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 401–500 of 1,010
Test question modulates cue competition between causes and between effects.
Matute, H., Arcediano, F., & Miller, R. R. (1996) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037//0278-7393.22.1.182 · Cited by 105
Summation and configuration in patterning schedules with the rat and rabbit
Bellingham, W. P., Gillette, K., & Kehoe, E. J. (1985) · Animal Learning & Behavior · doi:10.3758/bf03199268 · Cited by 106
What are intrinsic motivations? A biological perspective
Baldassarre, G. (2011) · IEEE International Conference on Development and Learning (ICDL) · doi:10.1109/devlrn.2011.6037367 · Cited by 111
Trask, S., Thrailkill, E. A., & Bouton, M. E. (2016) · Behavioural Processes · doi:10.1016/j.beproc.2016.10.003 · Cited by 100
Neural computations of threat in the aftermath of combat trauma
Homan, P., Levy, I., Feltham, E. M., Gordon, C., Hu, J., Li, J., Pietrzak, R. H., Southwick, S. M., Krystal, J. H., Harpaz‐Rotem, I., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0315-x · Cited by 109
Contextual inference in learning and memory
Heald, J. B., Lengyel, M., & Wolpert, D. M. (2022) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2022.10.004 · Cited by 120
Psychosocial theory and the creation of the risky self
Ogden, J. (1995) · Social Science & Medicine · doi:10.1016/0277-9536(94)00150-r · Cited by 103
Context, attention, and the switch between habit and goal-direction in behavior
Bouton, M. E. (2021) · Learning & Behavior · doi:10.3758/s13420-021-00488-z · Cited by 100
Behavioral and neural processes in counterconditioning: Past and future directions
Keller, N. E., Hennings, A. C., & Dunsmoor, J. E. (2019) · Behaviour Research and Therapy · doi:10.1016/j.brat.2019.103532 · Cited by 104
Signed and unsigned reward prediction errors dynamically enhance learning and memory
Rouhani, N., & Niv, Y. (2021) · eLife · doi:10.7554/elife.61077 · Cited by 114
Akiti, K., Tsutsui‐Kimura, I., Xie, Y., Mathis, A., Markowitz, J. E., Anyoha, R., Datta, S. R., Mathis, M. W., Uchida, N., & Watabe‐Uchida, M. (2022) · Neuron · doi:10.1016/j.neuron.2022.08.022 · Cited by 106
Adams, R. C., Lawrence, N., Verbruggen, F., & Chambers, C. (2016) · Appetite · doi:10.1016/j.appet.2016.11.014 · Cited by 105
Attention and expectation in human predictive learning: The role of uncertainty
Hogarth, L., Dickinson, A., Austin, A., Brown, C., & Duka, T. (2008) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470210701643439 · Cited by 97
Orbitofrontal Cortical Neurons Encode Expectation-Driven Initiation of Reward-Seeking
Moorman, D. E., & Aston‐Jones, G. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.3216-13.2014 · Cited by 104
Associative changes in excitors and inhibitors differ when they are conditioned in compound.
Rescorla, R. A. (2000) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037//0097-7403.26.4.428 · Cited by 101
Free-operant acquisition with delayed reinforcement
Dickinson, A., Watt, A. A., & Griffiths, W. J. (2007) · Quarterly Journal of Experimental Psychology · doi:10.1080/14640749208401019 · Cited by 101
The Nature of Reinforcement in Cerebellar Learning
Thompson, R. F., Thompson, J. K., Kim, J. J., Krupa, D. J., & Shinkman, P. G. (1998) · Neurobiology of Learning and Memory · doi:10.1006/nlme.1998.3845 · Cited by 100
Reconsideration of the role of the hippocampus in learned inhibition
Chan, K.-H., Morell, J. R., Jarrard, L. E., & Davidson, T. L. (2001) · Behavioural Brain Research · doi:10.1016/s0166-4328(00)00363-6 · Cited by 100
Latent inhibition as a measure of learned inattention: some problems and solutions
Lubow, R. E. (1997) · Behavioural Brain Research · doi:10.1016/s0166-4328(97)02307-3 · Cited by 100
Kehoe, E. J. (1986) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037//0097-7403.12.2.186 · Cited by 102
Levy, I., & Schiller, D. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.11.007 · Cited by 95
A simple model for learning in volatile environments
Piray, P., & Daw, N. D. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007963 · Cited by 104
Tsutsui‐Kimura, I., Matsumoto, H., Akiti, K., Yamada, M. M., Uchida, N., & Watabe‐Uchida, M. (2020) · eLife · doi:10.7554/elife.62390 · Cited by 92
Hogarth, L., & Duka, T. (2005) · Psychopharmacology · doi:10.1007/s00213-005-0150-0 · Cited by 102
Myers, C. E., Gluck, M. A., & Granger, R. (1995) · Psychobiology · doi:10.3758/bf03327068 · Cited by 98
Schmajuk, N. A., & Moore, J. W. (1988) · Psychobiology · doi:10.3758/bf03327296 · Cited by 99
Turner, D. C. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh046 · Cited by 94
Predictive Coding in Sensory Cortex
Kok, P., & de Lange, F. P. (2015) · An Introduction to Model-Based Cognitive Neuroscience · doi:10.1007/978-1-4939-2236-9_11 · Cited by 98
Spacing extinction trials alleviates renewal and spontaneous recovery
Urcelay, G. P., Wheeler, D. S., & Miller, R. R. (2009) · Learning & Behavior · doi:10.3758/lb.37.1.60 · Cited by 97
Ermakova, A. O., Knolle, F., Justicia, A., Bullmore, E. T., Jones, P. B., Robbins, T. W., Fletcher, P. C., & Murray, G. K. (2018) · Neuropsychopharmacology · doi:10.1038/s41386-018-0056-2 · Cited by 91
The role of reward prediction in the control of attention.
Sali, A. W., Anderson, B. A., & Yantis, S. (2014) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/a0037267 · Cited by 101
The structure of reinforcement-learning mechanisms in the human brain
O’Doherty, J. P., Lee, S. W., & McNamee, D. (2014) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2014.10.004 · Cited by 106
Norrholm, S. D., Jovanović, T., Gerardi, M. A., Breazeale, K. G., Price, M., Davis, M., Duncan, E., Ressler, K. J., Bradley, B., Rizzo, A., et al. (2016) · Behaviour Research and Therapy · doi:10.1016/j.brat.2016.05.002 · Cited by 96
Delayed extinction attenuates conditioned fear renewal and spontaneous recovery in humans.
Huff, N. C., Hernandez, J. A., Blanding, N. Q., & LaBar, K. S. (2009) · Behavioral Neuroscience · doi:10.1037/a0016511 · Cited by 109
A requirement for memory retrieval during and after long-term extinction learning
Ouyang, M., & THOMAS, S. A. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0502315102 · Cited by 94
Continuous monitoring of human contingency judgment across trials
Shanks, D. R. (1985) · Memory & Cognition · doi:10.3758/bf03197008 · Cited by 97
Learning about Multiple Attributes of Reward in Pavlovian Conditioning
Delamater, A. R., & Oakeshott, S. (2007) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1390.008 · Cited by 96
A theory of conditioning: Inductive learning within rule-based default hierarchies.
Holyoak, K. J., Koh, K., & Nisbett, R. E. (1989) · Psychological Review · doi:10.1037/0033-295x.96.2.315 · Cited by 93
The functions of contexts in associative learning
Urcelay, G. P., & Miller, R. R. (2014) · Behavioural Processes · doi:10.1016/j.beproc.2014.02.008 · Cited by 99
McNally, G. P., & Cole, S. (2006) · Behavioral Neuroscience · doi:10.1037/0735-7044.120.2.313 · Cited by 94
Reilly, S., Harley, C. W., & Revusky, S. (1993) · Behavioral Neuroscience · doi:10.1037//0735-7044.107.6.996 · Cited by 93
A Psychophysiological Theory of Reinforcement, Drive, Motivation, and Attention
Grossberg, S. (1987) · Advances in psychology · doi:10.1016/s0166-4115(08)60905-x · Cited by 93
Markou, A., Salamone, J. D., Bussey, T. J., Mar, A. C., Brunner, D., Gilmour, G., & Balsam, P. D. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.08.007 · Cited by 95
Theta oscillations synchronize human medial prefrontal cortex and amygdala during fear learning
Chen, S., Tan, Z., Xia, W., Gomes, C. A., Zhang, X., Zhou, W., Liang, S., Axmacher, N., & Wang, L. (2021) · Science Advances · doi:10.1126/sciadv.abf4198 · Cited by 95
Atlas, L. Y., Doll, B. B., Li, J., Daw, N. D., & Phelps, E. A. (2016) · eLife · doi:10.7554/elife.15192 · Cited by 95
Aguado, L., Symonds, M., & Hall, G. (1994) · Animal Learning & Behavior · doi:10.3758/bf03199919 · Cited by 93
Self-citationYoung, S. L., & Fanselow, M. S. (1992) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037//0097-7403.18.4.400 · Cited by 92
Microinjection of morphine into the nucleus accumbens impairs contextual learning in rats.
Westbrook, R. F., Good, A. J., & Kiernan, M. J. (1997) · Behavioral Neuroscience · doi:10.1037//0735-7044.111.5.996 · Cited by 93
Amygdala-dependent and amygdala-independent pathways for contextual fear conditioning
Ponnusamy, R., Poulos, A. M., & Fanselow, M. S. (2007) · Neuroscience · doi:10.1016/j.neuroscience.2007.04.026 · Cited by 95
Orbitofrontal control of visual cortex gain promotes visual associative learning
Liu, D., Deng, J., Zhang, Z., Zhang, Z., Sun, Y.-G., Yang, T., & Yao, H. (2020) · Nature Communications · doi:10.1038/s41467-020-16609-7 · Cited by 99
Positive and negative patterning in human classical skin conductance response conditioning
Lachnit, H., & Kimmel, H. D. (1993) · Animal Learning & Behavior · doi:10.3758/bf03197997 · Cited by 93
Extinction of the context and latent inhibition
Baker, A. G., & Mercier, P. (1982) · Learning and Motivation · doi:10.1016/0023-9690(82)90001-7 · Cited by 93
Uncertainty and predictiveness determine attention to cues during human associative learning
Beesley, T., Nguyen, K. P., Pearson, D., & Le Pelley, M. E. (2015) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2015.1009919 · Cited by 85
Dopamine neurons learn relative chosen value from probabilistic rewards
Lak, A., Stauffer, W. R., & Schultz, W. (2016) · eLife · doi:10.7554/elife.18044 · Cited by 88
Boll, S., Gamer, M., Gluth, S., Finsterbusch, J., & Büchel, C. (2012) · European Journal of Neuroscience · doi:10.1111/ejn.12094 · Cited by 98
Transient activation of midbrain dopamine neurons by reward risk
Fiorillo, C. D. (2011) · Neuroscience · doi:10.1016/j.neuroscience.2011.09.037 · Cited by 90
Human fear conditioning: From neuroscience to the clinic
Fullana, M. A., Dunsmoor, J. E., Schruers, K. R. J., Savage, H. S., Bach, D. R., & Harrison, B. J. (2019) · Behaviour Research and Therapy · doi:10.1016/j.brat.2019.103528 · Cited by 96
Rosas, J. M., & Bouton, M. E. (1997) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037//0097-7403.23.3.283 · Cited by 94
On Surprise, Change, and the Effect of Recent Outcomes
Nevo, I., & Erev, I. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00024 · Cited by 90
Lesions of the Amygdala Central Nucleus Alter Performance on a Selective Attention Task
Holland, P. C., Han, J., & Gallagher, M. (2000) · Journal of Neuroscience · doi:10.1523/jneurosci.20-17-06701.2000 · Cited by 90
Shaping robot behavior using principles from instrumental conditioning
Saksida, L. M., Raymond, S. M., & Touretzky, D. S. (1997) · Robotics and Autonomous Systems · doi:10.1016/s0921-8890(97)00041-9 · Cited by 90
Role of the hippocampus in temporal and spatial navigation
Schmajuk, N. A. (1990) · Behavioural Brain Research · doi:10.1016/0166-4328(90)90028-d · Cited by 90
Feedforward versus feedbackward: An ethological alternative to the law of effect
Gardner, R. A., & Gardner, B. T. (1988) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00058258 · Cited by 91
The conditions that promote fear learning: Prediction error and Pavlovian fear conditioning
Li, S. S. Y., & McNally, G. P. (2014) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2013.05.002 · Cited by 89
Expectations and outcomes: decision-making in the primate brain
McCoy, A. N., & Platt, M. L. (2004) · Journal of Comparative Physiology A · doi:10.1007/s00359-004-0565-9 · Cited by 90
Overt attention and predictiveness in human contingency learning.
Pelley, M. E. L., Beesley, T., & Griffiths, O. (2011) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/a0021384 · Cited by 102
Conditioning from an information processing perspective
Gallistel, C. R. (2003) · Behavioural Processes · doi:10.1016/s0376-6357(03)00019-6 · Cited by 84
Associative deficit accounts of disrupted latent inhibition and blocking in schizophrenia
Escobar, M. E., Oberling, P., & Miller, R. R. (2002) · Neuroscience & Biobehavioral Reviews · doi:10.1016/s0149-7634(01)00067-7 · Cited by 90
Green, J. T., & Woodruff‐Pak, D. S. (2000) · Psychological Bulletin · doi:10.1037/0033-2909.126.1.138 · Cited by 91
Balaz, M. A., Capra, S., Kasprow, W. J., & Miller, R. R. (1982) · Animal Learning & Behavior · doi:10.3758/bf03212277 · Cited by 89
The Dopamine Prediction Error: Contributions to Associative Models of Reward Learning
Nasser, H. M., Calu, D. J., Schoenbaum, G. M., & Sharpe, M. J. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00244 · Cited by 97
Acquired equivalence and distinctiveness of cues.
Honey, R. C., & Hall, G. (1989) · PubMed · Cited by 88
Self-citationDissociable Learning Processes Underlie Human Pain Conditioning
Zhang, S., Mano, H., Ganesh, G., Robbins, T. W., & Seymour, B. (2015) · Current Biology · doi:10.1016/j.cub.2015.10.066 · Cited by 84
What do children learn from testimony?
Harris, P. L. (2002) · Cambridge University Press eBooks · doi:10.1017/cbo9780511613517.018 · Cited by 88
Sensitization and habituation regulate reinforcer effectiveness
McSweeney, F. K., & Murphy, E. S. (2008) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2008.07.002 · Cited by 87
Singh, N. N., & Solman, R. T. (1990) · Journal of Applied Behavior Analysis · doi:10.1901/jaba.1990.23-525 · Cited by 86
Kopala‐Sibley, D. C., Cyr, M., Finsaas, M. C., O’Rawe, J. F., Huang, A., Tottenham, N., & Klein, D. N. (2018) · Child Development · doi:10.1111/cdev.13126 · Cited by 87
A feature-specific prediction error model explains dopaminergic heterogeneity
Lee, R. S., Sagiv, Y., Engelhard, B., Witten, I. B., & Daw, N. D. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01689-1 · Cited by 87
Herrero, E. M., & Marco‐Pallarés, J. (2013) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00516 · Cited by 96
Evidence of signaling benefits to contrasting internal color boundaries in warning coloration
Aronsson, M., & Gamberale‐Stille, G. (2012) · Behavioral Ecology · doi:10.1093/beheco/ars170 · Cited by 85
Cognitive mechanisms associated with auditory sensory gating
Jones, L., Hills, P. J., Dick, K. M., Jones, S. P., & Bright, P. (2015) · Brain and Cognition · doi:10.1016/j.bandc.2015.12.005 · Cited by 95
Associations and propositions: The case for a dual-process account of learning in humans
McLaren, I. P. L., Forrest, C., McLaren, R., Jones, F. W., Aitken, M. R. F., & Mackintosh, N. J. (2013) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2013.09.014 · Cited by 91
Learning and Stress Shape the Reward Response Patterns of Serotonin Neurons
Zhong, W., Li, Y., Feng, Q., & Luo, M. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.1181-17.2017 · Cited by 90
Configural processes in human associative learning.
Shanks, D. R., Charles, D., Darby, R. J., & Azmi, A. (1998) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.24.6.1353 · Cited by 85
Scaling prediction errors to reward variability benefits error-driven learning in humans
Diederen, K. M. J., & Schultz, W. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00483.2015 · Cited by 69
Computational models of adaptive behavior and prefrontal cortex
Soltani, A., & Koechlin, É. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-01123-1 · Cited by 86
Holland, P. C., & Gallagher, M. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.0390-06.2006 · Cited by 85
A Critical Role for the Anterior Thalamus in Directing Attention to Task-Relevant Stimuli
Wright, N. F., Vann, S. D., Aggleton, J. P., & Nelson, A. J. D. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4945-14.2015 · Cited by 94
The power of associative learning and the ontogeny of optimal behaviour
Enquist, M., Lind, J., & Ghirlanda, S. (2016) · Royal Society Open Science · doi:10.1098/rsos.160734 · Cited by 89
Stress attenuates the flexible updating of aversive value
Raio, C. M., Hartley, C. A., Orederu, T. A., Li, J., & Phelps, E. A. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1702565114 · Cited by 84
Holland, P. C. (1997) · Animal Learning & Behavior · doi:10.3758/bf03209846 · Cited by 81
Revision of Retrieval Theory of Forgetting: What does Make Information Context-Specific?
Rosas, J. M., Aguilera, J. E. C., Ramos‐Álvarez, M. M., & Abad, M. J. F. (2006) · Redalyc (Universidad Autónoma del Estado de México) · Cited by 80
On the nature of CS and US representations in Pavlovian learning
Delamater, A. R. (2011) · Learning & Behavior · doi:10.3758/s13420-011-0036-4 · Cited by 87
Analysis of Interaction in Binary Odorant Mixtures
Smith, B. H. (1998) · Physiology & Behavior · doi:10.1016/s0031-9384(98)00142-5 · Cited by 86
Fear but not awareness predicts enhanced sensory processing in fear conditioning
Moratti, S., Keil, A., & Miller, G. A. (2006) · Psychophysiology · doi:10.1111/j.1464-8986.2006.00386.x · Cited by 83
Overshadowing and latent inhibition counteract each other: Support for the comparator hypothesis.
Blaisdell, A. P., Bristol, A. S., Gunther, L. M., & Miller, R. R. (1998) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/0097-7403.24.3.335 · Cited by 83
Distinguishing Associative and Probabilistic Contrast Theories of Human Contingency Judgment
Shanks, D. R., López, F. J., Darby, R. J., & Dickinson, A. (1996) · The Psychology of learning and motivation/The psychology of learning and motivation · doi:10.1016/s0079-7421(08)60563-0 · Cited by 83
A mechanistic account of serotonin’s impact on mood
Michely, J., Eldar, E., Martin, I. M., & Dolan, R. J. (2020) · Nature Communications · doi:10.1038/s41467-020-16090-2 · Cited by 72
Specificity in the reactivation of infant memory
Rovee‐Collier, C., Patterson, J., & Hayne, H. (1985) · Developmental Psychobiology · doi:10.1002/dev.420180611 · Cited by 82
Motivational control of sign-tracking behaviour: A theoretical framework
Anselme, P. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.03.014 · Cited by 85
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