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Series:   Elements in Perception

Attentional Selection

Top-Down, Bottom-Up and History-Based Biases

Published online by Cambridge University Press:  05 August 2020

Jan Theeuwes  and
Michel Failing
Jan Theeuwes
Affiliation:
Vrije Universiteit, Amsterdam
Michel Failing
Affiliation:
Charité – Universitätsmedizin Berlin

Summary

In this Element, a framework is proposed in which it is assumed that visual selection is the result of the interaction between top-down, bottom-up and selection-history factors. The Element discusses top-down attentional engagement and suppression, bottom-up selection by abrupt onsets and static singletons as well as lingering biases due to selection-history entailing priming, reward and statistical learning. We present an integrated framework in which biased competition among these three factors drives attention in a winner-take-all-fashion. We speculate which brain areas are likely to be involved and how signals representing these three factors feed into the priority map which ultimately determines selection.
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Keywords

top–down and bottom–up controlattentionselection history
Type
Element
Information
Series: Elements in Perception
Online ISBN: 9781108891288
Publisher: Cambridge University Press
Print publication: 03 September 2020

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References

Anderson, B. A. (2013). A value-driven mechanism of attentional selection. Journal of Vision, 13(3), 1–17.CrossRefGoogle ScholarPubMed
Anderson, B. A. (2016a). The attention habit: How reward learning shapes attentional selection. Annals of the New York Academy of Sciences, 1369(1), 24–39.CrossRefGoogle ScholarPubMed
Anderson, B. A. (2016b). Value-driven attentional capture in the auditory domain. Attention, Perception, & Psychophysics, 78(1), 242–250.CrossRefGoogle ScholarPubMed
Anderson, B. A. & Halpern, M. (2017). On the value-dependence of value-driven attentional capture. Attention, Perception, & Psychophysics, 79(4), 1001–1011.CrossRefGoogle ScholarPubMed
Anderson, B. A. & Kim, H. (2019). On the relationship between value-driven and stimulus-driven attentional capture. Attention, Perception, & Psychophysics, 81(3), 607–613. http://doi.org/10.3758/s13414-019-01670-2CrossRefGoogle ScholarPubMed
Anderson, B. A., Kronemer, S. I., Rilee, J. J., Sacktor, N. & Marvel, C. L. (2016). Reward, attention, and HIV-related risk in HIV+ individuals. Neurobiology of Disease, 92, 157–165.CrossRefGoogle ScholarPubMed
Anderson, B. A., Laurent, P. A. & Yantis, S. (2011). Value-driven attentional capture. Proceedings of the National Academy of Sciences, 108(25), 10367–10371.Google Scholar
Anderson, B. A., Laurent, P. A. & Yantis, S. (2014). Value-driven attentional priority signals in human basal ganglia and visual cortex. Brain Research, 1587, 88–96.CrossRefGoogle ScholarPubMed
Anderson, B. A. & Yantis, S. (2012). Value-driven attentional and oculomotor capture during goal-directed, unconstrained viewing. Attention, Perception, & Psychophysics, 74(8), 1644–1653.CrossRefGoogle ScholarPubMed
Ansorge, U., Kiss, M., Worschech, F. & Eimer, M. (2011). The initial stage of visual selection is controlled by top-down task set: New ERP evidence. Attention, Perception, & Psychophysics, 73, 113–122.CrossRefGoogle ScholarPubMed
Asutay, E. & Västfjäll, D. (2016). Auditory attentional selection is biased by reward cues. Scientific Reports, 36989.CrossRefGoogle ScholarPubMed
Awh, E., Belopolsky, A. & Theeuwes, J. (2012). Top-down versus bottom-up attentional control: A failed theoretical dichotomy. Trends in Cognitive Sciences, 16(8), 437–443.CrossRefGoogle ScholarPubMed
Bacon, W. F. & Egeth, H. E. (1994). Overriding stimulus-driven attentional capture. Perception & Psychophysics, 55(5), 485–496.CrossRefGoogle ScholarPubMed
Baluch, F. & Itti, L. (2011). Mechanisms of top-down attention. Trends in Neurosciences, 34(4), 210–224.CrossRefGoogle ScholarPubMed
Barras, C. & Kerzel, D. (2016). Active suppression of salient-but-irrelevant stimuli does not underlie resistance to visual interference. Biological Psychology, 121, 74–83.CrossRefGoogle Scholar
Basso, M. A. & Wurtz, R. H. (1997). Modulation of neuronal activity by target uncertainty. Nature, 389(6646), 66–69.CrossRefGoogle ScholarPubMed
Batterink, L. J., Paller, K. A. & Reber, P. J. (2019). Understanding the neural bases of implicit and statistical learning. Topics in Cognitive Science. http://doi.org/10.1111/tops.12420CrossRefGoogle Scholar
Belopolsky, A. V., Schreij, D. & Theeuwes, J. (2010). What is top-down about contingent capture? Attention, Perception, & Psychophysics, 72(2), 326–341.CrossRefGoogle ScholarPubMed
Berridge, K. C. (2007). The debate over dopamine’s role in reward: The case for incentive salience. Psychopharmacology, 191(3), 391–431.CrossRefGoogle ScholarPubMed
Berridge, K. C. & Robinson, T. E. (1998). What is the role of dopamine in reward: Hedonic impact, reward learning, or incentive salience? Brain Research Reviews, 28(3), 309–369.Google Scholar
Berridge, K. C., Robinson, T. E. & Aldridge, J. W. (2009). Dissecting components of reward: “Liking,” “wanting,” and learning. Current Opinion in Pharmacology, 9(1), 65–73.CrossRefGoogle ScholarPubMed
Bichot, N. P. & Schall, J. D. (2002). Priming in macaque frontal cortex during popout visual search: Feature-based facilitation and location-based inhibition of return. Journal of Neuroscience, 22(11), 4675–4685.CrossRefGoogle ScholarPubMed
Biederman, I. (1972). Perceiving real-world scenes. Science, 177(4043), 77–80.CrossRefGoogle ScholarPubMed
Biederman, I., Mezzanotte, R. J. & Rabinowitz, J. C. (1982). Scene perception: Detecting and judging objects undergoing relational violations. Cognitive Psychology, 14(2), 143–177.CrossRefGoogle ScholarPubMed
Bisley, J. W. & Goldberg, M. E. (2010). Attention, intention, and priority in the parietal lobe. Annual Review of Neuroscience, 33, 1–21.CrossRefGoogle ScholarPubMed
Born, S., Kerzel, D. & Theeuwes, J. (2011). Evidence for a dissociation between the control of oculomotor capture and disengagement. Experimental Brain Research, 208(4), 621–631.CrossRefGoogle ScholarPubMed
Bravo, M. J. & Nakayama, K. (1992). The role of attention in different visual-search tasks. Perception & Psychophysics, 51, 465–472.CrossRefGoogle ScholarPubMed
Bucker, B., Belopolsky, A. V. & Theeuwes, J. (2015). Distractors that signal reward attract the eyes. Visual Cognition, 23(1–2), 1–24.Google Scholar
Bucker, B., Silvis, J. D., Donk, M. & Theeuwes, J. (2015). Reward modulates oculomotor competition between differently valued stimuli. Vision Research, 108, 103–112.Google Scholar
Bucker, B. & Theeuwes, J. (2014). The effect of reward on orienting and reorienting in exogenous cuing. Cognitive, Affective, & Behavioral Neuroscience, 14(2), 635–646.CrossRefGoogle ScholarPubMed
Bucker, B. & Theeuwes, J. (2017). Pavlovian reward learning underlies value driven attentional capture. Attention, Perception, & Psychophysics, 79(2), 415–428.CrossRefGoogle ScholarPubMed
Burra, N. & Kerzel, D. (2014). The distractor positivity (PD) signals lowering of attentional priority: Evidence from event‐related potentials and individual differences. Psychophysiology, 51(7), 685–696.CrossRefGoogle ScholarPubMed
Buschman, T. J. & Miller, E. K. (2007). Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science, 315(5820), 1860–1862.CrossRefGoogle ScholarPubMed
Carrasco, M. (2011). Visual attention: The past 25 years. Vision Research, 51(13), 1484–1525.CrossRefGoogle ScholarPubMed
Chao, H.-F. (2010). Top-down attentional control for distractor locations: The benefit of precuing distractor locations on target localization and discrimination. Journal of Experimental Psychology. Human Perception and Performance, 36, 303–316.CrossRefGoogle ScholarPubMed
Chelazzi, L., Duncan, J., Miller, E. K. & Desimone, R. (1998). Responses of neurons in inferior temporal cortex during memory-guided visual search. Journal of Neurophysiology, 80(6), 2918–2940.CrossRefGoogle ScholarPubMed
Chelazzi, L., Eštočinová, J., Calletti, R., Gerfo, E. L., Sani, I., Della Libera, C. & Santandrea, E. (2014). Altering spatial priority maps via reward-based learning. Journal of Neuroscience, 34(25), 8594–8604.CrossRefGoogle ScholarPubMed
Chelazzi, L., Marini, F., Pascucci, D. & Turatto, M. (2019). Getting rid of visual distractors: The why, when, how and where. Current Opinion in Psychology, 29, 135–147. http://doi.org/10.1016/j.copsyc.2019.02.004CrossRefGoogle ScholarPubMed
Chelazzi, L., Perlato, A., Santandrea, E. & Della Libera, C. (2013). Rewards teach visual selective attention. Vision Research, 85, 58–72.CrossRefGoogle ScholarPubMed
Chun, M. M. & Jiang, Y. (1998). Contextual cueing: Implicit learning and memory of visual context guides spatial attention. Cognitive Psychology, 36(1), 28–71.CrossRefGoogle ScholarPubMed
Chun, M. M. & Jiang, Y. (1999). Top-down attentional guidance based on implicit learning of visual covariation. Psychological Science, 10(4), 360–365.Google Scholar
Chun, M. M. & Jiang, Y. (2003). Implicit, long-term spatial contextual memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(2), 224.Google Scholar
Chun, M. M. & Phelps, E. A. (1999). Memory deficits for implicit contextual information in amnesic subjects with hippocampal damage. Nature Neuroscience, 2(9), 844–847.CrossRefGoogle ScholarPubMed
Connor, C. E., Egeth, H. E. & Yantis, S. (2004). Visual attention: Bottom-up versus top-down. Current Biology, 14(19), R850–R852.CrossRefGoogle ScholarPubMed
Corbetta, M. & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3(3), 201–215.Google Scholar
Cosman, J. D., Lowe, K. A., Zinke, W., Woodman, G. F. & Schall, J. D. (2018). Prefrontal control of visual distraction. Current Biology, 28(3), 414–420.CrossRefGoogle ScholarPubMed
Davoli, C. C., Suszko, J. W. & Abrams, R. A. (2007). New objects can capture attention without a unique luminance transient. Psychonomic Bulletin & Review, 14(2), 338–343.Google Scholar
Libera, C. & Chelazzi, L. (2006). Visual selective attention and the effects of monetary rewards. Psychological Science, 17(3), 222–227.Google Scholar
Della Libera, C. & Chelazzi, L. (2009). Learning to attend and to ignore is a matter of gains and losses. Psychological Science, 20(6), 778–784.Google Scholar
Della Libera, C., Perlato, A. & Chelazzi, L. (2011). Dissociable effects of reward on attentional learning: From passive associations to active monitoring. PloS One, 6(4), e19460.Google Scholar
Desimone, R. (1996). Neural mechanisms for visual memory and their role in attention. Proceedings of the National Academy of Sciences, 93(24), 13494–13499.CrossRefGoogle ScholarPubMed
Desimone, R. & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18(1), 193–222.Google Scholar
Duncan, J. (1985). Two techniques for investigating perception without awareness. Perception & Psychophysics, 38(3), 296–298.CrossRefGoogle ScholarPubMed
Dux, P. E. & Marois, R. (2009). The attentional blink: A review of data and theory. Attention, Perception, & Psychophysics, 71(8), 1683–1700.Google Scholar
Egeth, H. (2018). Comment on Theeuwes’s characterization of visual selection. Journal of Cognition, 1(1).CrossRefGoogle ScholarPubMed
Egeth, H. E. & Yantis, S. (1997). Visual attention: Control, representation, and time course. Annual Review of Psychology, 48(1), 269–297.Google Scholar
Eichenbaum, H., Yonelinas, A. P. & Ranganath, C. (2007). The medial temporal lobe and recognition memory. Annual Review of Neuroscience, 30, 123–152.CrossRefGoogle ScholarPubMed
Eimer, M. & Kiss, M. (2008). Involuntary attentional capture is determined by task set: Evidence from event-related brain potentials. Journal of Cognitive Neuroscience, 20(8), 1423–1433.CrossRefGoogle ScholarPubMed
Eriksen, B. A. & Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target letter in a nonsearch task. Perception & Psychophysics, 16(1), 143–149.Google Scholar
Eriksen, C. W. & Hoffman, J. E. (1972). Temporal and spatial characteristics of selective encoding from visual displays. Perception & Psychophysics, 12(2), 201–204.CrossRefGoogle Scholar
Failing, M., Feldmann-Wüstefeld, T., Wang, B., Olivers, C. & Theeuwes, J. (2019a). Statistical regularities induce spatial as well as feature-specific suppression. Journal of Experimental Psychology: Human Perception and Performance, 45(10), 1291–1303. http://doi.org/10.1037/xhp0000660Google Scholar
Failing, M., Nissens, T., Pearson, D., Le Pelley, M. & Theeuwes, J. (2015). Oculomotor capture by stimuli that signal the availability of reward. Journal of Neurophysiology, 114(4), 2316–2327.CrossRefGoogle ScholarPubMed
Failing, M. F. & Theeuwes, J. (2014). Exogenous visual orienting by reward. Journal of Vision, 14(5), 6.Google Scholar
Failing, M. & Theeuwes, J. (2016). Reward alters the perception of time. Cognition, 148, 19–26.Google Scholar
Failing, M. & Theeuwes, J. (2017). Don’t let it distract you: How information about the availability of reward affects attentional selection. Attention, Perception, & Psychophysics, 79(8), 2275–2298.CrossRefGoogle ScholarPubMed
Failing, M. & Theeuwes, J. (2018). Selection history: How reward modulates selectivity of visual attention. Psychonomic Bulletin & Review, 25(2), 514–538.Google Scholar
Failing, M. & Theeuwes, J. (2020). More capture, more suppression: Distractor suppression due to statistical regularities is determined by the magnitude of attentional capture. Psychonomic Bulletin & Review, 257, 86–95.Google Scholar
Failing, M., Wang, B. & Theeuwes, J. (2019b). Spatial suppression due to statistical regularities is driven by distractor suppression not by target activation. Attention, Perception, & Psychophysics, 1–10.Google Scholar
Fecteau, J. H. & Munoz, D. P. (2006). Salience, relevance, and firing: A priority map for target selection. Trends in Cognitive Sciences, 10(8), 382–390.CrossRefGoogle ScholarPubMed
Feldmann-Wüstefeld, T. & Schubö, A. (2016). Intertrial priming due to distractor repetition is eliminated in homogeneous contexts. Attention, Perception, & Psychophysics, 78 (7), 1935–1947.Google Scholar
Feldmann-Wüstefeld, T., Uengoer, M. & Schubö, A. (2015). You see what you have learned. Evidence for an interrelation of associative learning and visual selective attention. Psychophysiology, 52, 1483–1497.CrossRefGoogle ScholarPubMed
Fiser, J. & Aslin, R. N. (2001). Unsupervised statistical learning of higher-order spatial structures from visual scenes. Psychological Science, 12(6), 499–504.Google Scholar
Fiser, J. & Aslin, R. N. (2002a). Statistical learning of higher-order temporal structure from visual shape sequences. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28(3), 458–467.Google Scholar
Fiser, J. & Aslin, R. N. (2002b). Statistical learning of new visual feature combinations by infants. Proceedings of the National Academy of Sciences, 99(24), 15822–15826.CrossRefGoogle ScholarPubMed
Fockert, J. D., Rees, G., Frith, C. & Lavie, N. (2004). Neural correlates of attentional capture in visual search. Journal of Cognitive Neuroscience, 16(5), 751–759.CrossRefGoogle ScholarPubMed
Folk, C. L., Remington, R. W. & Johnston, J. C. (1992). Involuntary covert orienting is contingent on attentional control settings. Journal of Experimental Psychology: Human Perception and Performance, 18(4), 1030–1040.Google ScholarPubMed
Foster, J. J. & Awh, E. (2018). The role of alpha oscillations in spatial attention: Limited evidence for a suppression account. Current Opinion in Psychology, 29, 34–40.Google Scholar
Found, A. & Müller, H. J. (1996). Searching for unknown feature targets on more than one dimension: Investigating a “dimension-weighting” account. Perception & Psychophysics, 58(1), 88–101.Google Scholar
Foxe, J. J. & Snyder, A. C. (2011). The role of alpha-band brain oscillations as a sensory suppression mechanism during selective attention. Frontiers in Psychology, 2, 154. http://doi.org/10.3389/fpsyg.2011.00154Google Scholar
Franconeri, S. L., Hollingworth, A. & Simons, D. J. (2005). Do new objects capture attention? Psychological Science, 16(4), 275–281.Google Scholar
Fries, P. (2005). A mechanism for cognitive dynamics: Neuronal communication through neuronal coherence. Trends in Cognitive Sciences, 9(10), 474–480.Google Scholar
Gaffan, D. (1994). Scene-specific memory for objects: A model of episodic memory impairment in monkeys with fornix transection. Journal of Cognitive Neuroscience, 6(4), 305–320.CrossRefGoogle Scholar
Gaspelin, N., Leonard, C. J. & Luck, S. J. (2015). Direct evidence for active suppression of salient-but-irrelevant sensory inputs. Psychological Science, 26(11), 1740–1750.Google Scholar
Gaspelin, N. & Luck, S. J. (2018a). Combined electrophysiological and behavioral evidence for the suppression of salient distractors. Journal of Cognitive Neuroscience, 30(9), 1265–1280.Google Scholar
Gaspelin, N. & Luck, S. J. (2018b). The role of inhibition in avoiding distraction by salient stimuli. Trends in Cognitive Sciences, 22(1), 79–92.Google Scholar
Gaspelin, N. & Luck, S. J. (2018c) “‘Top-down’ does not mean ‘voluntary.’” Journal of Cognition, 1(1), 25, 1–4.CrossRefGoogle Scholar
Geng, J. J. & Behrmann, M. (2002). Probability cuing of target location facilitates visual search implicitly in normal participants and patients with hemispatial neglect. Psychological Science, 13(6), 520–525.CrossRefGoogle ScholarPubMed
Geng, J. J. & Behrmann, M. (2005). Spatial probability as an attentional cue in visual search. Perception & psychophysics, 67(7), 1252–1268.Google Scholar
Godijn, R. & Theeuwes, J. (2002). Programming of endogenous and exogenous saccades: Evidence for a competitive integration model. Journal of Experimental Psychology: Human Perception and Performance, 28(5), 1039–1054.Google Scholar
Goschy, H., Bakos, S., Müller, H. J. & Zehetleitner, M. (2014). Probability cueing of distractor locations: Both intertrial facilitation and statistical learning mediate interference reduction. Frontiers in Psychology, 5, 1195.CrossRefGoogle ScholarPubMed
Goujon, A., Didierjean, A. & Thorpe, S. (2015). Investigating implicit statistical learning mechanisms through contextual cueing. Trends in Cognitive Sciences, 19(9), 524–533.Google Scholar
Grubb, M. A. & Li, Y. (2018). Assessing the role of accuracy-based feedback in value-driven attentional capture. Attention, Perception, & Psychophysics, 1–7.Google Scholar
Hickey, C., Chelazzi, L. & Theeuwes, J. (2010). Reward changes salience in human vision via the anterior cingulate. Journal of Neuroscience, 30(33), 11096–11103.Google Scholar
Hickey, C., Chelazzi, L. & Theeuwes, J. (2014). Reward-priming of location in visual search. PloS one, 9(7), e103372.Google Scholar
Hickey, C., Di Lollo, V. & McDonald, J. J. (2009). Electrophysiological indices of target and distractor processing in visual search. Journal of Cognitive Neuroscience, 21(4), 760–775.Google Scholar
Hickey, C. & Los, S. A. (2015). Reward priming of temporal preparation. Visual Cognition, 23(1–2), 25–40.CrossRefGoogle Scholar
Hickey, C. & Peelen, M. V. (2015). Neural mechanisms of incentive salience in naturalistic human vision. Neuron, 85(3), 512–518.CrossRefGoogle ScholarPubMed
Hickey, C. & Peelen, M. V. (2017). Reward selectively modulates the lingering neural representation of recently attended objects in natural scenes. Journal of Neuroscience, 37(31), 7297–7304.CrossRefGoogle ScholarPubMed
Hikosaka, O., Kim, H. F., Yasuda, M. & Yamamoto, S. (2014). Basal ganglia circuits for reward value-guided behavior. Annual Review of Neuroscience, 37, 289–309.Google Scholar
Hikosaka, O., Takikawa, Y. & Kawagoe, R. (2000). Role of the basal ganglia in the control of purposive saccadic eye movements. Physiological Reviews, 80(3), 953–978.Google Scholar
Hillstrom, A. P. (2000). Repetition effects in visual search. Perception & Psychophysics, 62(4), 800–817.Google Scholar
Hillyard, S. A., Vogel, E. K. & Luck, S. J. (1998). Sensory gain control (amplification) as a mechanism of selective attention: Electrophysiological and neuroimaging evidence. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 353(1373), 1257–1270.Google Scholar
Holland, P. C. & Bouton, M. E. (1999). Hippocampus and context in classical conditioning. Current Opinion in Neurobiology, 9(2), 195–202.Google Scholar
Hopfinger, J. B., Buonocore, M. H. & Mangun, G. R. (2000). The neural mechanisms of top-down attentional control. Nature Neuroscience, 3(3), 284–291.Google Scholar
Itthipuripat, S., Võ, V. A., Sprague, T. C. & Serences, J. (2019). Value-driven attentional capture enhances distractor representations in early visual cortex. BioRxiv, 567354.CrossRefGoogle Scholar
Itti, L. & Koch, C. (2000). A saliency-based search mechanism for overt and covert shifts of visual attention. Vision Research, 1489–1506.CrossRefGoogle Scholar
Itti, L. & Koch, C. (2001). Computational modelling of visual attention. Nature Reviews Neuroscience, 2(3), 194–203.Google Scholar
Itti, L., Koch, C. & Niebur, E. (1998). A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis & Machine Intelligence, (11), 1254–1259.Google Scholar
Jensen, O., Gips, B., Bergmann, T. O. & Bonnefond, M. (2014). Temporal coding organized by coupled alpha and gamma oscillations prioritize visual processing. Trends in Neurosciences, 37(7), 357–369.CrossRefGoogle ScholarPubMed
Jensen, O. & Mazaheri, A. (2010). Shaping functional architecture by oscillatory alpha activity: Gating by inhibition. Frontiers in Human Neuroscience, 4, 186.Google Scholar
Jiang, Y. V. (2018). Habitual versus goal-driven attention. Cortex, 102, 107–120.Google Scholar
Jiang, Y. V. & Chun, M. M. (2001). Selective attention modulates implicit learning. Quarterly Journal of Experimental Psychology: Section A, 54(4), 1105–1124.CrossRefGoogle ScholarPubMed
Jiang, Y. V., Li, Z. S. & Remington, R. W. (2015). Modulation of spatial attention by goals, statistical learning, and monetary reward. Attention, Perception, & Psychophysics, 77(7), 2189–2206.CrossRefGoogle ScholarPubMed
Jonides, J. (1981). Voluntary versus automatic control over the mind’s eye’s movement. Attention and Performance, 187–203.Google Scholar
Jonides, J. & Yantis, S. (1988). Uniqueness of abrupt visual onset in capturing attention. Perception & Psychophysics, 43(4), 346–354.Google Scholar
Kahneman, D., Treisman, A. & Burkell, J. (1983). The cost of visual filtering. Journal of Experimental Psychology: Human Perception and Performance, 9(4), 510–522.Google Scholar
Katsuki, F. & Constantinidis, C. (2014). Bottom-up and top-down attention: Different processes and overlapping neural systems. Neuroscientist, 20(5), 509–521.Google Scholar
Kerzel, D. & Witzel, C. (2019). The allocation of resources in visual working memory and multiple attentional templates. Journal of Experimental Psychology: Human Perception and Performance, 45(5), 645–658.Google Scholar
Kim, M. S. & Cave, K. R. (1995). Spatial attention in visual search for features and feature conjunctions. Psychological Science, 6(6), 376–380.Google Scholar
Kim, H. F. & Hikosaka, O. (2013). Distinct basal ganglia circuits controlling behaviors guided by flexible and stable values. Neuron, 79(5), 1001–1010.Google Scholar
Kiss, M., Grubert, A., Petersen, A. & Eimer, M. (2012). Attentional capture by salient distractors during visual search is determined by temporal task demands. Journal of Cognitive Neuroscience, 24(3), 749–759.Google Scholar
Koch, C. & Ullman, S. (1985). Shifts in visual attention: Towards the underlying circuitry. Human Neurobiology, 4, 219–227.Google Scholar
Kristjánsson, Á. (2010). Priming in visual search: A spanner in the works for Theeuwes’s bottom-up attention sweeps? Acta Psychologica, 135(2), 114.Google Scholar
Kristjánsson, Á. & Campana, G. (2010). Where perception meets memory: A review of repetition priming in visual search tasks. Attention, Perception, & Psychophysics, 72(1), 5–18.Google Scholar
Kumada, T. (1999). Limitations in attending to a feature value for overriding stimulus-driven interference. Perception & Psychophysics, 61, 61–79.Google Scholar
Lamme, V. A. & Roelfsema, P. R. (2000). The distinct modes of vision offered by feedforward and recurrent processing. Trends in Neurosciences, 23(11), 571–579.Google Scholar
Lamy, D. F. & Kristjánsson, Á. (2013). Is goal-directed attentional guidance just intertrial priming? A review. Journal of Vision, 13(3), 14. http://doi.org/10.1167/13.3.14Google Scholar
Le Pelley, M. E., Mitchell, C. J., Beesley, T., George, D. N. & Wills, A. J. (2016). Attention and associative learning in humans: An integrative review. Psychological Bulletin, 142(10), 1111–1140.Google Scholar
Le Pelley, M. E., Pearson, D., Griffiths, O. & Beesley, T. (2015). When goals conflict with values: Counterproductive attentional and oculomotor capture by reward-related stimuli. Journal of Experimental Psychology: General, 144(1), 158–171.Google Scholar
Le Pelley, M. E., Seabrooke, T., Kennedy, B. L., Pearson, D. & Most, S. B. (2017). Miss it and miss out: Counterproductive nonspatial attentional capture by task-irrelevant, value-related stimuli. Attention, Perception, & Psychophysics, 1–15.Google Scholar
Le Pelley, M. E., Watson, P., Pearson, D., Abeywickrama, R. S. & Most, S. B. (2018). Winners and losers: Reward and punishment produce biases in temporal selection. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(5), 822–833. http://doi.org/10.1037/xlm0000612Google Scholar
Leber, A. B. & Egeth, H. E. (2006). It’s under control: Top-down search strategies can override attentional capture. Psychonomic Bulletin & Review, 13(1), 132–138.Google Scholar
Li, Z. (2002). A saliency map in primary visual cortex. Trends in Cognitive Sciences, 6(1), 9–16.Google Scholar
Luck, S. J. & Hillyard, S. A. (1994). Electrophysiological correlates of feature analysis during visual search. Psychophysiology, 31(3), 291–308.Google Scholar
Ludwig, C. J. & Gilchrist, I. D. (2002). Stimulus-driven and goal-driven control over visual selection. Journal of Experimental Psychology: Human Perception and Performance, 28(4), 902–912. http://doi.org/10.1037/0096-1523.28.4.902Google Scholar
MacLean, M. H. & Giesbrecht, B. (2015). Neural evidence reveals the rapid effects of reward history on selective attention. Brain Research, 1606, 86–94.Google Scholar
Maljkovic, V. & Nakayama, K. (1994). Priming of pop-out: I. Role of features. Memory & Cognition, 22(6), 657–672.Google Scholar
Maljkovic, V. & Nakayama, K. (2000). Priming of popout: III. A short-term implicit memory system beneficial for rapid target selection. Visual Cognition, 7(5), 571–595.Google Scholar
Martens, S. & Wyble, B. (2010). The attentional blink: Past, present, and future of a blind spot in perceptual awareness. Neuroscience & Biobehavioral Reviews, 34(6), 947–957.Google Scholar
McPeek, R. M. & Keller, E. L. (2002). Saccade target selection in the superior colliculus during a visual search task. Journal of Neurophysiology, 88(4), 2019–2034.Google Scholar
McPeek, R. M., Maljkovic, V. & Nakayama, K. (1999). Saccades require focal attention and are facilitated by a short-term memory system. Vision Research, 39(8), 1555–1566.Google Scholar
Mine, C. & Saiki, J. (2015). Task-irrelevant stimulus-reward association induces value-driven attentional capture. Attention, Perception, & Psychophysics, 77(6), 1896–1907.Google Scholar
Moher, J. & Egeth, H. E. (2012). The ignoring paradox: Cueing distractor features leads first to selection, then to inhibition of to-be-ignored items. Attention, Perception, & Psychophysics, 74(8), 1590–1605.CrossRefGoogle ScholarPubMed
Moran, J. &. Desimone, R. (1985). Selective attention gates visual processing in the extrastriate cortex. Science, 229, 782–784.Google Scholar
Müller, H. J., Heller, D. & Ziegler, J. (1995). Visual search for singleton feature targets within and across feature dimensions. Perception & Psychophysics, 57(1), 1–17.Google Scholar
Müller, H. J. & Rabbitt, P. M. (1989). Reflexive and voluntary orienting of visual attention: Time course of activation and resistance to interruption. Journal of Experimental Psychology: Human Perception and Performance, 15(2), 315.Google Scholar
Munneke, J., Van der Stigchel, S. & Theeuwes, J. (2008). Cueing the location of a distractor: An inhibitory mechanism of spatial attention? Acta Psychologica, 129(1), 101–107.Google Scholar
Musz, E., Weber, M. J. & Thompson-Schill, S. L. (2015). Visual statistical learning is not reliably modulated by selective attention to isolated events. Attention, Perception, & Psychophysics, 77(1), 78–96.Google Scholar
Neumann, O. (1984). Automatic processing: A review of recent findings and a plea for an old theory. In Cognition and motor processes (pp. 255–293). Berlin: Springer.Google Scholar
Nissens, T., Failing, M. & Theeuwes, J. (2016). People look at the object they fear: oculomotor capture by stimuli that signal threat. Cognition and Emotion, 31, 1–8. http://doi.org/10.1080/02699931.2016.1248905Google Scholar
Noonan, M. P., Adamian, N., Pike, A., Printzlau, F., Crittenden, B. M. & Stokes, M. G. (2016). Distinct mechanisms for distractor suppression and target facilitation. Journal of Neuroscience, 36(6), 1797–1807.Google Scholar
Noonan, M. P., Crittenden, B. M., Jensen, O. & Stokes, M. G. (2018). Selective inhibition of distracting input. Behavioural Brain Research, 355, 36–47.Google Scholar
Olivers, C. N. & Hickey, C. (2010). Priming resolves perceptual ambiguity in visual search: Evidence from behaviour and electrophysiology. Vision Research, 50(14), 1362–1371.Google Scholar
Olivers, C. N. & Humphreys, G. W. (2003). Visual marking inhibits singleton capture. Cognitive Psychology, 47(1), 1–42.Google Scholar
Pearson, D., Donkin, C., Tran, S. C., Most, S. B. & Le Pelley, M. E. (2015). Cognitive control and counterproductive oculomotor capture by reward-related stimuli. Visual Cognition, 23(1–2), 41–66.Google Scholar
Pearson, D., Osborn, R., Whitford, T. J., Failing, M., Theeuwes, J. & Le Pelley, M. E. (2016). Value-modulated oculomotor capture by task-irrelevant stimuli is feature-specific. Attention, Perception & Psychophysics, 78(7), 2226–2240.Google Scholar
Peck, C. J., Jangraw, D. C., Suzuki, M., Efem, R. & Gottlieb, J. (2009). Reward modulates attention independently of action value in posterior parietal cortex. Journal of Neuroscience, 29(36), 11182–11191.Google Scholar
Peelen, M. V., Heslenfeld, D. J. & Theeuwes, J. (2004). Endogenous and exogenous attention shifts are mediated by the same large-scale neural network. Neuroimage, 22(2), 822–830.Google Scholar
Pinto, Y., Olivers, C. L. & Theeuwes, J. (2005). Target uncertainty does not lead to more distraction by singletons: Intertrial priming does. Perception & Psychophysics, 67(8), 1354–1361.Google Scholar
Pollmann, S., Eštočinová, J., Sommer, S., Chelazzi, L. & Zinke, W. (2016). Neural structures involved in visual search guidance by reward-enhanced contextual cueing of the target location. Neuroimage, 124, 887–897.CrossRefGoogle ScholarPubMed
Popov, T., Kastner, S. & Jensen, O. (2017). FEF-controlled alpha delay activity precedes stimulus-induced gamma-band activity in visual cortex. Journal of Neuroscience, 37(15), 4117–4127.Google Scholar
Posner, M. I. (1978). Chronometric explorations of mind. Hillsdale, NJ: Erlbaum.Google Scholar
Posner, M. I. (1980). Orienting of Attention. Quarterly Journal of Experimental Psychology, 32, 3–25.Google Scholar
Posner, M. I. & Cohen, Y. (1984). Components of visual orienting. Attention and Performance X: Control of Language Processes, 32, 531–556.Google Scholar
Posner, M. I., Nissen, M. J. & Ogden, W. C. (1978). Attended and unattended processing modes: The role of set for spatial location. Modes of Perceiving and Processing Information, 137(158), 2.Google Scholar
Posner, M. I., Snyder, C. R. & Davidson, B. J. (1980). Attention and the detection of signals. Journal of Experimental Psychology: General, 109(2), 160.Google Scholar
Postle, B. R. & D’Esposito, M. (1999). Dissociation of human caudate nucleus activity in spatial and nonspatial working memory: An event-related fMRI study. Cognitive Brain Research, 8(2), 107–115.Google Scholar
Postle, B. R. & D’Esposito, M. (2003). Spatial working memory activity of the caudate nucleus is sensitive to frame of reference. Cognitive, Affective, & Behavioral Neuroscience, 3(2), 133–144.Google Scholar
Qi, S., Zeng, Q., Ding, C. & Li, H. (2013). Neural correlates of reward-driven attentional capture in visual search. Brain Research, 1532, 32–43.Google Scholar
Rajsic, J., Perera, H. & Pratt, J. (2016). Learned value and object perception: Accelerated perception or biased decisions? Attention, Perception, & Psychophysics, 1–11.Google Scholar
Raymond, J. E. & O’Brien, J. L. (2009). Selective visual attention and motivation: The consequences of value learning in an attentional blink task. Psychological Science, 20(8), 981–988.Google Scholar
Raymond, J. E., Shapiro, K. L. & Arnell, K. M. (1992). Temporary suppression of visual processing in an RSVP task: An attentional blink? Journal of Experimental Psychology: Human Perception and Performance, 18(3), 849–860.Google Scholar
Reynolds, J. H., Chelazzi, L. & Desimone, R. (1999). Competitive mechanisms subserve attention in macaque areas V2 and V4. Journal of Neuroscience, 19(5), 1736–1753.CrossRefGoogle ScholarPubMed
Reynolds, J. H. & Heeger, D. J. (2009). The normalization model of attention. Neuron, 61(2), 168–185.Google Scholar
Ristic, J. & Kingstone, A. (2006). Attention to arrows: Pointing to a new direction. Quarterly Journal of Experimental Psychology, 59(11), 1921–1930.Google Scholar
Roper, Z. J., Vecera, S. P. & Vaidya, J. G. (2014). Value-driven attentional capture in adolescence. Psychological Science, 25(11), 1987–1993.Google Scholar
Ruff, C. C. & Driver, J. (2006). Attentional preparation for a lateralized visual distractor: Behavioral and fMRI evidence. Journal of Cognitive Neuroscience, 18(4), 522–538.Google Scholar
Rungratsameetaweemana, N., Squire, L. R. & Serences, J. T. (2019). Preserved capacity for learning statistical regularities and directing selective attention after hippocampal lesions. Proceedings of the National Academy of Sciences, 116(39), 19705–19710.Google Scholar
Saffran, J. R., Aslin, R. N. & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274(5294), 1926–1928.Google Scholar
Saffran, J. R., Newport, E. L., Aslin, R. N., Tunick, R. A. & Barrueco, S. (1997). Incidental language learning: Listening (and learning) out of the corner of your ear. Psychological Science, 8(2), 101–105.Google Scholar
Sawaki, R. & Luck, S. J. (2010). Capture versus suppression of attention by salient singletons: Electrophysiological evidence for an automatic attend-to-me signal. Attention, Perception, & Psychophysics, 72(6), 1455–1470.Google Scholar
Sawaki, R., Geng, J. J. & Luck, S. J. (2012). A common neural mechanism for preventing and terminating attention. Journal of Neuroscience, 32, 10725–10736. http://doi.org/10.1523/JNEUROSCI.1864-12.2012Google Scholar
Schacter, D. L. & Buckner, R. L. (1998). Priming and the brain. Neuron, 20(2), 185–195.Google Scholar
Schall, J. D. & Hanes, D. P. (1993). Neural basis of saccade target selection in frontal eye field during visual search. Nature, 366(6454), 467–469.Google Scholar
Schapiro, A. C., Turk‐Browne, N. B., Norman, K. A. & Botvinick, M. M. (2016). Statistical learning of temporal community structure in the hippocampus. Hippocampus, 26(1), 3–8.Google Scholar
Schoeberl, T., Goller, F. & Ansorge, U. (2019). Testing a priming account of the contingent capture effect. Attention, Perception, & Psychophysics, 81, 1262–1282.Google Scholar
Schreij, D., Owens, C. & Theeuwes, J. (2008). Abrupt onsets capture attention independent of top-down control settings. Perception & Psychophysics, 70(2), 208–218.Google Scholar
Schreij, D., Theeuwes, J. & Olivers, C. N. (2010). Abrupt onsets capture attention independent of top-down control settings II: Additivity is no evidence for filtering. Attention, Perception, & Psychophysics, 72(3), 672–682.Google Scholar
Schultz, W. (2016). Dopamine reward prediction-error signalling: A two-component response. Nature Reviews Neuroscience, 17(3), 183–195.Google Scholar
Serences, J. T. (2008). Value-based modulations in human visual cortex. Neuron, 60(6), 1169–1181.Google Scholar
Serences, J. T. & Saproo, S. (2010). Population response profiles in early visual cortex are biased in favor of more valuable stimuli. Journal of Neurophysiology, 104(1), 76–87.Google Scholar
Serences, J. T., Shomstein, S., Leber, A. B., Golay, X., Egeth, H. E. & Yantis, S. (2005). Coordination of voluntary and stimulus-driven attentional control in human cortex. Psychological Science, 16(2), 114–122.Google Scholar
Serences, J. T., Yantis, S., Culberson, A. & Awh, E. (2004). Preparatory activity in visual cortex indexes distractor suppression during covert spatial orienting. Journal of Neurophysiology, 92(6), 3538–3545.Google Scholar
Shapiro, K. L., Raymond, J. E. & Arnell, K. M. (1997). The attentional blink. Trends in Cognitive Sciences, 1(8),291–296.Google Scholar
Shaw, M. L. & Shaw, P. (1977). Optimal allocation of cognitive resources to spatial locations. Journal of Experimental Psychology. Human Perception and Performance, 3, 201–211.Google Scholar
Sheliga, B. M., Riggio, L. & Rizzolatti, G. (1994). Orienting of attention and eye movements. Experimental Brain Research, 98(3), 507–522.Google Scholar
Shiffrin, R. M. & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. Psychological Review, 84(2), 127–190.Google Scholar
Sisk, C. A., Remington, R. W. & Jiang, Y. V. (2018). The risks of downplaying top-down control. Journal of Cognition, 1(1).Google Scholar
Slagter, H. A., Prinssen, S., Reteig, L. C. & Mazaheri, A. (2016). Facilitation and inhibition in attention: functional dissociation of pre-stimulus alpha activity, P1, and N1 components. Neuroimage, 125, 25–35.Google Scholar
Spaak, E. & de Lange, F. (2020). Hippocampal and prefrontal theta-band mechanisms underpin implicit spatial context learning. Journal of Neuroscience, 40(1), 191–202.Google Scholar
Squire, L. R. & Zola, S. M. (1996). Structure and function of declarative and nondeclarative memory systems. Proceedings of the National Academy of Sciences, 93(24), 13515–13522.Google Scholar
Staresina, B. P. & Davachi, L. (2009). Mind the gap: Binding experiences across space and time in the human hippocampus. Neuron, 63(2), 267–276.Google Scholar
Sussman, E. D., Bishop, H., Madnick, B. & Walter, R. (1985). Driver inattention and highway safety. Transportation Research Record, 1047, 40–48.Google Scholar
Taatgen, N. A., Juvina, I., Schipper, M., Borst, J. P. & Martens, S. (2009). Too much control can hurt: A threaded cognition model of the attentional blink. Cognitive Psychology, 59(1), 1–29.CrossRefGoogle Scholar
Theeuwes, J. (1989). Effects of location and form cuing on the allocation of attention in the visual field. Acta Psychologica, 72(2), 177–192.Google Scholar
Theeuwes, J. (1990). Perceptual selectivity is task dependent: Evidence from selective search. Acta Psychologica, 74(1), 81−99.Google Scholar
Theeuwes, J. (1991a). Cross-dimensional perceptual selectivity. Perception & Psychophysics, 50(2), 184–193.Google Scholar
Theeuwes, J. (1991b). Exogenous and endogenous control of attention: The effect of visual onsets and offsets. Attention, Perception, & Psychophysics, 49(1), 83–90.Google Scholar
Theeuwes, J. (1992). Perceptual selectivity for color and form. Perception & Psychophysics, 51(6), 599–606.Google Scholar
Theeuwes, J. (1994a). Endogenous and exogenous control of visual selection. Perception, 23(4), 429–440.Google Scholar
Theeuwes, J. (1994b). Stimulus-driven capture and attentional set: Selective search for color and visual abrupt onsets. Journal of Experimental Psychology: Human Perception and Performance, 20(4), 799–806. http://doi.org/10.1037/0096-1523.20.4.799Google Scholar
Theeuwes, J. (1995). Abrupt luminance change pops out; abrupt color change does not. Perception & Psychophysics, 57(5), 637–644.Google Scholar
Theeuwes, J. (2004). Top-down search strategies cannot override attentional capture. Psychonomic Bulletin & Review, 11(1), 65–70.Google Scholar
Theeuwes, J. (2010). Top-down and bottom-up control of visual selection. Acta Psychologica, 135(2), 77–99.CrossRefGoogle ScholarPubMed
Theeuwes, J. (2013). Feature-based attention: It is all bottom-up priming. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 368(1628), 20130055.Google Scholar
Theeuwes, J. (2018). Visual selection: Usually fast and automatic; seldom slow and volitional. Journal of Cognition, 1(1), 1–15. http://doi.org/10.5334/joc.13Google ScholarPubMed
Theeuwes, J. (2019). Goal-driven, stimulus-driven and history-driven selection. Current Opinion in Psychology, 29, 97–101.Google Scholar
Theeuwes, J., Atchley, P. & Kramer, A. F. (2000). On the time course of top-down and bottom-up control of visual attention. Control of Cognitive Processes: Attention and Performance XVIII, 105–124.Google Scholar
Theeuwes, J. & Belopolsky, A. V. (2012). Reward grabs the eye: Oculomotor capture by rewarding stimuli. Vision Research, 74, 80–85.Google Scholar
Theeuwes, J. & Burger, R. (1998). Attentional control during visual search: The effect of irrelevant singletons. Journal of Experimental Psychology: Human Perception and Performance, 24(5), 1342–1353. http://doi.org/10.1037/0096-1523.24.5.1342Google Scholar
Theeuwes, J. & Godthelp, H. (1995). Self-explaining roads. Safety Science, 19, 217–225.Google Scholar
Theeuwes, J., Kramer, A. F., Hahn, S. & Irwin, D. E. (1998). Our eyes do not always go where we want them to go: Capture of the eyes by new objects. Psychological Science, 9(5), 379–385.Google Scholar
Theeuwes, J., Kramer, A. F., Hahn, S., Irwin, D. E. & Zelinsky, G. J. (1999). Influence of attentional capture on oculomotor control. Journal of Experimental Psychology: Human Perception and Performance, 25(6), 1595–1608. http://doi.org/10.1037/0096-1523.25.6.1595Google Scholar
Theeuwes, J., Olivers, C. N. & Chizk, C. L. (2005). Remembering a location makes the eyes curve away. Psychological Science, 16(3), 196–199.Google Scholar
Theeuwes, J., Reimann, B. & Mortier, K. (2006). Visual search for featural singletons: No top-down modulation, only bottom-up priming. Visual Cognition, 14(4–8), 466–489.Google Scholar
Theeuwes, J. & Van der Burg, E. (2007). The role of spatial and nonspatial information in visual selection. Journal of Experimental Psychology: Human Perception and Performance, 33(6), 1335–1351. http://doi.org/10.1037/0096-1523.33.6.1335Google Scholar
Theeuwes, J. & Van der Burg, E. (2011). On the limits of top-down control of visual selection. Attention, Perception, & Psychophysics, 73(7), 2092–2103.Google Scholar
Theeuwes, J. & Van der Burg, E. (2013). Priming makes a stimulus more salient. Journal of Vision, 13(3), 21. http://doi.org/10.1167/13.3.21Google Scholar
Theeuwes, J., Van der Horst, A. R. A. & Kuiken, M (2012). Designing safe road systems: A human factors perspective. Burlington: Ashgate.Google Scholar
Thomas, N. W. & Paré, M. (2007). Temporal processing of saccade targets in parietal cortex area LIP during visual search. Journal of Neurophysiology, 97(1), 942–947.Google Scholar
Thompson, K. G. & Bichot, N. P. (2005). A visual salience map in the primate frontal eye field. Progress in Brain Research, 147, 249–262.Google Scholar
Thompson, K. G., Hanes, D. P., Bichot, N. P. & Schall, J. D. (1996). Perceptual and motor processing stages identified in the activity of macaque frontal eye field neurons during visual search. Journal of Neurophysiology, 76, 4040–4055.Google Scholar
Thorndike, E. L. (1911). Animal intelligence: Experimental studies. New York: Macmillan.Google Scholar
Tipper, S. P., Howard, L. A. & Jackson, S. R. (1997). Selective reaching to grasp: Evidence for distractor interference effects. Visual Cognition, 4(1), 1–38.Google Scholar
Todd, J. T. & Van Gelder, P. (1979). Implications of a transient-sustained dichotomy for the measurement of human performance. Journal of Experimental Psychology: Human Perception and Performance, 5(4), 625–638. http://doi.org/10.1037/0096-1523.5.4.625Google Scholar
Treisman, A. (1988). Features and objects: The fourteenth Bartlett memorial lecture. Quarterly Journal of Experimental Psychology Section A, 40(2), 201–237.Google Scholar
Tseng, Y. C. & Lleras, A. (2013). Rewarding context accelerates implicit guidance in visual search. Attention, Perception, & Psychophysics, 75(2), 287–298.Google Scholar
Tulving, E. & Schacter, D. L. (1990). Priming and human memory systems. Science, 247(4940), 301–306.Google Scholar
Turk-Browne, N. B. (2012). Statistical learning and its consequences. Nebraska Symposium on Motivation, 59, 117–146.Google Scholar
Turk-Browne, N. B., Jungé, J. A. & Scholl, B. J. (2005). The automaticity of visual statistical learning. Journal of Experimental Psychology: General, 134(4), 552–564. http://doi.org/10.1037/0096-3445.134.4.552Google Scholar
Van der Stigchel, S., Belopolsky, A. V., Peters, J.C., Wijnen, J. G., Meeter, M. & Theeuwes, J. (2009a). The limits of top-down control of visual attention. Acta Psychologica, 132, 201–212.Google Scholar
Van der Stigchel, S., Mulckhuyse, M. & Theeuwes, J. (2009b). Eye cannot see it: The interference of subliminal distractors on saccade metrics. Vision Research, 49(16), 2104–2109.Google Scholar
Van der Stigchel, S. & Theeuwes, J (2006). Faces capture attention: Evidence from inhibition of return. Visual Cognition, 13(6), 657–665.Google Scholar
Van Moorselaar, D. & Slagter, H. A. (2019). Learning what is irrelevant or relevant: Expectations facilitate distractor inhibition and target facilitation through distinct neural mechanisms. Journal of Neuroscience, 39(35), 6953–6967.Google Scholar
Vecera, S. P. & Rizzo, M. (2004). What are you looking at? Impaired “social attention” following frontal-lobe damage. Neuropsychologia, 42, 1657–1665.Google Scholar
Võ, M. L. H. & Wolfe, J. M. (2013). Differential electrophysiological signatures of semantic and syntactic scene processing. Psychological Science, 24(9), 1816–1823.Google Scholar
Vuilleumier, P. (2015). Affective and motivational control of vision. Current Opinion in Neurology, 28(1), 29–35.Google Scholar
Wallenstein, G. V., Eichenbaum, H. & Hasselmo, M. E. (1998). The hippocampus as an associator of discontiguous events. Trends in Neuroscience, 21, 317–323.Google Scholar
Wang, B., Samara, I. & Theeuwes, J. (2019). Statistical regularities bias overt attention. Attention, Perception, & Psychophysics, 1–9.Google Scholar
Wang, B. & Theeuwes, J. (2018a). How to inhibit a distractor location? Statistical learning versus active, top-down suppression. Attention, Perception, & Psychophysics, 1–11.Google Scholar
Wang, B. & Theeuwes, J. (2018b). Statistical regularities modulate attentional capture. Journal of Experimental Psychology: Human Perception and Performance, 44(1), 13–17. http://doi.org/10.1037/xhp0000472Google Scholar
Wang, B. & Theeuwes, J. (2018c). Statistical regularities modulate attentional capture independent of search strategy. Attention, Perception, & Psychophysics, 80(7), 1763–1774.Google Scholar
Wang, B. & Theeuwes, J. (2020). Implicit attentional biases in a changing environment. Acta Psychologia. http://doi.org/10.1016/j.actpsy.2020.103064Google Scholar
Wang, B. & Theeuwes, J. (in press). Salience determines attentional orienting in visual selection. Journal of Experimental Psychology: Human Perception and Performance.Google Scholar
Wang, B., Van Driel, J., Ort, E. & Theeuwes, J. (2019). Anticipatory distractor suppression elicited by statistical regularities in visual search. Journal of Cognitive Neuroscience, 1–14.Google Scholar
White, B. J., Berg, D. J., Kan, J. Y., Marino, R. A., Itti, L. & Munoz, D. P. (2017). Superior colliculus neurons encode a visual saliency map during free viewing of natural dynamic video. Nature Communications, 8, 14263.Google Scholar
Wolfe, J. (2018). Everything is foreseen, yet free will is given (Mishna Avot 3: 15). Journal of Cognition, 1(1).Google Scholar
Wolfe, J. M., Butcher, S. J., Lee, C. & Hyle, M. (2003). Changing your mind: On the contributions of top-down and bottom-up guidance in visual search for feature singletons. Journal of Experimental Psychology: Human Perception and Performance, 29(2), 483.Google Scholar
Won, B. Y., Kosoyan, M. & Geng, J. J. (2019). Evidence for second-order singleton suppression based on probabilistic expectations. Journal of Experimental Psychology: Human Perception and Performance, 45(1), 125–128. http://doi.org/10.1037/xhp0000594Google Scholar
Won, B. Y. & Leber, A. B. (2016). How do magnitude and frequency of monetary reward guide visual search? Attention, Perception, & Psychophysics, 1–11.Google Scholar
Wyble, B., Bowman, H. & Nieuwenstein, M. (2009). The attentional blink provides episodic distinctiveness: Sparing at a cost. Journal of Experimental Psychology: Human Perception and Performance, 35(3), 787–807. http://doi.org/10.1037/a0013902Google Scholar
Yamamoto, S., Monosov, I. E., Yasuda, M. & Hikosaka, O. (2012). What and where information in the caudate tail guides saccades to visual objects. Journal of Neuroscience, 32(32), 11005–11016.Google Scholar
Yantis, S. & Egeth, H. E. (1999). On the distinction between visual salience and stimulus-driven attentional capture. Journal of Experimental Psychology: Human Perception and Performance, 25(3), 661–676. http://doi.org/10.1037/0096-1523.25.3.661Google Scholar
Yantis, S. & Hillstrom, A. P. (1994). Stimulus-driven attentional capture: Evidence from equiluminant visual objects. Journal of Experimental Psychology: Human Perception and Performance, 20(1), 95–107. http://doi.org/10.1037/0096-1523.20.1.95Google Scholar
Yantis, S. & Jonides, J. (1984). Abrupt visual onsets and selective attention: Evidence from visual search. Journal of Experimental Psychology: Human Perception and Performance, 10(5), 601–621. http://doi.org/10.1037/0096-1523.10.5.601Google Scholar
Yasuda, M. & Hikosaka, O. (2015). Functional territories in primate substantia nigra pars reticulata separately signaling stable and flexible values. Journal of Neurophysiology, 113(6), 1681–1696.Google Scholar
Yeterian, E. H. & Van Hoesen, G. W. (1978). Cortico-striate projections in the rhesus monkey: The organization of certain cortico-caudate connections. Brain Research, 139(1), 43–63.Google Scholar
Zelinsky, G. J. & Bisley, J. W. (2015). The what, where, and why of priority maps and their interactions with visual working memory. Annals of the New York Academy of Sciences, 1339(1), 154–164.Google Scholar
Zhang, X., Zhaoping, L., Zhou, T. & Fang, F. (2012). Neural activities in V1 create a bottom-up saliency map. Neuron, 73(1), 183–192.Google Scholar
Zhao, J., Al-Aidroos, N. & Turk-Browne, N. B. (2013). Attention is spontaneously biased toward regularities. Psychological Science, 24(5), 667–677.Google Scholar
Zhaoping, L. (2008). Attention capture by eye of origin singletons even without awareness: A hallmark of a bottom-up saliency map in the primary visual cortex. Journal of Vision, 8(5), 1.1–18.Google Scholar

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Attentional Selection
  • Jan Theeuwes, Vrije Universiteit, Amsterdam, Michel Failing, Charité – Universitätsmedizin Berlin
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Attentional Selection
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Attentional Selection
  • Jan Theeuwes, Vrije Universiteit, Amsterdam, Michel Failing, Charité – Universitätsmedizin Berlin
  • Online ISBN: 9781108891288
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