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Visual Attention in Crisis

Published online by Cambridge University Press:  03 May 2024

Ruth Rosenholtz*
Affiliation:
Department of Brain & Cognitive Sciences, CSAIL, Massachusetts Institute of Technology, USA rruth@mit.edu
*
Corresponding author: Ruth Rosenholtz; Email: rruth@mit.edu

Short abstract

Recent research on peripheral vision has led to a paradigm-shifting conclusion: vision science as a field must rethink visual attention. This article reviews the evidence for a crisis in attention science and examines supposedly attentional phenomena to ask which point to additional capacity limits. Based on the resulting list of critical phenomena, and what they have in common, I propose an alternative way to think about capacity limits and the underlying mechanisms.

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© The Author(s), 2024. Published by Cambridge University Press

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References

Al-Janabi, S., & Greenberg, A. S. (2016). Target-object integration, attention distribution, and object orientation interactively modulate object-based selection. Attention, Perception, & Psychophysics, 78(7), 19681984.Google Scholar
Alvarez, G. A., & Franconeri, S. L. (2007). How many objects can you track?: Evidence for a resource-limited attentive tracking mechanism. Journal of Vision, 7(13), 14.Google Scholar
Anderson, B. (2011). There is no such thing as attention. Frontiers in Psychology, 2, 246.Google Scholar
Anton-Erxleben, K. A., Henrich, C., & Treue, S. (2007). Attention changes perceived size of moving visual patterns. Journal of Vision, 7(11), 5.Google Scholar
Ariely, D. (2001). Seeing sets: Representation by statistical properties. Psychological Science, 12(2), 157162.Google Scholar
Balas, B. J. (2016). Seeing number using texture: How summary statistics account for reductions in perceived numerosity in the visual periphery. Attention, Perception, & Psychophysics, 78(8), 23132319.Google Scholar
Balas, B. J., Nakano, L., & Rosenholtz, R. (2009). A summary-statistic representation in peripheral vision explains visual crowding. Journal of Vision, 8(12), 13. doi: 10.1167/9.12.13 Google Scholar
Bouma, H. (1970). Interactional effects in parafoveal letter recognition. Nature, 226, 177178.Google Scholar
Braun, J., & Julesz, B. (1998). Withdrawing attention at little or no cost: Detection and discrimination tasks. Perception & Psychophysics, 60(1), 112.Google Scholar
Carrasco, M. (2011). Visual attention: the past 25 years. Vision Research, 51(13), 14841525.Google Scholar
Chaney, W., Fischer, J., & Whitney, D. (2014). The hierarchical sparse selection model of visual crowding. Frontiers in Integrative Neuroscience, 8(73), 111. doi: 10.3389/fnint.2014.00073 Google Scholar
Chang, H., & Rosenholtz, R. (2016). Search performance is better predicted by tileability than by the presence of a unique basic feature. Journal of Vision, 16(10), 13.Google Scholar
Chen, N., Shin, K., Millin, R., Song, Y., Kwon, M., & Tjan, B. S. (2019). Cortical reorganization of peripheral vision induced by simulated central vision loss. Journal of Neuroscience, 39(18), 35293536.Google Scholar
Chen, Z., & Cave, K. R. (2019). When is object-based attention not based on objects? Journal of Experimental Psychology: Human Perception and Performance, 45(8), 10621082.Google Scholar
Chen, Z., Cave, K. R., Basu, D., Suresh, S., & Wiltshire, J. (2020). A region complexity effect masquerading as object-based attention. Journal of Vision, 20(7), 24.Google Scholar
Chong, S.-C., & Treisman, A. (2003). Representation of statistical properties. Vision Research, 43(4), 393404.Google Scholar
Chong, S.-C., & Treisman, A. (2005). Attentional spread in the statistical processing of visual displays. Perception & Psychophysics, 66, 12821294.Google Scholar
Chun, M. M., Golumb, J. D., & Turk-Browne, N. B. (2011). A taxonomy of external and internal attention. Annual Review of Psychology, 62, 73101.Google Scholar
Cohen, A., & Ivry, R. (1989). Illusory conjunctions inside and outside the focus of attention. Journal of Experimental Psychology: Human Perception and Performance, 15(4), 650663.Google Scholar
Cohen, M. A., Alvarez, G. A., & Nakayama, K. (2011). Natural-scene perception requires attention. Psych. Science, 22(9), 11651172.Google Scholar
Cohen, M. A., Dennett, D. C., & Kanwisher, N. (2016). What is the bandwidth of perceptual experience? Trends in Cognitive Sciences, 20(5), 324335.Google Scholar
Davis, E. T., Kramer, P., & Graham, N. (1983). Uncertainty about spatial frequency, spatial position, or contrast of visual patterns. Perception and Psychophysics, 33(1), 2028.Google Scholar
Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193222.Google Scholar
Deutsch, J. A., & Deutsch, D. (1963). Attention: Some theoretical considerations. Psychological Review, 70, 8090.Google Scholar
Egly, R., Driver, J., & Rafal, R. D. (1994). Shifting visual attention between objects and locations: Evidence from normal and parietal lesion subjects. Journal of Experimental Psychology: General, 123(2), 161177.Google Scholar
Ehinger, K. A., & Rosenholtz, R. (2016). A general account of peripheral encoding also predicts scene perception performance. Journal of Vision, 16(2), 13.Google Scholar
Ellis, S. R., & Stark, L. (1978). Eye movements during the viewing of Necker cubes. Perception, 7, 575581.Google Scholar
Eriksen, C. W., & Lappin, J. S. (1967). Selective attention and very short-term recognition memory for nonsense forms. Journal of Experimental Psychology, 73(3), 358364.Google Scholar
Eriksen, C. W., & Rohrbaugh, J. (1970). Visual masking in multielement displays. Journal of Experimental Psychology, 83(1, pt. 1), 147154.Google Scholar
Eriksen, C. W., & Webb, J. M. (1989). Shifting of attentional focus within and about a visual display. Perception & Psychophysics, 45(2), 175183.Google Scholar
Folk, C. L., Remington, R. W., & Johnston, J. C. (1992). Involuntary covert orienting is contingent on attentional control settings. Journal of Experimental Psychology: Perception & Performance, 18(4), 10301044.Google Scholar
Fortenbaugh, F. C., Prinzmetal, W., & Robertson, L. C. (2011). Rapid changes in visual-spatial attention distort object shape. Psychonomic Bulletin & Review, 18, 287294.Google Scholar
Fougnie, D., Cockhren, J., & Marois, R. (2018). A common source of attention for auditory and visual tracking. Attention, Perception, & Psychophysics, 80, 15711583.Google Scholar
Francis, G., & Thunell, E. (2022). Excess success in articles on object-based attention. Attention, Perception, & Psychophysics, 84, 700714.Google Scholar
Franconeri, S. L., Alvarez, G. A., & Cavanagh, P. (2013). Flexible cognitive resources: Competitive content maps for attention and memory. Trends in Cognitive Sciences, 17(3), 134141.Google Scholar
Freeman, J., & Simoncelli, E. P. (2011). Metamers of the ventral stream. Nature Neuroscience, 14(9), 11951201.Google Scholar
Freeman, J., Ziemba, C. M., Heeger, D. J., Simoncelli, E. P., & Movshon, J. A. (2013). A functional and perceptual signature of the second visual area in primates. Nature Neuroscience, 16, 974981.Google Scholar
Gaspar, J. G., Ward, N., Neider, M. B., Crowell, J., Carbonari, R., Kaczmarski, H., … Loschky, L. C. (2016). Measuring the Useful Field of View during simulated driving with gaze-contingent displays. Human Factors, 58(4), 630641.Google Scholar
Gingerich, O. (1975). ’Crisis’ versus aesthetic in the Copernican Revolution. In Beer, A. (Ed.), Vistas in Astronomy (Vol. 17, pp. 8594). Oxford: Pergamon.Google Scholar
Gobell, J. L., Tseng, C.-H., & Sperling, G. (2004). The spatial distribution of visual attention. Vision Research, 44(12), 12731296.Google Scholar
Greene, M. R., & Oliva, A. (2009). Recognition of natural scenes from global properties: Seeing the forest without representing the trees. Cognitive Psychology, 58(2), 137176.Google Scholar
Grindley, G. C., & Townsend, V. (1968). Voluntary attention in peripheral vision and its effects on acuity and differential thresholds. Quarterly Journal of Experimental Psychology, 20(1), 1119.Google Scholar
Haberman, J., & Whitney, D. (2009). Seeing the mean: Ensemble coding for sets of faces. Journal of Experimental Psychology: Human Perception & Performance, 35(3), 718734.Google Scholar
Heliocentrism. (2023, December 19). Retrieved from Wikipedia: https://en.wikipedia.org/wiki/Heliocentrism Google Scholar
Hommel, B., Chapman, C. S., Cisek, P., Neyedli, H. F., Song, J.-H., & Welsh, T. N. (2019). No one knows what attention is. Attention, Perception, & Psychophysics, 81, 22882303.Google Scholar
Houtkamp, R., Spekreijse, H., & Roelfsema, P. R. (2003). A gradual spread of attention during mental curve tracing. Perception & Psychophysics, 65(7), 11361144.Google Scholar
Huang, L., & Pashler, H. (2007). A Boolean map theory of visual attention. Psychological Review, 114(3), 599631.Google Scholar
Huang, L., & Pashler, H. (2009). Reversing the attention effect in figure-ground perception. Psychological Science, 20(10), 11991201.Google Scholar
Huestegge, L., & Bröcker, A. (2016). Out of the corner of the driver’s eye: Peripheral processing of hazards in static traffic scenes. Journal of Vision, 16(2), 11.Google Scholar
Hyman, I. E., Boss, S. M., Wise, B. M., McKenzie, K. E., & Caggiano, J. M. (2010). Did you see the unicycling clown? Inattentional blindness while walking and talking on a cell phone. Applied Cognitive Psychology, 24(5), 597607.Google Scholar
Hyman, I. E., Sarb, B. A., & Wise-Swanson, B. M. (2014). Failure to see money on a tree: inattentional blindness for objects that guided behavior. Frontiers in Psychology, 5, 356.Google Scholar
Intriligator, J., & Cavanagh, P. (2001). The spatial resolution of visual attention. Cogn. Psychol., 43, 171216.Google Scholar
James, W. (1890). Principles of Psychology. New York: Holt.Google Scholar
Jolicoeur, P., & Ingleton, M. (1991). Size invariance in curve tracing. Memory & Cognition, 19, 2136.Google Scholar
Jolicoeur, P., Ullman, S., & Mackay, M. (1986). Curve tracing: A possible basic operation in the perception of spatial relations. Memory & Cognition, 14(2), 129140.Google Scholar
Jolicoeur, P., Ullman, S., & Mackay, M. (1991). Visual curve tracing properties. Journal of Experimental Psychology: Human Perception and Performance, 17(4), 9971022. doi: 10.1037/0096-1523.17.4.997 Google Scholar
Joseph, J. S., Chun, M. M., & Nakayama, K. (1997). Attentional requirements in a ’preattentive’ feature search task. Nature, 387(6635), 805807.Google Scholar
Kanwisher, N., & Driver, J. (1992). Objects, attributes, and visual attention: Which, what, and where. Current Directions in Psychological Science, 1(1), 2631.Google Scholar
Kawabata, N., Yamagami, K., & Noaki, M. (1978). Visual fixation points and depth perception. Vision Research, 18(7), 853854.Google Scholar
Keshvari, S., & Rosenholtz, R. (2016). Pooling of continuous feature provides a unifying account of crowding. Journal of Vision, 16(3), 39.Google Scholar
Koch, C., & Crick, F. (2001). The zombie within. Nature, 411, 893.Google Scholar
Krauzlis, R. J., Bollimunta, A., Arcizet, F., & Wang, L. (2014). Attention as an effect not cause. (457-464, Ed.) Trends in Cognitive Sciences, 18(9), 457-464.Google Scholar
Kravitz, D. J., & Behrmann, M. (2014). Space-, object-, and feature-based attention interact to organize visual scenes. Attention, Percetpion, & Psychophysics, 73(8), 24342447.Google Scholar
Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago: University of Chicago Press.Google Scholar
Lamy, D., & Egeth, H. (2002). Object-based selection: The role of attentional shifts. Perception & Psychophysics, 64(1), 5266.Google Scholar
Larson, A. M., Freeman, T. E., Ringer, R. V., & Loschky, L. C. (2014). The spatiotemporal dynamics of scene gist recognition. J. Exp. Psych: Human Perception & Performance, 40(2), 471487.Google Scholar
Lavie, N., Hirst, A., de Fockert, J. W., & Viding, E. (2004). Load theory of selective attention and cognitive control. J. Exp. Psych.: General, 133(3), 339354.Google Scholar
Lettvin, J. Y. (1976). On seeing sidelong. The Sciences, 16(4), 1020.Google Scholar
Levin, D. T., & Simons, D. J. (1997). Failure to detect changes to attended objects in motion pictures. Psychonomic Bulletin & Review, 4, 501506.Google Scholar
Loftus, G. R., & Ginn, M. (1984). Perceptual and conceptual masking of pictures. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10(3), 435441.Google Scholar
Mack, A., & Clarke, J. (2012). Gist perception requires attention. Visual Cognition, 20(3), 300327.Google Scholar
Mack, A., & Rock, I. (1998). Inattentional blindness. Cambridge, MA: MIT Press.Google Scholar
Manassi, M., Lonchampt, S., Clarke, A., & Herzog, M. H. (2016). What crowding can tell us about object representations. Journal of Vision, 16(3):35, 113.Google Scholar
Manassi, M., Sayim, B., & Herzog, M. H. (2012). Grouping, pooling, and when bigger is better in visual crowding. Journal of Vision, 12(10):13, 114.Google Scholar
Martinez-Trujillo, J., & Treue, S. (2002). Attentional modulation strength in cortical area MT depends on stimulus contrast. Neuron, 35, 365370.Google Scholar
Matsukura, M., Brockmole, J. R., Boot, W. R., & Henderson, J. M. (2011). Oculomotor capture during real-world scene viewing depends on cognitive load. Vision Research, 5(1), 546552.Google Scholar
Maunsell, J. H., & Treue, S. (2006). Feature-based attention in visual cortex. Trends in Neuroscience, 29(6), 317322.Google Scholar
McDermott, J. H., & Simoncelli, E. P. (2011). Sound texture perception via statistics of the auditory periphery: evidence from sound synthesis. Neuron, 71, 926940.Google Scholar
Moran, J., & Desimone, R. (1985). Selective attention gates visual processing in the extrastriate cortex. Science, 229(4715), 782784.Google Scholar
Neisser, U. (1976). Cognition and reality. San Francisco: Freeman.Google Scholar
Neumann, O. (1987). Beyond capacity: A functional view of attention. In Heuer, H., & Sanders, A. F., Perspectives on Perception and Action, pp. 361394. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Oliva, A., & Torralba, A. (2001). Modeling the shape of the scene: A holistic representation of the spatial envelope. International Journal of Computer Vision 42, 145175. doi: 10.1023/A:1011139631724 Google Scholar
Oliva, A., & Torralba, A. (2006). Building the gist of a scene: The role of global image features in recognition. Prog. Brain Res., 155, 2336.Google Scholar
Palmer, E. M., Fencsik, D. E., Flusberg, S. J., Horowitz, T. S., & Wolfe, J. M. (2011). Signal detection evidence for limited capacity in visual search. Attention, Perception, & Psychophysics, 73, 24132424.Google Scholar
Palmer, J., Ames, C. T., & Lindsey, D. T. (1993). Measuring the effect of attention on simple visual search. J. of Exp. Psych.: Human Perception & Performance, 19(1), 108130.Google Scholar
Parkes, L., Lund, J., Angelucci, A., Solomon, J. A., & Morgan, J. (2001). Compulsory averaging of crowded orientation signals in human vision. Nature Neuroscience, 4, 739744.Google Scholar
Peterson, M. A., & Gibson, B. S. (1991). Directing spatial attention within an object: Altering the functional equivalence of shape description. Journal of Experimental Psychology: Human Perception and Performance, 17(1), 170182.Google Scholar
Piggins, D. (1979). the influence of line reduction and image stabilization on Necker cube reversal: comments upon Ellis and Stark (1978). Perception, 8, 719720.Google Scholar
Poder, E., & Wagemans, J. (2007). Crowding with conjunctions of simple features. Journal of Vision, 7(2), 23.Google Scholar
Pooresmaeli, A., & Roelfsema, P. R. (2014). A growth-cone model for the spread of object-based attention during contour grouping. Current Biology, 24, 28692877. doi: 10.1016/j.cub.2014.10.007 Google Scholar
Portilla, J., & Simoncelli, E. P. (2000). A parametric texture model based on joint statistics of complex wavelet coefficients. International Journal of Computer Vision, 40(1), 4970.Google Scholar
Potter, M. C. (1975). Meaning in visual search. Science, 187, 965966.Google Scholar
Pylyshyn, Z. W., & Storm, R. W. (1988). Tracking multiple independent targets: evidence for a parallel tracking mechanism. Spatial Vision, 3(3), 119.Google Scholar
Recarte, M. A., & Nunes, L. M. (2003). Mental workload while driving: Effects on visual search, discrimination, and decision making. Journal of Experimental Psychology: Applied, 9(2), 119137.Google Scholar
Rensink, R. A. (2000). Seeing, sensing, and scrutinizing. Vision Research, 40, 14691487.Google Scholar
Rensink, R. A., O’Regan, J. K., & Clark, J. J. (1997). To see or not to see: The need for attention to perceive changes in scenes. Psychological Science, 8(5), 368373.Google Scholar
Reynolds, J. H., Pasternak, T., & Desimone, R. (2000). Attention increases sensitivity of V4 neurons. Neuron, 26, 703714.Google Scholar
Robertshaw, K. D., & Wilkie, R. M. (2008). Does gaze influence steering around a bend? Journal of Vision, 8(4), 18.113.Google Scholar
Rosenholtz, R. (2011). What your visual system sees where you are not looking. Proc. SPIE 7865, Hum. Vis. Electron. Imaging, XVI. San Francisco: SPIE.Google Scholar
Rosenholtz, R. (2014). Texture perception. In Wagemans, J. (Ed.), The Oxford Handbook of Perceptual Organization (pp. 167186). Oxford, UK: Oxford University Press.Google Scholar
Rosenholtz, R. (2016). Capabilities and limitations of peripheral vision. Annual Rev. of Vision Sci., 2(1), 437457.Google Scholar
Rosenholtz, R. (2017). Capacity limits and how the visual system copes with them. Journal of Imaging Science and Technology (Proc. HVEI, 2017), 7865, 823.Google Scholar
Rosenholtz, R. (2020). Demystifying visual awareness: Peripheral encoding plus limited decision complexity resolve the paradox of rich visual experience and curious perceptual failures. Attention, Perception, & Psychophysics, 82(3), 901925. doi: 10.3758/s13414-019-01968-1 Google Scholar
Rosenholtz, R., Huang, J., & Ehinger, K. A. (2012). Rethinking the role of top-down attention in vision: effects attributable to a lossy representation in peripheral vision. Frontiers in Psychology, 3:13. doi: 10.3389/fpsyg.2012.00013 Google Scholar
Rosenholtz, R., Huang, J., Raj, A., Balas, B., & Ilie, L. (2012). A summary statistic representation in peripheral vision explains visual search. Journal of Vision, 12(4):14, 117.Google Scholar
Rosenholtz, R., Yu, D., & Keshvari, S. (2019). Challenges to pooling models of crowding: Implications for visual mechanisms. Journal of Vision, 19(7), 15.Google Scholar
Rousselet, G. A., Joubert, O., & Fabre-Thorpe, M. (2005). How long to get to the “gist” of real-world natural scenes. Visual Cognition, 12(6), 852877.Google Scholar
Rousselet, G. A., Thorpe, S. J., & Fabre-Thorpe, M. (2004). Processing of one, two, or four natural scenes in humans: the limits of parallelism. Vision Research, 44(9), 877894.Google Scholar
Ruggieri, V., & Fernandez, M. F. (1994). Gaze orientation in perception of reversible figures. Perceptual and Motor Skills, 78, 299303.Google Scholar
Sayim, B., Westheimer, G., & Herzog, M. H. (2010). Gestalt factors modulate basic spatial vision. Psychological Science, 21(5), 641644.Google Scholar
Shaw, M. L. (1978). A capacity allocation model for reaction time. Journal of Experimental Psychology: Human Perception and Performance, 4(4), 586598.Google Scholar
Simons, D. J., & Chabris, C. F. (1999). Gorillas in our midst: Sustained inattentional blindness for dynamic events. Perception, 28, 10591074.Google Scholar
Smith, M. E., Sharan, L., Park, E., Loschky, L. C., & Rosenholtz, R. (under revision). Difficulty detecting changes in complex scenes depends in part upon the strengths and limitations of peripheral vision. Journal of Vision.Google Scholar
Snyder, C. R. (1972). Selection, inspection, and naming in visual search. Journal of Experimental Psychology, 92(3), 428431.Google Scholar
Stewart, T. (2022, March). Overview of motor vehicle crashes in 2020. National Highway Safety Traffic Administration.Google Scholar
Strasburger, H., Rentschler, I., & Jüttner, M. (2011). Peripheral vision and pattern recognition: A review. Journal of Vision, 11(5), 13.Google Scholar
Theeuwes, J. (1992). Perceptual selectivity for color and form. Perception & Psychophysics, 51(6), 599606.Google Scholar
Tractinsky, N., & Shinar, D. (2008). Do we bump into things more while speaking on a cell phone? Proc. CHI ’08 Extended Abstracts, Alt CHI (pp. 2433-2442). New York: ACM.Google Scholar
Treisman, A. (2006). How the deployment of attention determines what we see. Visual Cognition, 14, 411443.Google Scholar
Treisman, A., & Gelade, G. (1980). A feature-integration theory of attention. Cogn. Psychol., 12, 97136.Google Scholar
Treisman, A., & Schmidt, H. (1982). Illusory conjunctions in the perception of objects. Cognitive Psychology, 14, 107141.Google Scholar
Tsal, Y., & Kolbet, L. (1985). Disambiguating ambiguous figures by selective attention. Quarterly Journal of Experimental Psychology, 37(1), 2537.Google Scholar
Ullman, S. (1984). Visual routines. Cognition, 18, 94159.Google Scholar
Ullman, S. (1996). Visual cognition and visual routines. In Ullman, S., High-Level Vision (pp. 263315). Cambridge, MA: MIT Press.Google Scholar
Van Essen, D. C., & Anderson, C. H. (1995). Information processing strategies and pathways in the primate visual system. In Zornetzer, S. F., Davis, J. L., Lau, C., & McKenna, T. (Eds.), An Introduction to Neural and Electronic Networks (2nd ed., pp. 4576). San Diego, CA: Academic.Google Scholar
VanRullen, R., Reddy, L., & Koch, C. (2004). Visual search and dual tasks reveal two distinct attentional resources. J. Cogn. Neurosci., 16, 414.Google Scholar
Wolfe, B., Dobres, J., Rosenholtz, R., & Reimer, B. (2017). More than the Useful Field: Considering peripheral vision in driving. Applied Ergonomics, 65, 316325.Google Scholar
Wolfe, B., Sawyer, B. D., Kosovicheva, A., Reimer, B., & Rosenholtz, R. (2019). Detection of brake lights while distracted: Separating peripheral vision from cognitive load. Attention, Perception, & Psychophysics, 81(8), 27982813.Google Scholar
Wolfe, B., Seppelt, B. D., Mehler, B., Reimer, B., & Rosenholtz, R. (2019). Rapid holistic perception and evasion of road hazards. Journal of Experimental Psychology: General, 149(3), 490500.Google Scholar
Wolfe, J. M. (1998). What can 1 million trials tell us about visual search. Psychological Science, 9(1), 3339.Google Scholar
Wolfe, J. M. (1999). Inattentional amnesia. In Coltheart, V. (Ed.), Fleeting Memories (pp. 7194). Cambridge, MA: MIT Press.Google Scholar
Wolfe, J. M., Kosovicheva, A., & Wolfe, B. (2022). Normal blindness: when we Look But Fail To See. Trends in Cognitive Sciences, 26(9), 809819.Google Scholar
Wolfe, J. M., Vo, M. L.-H., Evans, K. K., & Greene, M. R. (2011). Visual search in scenes involves selective and non-selective pathways. Trends in Cognitive Sciences, 15(2), 7784.Google Scholar
Wu, W. (2023, December 15). We know what attention is! Retrieved from Trends in Cognitive Sciences: https://doi.org/10.1016/j.tics.2023.11.007 Google Scholar
Young, R. (2012). Cognitive distraction while driving: A critical review of definitions and prevalence in crashes. SAE International Journal of Passenger Cars -- Electronic and Electrical Systems, 5(1), 326342.Google Scholar
Zhang, X., Huang, J., Yigit-Elliot, S., & Rosenholtz, R. (2015). Cube search, revisited. Journal of Vision, 15(3), 9.Google Scholar
Zivony, A., & Eimer, M. (2021). The diachronic account of attentional selectivity. Psychonomic Bulletin & Review 29(4). doi: 10.3758/s13423-021-02023-7 Google Scholar