0097-7403.27.4.329 · Cited by 111
Self-citationContext and performance in aversive-to-appetitive and appetitive-to-aversive transfer
Peck, C. A., & Bouton, M. E. (1990) · Learning and Motivation · doi:10.1016/0023-9690(90)90002-6 · Cited by 112
Schematic Influences on Category Learning and Recognition Memory.
Sakamoto, Y., & Love, B. C. (2004) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.133.4.534 · Cited by 118
Representation-mediated overshadowing and potentiation of conditioned aversions.
Holland, P. C. (1983) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/0097-7403.9.1.1 · Cited by 109
Successful overshadowing and blocking in hippocampectomized rats
Garrud, P., Rawlins, J. N. P., Mackintosh, N. J., Goodall, G., Cotton, M. M., & Feldon, J. (1984) · Behavioural Brain Research · doi:10.1016/0166-4328(84)90201-8 · Cited by 110
Hall, G. (2003) · The Quarterly Journal of Experimental Psychology Section B · doi:10.1080/02724990244000151 · Cited by 113
Self-citationSpetch, M. L., Belke, T. W., Barnet, R. C., Dunn, R. M., & Pierce, W. D. (1990) · Journal of the Experimental Analysis of Behavior · doi:10.1901/jeab.1990.53-219 · Cited by 109
Hippocampal lesions disrupt decrements but not increments in conditioned stimulus processing
Han, J., Gallagher, M., & Holland, P. C. (1995) · Journal of Neuroscience · doi:10.1523/jneurosci.15-11-07323.1995 · Cited by 109
Lysle, D. T., & Fowler, H. (1985) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037//0097-7403.11.1.71 · Cited by 110
Occasional reinforced trials during extinction can slow the rate of rapid reacquisition
Bouton, M. E., Woods, A. M., & Pineño, O. (2004) · Learning and Motivation · doi:10.1016/j.lmot.2004.05.001 · Cited by 109
Holistic Reinforcement Learning: The Role of Structure and Attention
Radulescu, A., Niv, Y., & Ballard, I. C. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.01.010 · Cited by 109
Cognitive versus stimulus-response theories of learning
Holland, P. C. (2008) · Learning & Behavior · doi:10.3758/lb.36.3.227 · Cited by 117
Slow reacquisition following the extinction of conditioned suppression
Bouton, M. E. (1986) · Learning and Motivation · doi:10.1016/0023-9690(86)90017-2 · Cited by 107
Dynamic causal modelling of anticipatory skin conductance responses
Bach, D. R., Jean Daunizeau, A., Friston, K. J., & Dolan, R. J. (2010) · Biological Psychology · doi:10.1016/j.biopsycho.2010.06.007 · Cited by 107
Bouton, M. E., & King, D. A. (1986) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/0097-7403.12.1.4 · Cited by 111
How foraging works: Uncertainty magnifies food-seeking motivation
Anselme, P., & Güntürkün, O. (2018) · Behavioral and Brain Sciences · doi:10.1017/s0140525x18000948 · Cited by 109
Dopamine, Prediction Error and Beyond
Diederen, K. M. J., & Fletcher, P. C. (2021) · The Neuroscientist · doi:10.1177/1073858420907591 · Cited by 106
The role of drug expectancy in the control of human drug seeking.
Hogarth, L., Dickinson, A., Wright, A., Kouvaraki, M., & Duka, T. (2007) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/0097-7403.33.4.484 · Cited by 117
Contextual control over conditioned responding in a latent inhibition paradigm.
Westbrook, R. F., Jones, M. L., Bailey, G. K., & Harris, J. A. (2000) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037//0097-7403.26.2.157 · Cited by 109
The Known Unknowns: Neural Representation of Second-Order Uncertainty, and Ambiguity
Bach, D. R., Hulme, O. J., Penny, W. D., & Dolan, R. J. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.1452-10.2011 · Cited by 109
Evaluating the TD model of classical conditioning
Ludvig, E. A., Sutton, R. S., & Kehoe, E. J. (2012) · Learning & Behavior · doi:10.3758/s13420-012-0082-6 · Cited by 113
Learning Enhances Sensory Processing in Mouse V1 before Improving Behavior
Jurjut, O., Georgieva, P., Busse, L., & Katzner, S. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3485-16.2017 · Cited by 99
Ketamine effects on memory reconsolidation favor a learning model of delusions
Corlett, P. R., Cambridge, V., Gardner, J. M., Piggot, J. S., Turner, D. C., Everitt, J. C., Arana, F. S., Morgan, H. L., Milton, A. L., Lee, J. L., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0065088 · Cited by 105
Asaad, W. F., & Eskandar, E. N. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.3793-11.2011 · Cited by 105
Exploration Disrupts Choice-Predictive Signals and Alters Dynamics in Prefrontal Cortex
Ebitz, R. B., Albarran, E., & Moore, T. (2017) · Neuron · doi:10.1016/j.neuron.2017.12.007 · Cited by 105
Role of Human Ventromedial Prefrontal Cortex in Learning and Recall of Enhanced Extinction
Dunsmoor, J. E., Kroes, M. C. W., Li, J., Daw, N. D., Simpson, H. B., & Phelps, E. A. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.2713-18.2019 · Cited by 110
Dayan, P., & Jyu, A. (2003) · IETE Journal of Research · doi:10.1080/03772063.2003.11416335 · Cited by 105
Bayesian modeling of flexible cognitive control
Jiang, J., Heller, K., & Egner, T. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.06.001 · Cited by 112
Neural Computations Mediating One-Shot Learning in the Human Brain
Lee, S. W., O’Doherty, J. P., & Shimojo, S. (2015) · PLoS Biology · doi:10.1371/journal.pbio.1002137 · Cited by 111
Fox, M. T., Barense, M. D., & Baxter, M. G. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-02-00676.2003 · Cited by 105
Extinction can be enhanced by a concurrent excitor.
Rescorla, R. A. (2000) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037//0097-7403.26.3.251 · Cited by 101
Restoration of the orienting response to a light by a change in its predictive accuracy
Wilson, P. N., Boumphrey, P., & Pearce, J. M. (2007) · The Quarterly Journal of Experimental Psychology Section B · doi:10.1080/02724999208250600 · Cited by 103
Self-citationContext change and associative learning
Rosas, J. M., Todd, T. P., & Bouton, M. E. (2013) · Wiley Interdisciplinary Reviews Cognitive Science · doi:10.1002/wcs.1225 · Cited by 110
Diederen, K. M. J., Spencer, T., Vestergaard, M. D., Fletcher, P. C., & Schultz, W. (2016) · Neuron · doi:10.1016/j.neuron.2016.04.019 · Cited by 102
Reward signals in the cerebellum: Origins, targets, and functional implications
Kostadinov, D., & Häusser, M. (2022) · Neuron · doi:10.1016/j.neuron.2022.02.015 · Cited by 112
Acquisition and extinction in autoshaping.
Kakade, S. M., & Dayan, P. (2002) · Psychological Review · doi:10.1037/0033-295x.109.3.533 · Cited by 101
Metadata
- Authors
- Pearce, J. M., & Hall, G.
- Affiliations
- University of Wales (GB)
- ORCID
- Hall, Geoffrey
- Venue
- Psychological Review
- Published
- 1980
- Volume
- 87
- Issue
- 6
- Pages
- 532-552
- ISSN
- 0033-295X (ISSN-L)
- 1939-1471
- OpenAlex
- W2090144013
- Cited by
- 3,023
- References
- 46
- Citations by year
- 2026: 64 · 2025: 81 · 2024: 88 · 2023: 84 · 2022: 97 · 2021: 97 · 2020: 142 · 2019: 110 · 2018: 104 · 2017: 141 · 2016: 108 · 2015: 95 · 2014: 103 · 2013: 109 · 2012: 102
- FWCI
- 12.96
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Review (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- Pavlovian learning, classical conditioning, excitatory conditioning, inhibitory conditioning, unconditioned stimulus, reinforcer effectiveness, associative learning
- MeSH terms
- Animals, Association Learning, Conditioning, Classical, Humans, Models, Psychological
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
