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Attention Is Spontaneously Biased Toward Regularities
Open accessAbstract
Knowledge about regularities in the environment can be used to facilitate perception, memory, and language acquisition. Given this usefulness, we hypothesized that statistically structured sources of information receive attentional priority over noisier sources, independent of their intrinsic salience or goal relevance. We report three experiments that support this hypothesis. Experiment 1 shows that regularities bias spatial attention: Visual search was facilitated at a location containing temporal regularities, even though these regularities did not predict target location, timing, or identity. Experiments 2 and 3 show that regularities bias feature attention: Attentional capture doubled in magnitude when singletons appeared, respectively, in a color or dimension with temporal regularities among task-irrelevant stimuli. Prioritization of the locations and features of regularities is not easily accounted for in the conventional dichotomy between stimulus-driven and goal-directed attention. This prioritization may in turn promote further statistical learning, helping the mind to acquire knowledge about stable aspects of the environment.
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“This effect was observed although the vast majority of the participants were unaware of the temporal regularities.”
From Selection history: How reward modulates selectivity of visual attention. (2018) · cites this paper as Zhao, Al-Aidroos, & Turk-Browne, 2013
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“Participants were found to respond quicker when the target happened to be at the stream location that contained temporal regularities relative to when it appeared at the location of a random stream.”
From Selection history: How reward modulates selectivity of visual attention. (2018) · cites this paper as Zhao, Al-Aidroos, & Turk-Browne, 2013
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“Shorter WM timescales interact with longer reward-based and choice-based learning processes over task sessions 63 and with implicit statistical learning of temporal or sequential associations among stimuli across minutes 64,65 .”
Dissociable behavioural outcomes of visual statistical learning
Bays, B. C., Turk‐Browne, N. B., & Seitz, A. R. (2015) · Visual Cognition · doi:10.1080/13506285.2016.1139647 · Cited by 31
“Growing evidence suggests that numerous cognitive processes are sensitive to statistical relationships and that learning in even simple tasks can involve simultaneous dissociable processes (Frost, Siegelman, Narkiss, & Afek, 2013; Le Dantec, Melton, & Seitz, 2012; Zhao et al., 2013; Zhao, Ngo, McKendrick, & Turk-Brown…”
BackgroundSelf-citationPriming and statistical learning in right brain damaged patients
Shaqiri, A., & Anderson, B. (2013) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2013.09.024 · Cited by 29
Seeing is believing: Utilization of subliminal symbols requires a visible relevant context
Gayet, S., der Stigchel, S. V., & Paffen, C. L. E. (2013) · Attention Perception & Psychophysics · doi:10.3758/s13414-013-0580-4 · Cited by 25
Takács, Á., Kóbor, A., Kardos, Z., Janacsek, K., Horváth, K., Beste, C., & Németh, D. (2021) · Human Brain Mapping · doi:10.1002/hbm.25427 · Cited by 25
“Prioritizing a regular stimulus event over irregular ones is not a strictly stimulus-driven process since it relies on the internal representation of the regularities (Zhao et al., 2013).”
BackgroundInfluentialLearned states of preparatory attentional control.
Sali, A. W., Anderson, B. A., & Yantis, S. (2015) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/xlm0000146 · Cited by 30
“, 2013) or stimulus feature (Zhao et al., 2013), statistical structure may also influence future settings of attentional priority, even when these regularities are no longer present.”
BackgroundSOAP Opera: Self as Object and Agent in Prioritizing Attention
Truong, G., & Todd, R. M. (2016) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01083 · Cited by 26
Mano, Q. R. (2016) · Scientific Studies of Reading · doi:10.1080/10888438.2016.1141210 · Cited by 27
Attention Shifts to More Complex Structures With Experience
Forest, T. A., Siegelman, N., & Finn, A. S. (2022) · Psychological Science · doi:10.1177/09567976221114055 · Cited by 24
Automatic guidance of attention during real-world visual search
Seidl-Rathkopf, K., Turk‐Browne, N. B., & Kästner, S. (2015) · Attention Perception & Psychophysics · doi:10.3758/s13414-015-0903-8 · Cited by 24
Self-citationDavis, B., & Hasson, U. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.06.001 · Cited by 24
Vision and abstraction: an empirical refutation of Nico Orlandi’s non-cognitivism
Mole, C., & Zhao, J. (2015) · Philosophical Psychology · doi:10.1080/09515089.2015.1081163 · Cited by 23
“The current orthodoxy among philosophers and psychologists is that visual attention is the result of an “integrated competition” taking place between the several different representations that are generated in the course of normal visual processing (see Ruff, 2011; Wu, 2014, section 2.4).”
BackgroundInfluentialSelf-citationValsecchi, M., & Turatto, M. (2021) · Attention Perception & Psychophysics · doi:10.3758/s13414-021-02303-3 · Cited by 22
Trichotomy revisited: A monolithic theory of attentional control
Anderson, B. A. (2024) · Vision Research · doi:10.1016/j.visres.2024.108366 · Cited by 27
Otsuka, S., & Saiki, J. (2015) · Cognition · doi:10.1016/j.cognition.2015.11.004 · Cited by 21
“In addition, significant VSL was found when structured and random streams, or attended and unattended triplets were interleaved in the familiarization phase (Campbell et al., 2012; Zhao et al., 2013).”
InfluentialPerceptual suppression of predicted natural images
Denison, R. N., Sheynin, J., & Silver, M. A. (2016) · Journal of Vision · doi:10.1167/16.13.6 · Cited by 22
“The rivalrous image pairs were the same as those used in the rivalry test.”
MethodStatistical regularities guide the spatial scale of attention
Zhao, J., & Luo, Y. (2016) · Attention Perception & Psychophysics · doi:10.3758/s13414-016-1233-1 · Cited by 22
“co-occurrences between individual objects can bias attention to the objects themselves (Yu & Zhao, 2015; Zhao et al., 2013).”
BackgroundResultInfluentialSelf-citationStatistical Learning Creates Novel Object Associations via Transitive Relations
Luo, Y., & Zhao, J. (2018) · Psychological Science · doi:10.1177/0956797618762400 · Cited by 18
Self-citationReplication and the Establishment of Scientific Truth
Iso‐Ahola, S. E. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.02183 · Cited by 25
“In fact, at the fundamental level, attention and visual search are biased toward temporal regularities (Zhao et al., 2013).”
BackgroundEmotion has no impact on attention in a change detection flicker task
Bendall, R. C. A., & Thompson, C. R. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.01592 · Cited by 22
“Attention has also been shown to be biased by statistical irregularities learned over time that cannot be explained by top–down or bottom–up processing (Zhao et al., 2013).”
BackgroundReward history but not search history explains value-driven attentional capture
Marchner, J. R., & Preuschhof, C. (2018) · Attention Perception & Psychophysics · doi:10.3758/s13414-018-1513-z · Cited by 21
“…involving past experiences (also termed Bhistory^ effects; Awh et al., 2012), and the role of memory processes in the deployment of attentional resources was emphasized (e.g., Hutchinson & Turk-Browne, 2012; Kiyonaga & Egner, 2013; Olivers, Peters, Houtkamp, & Roelfsema, 2011; Zhao et al., 2013).”
BackgroundIndividual differences in the tendency to see the expected
Andermane, N., Bosten, J. M., Seth, A. K., & Ward, J. (2020) · Consciousness and Cognition · doi:10.1016/j.concog.2020.102989 · Cited by 18
Attentional suppression in time and space.
Xu, Z., Los, S. A., & Theeuwes, J. (2021) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/xhp0000925 · Cited by 21
Statistical learning of spatiotemporal regularities dynamically guides visual attention across space
Xu, Z., Theeuwes, J., & Los, S. A. (2022) · Attention Perception & Psychophysics · doi:10.3758/s13414-022-02573-5 · Cited by 20
“Subsequent studies confirmed that SL of temporal order regularities biases visual attention in an automatic and implicit way (Li & Theeuwes, 2020; Turk-Browne et al., 2005; Wang et al., 2021; Zhao et al., 2013).”
Background
Metadata
- Authors
- Zhao, J., Al-Aidroos, N., & Turk-Browne, N. B.
- Affiliations
- Princeton University (US)
- University of Guelph (CA)
- Princeton University
- Venue
- Psychological Science
- Publisher
- SAGE Publications
- Published
- 2013-04-04
- Volume
- 24
- Issue
- 5
- Pages
- 667-677
- ISSN
- 0956-7976 (ISSN-L)
- 1467-9280
- PMC
- PMC3734864
- OpenAlex
- W2145638643
- Cited by
- 266
- References
- 45
- Citations by year
- 2026: 11 · 2025: 15 · 2024: 18 · 2023: 17 · 2022: 14 · 2021: 25 · 2020: 21 · 2019: 18 · 2018: 28 · 2017: 25 · 2016: 21 · 2015: 25 · 2014: 16 · 2013: 8
- FWCI
- 12.75
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Psychological Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Eye Institute (R01EY021755)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- attentional bias, statistical learning, temporal regularity, spatial attention, feature attention, visual search, attentional capture, singleton detection, bottom-up attention, top-down attention
- MeSH terms
- Adult, Attention, Cognition, Female, Humans, Male, Pattern Recognition, Visual, Photic Stimulation, Reaction Time, Space Perception, Students, Visual Perception, Bias, Young Adult
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