Element contents
Series: Elements in Perception
Attending to Moving Objects
Published online by Cambridge University Press: 18 January 2023
Summary
Our minds are severely limited in how much information they can extensively process, in spite of being massively parallel at the visual end. When people attempt to track moving objects, only a limited number can be tracked, which varies with display parameters. Associated experiments indicate that spatial selection and updating has higher capacity than selection and updating of features such as color and shape, and is mediated by processes specific to each cerebral hemisphere, such that each hemifield has its own spatial tracking limit. These spatial selection processes act as a bottleneck that gate subsequent processing. To improve our understanding of this bottleneck, future work should strive to avoid contamination of tracking tasks by high-level cognition. While we are far from fully understanding how attention keeps up with multiple moving objects, what we already know illuminates the architecture of visual processing and offers promising directions for new discoveries.
Information
- Type
- Element
- Information
- Series: Elements in PerceptionOnline ISBN: 9781009003414Publisher: Cambridge University PressPrint publication: 09 February 2023
References
Aczel, B., Palfi, B., Szollosi, A. et al. (2018). Quantifying support for the null hypothesis in psychology: An empirical investigation. Advances in Methods and Practices in Psychological Science, 1(3):357–366.Google Scholar
Agosta, S., Magnago, D., Tyler, S. et al. (2017). The pivotal role of the right parietal lobe in temporal attention. Journal of Cognitive Neuroscience, 29(5):805–815.Google Scholar
Alnaes, D., Sneve, M. H., Espeseth, T., Pieter, S. H., and Laeng, B. (2014). Pupil size signals mental effort deployed during multiple object tracking and predicts brain activity in the dorsal attention network and the locus coeruleus. Journal of Vision, 14:1–20.Google Scholar
Alvarez, G. and Scholl, B. J. (2005). How does attention select and track spatially extended objects? New effects of attentional concentration and amplification. Journal of Experimental Psychology: General, 134(4):461–476.Google Scholar
Alvarez, G. A. and Cavanagh, P. (2005). Independent resources for attentional tracking in the left and right visual hemifields. Psychological Science, 16(8):637–643.Google Scholar
Alvarez, G. A. and Franconeri, S. L. (2007). How many objects can you track? Evidence for a resource-limited attentive tracking mechanism. Journal of Vision, 7(13):14,1–10.Google Scholar
Alvarez, G. A., Gill, J., and Cavanagh, P. (2012). Anatomical constraints on attention: Hemifield independence is a signature of multifocal spatial selection. Journal of Vision, 12(5):9, 1–20.Google Scholar
Alvarez, G. A. and Oliva, A. (2009). Spatial ensemble statistics are efficient codes that can be represented with reduced attention. Proceedings of the National Academy of Sciences of the United States of America, 106(18):7345–7350.Google Scholar
Alzahabi, R. and Cain, M. S. (2021). Ensemble perception during multiple-object tracking. Attention, Perception, & Psychophysics, 83(3):1263–1274.Google Scholar
Anstis, S. (1990). Imperceptible intersections: The chopstick illusion. In Blake, A. and Troscianko, T., editors, AI and the Eye, 105–117. John Wiley, London.Google Scholar
Awh, E. and Pashler, H. (2000). Evidence for split attentional foci. Journal of Experimental Psychology: Human Perception and Performance, 26(2):834–846.Google Scholar
Battelli, L., Alvarez, G., Carlson, T., and Pascual-Leone, A. (2009). The role of the parietal lobe in visual extinction studied with transcranial magnetic stimulation. Journal of Cognitive Neuroscience, 21(10):1946–1955.Google Scholar
Battelli, L., Cavanagh, P., Intriligator, J., Tramo, M. J., and Barton, J. J. S. (2001). Unilateral right parietal damage leads to bilateral deficit for high-level motion. Neuron, 32(1992):985–995.Google Scholar
Battelli, L., Cavanagh, P., Martini, P., and Barton, J. J. S. (2003). Bilateral deficits of transient visual attention in right parietal patients. Brain: A Journal of Neurology, 126(Pt 10):2164–2174.Google Scholar
Bertoni, S., Franceschini, S., Ronconi, L., Gori, S., and Facoetti, A. (2019). Is excessive visual crowding causally linked to developmental dyslexia? Neuropsychologia, 130:107–117.Google Scholar
Bettencourt, K. C., Michalka, S. W., and Somers, D. C. (2011). Shared filtering processes link attentional and visual short-term memory capacity limits. Journal of Vision, 11(10):22–22.Google Scholar
Bex, P. J., Dakin, S. C., and Simmers, A. J. (2003). The shape and size of crowding for moving targets. Vision Research, 43(27):2895–2904.Google Scholar
Bill, J., Pailian, H., Gershman, S. J., and Drugowitsch, J. (2020). Hierarchical structure is employed by humans during visual motion perception. Proceedings of the National Academy of Sciences, 117(39): 24581–24589.Google Scholar
Bouma, H. (1970). Interaction effects in parafoveal letter recognition. Nature, 226(5241):177–178.Google Scholar
Bowers, A. R., Anastasio, R. J., Sheldon, S. S. et al. (2013). Can we improve clinical prediction of at-risk older drivers? Accident Analysis & Prevention, 59: 537–547.Google Scholar
Burt, P. and Sperling, G. (1981). Time, distance, and feature trade-offs in visual apparent motion. Psychological Review, 88(2):171.Google Scholar
Button, K. S., Ioannidis, J. P., Mokrysz, C. et al. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14(May): 365–376.Google Scholar
Callahan-Flintoft, C., Holcombe, A. O., and Wyble, B. (2020). A delay in sampling information from temporally autocorrelated visual stimuli. Nature Communications, 11(1):1852.Google Scholar
Carlson, T., Alvarez, G., and Cavanagh, P. (2007). Quadrantic deficit reveals anatomical constraints on selection. Proceedings of the National Academy of Sciences of the United States of America, 104(33):13496–13500.Google Scholar
Chen, W.-Y., Howe, P. D., and Holcombe, A. O. (2013). Resource demands of object tracking and differential allocation of the resource. Attention, Perception & Psychophysics, 75(4):710–725.Google Scholar
Chesney, D. L. and Haladjian, H. H. (2011). Evidence for a shared mechanism used in multiple-object tracking and subitizing. Attention, Perception, & Psychophysics, 73(8):2457–2480.Google Scholar
Chin, J. M., Pickett, J. T., Vazire, S., and Holcombe, A. O. (2021). Questionable research practices and open science in quantitative criminology. Journal of Quantitative Criminology. https://doi.org/10.1007/s10940-021-09525-6.Google Scholar
Cohen, M., Pinto, Y., Howe, P. D. L., and Horowitz, T. S. (2011). The what-where trade-off in multiple-identity tracking. Attention, Perception & Psychophysics, 73(5):1422–1434.Google Scholar
Cohen, M. R. and Maunsell, J. H. (2011). Using neuronal populations to study the mechanisms underlying spatial and feature attention. Neuron, 70(6):1192–1204.Google Scholar
Cotton, P. L. and Smith, A. T. (2007). Contralateral visual hemifield representations in the human pulvinar nucleus. Journal of Neurophysiology, 98(3):1600–1609.Google Scholar
Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24(1):87–114.Google Scholar
Crowe, E. M., Howard, C. J., Attwood, A. S., and Kent, C. (2019). Goal-directed unequal attention allocation during multiple object tracking. Attention, Perception, & Psychophysics, 81(5):1312–1326.Google Scholar
Culham, J. C., Cavanagh, P., and Kanwisher, N. G. (2001). Attention response functions: Characterizing brain areas using fMRI activation during parametric variations of attentional load. Neuron, 32(4):737–745.Google Scholar
Davis, G. and Holmes, A. (2005). Reversal of object-based benefits in visual attention. Visual Cognition, 12(5):817–846.Google Scholar
Delvenne, J. (2012). Visual short-term memory and the bilateral field advantage. In Kalivas, G and Petralia, SF, editors, Short-Term Memory: New Research. Nova.Google Scholar
Delvenne, J.-F. (2005). The capacity of visual short-term memory within and between hemifields. Cognition, 96(3):B79–B88.Google Scholar
Dimond, S. and Beaumont, G. (1971). Use of two cerebral hemispheres to increase brain capacity. Nature, 232(5308):270–271.Google Scholar
Doran, M. M. and Hoffman, J. E. (2010). The role of visual attention in multiple object tracking: Evidence from ERPs. Attention, Perception, & Psychophysics, 72(1):33–52.Google Scholar
Drew, T., Mance, I., Horowitz, T. S., Wolfe, J. M., and Vogel, E. K. (2014). A soft handoff of attention between cerebral hemispheres. Current Biology, 24(10):1133–1137.Google Scholar
Eayrs, J. and Lavie, N. (2018). Establishing individual differences in perceptual capacity. Journal of Experimental Psychology: Human Perception and Performance, 44(8):1240.Google Scholar
Editors, W. (2021). Multiple object tracking. Wikipedia. https://en.wikipedia.org/wiki/Multiple_object_tracking.Google Scholar
Edwards, G., Berestova, A., and Battelli, L. (2021). Behavioral gain following isolation of attention. Scientific Reports, 11(1):19329.Google Scholar
Egly, R., Driver, J., and 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):161.Google Scholar
Falkner, A. L., Krishna, B. S., and Goldberg, M. E. (2010). Surround suppression sharpens the priority map in the lateral intraparietal area. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 30(38):12787–12797.Google Scholar
Faubert, J. and Von Grunau, M. (1995). The influence of two spatially distinct primers and attribute priming on motion induction. Vision Research, 35(22):3119–3130.Google Scholar
Fecteau, J. and Munoz, D. (2006). Salience, relevance, and firing: A priority map for target selection. Trends in Cognitive Sciences, 10(8):382–390.Google Scholar
Fehd, H. M. and Seiffert, A. E. (2008). Eye movements during multiple object tracking: Where do participants look? Cognition, 108(1):201–209.Google Scholar
Fencsik, D. E., Klieger, S. B., and Horowitz, T. S. (2007). The role of location and motion information in the tracking and recovery of moving objects. Perception & Psychophysics, 69(4):567–577.Google Scholar
Feria, C. S. (2013). Speed has an effect on multiple-object tracking independently of the number of close encounters between targets and distractors. Attention, Perception & Psychophysics, 75(1):53–67.Google Scholar
Fortenbaugh, F. C., DeGutis, J., Germine, L. et al. (2015). Sustained attention across the life span in a sample of 10,000: Dissociating ability and strategy. Psychological Science, 26(9):1497–1510.Google Scholar
Fougnie, D. and Marois, R. (2006). Distinct capacity limits for attention and working memory: Evidence from attentive tracking and visual working memory paradigms. Psychological Science, 17(6):526–534.Google Scholar
Francis, G. and Thunell, E. (2022). Excess success in articles on object-based attention. Attention, Perception & Psychophysics, 84: 700–714.Google Scholar
Franconeri, S. L. (2013). The nature and status of visual resources. In Reisberg, D., editor, Oxford Handbook of Cognitive Psychology, volume 8481. Oxford University Press, Oxford.Google Scholar
Franconeri, S. L., Alvarez, G. A., and Cavanagh, P. (2013a). Flexible cognitive resources: Competitive content maps for attention and memory. Trends in Cognitive Sciences, 17(3):134–141.Google Scholar
Franconeri, S. L., Alvarez, G. A., and Cavanagh, P. (2013b). Resource theory is not a theory: A reply to Holcombe. Online comment on Trends in Cognitive Sciences, 17(3): 134–141.Google Scholar
Franconeri, S. L., Jonathan, S. V., and Scimeca, J. M. (2010). Tracking multiple objects is limited only by object spacing, not by speed, time, or capacity. Psychological Science, 21(7):920–925.Google Scholar
Franconeri, S. L., Lin, J. Y., Pylyshyn, Z. W., Fisher, B., and Enns, J. T. (2008). Evidence against a speed limit in multiple-object tracking. Psychonomic Bulletin & Review, 15(4):802–808.Google Scholar
Goodale, M. A. and Milner, A. (1992). Separate visual pathways for perception and action. Trends in Neurosciences, 15(1):20–25.Google Scholar
Gurnsey, R., Roddy, G., and Chanab, W. (2011). Crowding is size and eccentricity dependent. Journal of Vision, 11:1–17.Google Scholar
Hagler, D. J.Jr, and Sereno, M. I. (2006). Spatial maps in frontal and prefrontal cortex. Neuroimage, 29(2):567–577.Google Scholar
Harrison, W. J., Ayeni, A. J., and Bex, P. J. (2019). Attentional selection and illusory surface appearance. Scientific Reports, 9(1):2227.Google Scholar
Harrison, W. J. and Rideaux, R. (2019). Voluntary control of illusory contour formation. Attention, Perception, & Psychophysics, 81(5):1522–1531.Google Scholar
Hayhoe, M. M., Bensinger, D. G., and Ballard, D. H. (1998). Task constraints in visual working memory. Vision Research, 38(1):125–137.Google Scholar
Hedge, C., Powell, G., and Sumner, P. (2018). The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences. Behavior Research Methods, 50(3):1166–1186.Google Scholar
Hemond, C. C., Kanwisher, N. G., and Op de Beeck, H. P. (2007). A preference for contralateral stimuli in human object- and face-selective cortex. PLoS ONE, 2(6):e574.Google Scholar
Hogendoorn, H., Carlson, T. A., and Verstraten, F. A. (2007). The time course of attentive tracking. Journal of Vision, 7(14):2, 1–10.Google Scholar
Holcombe, A. O. (2009). Temporal binding favours the early phase of colour changes, but not of motion changes, yielding the colour-motion asynchrony illusion. Visual Cognition, 17(1–2):232–253.Google Scholar
Holcombe, A. O. (2019). Comment: Capacity limits are caused by a finite resource, not spatial competition, 1–2. https://psyarxiv.com/2tg4n/. DOI: 10.31234/osf.io/2tg4n.Google Scholar
Holcombe, A. O. Temporal crowding imposes strong constraints on multiple object tracking. Unpublished manuscript. http://trackinglimits.whatanimalssee.com/Google Scholar
Holcombe, A. O., Chen, W., and Howe, P. D. L. (2014). Object tracking: Absence of long-range spatial interference supports resource theories. Journal of Vision, 14(6):1–21.Google Scholar
Holcombe, A. O. and Chen, W.-Y. (2012). Exhausting attentional tracking resources with a single fast-moving object. Cognition, 123(2).Google Scholar
Holcombe, A. O. and Chen, W.-y. (2013). Splitting attention reduces temporal resolution from 7 Hz for tracking one object to <3 Hz when tracking three. Journal of Vision, 13(1):1–19.Google Scholar
Holt, J. L. and Delvenne, J.-F. (2015). A bilateral advantage for maintaining objects in visual short term memory. Acta Psychologica, 154:54–61.Google Scholar
Horowitz, T. and Treisman, A. (1994). Attention and apparent motion. Spatial Vision, 8(2):193–220.Google Scholar
Horowitz, T. S., Klieger, S. B., Fencsik, D. E., Yang, K. K., a Alvarez, G., and Wolfe, J. M. (2007). Tracking unique objects. Perception & Psychophysics, 69(2):172–184.Google Scholar
Howard, C. J. and Holcombe, A. O. (2008). Tracking the changing features of multiple objects: Progressively poorer perceptual precision and progressively greater perceptual lag. Vision Research, 48(9):1164–1180.Google Scholar
Howard, C. J., Masom, D., and Holcombe, A. O. (2011). Position representations lag behind targets in multiple object tracking. Vision Research, 51(17): 1907-1919. https://doi.org/10.1016/j.visres.2011.07.001.Google Scholar
Howe, P. D. and Holcombe, A. O. (2012). Motion information is sometimes used as an aid to the visual tracking of objects. Journal of Vision, 12(13):1–10.Google Scholar
Howe, P. D., Horowitz, T. S., Wolfe, J., and Livingstone, M. S. (2009). Using fMRI to distinguish components of the multiple object tracking task. Journal of Vision, 9(4):1–11.Google Scholar
Howe, P. D., Incledon, N. C., and Little, D. R. (2012). Can attention be confined to just part of a moving object? Revisiting target-distractor merging in multiple object tracking. PloS One, 7(7):e41491.Google Scholar
Howe, P. D. L., Cohen, M. A., and Horowitz, T. S. (2010a). Distinguishing between parallel and serial accounts of multiple object tracking. Journal of Vision, 10:1–13.Google Scholar
Howe, P. D. L. and Ferguson, A. (2015). The identity-location binding problem. Cognitive Science, 39(7):1622–1645.Google Scholar
Howe, P. D. L., Holcombe, A. O., Lapierre, M. D., and Cropper, S. J. (2013). Visually tracking and localizing expanding and contracting objects. Perception, 42(12):1281–1300.Google Scholar
Howe, P. D. L., Pinto, Y., and Horowitz, T. S. (2010b). The coordinate systems used in visual tracking. Vision Research, 50(23):2375–2380.Google Scholar
Huang, L., Mo, L., and Li, Y. (2012). Measuring the interrelations among multiple paradigms of visual attention: An individual differences approach. Journal of Experimental Psychology: Human Perception and Performance, 38(2):414.Google Scholar
Hudson, C., Howe, P. D., and Little, D. R. (2012). Hemifield effects in multiple identity tracking. PloS One, 7(8):e43796.Google Scholar
Hung, G. K., Wilder, J., Curry, R., and Julesz, B. (1995). Simultaneous better than sequential for brief presentations. Journal of the Optical Society of America. A, Optics, Image Science, and Vision, 12(3):441–449.Google Scholar
Hyönä, J., Li, J., and Oksama, L. (2019). Eye behavior during multiple object tracking and multiple identity tracking. Vision, 3(3):37.Google Scholar
Intriligator, J. and Cavanagh, P. (2001). The spatial resolution of visual attention. Cognitive Psychology, 43(3):171–216.Google Scholar
Johansson, G. (1973). Visual perception of biological motion and a model for its analysis. Perception & Psychophysics, 14: 201–211.Google Scholar
John, L. K., Loewenstein, G., and Prelec, D. (2012). Measuring the prevalence of questionable research practices with incentives for truth telling. Psychological Science, 23(5):524–532.Google Scholar
Joo, S. J., White, A. L., Strodtman, D. J., and Yeatman, J. D. (2018). Optimizing text for an individual’s visual system: The contribution of visual crowding to reading difficulties. Cortex, 103:291–301.Google Scholar
Jovicich, J., Peters, R. J., Koch, C. et al. (2001). Brain areas specific for attentional load in a motion-tracking task. Journal of cognitive neuroscience, 13(8):1048–58.Google Scholar
Kahneman, D., Treisman, A., and Gibbs, B. J. (1992). The reviewing of object files: Object-specific integration of information. Cognitive Psychology, 24(2):175–219.Google Scholar
Kennedy, G. J., Tripathy, S. P., and Barrett, B. T. (2009). Early age-related decline in the effective number of trajectories tracked in adult human vision. Journal of Vision, 9(2):21–21.Google Scholar
Kimchi, R. and Peterson, M. A. (2008). Figure-ground segmentation can occur without attention. Psychological Science, 19(7):660–668.Google Scholar
Kolers, P. A. and Pomerantz, J. R. (1971). Figural change in apparent motion. Journal of Experimental Psychology, 87(1):99.Google Scholar
Korte, W. (1923). über die Gestaltauffassung im indirekten Sehen. Zeitschrift für Psychologie, 93:17–82.Google Scholar
Kubovy, M., Holcombe, A. O., and Wagemans, J. (1998). On the lawfulness of grouping by proximity. Cognitive Psychology, 35(1):71–98.Google Scholar
Li, J., Oksama, L., and Hyönä, J. (2019). Model of Multiple Identity Tracking (MOMIT) 2.0: Resolving the serial vs. parallel controversy in tracking. Cognition, 182:260–274.Google Scholar
Liu, G., Austen, E. L., Booth, K. S. et al. (2005). Multiple-object tracking is based on scene, not retinal, coordinates. Journal of experimental psychology. Human Perception and Performance, 31(2):235–247.Google Scholar
Liu, T., Jiang, Y., Sun, X., and He, S. (2009). Reduction of the crowding effect in spatially adjacent but cortically remote visual stimuli. Current Biology, 19(2):127–32.Google Scholar
Lo, S.-Y. and Holcombe, A. O. (2014). How do we select multiple features? Transient costs for selecting two colors rather than one, persistent costs for color– location conjunctions. Attention, Perception, & Psychophysics, 76(2):304–321.Google Scholar
Lochner, M. J. and Trick, L. M. (2014). Multiple-object tracking while driving: The multiple-vehicle tracking task. Attention, Perception & Psychophysics, 76: 2326–2345. https://doi.org/10.3758/s13414-014-0694-3.Google Scholar
Lou, H., Lorist, M. M., and Pilz, K. S. (2020). Individual differences in the temporal dynamics of attentional selection. https://doi.org/10.31234/osf.io/w5b43.Google Scholar
Lovett, A., Bridewell, W., and Bello, P. (2019). Selection enables enhancement: An integrated model of object tracking. Journal of Vision, 19(14):23.Google Scholar
Luck, S. J., Hillyard, S. A., Mangun, G. R., and Gazzaniga, M. S. (1989). Independent hemispheric attentional systems mediate visual search in split-brain patients. Nature, 342(6249):543–545.Google Scholar
Luck, S. J., Hillyard, S. A., Mangun, G. R., and Gazzaniga, M. S. (1994). Independent attentional scanning in the separated hemispheres of split-brain patients. Journal of Cognitive Neuroscience, 6(1):84–91.Google Scholar
Lukavskỳ, J. (2013). Eye movements in repeated multiple object tracking. Journal of Vision, 13(7):1–16.Google Scholar
Lunghi, C., Burr, D. C., and Morrone, C. (2011). Brief periods of monocular deprivation disrupt ocular balance in human adult visual cortex. Current Biology, 21(14):R538–R539.Google Scholar
Luu, T. and Howe, P. D. L. (2015). Extrapolation occurs in multiple object tracking when eye movements are controlled. Attention, Perception, & Psychophysics, 77: 1919–1929. https://doi.org/10.3758/s13414-015-0891-8.Google Scholar
Mackenzie, A. K. and Harris, J. M. (2017). A link between attentional function, effective eye movements, and driving ability. Journal of Experimental Psychology: Human Perception and Performance, 43(2):381.Google Scholar
Mackenzie, A. K., Vernon, M. L., Cox, P. R. et al. (2021). The Multiple Object Avoidance (MOA) task measures attention for action: Evidence from driving and sport. Behavior Research Methods, 54: 1508–1529.Google Scholar
Maechler, M. R., Cavanagh, P., and Tse, P. U. (2021). Attentional tracking takes place over perceived rather than veridical positions. Attention, Perception, & Psychophysics, 83: 1455–1462.Google Scholar
Makovski, T. and Jiang, Y. V. (2009). Feature binding in attentive tracking of distinct objects. Visual Cognition, 17(1–2):180–194.Google Scholar
Mareschal, I., Morgan, M. J., and Solomon, J. A. (2010). Attentional modulation of crowding. Vision Research, 50(8):805–809.Google Scholar
Maruya, K., Holcombe, A. O., and Nishida, S. (2013). Rapid encoding of relationships between spatially remote motion signals. Journal of Vision, 13(4):1–20.Google Scholar
Matthews, N. and Welch, L. (2015). Left visual field attentional advantage in judging simultaneity and temporal order. Journal of Vision, 15(2):7.Google Scholar
Merkel, C., Hopf, J.-M., and Schoenfeld, M. A. (2017). Spatio-temporal dynamics of attentional selection stages during multiple object tracking. NeuroImage, 146:484–491.Google Scholar
Merkel, C., Stoppel, C. M., Hillyard, S. A. et al. (2014). Spatio-temporal patterns of brain activity distinguish strategies of multiple-object tracking. Journal of Cognitive Neuroscience, 26(1):28–40.Google Scholar
Mesulam, M.-M. (1999). Spatial attention and neglect: Parietal, frontal and cingulate contributions to the mental representation and attentional targeting of salient extrapersonal events. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 354(1387):1325–1346.Google Scholar
Meyerhoff, H. S. and Papenmeier, F. (2020). Individual differences in visual attention: A short, reliable, open-source, and multilingual test of multiple object tracking in PsychoPy. Behavior Research Methods, 52(6):2556–2566.Google Scholar
Meyerhoff, H. S., Papenmeier, F., Jahn, G., and Huff, M. (2015). Distractor locations influence multiple object tracking beyond interobject spacing: Evidence from equidistant distractor displacements. Experimental Psychology, 62(3):170–180.Google Scholar
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2):81.Google Scholar
Minami, T., Shinkai, T., and Nakauchi, S. (2019). Hemifield crossings during multiple object tracking affect task performance and steady-state visual evoked potentials. Neuroscience, 409:162–168.Google Scholar
Nakayama, K., He, Z. J., and Shimojo, S. (1995). Visual surface representation: A critical link between lower-level and higher-level vision. Visual Cognition: An Invitation to Cognitive Science, 2:1–70.Google Scholar
Neisser, U. (1963). Decision-time without reaction-time: Experiments in visual scanning. The American Journal of Psychology, 76(3):376.Google Scholar
Ngiam, W. X., Khaw, K. L., Holcombe, A. O., and Goodbourn, P. T. (2019). Visual working memory for letters varies with familiarity but not complexity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(10):1761.Google Scholar
Norman, D. A. and Bobrow, D. G. (1975). On data-limited and resource-limited processes. Cognitive Psychology, 7:44–64.Google Scholar
Nummenmaa, L., Oksama, L., Glerean, E., and Hyönä, J. (2017). Cortical circuit for binding object identity and location during multiple-object tracking. Cerebral Cortex, 27(1):162–172.Google Scholar
Oberauer, K. (2002). Access to information in working memory: Exploring the focus of attention. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28(3):411.Google Scholar
Oberauer, K. et al. (2018). Benchmarks for models of short-term and working memory. Psychological Bulletin, 144(9):885.Google Scholar
Oksama, L. and Hyönä, J. (2004). Is multiple object tracking carried out automatically by an early vision mechanism independent of higher-order cognition? An individual difference approach. Visual Cognition, 11(5):631–671.Google Scholar
Oksama, L. and Hyönä, J. (2016). Position tracking and identity tracking are separate systems: Evidence from eye movements. Cognition, 146:393–409.Google Scholar
Ongchoco, J. D. K. and Scholl, B. J. (2019). How to create objects with your mind: From object-based attention to attention-based objects. Psychological Science, 30(11):1648–1655.Google Scholar
O’Regan, J. K. (1992). Solving the “real” mysteries of visual perception: The world as an outside memory. Canadian Journal of Psychology/Revue Canadienne De Psychologie, 46(3):461.Google Scholar
O’Reilly, R. C., Ranganath, C., and Russin, J. L. (2022). The Structure of Systematicity in the Brain. Current Directions in Psychological Science, 31(2): 124–130.Google Scholar
Pailian, H., Carey, S. E., Halberda, J., and Pepperberg, I. M. (2020). Age and species comparisons of visual mental manipulation ability as evidence for its development and evolution. Scientific Reports, 10(1):1–7.Google Scholar
Palmer, J. (1995). Attention in visual search: Distinguishing four causes of a set-size effect. Current Directions in Psychological Science, 4(4):118–123.Google Scholar
Papenmeier, F., Meyerhoff, H. S., Jahn, G., and Huff, M. (2014). Tracking by location and features: Object correspondence across spatiotemporal discontinuities during multiple object tracking. Journal of Experimental Psychology: Human Perception and Performance, 40(1):159.Google Scholar
Pelli, D. G. and Tillman, K. A. (2008). The uncrowded window of object recognition. Nature Neuroscience, 11(10):1129–1135.Google Scholar
Peter, U. T. (2005). Voluntary attention modulates the brightness of overlapping transparent surfaces. Vision Research, 45(9):1095–1098.Google Scholar
Peterson, M. A. (2014). Low-level and high-level contributions to figure-ground organization: evidence and theoretical implications. In Wagemans, J, editor. The Oxford Handbook of Perceptual Organization. New York: Oxford University Press.Google Scholar
Petrov, Y. and Meleshkevich, O. (2011). Asymmetries and idiosyncratic hot spots in crowding. Vision Research, 51(10):1117–1123.Google Scholar
Piazza, M. (2010). Neurocognitive start-up tools for symbolic number representations. Trends in Cognitive Sciences, 14(12):542–551.Google Scholar
Pilz, K. S., Roggeveen, A. B., Creighton, S. E., Bennett, P. J., and Sekuler, A. B. (2012). How prevalent is object-based attention? PLoS ONE, 7(2):e30693.Google Scholar
Proffitt, D. R., Kaiser, M. K., and Whelan, S. M. (1990). Understanding wheel dynamics. Cognitive Psychology, 22(3):342–373.Google Scholar
Pylyshyn, Z. (1989). The role of location indexes in spatial perception: A sketch of the FINST spatial-index model. Cognition, 32(1):65–97.Google Scholar
Pylyshyn, Z. (2001). Visual indexes, preconceptual objects, and situated vision. Cognition, 80:127–158.Google Scholar
Pylyshyn, Z. (2004). Some puzzling findings in multiple object tracking: I. Tracking without keeping track of object identities. Visual Cognition, 11(7):801–822.Google Scholar
Pylyshyn, Z., Burkell, J., Fisher, B. et al. (1994). Multiple parallel access in visual attention. Canadian Journal of Experimental Psychology/Revue Canadienne De Psychologie Expérimentale, 48(2):260.Google Scholar
Pylyshyn, Z. W. (2006). Seeing and Visualizing: It’s Not What You Think. Life and Mind. MIT Press, Cambridge, Mass., 1. mit press paperback ed.Google Scholar
Pylyshyn, Z. W. (2007). Things and Places: How the Mind Connects with the World. MIT Press.Google Scholar
Pylyshyn, Z. W. and Storm, R. W. (1988). Tracking multiple independent targets: Evidence for a parallel tracking mechanism. Spatial Vision, 3(3):179–197.Google Scholar
Rabelo, A. L. A., Farias, J. E. M., Sarmet, M. M. et al. (2020). Questionable research practices among Brazilian psychological researchers: Results from a replication study and an international comparison. International Journal of Psychology, 55(4):674–683.Google Scholar
Redick, T. S. and Engle, R. W. (2006). Working memory capacity and attention network test performance. Applied Cognitive Psychology: The Official Journal of the Society for Applied Research in Memory and Cognition, 20(5):713–721.Google Scholar
Reichle, E. D., Liversedge, S. P., Pollatsek, A., and Rayner, K. (2009). Encoding multiple words simultaneously in reading is implausible. Trends in Cognitive Sciences, 13(February):115–119.Google Scholar
Rensink, R. (2000). Visual search for change: A probe into the nature of attentional processing. Visual Cognition, 7(1):345–376.Google Scholar
Revkin, S. K., Piazza, M., Izard, V., Cohen, L., and Dehaene, S. (2008). Does subitizing reflect numerical estimation? Psychological science, 19(6):607–614.Google Scholar
Rizzolatti, G., Umiltà, C., and Berlucchi, G. (1971). Opposite superiorities of the right and left cerbral hemispheres in discriminative reaction time to physiognomical and alphabetical material. Brain: A Journal of Neurology, 94(3): 431–442.Google Scholar
Robinson, M. M., Benjamin, A. S., and Irwin, D. E. (2020). Is there a K in capacity? Assessing the structure of visual short-term memory. Cognitive Psychology, 121:101305.Google Scholar
Roudaia, E. and Faubert, J. (2017). Different effects of aging and gender on the temporal resolution in attentional tracking. Journal of Vision, 17(11):1.Google Scholar
Saenz, M., Buracas, G. T., and Boynton, G. M. (2002). Global effects of feature-based attention in human visual cortex. Nature Neuroscience, 5(7):631–632.Google Scholar
Saiki, J. (2002). Multiple-object permanence tracking: Limitation in maintenance and transformation of perceptual objects. Progress in Brain Research, 140:133–148.Google Scholar
Saiki, J. (2019). Robust color-shape binding representations for multiple objects in visual working memory. Journal of Experimental Psychology: General, 148(5):905–925.Google Scholar
Saiki, J. and Holcombe, A. O. (2012). Blindness to a simultaneous change of all elements in a scene, unless there is a change in summary statistics. Journal of Vision, 12:1–11.Google Scholar
Schneider, K. A. and Kastner, S. (2005). Visual responses of the human superior colliculus: A high-resolution functional magnetic resonance imaging study. Journal of Neurophysiology, 94(4):2491–2503.Google Scholar
Scholl, B. (2001). Objects and attention: The state of the art. Cognition, 80(1/2):1–46.Google Scholar
Scholl, B. J. (2008). What have we learned about attention from multiple-object tracking (and vice versa)? In Dedrick, D. and Trick, L., editors, Computation, Cognition, and Pylyshyn, pages 49–78. MIT Press.Google Scholar
Scholl, B. J., Pylyshyn, Z. W., and Feldman, J. (2001). What is a visual object? Evidence from target merging in multiple object tracking. Cognition, 80(1-2):159–177.Google Scholar
Scholl, B. J., Simons, D. J., and Levin, D. T. (2004). “Change blindness” blindness: An implicit measure of a metacognitive error. In Levin, D. T., editor, Thinking and Seeing: Visual Metacognition in Adults and Children, pages 145–164. MIT Press, Cambridge, MA.Google Scholar
Schönbrodt, F. D. and Perugini, M. (2013). At what sample size do correlations stabilize? Journal of Research in Personality, 47(5):609–612.Google Scholar
Sekuler, R., McLaughlin, C., and Yotsumoto, Y. (2008). Age-related changes in attentional tracking of multiple moving objects. Perception, 37(6):867–876.Google Scholar
Sereno, A. B. and Kosslyn, S. M. (1991). Discrimination within and between hemifields: A new constraint on theories of attention. Neuropsychologia, 29(7):659–675.Google Scholar
Sereno, M. I., Pitzalis, S., and Martinez, A. (2001). Mapping of contralateral space in retinotopic coordinates by a parietal cortical area in humans. Science, 294(5545):1350–1354.Google Scholar
Shiffrin, R. M. and Gardner, G. T. (1972). Visual processing capacity and attentional control. Journal of Experimental Psychology, 93(1):72.Google Scholar
Shim, W. M., a. Alvarez, G., and Jiang, Y. V. (2008). Spatial separation between targets constrains maintenance of attention on multiple objects. Psychonomic Bulletin & Review, 15(2):390–397.Google Scholar
Shim, W. M., a Alvarez, G., Vickery, T. J., and Jiang, Y. V. (2010). The number of attentional foci and their precision are dissociated in the posterior parietal cortex. Cerebral Cortex, 20(6):1341–1349.Google Scholar
Shomstein, S. and Behrmann, M. (2008). Object-based attention: Strength of object representation and attentional guidance. Perception & Psychophysics, 70(1):132–144.Google Scholar
Shomstein, S. and Yantis, S. (2002). Object-based attention: Sensory modulation or priority setting? Perception & Psychophysics, 64(1):41–51.Google Scholar
Simon, H. A. (1969). The Sciences of the Artificial, Reissue of the Third Edition with a New Introduction by John Laird. MIT Press Academic, Cambridge, MA, 3rd ed.Google Scholar
Simons, D. J., Boot, W. R., Charness, N. et al. (2016). Do “brain-training” programs work? Psychological Science in the Public Interest, 17(3):103–186.Google Scholar
Sternberg, S. (1969). The discovery of processing stages: Extensions of Donders’ method. Acta Psychologica, 30:276–315.Google Scholar
Störmer, V. S., a Alvarez, G., and Cavanagh, P. (2014). Within-hemifield competition in early visual areas limits the ability to track multiple objects with attention. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 34(35):11526–11533.Google Scholar
Strasburger, H. (2014). Dancing letters and ticks that buzz around aimlessly: On the origin of crowding. Perception, 43(9):963–976.Google Scholar
Strong, R. W. and Alvarez, G. A. (2020). Hemifield-specific control of spatial attention and working memory: Evidence from hemifield crossover costs. Journal of Vision, 20(8):24.Google Scholar
Suchow, J. W. and Alvarez, G. A. (2011). Motion Silences Awareness of Visual Change. Current Biology, 21(2): 140–143.Google Scholar
Tadin, D., Lappin, J. S., Blake, R., and Grossman, E. D. (2002). What constitutes an efficient reference frame for vision? Nature Neuroscience, 5(10):1010–1015.Google Scholar
Tombu, M. and Seiffert, A. E. (2008). Attentional costs in multiple-object tracking. Cognition, 108:1–25.Google Scholar
Tombu, M. and Seiffert, A. E. (2011). Tracking planets and moons: Mechanisms of object tracking revealed with a new paradigm. Attention, Perception, & Psychophysics, 73: 738–750.Google Scholar
Townsend, J. T. (1990). Serial vs. parallel processing: Sometimes they look like Tweedledum and Tweedledee but they can (and should) be distinguished. Psychological Science, 1(1):46–54.Google Scholar
Treisman, A. and Gelade, G. (1980). A feature integration theory of attention. Cognitive Psychology, 12:97–136.Google Scholar
Treisman, A. and Schmidt, H. (1982). Illusory conjunctions in the perception of objects. Cognitive Psychology, 14:107–141.Google Scholar
Treisman, A. M. (1964). Verbal cues, language, and meaning in selective attention. The American Journal of Psychology, 77(2):206.Google Scholar
Treviño, M., Zhu, X., Lu, Y. Y. et al. (2021). How do we measure attention? Using factor analysis to establish construct validity of neuropsychological tests. Cognitive Research: Principles and Implications, 6(1):51.Google Scholar
Trick, L. M., Mutreja, R., and Hunt, K. (2012). Spatial and visuospatial working memory tests predict performance in classic multiple-object tracking in young adults, but nonspatial measures of the executive do not. Attention, Perception, & Psychophysics, 74(2):300–311.Google Scholar
Trick, L. M., Perl, T., and Sethi, N. (2005). Age-related differences in multiple-object tracking. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 60(2):P102–P105.Google Scholar
Tse, P., Cavanagh, P., and Nakayama, K. (1998). The role of parsing in high-level motion processing. In Watanabe, T., editor, High-level Motion Processing: Computational, Neurobiological, and Psychophysical Perspectives, 249–266. MIT Press.Google Scholar
Tsotsos, J. K., Culhane, S. M., Wai, W. et al. (1995). Modeling visual attention via selective tuning. Artificial Intelligence, 78:507–545.Google Scholar
Tsotsos, J. K., Rodríguez-Sánchez, A. J., Rothenstein, A. L., and Simine, E. (2008). The different stages of visual recognition need different attentional binding strategies. Brain Research, 1225(2007):119–132.Google Scholar
Umemoto, A., Drew, T., Ester, E. F., and Awh, E. (2010). A bilateral advantage for storage in visual working memory. Cognition, 117(1):69–79.Google Scholar
Van der Burg, E., Cass, J., and Theeuwes, J. (2019). Changes (but not differences) in motion direction fail to capture attention. Vision Research, 165:54–63.Google Scholar
VanMarle, K. and Scholl, B. J. (2003). Attentive tracking of objects versus substances. Psychological Science, 14(5):498–504.Google Scholar
Vater, C., Gray, R., and Holcombe, A. O. (2021). A critical systematic review of the Neurotracker perceptual-cognitive training tool. Psychonomic Bulletin & Review, 28: 1458–1483.Google Scholar
Vater, C., Kredel, R., and Hossner, E.-J. (2017). Disentangling vision and attention in multiple-object tracking: How crowding and collisions affect gaze anchoring and dual-task performance. Journal of Vision, 17(5):1–13.Google Scholar
Vogel, E. K., Woodman, G. F., and Luck, S. J. (2006). The time course of consolidation in visual working memory. Journal of Experimental Psychology. Human Perception and Performance, 32(6):1436–1451.Google Scholar
Wang, L., Zhang, K., He, S., and Jiang, Y. (2010). Searching for life motion signals: Visual search asymmetry in local but not global biological-motion processing. Psychological Science, 21(8):1083–1089.Google Scholar
Wang, Y. and Vul, E. (2021). The role of kinematic properties in multiple object tracking. Journal of Vision, 21(3):1–15.Google Scholar
Wannig, A., Stanisor, L., and Roelfsema, P. R. (2011). Automatic spread of attentional response modulation along Gestalt criteria in primary visual cortex. Nature Neuroscience, 14(10):1243–1244.Google Scholar
Warren, P. A. and Rushton, S. K. (2007). Perception of object trajectory: Parsing retinal motion into self and object movement components. Journal of Vision, 7(11):2.Google Scholar
Wertheimer, M. (1912). Experimentelle Studien über das Sehen von Bewegung. Zeitschrift für Psychologie, 61:161–165.Google Scholar
White, A. L. and Carrasco, M. (2011). Feature-based attention involuntarily and simultaneously improves visual performance across locations. Journal of Vision, 11(6):1–10.Google Scholar
White, A. L., Palmer, J., and Boynton, G. M. (2018). Evidence of serial processing in visual word recognition. Psychological Science, 29(7):1062–1071.Google Scholar
White, A. L., Palmer, J., Boynton, G. M., and Yeatman, J. D. (2019). Parallel spatial channels converge at a bottleneck in anterior word-selective cortex. Proceedings of the National Academy of Sciences, 116(20):10087–10096.Google Scholar
Wilbiks, J. M. P. and Beatteay, A. (2020). Individual differences in multiple object tracking, attentional cueing, and age account for variability in the capacity of audiovisual integration. Attention, Perception, & Psychophysics, 82: 3521–3543.Google Scholar
Wolfe, J. M. (2021). Guided Search 6.0: An updated model of visual search. Psychonomic Bulletin & Review, 28(4):1060–1092.Google Scholar
Wolfe, J. M. and Bennett, S. C. (1997). Preattentive object files: Shapeless bundles of basic features. Vision Research, 37(1):25–43.Google Scholar
Wolford, G. (1975). Perturbation model for letter identification. Psychological Review, 82(3):184.Google Scholar
Wu, C.-C. and Wolfe, J. M. (2018). Comparing eye movements during position tracking and identity tracking: No evidence for separate systems. Attention, Perception, & Psychophysics, 80(2):453–460.Google Scholar
Wuerger, S., Shapley, R., and Rubin, N. (1996). “On the visually perceived direction of motion” by Hans Wallach: 60 years later. Perception, 25:1317–1367.Google Scholar
Xu, Y. and Franconeri, S. L. (2015). Capacity for Visual Features in Mental Rotation. Psychological Science, 26(8):1241–1251.Google Scholar
Yantis, S. (1992). Multielement visual tracking: Attention and perceptual organization. Cognitive Psychology, 24(3):295–340.Google Scholar
Yilmaz, A., Javed, O., and Shah, M. (2006). Object tracking: A survey. ACM Computing Surveys, 38(4):13.Google Scholar
Zelinsky, G. J. and Neider, M. B. (2008). An eye movement analysis of multiple object tracking in a realistic environment. Visual Cognition, 16(5):553–566.Google Scholar
Zelinsky, G. J. and Todor, A. (2010). The role of “rescue saccades” in tracking objects through occlusions. Journal of Vision, 10(14):1–13.Google Scholar
Zhang, J. and Mueller, S. T. (2005). A note on ROC analysis and non-parametric estimate of sensitivity. Psychometrika, 70(1):203–212.Google Scholar
Zylberberg, A., Fernández Slezak, D., Roelfsema, P. R., Dehaene, S., and Sigman, M. (2010). The brain’s router: A cortical network model of serial processing in the primate brain. PLoS Computational Biology, 6(4):e1000765.Google Scholar
Accessibility standard: Unknown
Why this information is here
This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.Accessibility Information
Accessibility compliance for the HTML of this element is currently unknown
and may be updated in the future.
- 20
- Cited by