Uncertainty and predictiveness determine attention to cues during human associative learning
Abstract
Prior research has suggested that attention is determined by exploiting what is known about the most valid predictors of outcomes and exploring those stimuli that are associated with the greatest degree of uncertainty about subsequent events. Previous studies of human contingency learning have revealed evidence for one or other of these processes, but differences in the designs and procedures of these studies make it difficult to pinpoint the crucial determinant of whether attentional exploitation or exploration will dominate. Here we present two studies in which we systematically manipulated both the predictiveness of cues and uncertainty regarding the outcomes with which they were associated. This allowed us to demonstrate, for the first time, evidence of both attentional exploration and exploitation within the same experiment. Moreover, while the effect of predictiveness persisted to influence the rate of novel learning about the same cues in a second stage, the effect of uncertainty did not. This suggests that attentional exploration is more sensitive to a change of context than is exploitation. The pattern of data is simulated with a hybrid attentional model.
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When a behavior is in habit mode, it exploits the tried and true; when it is in action mode, it can explore new opportunities or connections.
“When a behavior is in habit mode, it exploits the tried and true; when it is in action mode, it can presumably explore new opportunities or connections (cf. Beeseley et al., 2015)”
From Context, attention, and the switch between habit and goal-direction in behavior (2021) · cites this paper as Beeseley et al., 2015
Cites
Brainard, D. H. (1997) · Spatial Vision · doi:10.1163/156856897x00357 · Cited by 19,308 · see citing works
The VideoToolbox software for visual psychophysics: transforming numbers into movies
Pelli, D. G. (1997) · Spatial Vision · doi:10.1163/156856897x00366 · Cited by 11,110 · see citing works
Rescorla, R. A. (1972) · Medical Entomology and Zoology · Cited by 7,268 · see citing works
Classical conditioning II: Current research and theory.
Black, A. H., & Prokasy, W. F. (1972) · Appleton-Century-Crofts eBooks · Cited by 4,449 · see citing works
Pearce, J. M., & Hall, G. (1980) · Psychological Review · doi:10.1037/0033-295x.87.6.532 · Cited by 3,023 · see citing works
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 · see citing works
Identifying fixations and saccades in eye-tracking protocols
Salvucci, D. D., & Goldberg, J. H. (2000) · ACM Symposium on Eye Tracking Research and Applications (ETRA) · doi:10.1145/355017.355028 · Cited by 2,229 · see citing works
Confidence intervals in within-subject designs: A simpler solution to Loftus and Masson's method
Cousineau, D. (2005) · Tutorials in Quantitative Methods for Psychology · doi:10.20982/tqmp.01.1.p042 · Cited by 1,969 · see citing works
A model for stimulus generalization in Pavlovian conditioning.
Pearce, J. M. (1987) · Psychological Review · doi:10.1037/0033-295x.94.1.61 · Cited by 1,046 · see citing works
Similarity and discrimination: A selective review and a connectionist model.
Pearce, J. M. S. (1994) · Psychological Review · doi:10.1037/0033-295x.101.4.587 · Cited by 750 · see citing works
Quantitative Analyses of Behavior
(2019) · Psychology Press eBooks · doi:10.4324/9781315788999 · Cited by 422 · see citing works
Le Pelley, M. E. (2004) · The Quarterly Journal of Experimental Psychology Section B · doi:10.1080/02724990344000141 · Cited by 360 · see citing works
Eyetracking and selective attention in category learning
Rehder, B., & Hoffman, A. B. (2005) · Cognitive Psychology · doi:10.1016/j.cogpsych.2004.11.001 · Cited by 315 · see citing works
Evaluation and development of a connectionist theory of configural learning
Pearce, J. M. S. (2002) · Animal Learning & Behavior · doi:10.3758/bf03192911 · Cited by 228 · see citing works
Esber, G. R., & Haselgrove, M. (2011) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2011.0836 · Cited by 178 · see citing works
Learned Associability and Associative Change in Human Causal Learning
Pelley, M. E. L., & McLaren, I. P. L. (2003) · The Quarterly Journal of Experimental Psychology Section B · doi:10.1080/02724990244000179 · Cited by 153 · see citing works
Kruschke, J. K., Kappenman, E. S., & Hetrick, W. P. (2005) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.31.5.830 · Cited by 152 · see citing works
Attention and Associative Learning: From Brain to Behaviour
Mitchell, C. J., & Pelley, M. E. L. (2010) · Cited by 146 · see citing works
Dimensional Relevance Shifts in Category Learning
Kruschke, J. (1996) · Connection science · doi:10.1080/095400996116893 · Cited by 138 · see citing works
Contextual effects in latent inhibition with an appetitive conditioning procedure
Channell, S., & Hall, G. (1983) · Animal Learning & Behavior · doi:10.3758/bf03212309 · Cited by 134 · see citing works
Two theories of attention: a review and a possible integration
Pearce, J. M., & Mackintosh, N. J. (2010) · Oxford University Press eBooks · Cited by 123 · see citing works
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 113 · see citing works
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 · see citing works
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 89 · see citing works
Self-citationStereotype formation: Biased by association.
Pelley, M. E. L., Reimers, S. J., Calvini, G., Spears, R., Beesley, T., & Murphy, R. A. (2010) · Journal of Experimental Psychology General · doi:10.1037/a0018210 · Cited by 65 · see citing works
Self-citationA configural theory of attention and associative learning
George, D. N., & Pearce, J. M. (2012) · Learning & Behavior · doi:10.3758/s13420-012-0078-2 · Cited by 59 · see citing works
The influence of blocking on overt attention and associability in human learning.
Beesley, T., & Pelley, M. E. L. (2010) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/a0019526 · Cited by 53 · see citing works
Self-citationPrediction and uncertainty in human Pavlovian to instrumental transfer.
Trick, L., Hogarth, L., & Duka, T. (2011) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/a0022310 · Cited by 46 · see citing works
Bonardi, C., Graham, S., Hall, G., & Mitchell, C. J. (2005) · Psychonomic Bulletin & Review · doi:10.3758/bf03196351 · Cited by 41 · see citing works
Contextual control of negative transfer produced by prior CS-US pairings
Swartzentruber, D., & Bouton, M. E. (1986) · Learning and Motivation · doi:10.1016/0023-9690(86)90004-4 · Cited by 37 · see citing works
Predictive History in an Allergy Prediction Task
Lochmann, T., & Wills, A. J. (2019) · Routledge eBooks · doi:10.4324/9781315782362-46 · Cited by 37 · see citing works
Negative Transfer in Human Associative Learning
Griffiths, O., Johnson, A. M., & Mitchell, C. J. (2011) · Psychological Science · doi:10.1177/0956797611419305 · Cited by 36 · see citing works
Computational Models of Conditioning
Schmajuk, N. A. (2010) · Cambridge University Press eBooks · doi:10.1017/cbo9780511760402 · Cited by 33 · see citing works
(2019) · Routledge eBooks · doi:10.4324/9781315782362 · Cited by 31 · see citing works
The effect of predictive history on the learning of sub-sequence contingencies
Beesley, T., & Pelley, M. E. L. (2009) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470210902831767 · Cited by 30 · see citing works
Self-citationLearned predictiveness effects in humans: A function of learning, performance, or both?
Pelley, M. E. L., Suret, M. B., & Beesley, T. (2009) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/a0014315 · Cited by 26 · see citing works
Self-citationPelley, M. E. L., Mitchell, C. J., & Johnson, A. M. (2013) · Journal of Experimental Psychology Animal Behavior Processes · doi:10.1037/a0031230 · Cited by 26 · see citing works
Pelley, M. E. L., Beesley, T., & Griffiths, O. (2013) · Journal of Experimental Psychology Animal Learning and Cognition · doi:10.1037/xan0000006 · Cited by 21 · see citing works
Self-citationThe hybrid modeling approach to conditioning
Pelley, M. E. L. (2010) · Cambridge University Press eBooks · doi:10.1017/cbo9780511760402.004 · Cited by 14 · see citing works
Dimensional Shift and the Transfer of Attention
Whitney, L., & White, K. G. (1993) · The Quarterly Journal of Experimental Psychology Section B · doi:10.1080/14640749308401087 · Cited by 13 · see citing works
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Attention and associative learning in humans: An integrative review.
Le Pelley, M. E., Mitchell, C. J., Beesley, T., George, D. N., & Wills, A. J. (2016) · Psychological Bulletin · doi:10.1037/bul0000064 · Cited by 329 · see citing works
Self-citationWhen Is More Uncertainty Better? A Model of Uncertainty Regulation and Effectiveness
Griffin, M. A., & Grote, G. (2020) · Academy of Management Review · doi:10.5465/amr.2018.0271 · Cited by 223 · see citing works
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 · see citing works
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Rouhani, N., & Niv, Y. (2021) · eLife · doi:10.7554/elife.61077 · Cited by 105 · see citing works
Thrailkill, E. A., Trask, S., Vidal, P., Alcalá, J. A., & Bouton, M. E. (2018) · Journal of Experimental Psychology Animal Learning and Cognition · doi:10.1037/xan0000188 · Cited by 71 · see citing works
Prioritizing pleasure and pain: attentional capture by reward-related and punishment-related stimuli
Watson, P., Pearson, D., Wiers, R. W. H. J., & Pelley, M. E. L. (2019) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2018.12.002 · Cited by 68 · see citing works
Self-citationKoenig, S., Uengoer, M., & Lachnit, H. (2017) · Psychophysiology · doi:10.1111/psyp.13020 · Cited by 45 · see citing works
A computational account of threat-related attentional bias
Wise, T., Michely, J., Dayan, P., & Dolan, R. (2019) · PLoS Comput. Biol. · doi:10.1371/journal.pcbi.1007341 · Cited by 37 · see citing works
An examination of active inference in autistic adults using immersive virtual reality
Arthur, T., Harris, D., Buckingham, G., Brosnan, M., Wilson, M., Williams, G., & Vine, S. (2021) · Scientific Reports · doi:10.1038/s41598-021-99864-y · Cited by 44 · see citing works
From sign-tracking to attentional bias: Implications for gambling and substance use disorders
Anselme, P., & Robinson, M. J. F. (2020) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2020.109861 · Cited by 41 · see citing works
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Pelley, M. E. L., Pearson, D., Porter, A., Yee, H. F., & Luque, D. (2017) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2017.1313874 · Cited by 42 · see citing works
Self-citationThe development and present status of the SOP model of associative learning
Vogel, E. H., Ponce, F. P., & Wagner, A. R. (2018) · Quarterly Journal of Experimental Psychology · doi:10.1177/1747021818777074 · Cited by 42 · see citing works
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Sharpe, M. J. (2023) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.08.019 · Cited by 38 · see citing works
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Walker, A. R., Luque, D., Pelley, M. E. L., & Beesley, T. (2019) · Psychonomic Bulletin & Review · doi:10.3758/s13423-019-01653-2 · Cited by 38 · see citing works
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Luque, D., Vadillo, M. A., Pelley, M. E. L., & Beesley, T. (2016) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2016.1188407 · Cited by 34 · see citing works
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Benitez, V. L., & Saffran, J. R. (2018) · Current Biology · doi:10.1016/j.cub.2018.06.017 · Cited by 34 · see citing works
Koenig, S., Kadel, H., Uengoer, M., Schubö, A., & Lachnit, H. (2017) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2017.00128 · Cited by 32 · see citing works
Easdale, L. C., Pelley, M. E. L., & Beesley, T. (2017) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2017.1363257 · Cited by 29 · see citing works
Self-citationAchievement motivation modulates Pavlovian aversive conditioning to goal-relevant stimuli
Stussi, Y., Ferrero, A., Pourtois, G., & Sander, D. (2019) · npj Science of Learning · doi:10.1038/s41539-019-0043-3 · Cited by 29 · see citing works
Arthur, T., & Harris, D. (2021) · Cortex · doi:10.1016/j.cortex.2021.09.017 · Cited by 23 · see citing works
Lake, J. I., Spielberg, J. M., Infantolino, Z. P., Crocker, L. D., Yee, C. M., Heller, W., & Miller, G. A. (2019) · Psychophysiology · doi:10.1111/psyp.13381 · Cited by 21 · see citing works
Confirmation bias optimizes reward learningPreprint
Tarantola, T., Folke, T., Boldt, A., Perez, O. D., & Martino, B. D. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.27.433214 · Cited by 22 · see citing works
The blocking effect in associative learning involves learned biases in rapid attentional capture
Luque, D., Vadillo, M. A., Gutiérrez‐Cobo, M. J., & Pelley, M. E. L. (2016) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2016.1262435 · Cited by 21 · see citing works
Uncertainty modulates value-driven attentional capture
Cho, S. A., & Cho, Y. S. (2020) · Attention Perception & Psychophysics · doi:10.3758/s13414-020-02171-3 · Cited by 25 · see citing works
Reversal training facilitates acquisition of new learning in a Morris water maze
Alcalá, J. A., Callejas-Aguilera, J. E., Nelson, J. B., & Rosas, J. M. (2019) · Learning & Behavior · doi:10.3758/s13420-019-00392-7 · Cited by 19 · see citing works
Beesley, T., Hanafi, G., Vadillo, M. A., Shanks, D. R., & Livesey, E. J. (2018) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/xlm0000467 · Cited by 18 · see citing works
Self-citationUncertainty, entrepreneurial orientation, and the pursuit of M&A: Managing the unpredictable
Simpson, J. J., & Sariol, M. (2022) · Journal of business research · doi:10.1016/j.jbusres.2022.01.006 · Cited by 17 · see citing works
Learned predictiveness models predict opposite attention biases in the inverse base-rate effect.
Don, H. J., Beesley, T., & Livesey, E. J. (2019) · Journal of Experimental Psychology Animal Learning and Cognition · doi:10.1037/xan0000196 · Cited by 16 · see citing works
Self-citationUncertainty-modulated attentional capture: Outcome variance increases attentional priority.
Pearson, D., Chong, A., Chow, J. Y. L., Garner, K., Theeuwes, J., & Pelley, M. E. L. (2024) · Journal of Experimental Psychology General · doi:10.1037/xge0001586 · Cited by 15 · see citing works
Self-citationA rise in prediction error increases attention to irrelevant cues
Torrents‐Rodas, D., Koenig, S., Uengoer, M., & Lachnit, H. (2020) · Biological Psychology · doi:10.1016/j.biopsycho.2020.108007 · Cited by 14 · see citing works
Context dependency as a Function of Prediction Error-Based Attention
Rosas, J. M., & Nelson, J. B. (2019) · Psicologica · doi:10.2478/psicolj-2019-0003 · Cited by 13 · see citing works
Protection from uncertainty in the exploration/exploitation trade-off.
Walker, A. R., Navarro, D., Newell, B. R., & Beesley, T. (2021) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/xlm0000883 · Cited by 13 · see citing works
Self-citationChoi, E., Kim, C. G., & Lee, K. C. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.557292 · Cited by 17 · see citing works
The redundancy effect in human causal learning: No evidence for changes in selective attention
Jones, P. M., & Zaksaite, T. (2017) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2017.1350868 · Cited by 11 · see citing works
Learned predictiveness and outcome predictability effects are not simply two sides of the same coin.
Thorwart, A., Livesey, E. J., Wilhelm, F., Liu, W., & Lachnit, H. (2017) · Journal of Experimental Psychology Animal Learning and Cognition · doi:10.1037/xan0000150 · Cited by 11 · see citing works
Harris, A., Davenport, M. K., & Fasbender, U. (2024) · Work Aging and Retirement · doi:10.1093/workar/waae008 · Cited by 10 · see citing works
Flexible learning in complex worlds
Leimar, O., Quiñones, A. E., & Bshary, R. (2023) · Behavioral Ecology · doi:10.1093/beheco/arad109 · Cited by 8 · see citing works
Evidence for two attentional mechanisms during learning
Torrents‐Rodas, D., Koenig, S., Uengoer, M., & Lachnit, H. (2021) · Quarterly Journal of Experimental Psychology · doi:10.1177/17470218211019308 · Cited by 9 · see citing works
Tommaso, M. D., Mastropasqua, T., & Turatto, M. (2018) · Psychological Research · doi:10.1007/s00426-017-0960-9 · Cited by 9 · see citing works
Testing learning mechanisms of rule-based judgment.
Hoffmann, J., von Helversen, B., & Rieskamp, J. (2019) · Decision · doi:10.1037/dec0000109 · Cited by 7 · see citing works
Uncertainty and predictiveness modulate attention in human predictive learning.
Chao, C., McGregor, A., & Sanderson, D. J. (2020) · Journal of Experimental Psychology General · doi:10.1037/xge0000991 · Cited by 8 · see citing works
Reed, P. (2018) · Research in Autism · doi:10.1016/j.rasd.2018.10.006 · Cited by 7 · see citing works
Discrimination Reversal Facilitates Contextual Conditioning in Rats’ Appetitive conditioning
Alcalá, J. A., González, G., Aristizabal, J. A., Callejas-Aguilera, J. E., & Rosas, J. M. (2018) · Psicologica · doi:10.2478/psicolj-2018-0004 · Cited by 5 · see citing works
Cue predictiveness and uncertainty determine cue representation during visual statistical learningPreprint
Zhang, P., Chen, H., & Tong, S. X. (2023) · Learning & Memory · doi:10.1101/lm.053777.123 · Cited by 5 · see citing works
Weichart, E. R., Unger, L., King, N. R., Sloutsky, V. M., & Turner, B. M. (2024) · Psychological Review · doi:10.1037/rev0000475 · Cited by 4 · see citing works
Attention biases in the inverse base-rate effect persist into new learning
Don, H. J., & Livesey, E. J. (2020) · Quarterly Journal of Experimental Psychology · doi:10.1177/1747021820985522 · Cited by 4 · see citing works
Transfer of dimensional associability in human contingency learning.
Kattner, F., & Green, C. S. (2015) · Journal of Experimental Psychology Animal Learning and Cognition · doi:10.1037/xan0000082 · Cited by 4 · see citing works
Zhang, Z., Zhang, Z., & Zhang, Z. (2023) · Aslib Journal of Information Management · doi:10.1108/ajim-08-2022-0369 · Cited by 3 · see citing works
Conditioned anticipatory outcome searching in humans
Nelson, J. B., Navarro, A. D., & Sanjuán, M. D. C. (2019) · Behavioural Processes · doi:10.1016/j.beproc.2019.05.015 · Cited by 3 · see citing works
Mackintosh, pearce-hall and time: An EEG study on Inhibition of return
Russo, S., Burns, N. R., & Baetu, I. (2019) · Biological Psychology · doi:10.1016/j.biopsycho.2019.107731 · Cited by 3 · see citing works
The effect of prediction error on overt attention and learning in humans
Torrents‐Rodas, D., Koenig, S., Uengoer, M., & Lachnit, H. (2023) · Behavioural Processes · doi:10.1016/j.beproc.2023.104843 · Cited by 2 · see citing works
Prediction error generated by extinction attenuates overshadowing in humans
Jiménez-Castillo, R., Aguilar-Espinosa, C., & Vila, J. (2025) · Learning and Motivation · doi:10.1016/j.lmot.2025.102111 · Cited by 2 · see citing works
Whether, When, How, and Why Sales Managers Should Be Involved in Sales Teams
Chavez, D., Burchett, M. R., & Murtha, B. R. (2026) · Journal of Marketing · doi:10.1177/00222429261448212 · Cited by 2 · see citing works
The role of prediction in learned predictiveness.
Eatherington, C. J., & Haselgrove, M. (2022) · Journal of Experimental Psychology Animal Learning and Cognition · doi:10.1037/xan0000330 · Cited by 2 · see citing works
Control over reward gain unlocks the reward cue motivational salience
Tommaso, M. D., & Turatto, M. (2022) · Motivation and Emotion · doi:10.1007/s11031-022-10001-2 · Cited by 3 · see citing works
An Empirical Evaluation of Models for How People Learn Cue Search Orders
Mistry, P. K., Lee, M. D., & Newell, B. R. (2016) · eScholarship (California Digital Library) · Cited by 2 · see citing works
Exploitative and Exploratory Attention in a Four-Armed Bandit Task.
Walker, A. R., Pelley, M. E. L., & Beesley, T. (2017) · Lancaster EPrints (Lancaster University) · Cited by 2 · see citing works
Self-citationRecovery of attention with renewalPreprint
Nelson, J. B., Craddock, P., Molet, M., & Renaux, C. (2017) · Learning & Memory · doi:10.1101/lm.045682.117 · Cited by 2 · see citing works
Flexibility of learning in complex worldsPreprint
Leimar, O., Quiñones, A. E., & Bshary, R. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.12.544544 · Cited by 2 · see citing works
Human temporal learning with mixed signals
Subramaniam, S., & Kyonka, E. G. E. (2021) · Behavioural Processes · doi:10.1016/j.beproc.2021.104568 · Cited by 1 · see citing works
Sengupta, A., & Sridharan, D. (2025) · PLoS Biology · doi:10.1371/journal.pbio.3003234 · Cited by 1 · see citing works
The role of selective attention in value-modulated attentional capture
Garre-Frutos, F., Vadillo, M. A., Theeuwes, J., van Moorselaar, D., & Lupiáñez, J. (2026) · Psychonomic Bulletin & Review · doi:10.3758/s13423-026-02964-x · Cited by 1 · see citing works
González, G., Alcalá, J. A., Ogállar, P. M., Rosas, J. M., & Callejas-Aguilera, J. E. (2021) · Behavioural Processes · doi:10.1016/j.beproc.2021.104529 · Cited by 1 · see citing works
Uncertain reward cues show increased dominance in early phases of binocular rivalryPreprint
Pothast, M., Koenig, S., Lachnit, H., & Wolfgang Einhäuser, A. (2021) · doi:10.31234/osf.io/2t9un · Cited by 1 · see citing works
Two Distinct Attentional Priorities Guide Exploratory and Exploitative Gaze in ParallelPreprint
Wen, X., Hassani, A. S., Neumann, A. R., Tiesinga, P. H. E., & Womelsdorf, T. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.20.677503 · Cited by 1 · see citing works
Dissociating variations in attention with schizotypy and anxiety
Granger, K. T. (2017) · Nottingham ePrints (University of Nottingham)
Reward Recognition in NCLT Practice
Wasserman, T. H., & Wasserman, L. D. (2017) · Springer eBooks · doi:10.1007/978-3-319-60849-5_5
Getting Started With Eye Tracking
Pearson, D., Pelley, M. E. L., & Beesley, T. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-813092-6.09990-1
Self-citationExplaining learned predictiveness: Roles of attention and integration of associative structures.
Rodrı́guez, G., & Hall, G. (2019) · Journal of Experimental Psychology Animal Learning and Cognition · doi:10.1037/xan0000202
Márquez, I., Loewinger, G. C., Vargas, J. P., López, J. C., Díaz, E., & Esber, G. R. (2022) · Behavioral Neuroscience · doi:10.1037/bne0000505
Cue Predictiveness and Uncertainty Determine Cue Perception During Statistical LearningPreprint
Zhang, P., Chen, H., & Tong, S. X. (2022) · doi:10.31234/osf.io/s2qu9
Tradeoffs in Uncertain Decision Making
Strickland, L. J. G., & Boag, R. J. (2023) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780197501061.013.19
Papastamou, F., Destrebecqz, A., & Kissine, M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4668511
The role of selection history in the learned predictiveness effect.
Balea, P., Molinero, S., Vadillo, M. A., & Luque, D. (2024) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/xhp0001240
Aperiodic Pupil Fluctuations at Rest Predict Orienting of Visual Attention
Wang, R., & Jia, J. (2025) · Psychophysiology · doi:10.1111/psyp.14755
Social and non-social directional cues differentially orient attention by learned habit
Salera, C., Yankouskaya, A., Petrucci, M., & Pecchinenda, A. (2025) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2025.1636726
Prasad, S. G., Talebi, N., Wendiggensen, P., Mückschel, M., Hommel, B., & Beste, C. (2025) · Human Brain Mapping · doi:10.1002/hbm.70333
Predictable events enhance word learning in toddlersPreprint
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Self-citationRave, J., Hanert, A., Tabi, Y. A., Fiedler, Y., Philippen, S., Granert, O., Leypoldt, F., Jan Born, A., Burgalossi, A., Schönfeld, R., et al. (2026) · Brain Communications · doi:10.1093/braincomms/fcag255
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- Authors
- Beesley, T., Nguyen, K. P., Pearson, D., & Le Pelley, M. E.
- Affiliations
- UNSW Sydney (AU)
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
- Corresponding author
- Beesley, Tom
- Venue
- Quarterly Journal of Experimental Psychology
- Publisher
- SAGE Publications
- Published
- 2015-11
- Volume
- 68
- Issue
- 11
- Pages
- 2175-2199
- ISSN
- 0033-555X (ISSN-L)
- 1747-0218
- 1747-0226
- OpenAlex
- W2009002319
- Cited by
- 85
- References
- 40
- Citations by year
- 2026: 8 · 2025: 6 · 2024: 4 · 2023: 8 · 2022: 5 · 2021: 11 · 2020: 7 · 2019: 13 · 2018: 8 · 2017: 10 · 2016: 4 · 2015: 1
- FWCI
- 4.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Quarterly Journal of Experimental Psychology (publishedVersion)
- PubMed (publishedVersion)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- Funders
- Australian Research Council (DP140103268)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- contingency learning, associative learning, outcome uncertainty, attentional bias, context sensitivity, attentional models
- MeSH terms
- Association Learning, Attention, Choice Behavior, Cues, Fixation, Ocular, Humans, Photic Stimulation, Uncertainty
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