The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
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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Citations
Cites
Brainard, D. H. (1997) · Spatial Vision · doi:10.1163/156856897x00357 · Cited by 20,012 · cited 2×
“Stimuli were presented using MATLAB (The MathWorks, Natick, MA) and the Psychophysics Toolbox (Brainard, 1997; Pelli, 1997).”
MethodControl of goal-directed and stimulus-driven attention in the brain
Corbetta, M., & Shulman, G. L. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn755 · Cited by 12,881 · cited 1×
“Attention is known to be controlled by two factors (Chun, Golomb, & Turk-Browne, 2011; Corbetta & Shulman, 2002; Jonides, 1981; Pashler, Johnston, & Ruthruff, 2001; Posner, 1980; Yantis, 2000).”
An Integrative Theory of Prefrontal Cortex Function
Miller, E. K., & Cohen, J. D. (2001) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.24.1.167 · Cited by 12,803 · cited 1×
“Second, attention can be directed endogenously by internal goals or task rules (Hopfinger, Buonocore, & Mangun, 2000; Miller & Cohen, 2001), which enhances the processing of goal-relevant stimuli irrespective of salience (Bacon & Egeth, 1994; Folk, Remington, & Johnston, 1992; cf. Theeuwes, 2004).”
BackgroundThe VideoToolbox software for visual psychophysics: transforming numbers into movies
Pelli, D. G. (1997) · Spatial Vision · doi:10.1163/156856897x00366 · Cited by 11,110 · cited 2×
“Stimuli were presented using MATLAB (The MathWorks, Natick, MA) and the Psychophysics Toolbox (Brainard, 1997; Pelli, 1997).”
MethodPosner, M. I. (1980) · Quarterly Journal of Experimental Psychology · doi:10.1080/00335558008248231 · Cited by 9,670 · cited 1×
“Attention is known to be controlled by two factors (Chun, Golomb, & Turk-Browne, 2011; Corbetta & Shulman, 2002; Jonides, 1981; Pashler, Johnston, & Ruthruff, 2001; Posner, 1980; Yantis, 2000).”
Statistical learning by 8-month-old infants
Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996) · Science · doi:10.1126/science.274.5294.1926 · Cited by 5,659
Computational modelling of visual attention
Itti, L., & Koch, C. (2001) · Nature Reviews Neuroscience · doi:10.1038/35058500 · Cited by 4,733 · cited 1×
“First, attention can be driven exogenously by salient external stimuli (Itti & Koch, 2001; Wolfe & Horowitz, 2004), such as unique features (Theeuwes, 1992), abrupt onsets (Yantis & Jonides, 1984), new and looming motion (Abrams & Christ, 2003; Franconeri & Simons, 2003), and novelty (Johnston,…”
BackgroundInvoluntary covert orienting is contingent on attentional control settings
Folk, C. L., Remington, R. W., & Johnston, J. C. (1992) · Journal of Experimental Psychology: Human Perception and Performance · doi:10.1037/0096-1523.18.4.1030 · Cited by 2,487
Contextual Cueing: Implicit Learning and Memory of Visual Context Guides Spatial Attention
Chun, M. M., & Jiang, Y. (1998) · Cognitive Psychology · doi:10.1006/cogp.1998.0681 · Cited by 1,959 · cited 3×
“…to regularities improves learning of object labels (Graf Estes, Evans, Alibali, & Saffran, 2007), facilitates object categorization (Turk-Browne, Scholl, Johnson, & Chun, 2010), and expands visual short-term memory capacity (Brady, Konkle, & Alvarez, 2009; Umemoto, Scolari, Vogel, & Awh, 2010).”
BackgroundThe neural mechanisms of top-down attentional control
Hopfinger, J. B., Buonocore, M. H., & Mangun, G. R. (2000) · Nature Neuroscience · doi:10.1038/72999 · Cited by 1,876
Flagged first, then by citations
Research works printed but not linked: 1
- Jonides J., 1981, Attention and performance, 9, 187
Cited by
Sorted by citations
Items 201–266 of 266
Retirados para vivir en España: condiciones, situaciones, escenarios
Rodríguez, V. R. (2008) · Cited by 2
Moon, A., Zhao, J., Peters, M. A. K., & Wu, R. (2022) · Cognitive Research Principles and Implications · doi:10.1186/s41235-022-00356-y · Cited by 2
“Ultimately, we were unable to replicate the previously reported behavioral search advantage for targets appearing in patterned locations (Zhao et al., 2013).”
BackgroundSelf-citationRotating objects cue spatial attention via the perception of frictive surface contact
Nguyen, H. B., & van Buren, B. F. (2023) · Cognition · doi:10.1016/j.cognition.2023.105655 · Cited by 3
Hu, R., Li, S., Yuan, P., Wang, Y., & Jiang, Y. (2024) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.15099 · Cited by 2
“11,55 Future research could examine whether temporal structures defined by perceptual-and semantic-level regularities modulate visual attention and identify whether the findings contribute to the advantage of structured streams in BR. Addressing these issues may help advance our understanding of…”
BackgroundCécile, G., Ţincaş, I., Moca, V. V., Ciuparu, A., Dan, E. L., Smith, M. L., Gliga, T., & Muresan, R. C. (2024) · Scientific Reports · doi:10.1038/s41598-024-59089-1 · Cited by 2
“It has been suggested that the hindering effects of randomness are due to its low saliency compared to predictable events, resulting in attentional capture and facilitation of the processing of information related to predictable events over unpredictable ones 30,36 .”
BackgroundPerception of multi-dimensional regularities is driven by salience
Yu, R. Q., Luo, Y., Osherson, D. N., & Zhao, J. (2019) · Attention Perception & Psychophysics · doi:10.3758/s13414-019-01667-x · Cited by 2
Self-citationCombined expectancies: the role of expectations for the coding of salient bottom-up signals
Wiesing, M., Fink, G. R., Weidner, R., & Vossel, S. (2020) · Experimental Brain Research · doi:10.1007/s00221-019-05710-z · Cited by 2
Statistically learned associations among objects bias attention
Clement, A., & Anderson, B. A. (2024) · Attention Perception & Psychophysics · doi:10.3758/s13414-024-02941-3 · Cited by 2
“Thus, these associations appeared to automatically bias attention (Yu & Zhao, 2015; Zhao et al., 2013).”
Enjoying Art: The Experience of Beauty from Understanding Regularities
Serrao, F. (2019) · Art & Perception · doi:10.1163/22134913-20191106 · Cited by 2
Salet, J. M., Kruijne, W., van Rijn, H., Zimmermann, E., & Schlichting, N. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.06.502990 · Cited by 2
Gozli, D. G. (2019) · Springer eBooks · doi:10.1007/978-3-030-20422-8_8 · Cited by 1
The effect of temporal predictability on sensory gating: Cortical responses inform perception
Favero, J. D., Luck, C. C., Lipp, O. V., & Marinovic, W. (2024) · Psychophysiology · doi:10.1111/psyp.14687 · Cited by 1
“A large body of evidence, across psychophysical paradigms, indicates that expectation (Zhao et al., 2013) and temporal predictability, optimize the allocation of attention and other cognitive resources to task relevant processes (Alegria, 1974; Nobre & van Ede, 2018).”
Geddert, R., Madlon‐Kay, S., O’Neill, K. J., Pearson, J., & Egner, T. (2025) · Psychonomic Bulletin & Review · doi:10.3758/s13423-025-02712-7 · Cited by 4
“Incremental learning is a fundamental mechanism by which humans learn the statistical regularities of their environments (Sali et al., 2013; Yu & Zhao, 2015; Zhao et al., 2013).”
Meaning and Attention Intertwined: Experimental and Experience-Sampling Findings
Tam, K. Y. Y., van Tilburg, W. A. P., Chan, C. S., & Inzlicht, M. (2025) · Personality and Social Psychology Bulletin · doi:10.1177/01461672251383966 · Cited by 1
“Cognitive research demonstrates that attention is automatically drawn to salient stimuli (Nothdurft, 2002), such as those exhibiting coherence (e.g., Zhao et al., 2013) or linked to monetary reward in previous tasks (e.g., Hickey et al., 2015).”
Woodman, G. F., & Polyn, S. M. (2026) · Attention Perception & Psychophysics · doi:10.3758/s13414-025-03214-3 · Cited by 1
“…a decade ago, several laboratories simultaneously began focusing on the question of whether information acquired across the long term can bias attention during the processing of complex visual scenes or listening in noisy environments (Awh et al., 2012; Car-lisle et al., 2011; Zhao et al., 2013).”
Sheinenson, Y., Kleiman, T., & Siegelman, N. (2026) · Cognitive Science · doi:10.1111/cogs.70226 · Cited by 1
Dissociation of sensory facilitation and decision bias in statistical learning
Simard, F., & Pack, C. C. (2015) · Visual Cognition · doi:10.1080/13506285.2015.1085477 · Cited by 1
“Regularities in the environment are known to spontaneously capture attention (Zhao et al., 2013), and contextual cuing has been showed to guide visual attention (Chun, 2000).”
BackgroundLearning induced illusions: Statistical learning creates false memories.
Luo, Y., & Zhao, J. (2017) · eScholarship (California Digital Library) · Cited by 1
Self-citationAuditory facilitation in deterministic versus stochastic worlds
Bastug, B., Roeber, U., & Schröger, E. (2025) · Cognitive Neuroscience · doi:10.1080/17588928.2025.2497762 · Cited by 1
“Because pre-dictability guides attention (Klein, 1994; Zhao et al., 2013), reduces cognitive load (Ambrus et al., 2020; respective transition probabilities (TPs) for tone pitch (task-irrelevant dimension), (c) TPs for the tone duration (task-relevant dimension), small rectangles represent short…”
Semantically predictable input streams impede gaze-orientation to surprising locations
Notaro, G., & Hasson, U. (2021) · Cortex · doi:10.1016/j.cortex.2021.03.009 · Cited by 1
Confirmation bias in visual attention
Rajsic, J. (2017) · TSpace (University of Toronto) · Cited by 1
Pahi, M. R., Cavalli, J., Nees, F., Flor, H., & Andoh, J. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.05915 · Cited by 1
“suggests that implicit and explicit memories also play an important role in guiding attention (Chun and Jiang 1998; Moores et al. 2003; Kristjánsson and Campana 2010; Stokes et al. 2012; Hutchinson and Turk-Browne 2012; Zhao et al. 2013).”
BackgroundLearning to Expect the Predictable: The Role of Expectation in the Cognitive Control of Attention
Botes, A. (2020) · doi:10.26686/wgtn.17148176.v1 · Cited by 1
Holistic Processing: A Matter of Experience
Chua, K.-W. (2017) · Cited by 1
Neurophysiological coding of statistical and deterministic rule informationPreprint
Takács, Á., Kóbor, A., Kardos, Z., Janacsek, K., Horváth, K., Beste, C., & Németh, D. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.10.14.338913 · Cited by 1
“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).”
BackgroundInfluentialAttention shifts to more complex locations with experiencePreprint
Forest, T. A., Siegelman, N., & Finn, A. S. (2021) · doi:10.31234/osf.io/kr5a9 · Cited by 1
Zhao, G. W., Duan, Y., Chen, J., Li, D., Li, S., Wang, Q., & Sun, H. (2023) · doi:10.22541/au.169735586.60442724/v1 · Cited by 1
Spatial cueing of attention by rotational motionPreprint
Nguyen, H. B., & van Buren, B. F. (2024) · OSF Preprints (OSF Preprints) · doi:10.31219/osf.io/x6ajz · Cited by 1
Ling, X., Zhang, Q., Sun, P., Zhao, L., Zheng, L., & Dienes, Z. P. (2024) · doi:10.31234/osf.io/uyhft · Cited by 1
Meaning and attention intertwined: Experimental and experience-sampling findingsPreprint
Tam, K. Y. Y., van Tilburg, W. A. P., Chan, C. S., & Inzlicht, M. (2024) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/f5t9u · Cited by 1
Bai, S., Menétrey, M. Q., & Pascucci, D. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.16.682933 · Cited by 1
Neural correlates of implicit memory for reoccurring sound patternsPreprint
Kolken, Y., Li, C. R., van de Ven, V. G., Weerd, P. D., Auksztulewicz, R., Bianco, R., Maria Chait, A., & Martino, F. D. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.18.695138 · Cited by 1
“We suggest that, for regularity alone, reduced uncertainty (i.e., increased precision of priors) may be increasing this disinhibitory input (from higher to lower regions), resulting in a larger response to regular compared to random sequences [38–40] (see Figure 7A).”
Visual statistical learning and its impact on spatial attention
Won, B.-Y. (2014) · University of Minnesota Digital Conservancy (University of Minnesota)
Statistical learning in brain damaged patients: A multimodal impairment
Shaqiri, A. (2014) · UWSpace (University of Waterloo)
Towards an Understanding of How People Build Mental Representations
Valadao, D. F. (2016) · UWSpace (University of Waterloo)
The “item” as a window into how prior knowledge guides visual search
Wu, R., & Zhao, J. (2017) · Behavioral and Brain Sciences · doi:10.1017/s0140525x16000315
Self-citationAlternation between different types of evidence attenuates judgments of severity
Whitman, J. C., Zhao, J., & Todd, R. M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0180585
Self-citationRandomness and Structure to Humans and Rhesus Macaques
Whitham, W. (2022) · Digital Archive @ GSU · doi:10.57709/11928966
Statistical learning of target selection and distractor filtering
Ferrante, O. (2018)
ATTENTIONAL MODULATION OF THE MEDIAL TEMPORAL LOBE
Córdova, N. I. (2017)
Superstitious Perception: Comparing Perceptual Prediction by Humans and Neural Networks
Laflamme, P., & Enns, J. T. (2018) · Current topics in behavioral neurosciences · doi:10.1007/7854_2018_65
Spatial and semantic regularities produce interactive effects in early stages of visual orientationPreprint
Notaro, G., & Hasson, U. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/639385
“For instance, Zhao, Al-Aidroos, and Turk-Browne (2013) demonstrated that attention is drawn to regular, task-irrelevant shape streams, and Otsuka and Saiki (2016) have shown that items presented in regular series are better remembered than those presented within random series.”
BackgroundStatistical learning creates implicit subadditive predictions.
Luo, Y., & Zhao, J. (2019) · eScholarship (California Digital Library)
Self-citationPupil tracks statistical regularities: behavioral and neural implications
Warda, S., & Pandey, S. (2020) · Journal of Integrative Neuroscience · doi:10.31083/j.jin.2020.04.331
“Second, as attention gets biased towards statistically reliable stimuli (Zhao et al., 2013), this biased attentionmay allocatemore attentional resources for processing the predicted second face, thus enhancing the second face's internal representation in a pair (Barakat et al., 2013).”
BackgroundA weighted summation framework for conjunctive predictions
Yu, R. Q. (2021) · cIRcle (University of British Columbia) · doi:10.14288/1.0402139
For Visual Attention, are there any Tendencies in Form Interpretation?
Kim, J., & Fritsch, M. H. (2021) · Visible Language · doi:10.34314/vl.v53i2.4650
The influence of regularities on temporal order judgments.
Haverkort, S. Q. (2015) · Utrecht University Repository (Utrecht University)
The link between conceptual and perceptual information in memory
Coutanche, M. N. (2022) · Routledge eBooks · doi:10.4324/9781003158134-13
Gozli, D. G. (2019) · Springer eBooks · doi:10.1007/978-3-030-20422-8_1
de Jong, J. (2024) · University of Groningen research database (University of Groningen / Centre for Information Technology) · doi:10.33612/diss.1004106212
Task-irrelevant semantic relationship between objects and scene influence attentional allocation
Nah, J. C., Malcolm, G. L., & Shomstein, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-62867-6
Хрущ, О. (2024) · Наукові інновації та передові технології · doi:10.52058/2786-5274-2024-11(39)-1916-1928
The role of memory in affirming-the-consequent fallacy
Higuchi, Y., Oblak, E. F., Nakamura, H., Yamada, M., & Shibata, K. (2025) · iScience · doi:10.1016/j.isci.2025.111889 · Cited by 1
Society and Unnatural Sciences
Tambovtsev, V. (2025) · Science management theory and practice · doi:10.19181/smtp.2025.7.2.13
Super rapid learning of new attentional sets
Marx, S. A., Wang, S., & Woodman, G. F. (2025) · Psychonomic Bulletin & Review · doi:10.3758/s13423-025-02728-z
“By extracting statistics continuously, human visual attention can retune itself to the biases inherent in the environment (Awh et al., 2012; Rein-hart & Woodman, 2015; Woodman & Chun, 2006; Zhao et al., 2013).”
Learned saccade readiness varies with fluctuations in sustained attention
Sali, A. W., Shaver, M. P., Toledo, A. B., Torain, A. L., & Flicker, I. N. (2025) · Scientific Reports · doi:10.1038/s41598-025-14340-1
“Furthermore, surprising stimuli, such as a color or shape singleton, are afforded elevated attentional priority 33,34 and spatial attention is drawn to information sources with predictable statistical structures 35 .”
Yan, N., Jiang, R., & Anderson, B. A. (2025) · Attention Perception & Psychophysics · doi:10.3758/s13414-025-03178-4
“For example, attention is automatically drawn to areas with consistent patterns in the environment (Zhao et al., 2013).”
Predictable events enhance word learning in toddlersPreprint
Saffran, J. R., & Benitez, V. L. (2018) · OSF Preprints (OSF Preprints)
Events at predicted location expand in time
Warda, S., & Khan, A. (2026) · Psychonomic Bulletin & Review · doi:10.3758/s13423-025-02817-z
“These findings collectively suggest the possibility of an attentional bias towards the location where the events are more likely to occur (Zhao et al., 2013).”
Neural Evidence of Early Sensitivity to Text in Pre-reading ToddlersPreprint
Kherbawy, N., Potter, C. E., & Jaffe‐Dax, S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.24.707347
Carry-over effect of learned distractor suppression on visual working memory
George, N., & Patel, P. (2026) · Frontiers in Neuroscience · doi:10.3389/fnins.2026.1768751
“This eect is observed when regularity is associated with locations, features (Goschy et al., 2014; Failing and Theeuwes, 2018; Stilwell et al., 2019), and time (Zhao et al., 2013).”
Diversity of Rhythm from Oral Speech to Music
Meyer, L., Meyer, L., & Meyer, L. (2026) · Cambridge University Press eBooks · doi:10.1017/9781009295888.027
Task-Irrelevant Information Reduces Attentional Uncertainty
Geng, J. J., Shomstein, S., Wan, Q., & McEvoy, K. E. (2026) · Annual Review of Vision Science · doi:10.1146/annurev-vision-102122-112153 · Cited by 1
Structuring the World: Statistical Learning From the Top and From the Bottom
Tabas, A., Fiser, J., Lengyel, M., & de Hoz, L. (2026) · European Journal of Neuroscience · doi:10.1111/ejn.70712
“…al. 1996); investigations of this type of learning quickly expanded to other modalities including vision (Fiser and Aslin 2001; Kirkham et al. 2002; Zhao et al. 2013; Lee et al. 2021), where the focus shifted from explaining specific segmentation tasks to investigating SL as a general mechanism…”
The role of long-term memory, flexible templates and learning in attentional guidance
Carlisle, N. B., & Woodman, G. F. (2026) · Nature Reviews Psychology · doi:10.1038/s44159-026-00626-2
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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