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Artículos de revistas sobre el tema "Visual attention in time"

Autor: Grafiati

Publicado: 11 de marzo de 2023

Última modificación: 31 de julio de 2025

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1

Zhou, Yan-Bang, Qiang Li, and Hong-Zhi Liu. "Visual attention and time preference reversals." Judgment and Decision Making 16, no. 4 (2021): 1010–38. http://dx.doi.org/10.1017/s1930297500008068.

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AbstractTime preference reversal refers to systematic inconsistencies between preferences and bids for intertemporal options. From the two eye-tracking studies (N1 = 60, N2 = 110), we examined the underlying mechanisms of time preference reversal. We replicated the reversal effect in which individuals facing a pair of intertemporal options choose the smaller-sooner option but assign a higher value to the larger-later one. Results revealed that the mean fixation duration and the proportion of gaze time on the outcome attribute varied across the choice and bid tasks. In addition, time preference

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2

Chun, Marvin M. "Visual working memory as visual attention sustained internally over time." Neuropsychologia 49, no. 6 (2011): 1407–9. http://dx.doi.org/10.1016/j.neuropsychologia.2011.01.029.

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3

Busse, L. "The Time Course of Shifting Visual Attention." Journal of Neuroscience 26, no. 15 (2006): 3885–86. http://dx.doi.org/10.1523/jneurosci.0459-06.2006.

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4

Egeth, Howard E., and Steven Yantis. "VISUAL ATTENTION: Control, Representation, and Time Course." Annual Review of Psychology 48, no. 1 (1997): 269–97. http://dx.doi.org/10.1146/annurev.psych.48.1.269.

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5

Ruhnau, E., and V. Haase. "Space-time structure of selective visual attention." International Journal of Psychophysiology 14, no. 2 (1993): 146. http://dx.doi.org/10.1016/0167-8760(93)90239-l.

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6

Ward, Robert, John Duncan, and Kimron Shapiro. "The Slow Time-Course of Visual Attention." Cognitive Psychology 30, no. 1 (1996): 79–109. http://dx.doi.org/10.1006/cogp.1996.0003.

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7

Srivastava, Priyanka, and Narayanan Srinivasan. "Time course of visual attention with emotional faces." Attention, Perception, & Psychophysics 72, no. 2 (2010): 369–77. http://dx.doi.org/10.3758/app.72.2.369.

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8

Chastain, Garvin. "Time-course of location changes of visual attention." Bulletin of the Psychonomic Society 29, no. 5 (1991): 425–28. http://dx.doi.org/10.3758/bf03333960.

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9

Couffe, C., R. Mizzi, and G. A. Michael. "Salience-based progression of visual attention: Time course." Psychologie Française 61, no. 3 (2016): 163–75. http://dx.doi.org/10.1016/j.psfr.2015.04.003.

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10

Drisdelle, Brandi L., Greg L. West, and Pierre Jolicoeur. "The deployment of visual spatial attention during visual search predicts response time." NeuroReport 27, no. 16 (2016): 1237–42. http://dx.doi.org/10.1097/wnr.0000000000000684.

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11

Mathôt, Sebastiaan, and Jan Theeuwes. "Visual attention and stability." Philosophical Transactions of the Royal Society B: Biological Sciences 366, no. 1564 (2011): 516–27. http://dx.doi.org/10.1098/rstb.2010.0187.

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In the present review, we address the relationship between attention and visual stability. Even though with each eye, head and body movement the retinal image changes dramatically, we perceive the world as stable and are able to perform visually guided actions. However, visual stability is not as complete as introspection would lead us to believe. We attend to only a few items at a time and stability is maintained only for those items. There appear to be two distinct mechanisms underlying visual stability. The first is a passive mechanism: the visual system assumes the world to be stable, unle

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12

RODRIGUEZ-SANCHEZ, ANTONIO J., EVGUENI SIMINE, and JOHN K. TSOTSOS. "ATTENTION AND VISUAL SEARCH." International Journal of Neural Systems 17, no. 04 (2007): 275–88. http://dx.doi.org/10.1142/s0129065707001135.

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Selective Tuning (ST) presents a framework for modeling attention and in this work we show how it performs in covert visual search tasks by comparing its performance to human performance. Two implementations of ST have been developed. The Object Recognition Model recognizes and attends to simple objects formed by the conjunction of various features and the Motion Model recognizes and attends to motion patterns. The validity of the Object Recognition Model was first tested by successfully duplicating the results of Nagy and Sanchez. A second experiment was aimed at an evaluation of the model's

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13

Saarinen, Jukka. "Focal Visual Attention and Pattern Discrimination." Perception 22, no. 5 (1993): 509–15. http://dx.doi.org/10.1068/p220509.

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Pattern discrimination in the presence of distractor patterns is improved when the stimulus display is preceded by a precue designating the location of the target pattern. Experiments were conducted to determine how big an improvement the precue produced. The specific question of whether the observer is able to process selectively the stimulus pattern in the cued location of the display and ignore the patterns of the noncued locations was addressed. In order to study this, reaction time for pattern discrimination on a blank background (no distractors) was compared with the reaction time when t

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14

Gottlob, Lawrence R. "Location cuing and response time distributions in visual attention." Perception & Psychophysics 66, no. 8 (2004): 1293–302. http://dx.doi.org/10.3758/bf03194999.

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15

Watanabe, Katsumi. "Maintaining Visual Attention over Time: Effects of Object Continuity." i-Perception 2, no. 4 (2011): 207. http://dx.doi.org/10.1068/ic207.

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16

Carlson, Thomas A., Hinze Hogendoorn, and Frans A. J. Verstraten. "The speed of visual attention: What time is it?" Journal of Vision 6, no. 12 (2006): 6. http://dx.doi.org/10.1167/6.12.6.

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17

Scalf, Paige, Elexa ST. JOHN-SAALTINK, Markus Barth, Hakwan Lau, and Floris De Lange. "Time-resolved fMRI tracks attention through the visual field." Journal of Vision 16, no. 12 (2016): 907. http://dx.doi.org/10.1167/16.12.907.

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18

Tünnermann, Jan, and Bärbel Mertsching. "Region-Based Artificial Visual Attention in Space and Time." Cognitive Computation 6, no. 1 (2013): 125–43. http://dx.doi.org/10.1007/s12559-013-9220-5.

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19

Kim, Yeongbin, Joongchol Shin, Hasil Park, and Joonki Paik. "Real-Time Visual Tracking with Variational Structure Attention Network." Sensors 19, no. 22 (2019): 4904. http://dx.doi.org/10.3390/s19224904.

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Online training framework based on discriminative correlation filters for visual tracking has recently shown significant improvement in both accuracy and speed. However, correlation filter-base discriminative approaches have a common problem of tracking performance degradation when the local structure of a target is distorted by the boundary effect problem. The shape distortion of the target is mainly caused by the circulant structure in the Fourier domain processing, and it makes the correlation filter learn distorted training samples. In this paper, we present a structure–attention network t

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20

Duck, Julie M., Robert A. M. Gregson, Eileen B. J. Jones, Grant Noble, and Michael Noy. "Children's visual attention to “playschool”: A time series analysis." Australian Journal of Psychology 40, no. 4 (1988): 413–20. http://dx.doi.org/10.1080/00049538808260060.

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21

Barnard, Philip, Cristina Ramponi, Geoffrey Battye, and Bundy Mackintosh. "Anxiety and the deployment of visual attention over time." Visual Cognition 12, no. 1 (2005): 181–211. http://dx.doi.org/10.1080/13506280444000139.

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22

Mondor, T. A., and M. P. Bryden. "On the Relation between Visual Spatial Attention and Visual Field Asymmetries." Quarterly Journal of Experimental Psychology Section A 44, no. 3 (1992): 529–55. http://dx.doi.org/10.1080/14640749208401297.

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In the typical visual laterality experiment, words and letters are more rapidly and accurately identified in the right visual field than in the left. However, while such studies usually control fixation, the deployment of visual attention is rarely restricted. The present studies investigated the influence of visual attention on the visual field asymmetries normally observed in single-letter identification and lexical decision tasks. Attention was controlled using a peripheral cue that provided advance knowledge of the location of the forthcoming stimulus. The time period between the onset of

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23

Furst, David M., and Gershon Tenenbaum. "Influence of Attentional Focus on Reaction Time." Psychological Reports 56, no. 1 (1985): 299–302. http://dx.doi.org/10.2466/pr0.1985.56.1.299.

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It was hypothesized that attention could be directed to the emphasized task regardless of its spatial location. 20 subjects performed a simple RT to a stimulus located in foveal vision and a simple RT to four surrounding stimuli set in the visual periphery. Importance of task was manipulated through instructions. Analysis of variance showed subjects had shorter RTs to the emphasized area regardless of its spatial location. The attentional demands of the tasks and the importance assigned to the tasks were critical factors in response speed. This may help to explain the results of visual-narrowi

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24

Liu, Fan, Zhao Xiang, Yuhai Chen, et al. "Time course of visual attention in rats by atomic magnetometer." PLOS ONE 19, no. 10 (2024): e0312589. http://dx.doi.org/10.1371/journal.pone.0312589.

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Atomic magnetometer (AM) is utilized to non-invasively detect event-related magnetic fields (ERMFs) evoked by visual stimuli in rats. The aim of this study was to investigate the relationship between N2-like amplitude and visual attention. To achieve this, we combined the AM with a visual stimulation system and employed the passive single-stimulus paradigm. By measuring the ERMFs at various inter-stimulus intervals (ISIs) with a sensitivity of 20 fT/Hz, we analyzed the effects of the ISI and the ‘habituation’ resulting from repeated stimuli on the N2-like amplitude. Our method serves as a valu

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25

Buonocore, Antimo, Niklas Dietze, and Robert D. McIntosh. "Time-dependent inhibition of covert shifts of attention." Experimental Brain Research 239, no. 8 (2021): 2635–48. http://dx.doi.org/10.1007/s00221-021-06164-y.

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AbstractVisual transients can interrupt overt orienting by abolishing the execution of a planned eye movement due about 90 ms later, a phenomenon known as saccadic inhibition (SI). It is not known if the same inhibitory process might influence covert orienting in the absence of saccades, and consequently alter visual perception. In Experiment 1 (n = 14), we measured orientation discrimination during a covert orienting task in which an uninformative exogenous visual cue preceded the onset of an oriented probe by 140–290 ms. In half of the trials, the onset of the probe was accompanied by a brie

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26

Pu, Lei, Xinxi Feng, Zhiqiang Hou, Wangsheng Yu, and Yufei Zha. "SiamDA: Dual attention Siamese network for real-time visual tracking." Signal Processing: Image Communication 95 (July 2021): 116293. http://dx.doi.org/10.1016/j.image.2021.116293.

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27

Iavecchia, Helene P., and Charles L. Folk. "Shifting Visual Attention in Stereographic Displays: A Time Course Analysis." Human Factors: The Journal of the Human Factors and Ergonomics Society 36, no. 4 (1994): 606–18. http://dx.doi.org/10.1177/001872089403600404.

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28

Sanscartier, Shayne, Jessica Maxwell, Eric Taylor, and Penelope Lockwood. "Attachment Avoidance and Visual Attention for Emotional Faces over Time." Journal of Vision 16, no. 12 (2016): 79. http://dx.doi.org/10.1167/16.12.79.

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29

Deco, Gustavo, Olga Pollatos, and Josef Zihl. "The time course of selective visual attention: theory and experiments." Vision Research 42, no. 27 (2002): 2925–45. http://dx.doi.org/10.1016/s0042-6989(02)00358-9.

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30

Ouerhani, Nabil, and Heinz Hügli. "Real-time visual attention on a massively parallel SIMD architecture." Real-Time Imaging 9, no. 3 (2003): 189–96. http://dx.doi.org/10.1016/s1077-2014(03)00036-6.

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31

Battistoni, Elisa, Daniel Kaiser, Clayton Hickey, and Marius V. Peelen. "The time course of spatial attention during naturalistic visual search." Cortex 122 (January 2020): 225–34. http://dx.doi.org/10.1016/j.cortex.2018.11.018.

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32

Madden, D. J. "Adult Age Differences in the Time Course of Visual Attention." Journal of Gerontology 45, no. 1 (1990): P9—P16. http://dx.doi.org/10.1093/geronj/45.1.p9.

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33

Dombrowe, Isabel, Christian N. L. Olivers, and Mieke Donk. "The time course of working memory effects on visual attention." Visual Cognition 18, no. 8 (2010): 1089–112. http://dx.doi.org/10.1080/13506281003651146.

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34

Srivastava, Priyanka, Devpriya Kumar, and Narayanan Srinivasan. "Time course of visual attention across perceptual levels and objects." Acta Psychologica 135, no. 3 (2010): 335–42. http://dx.doi.org/10.1016/j.actpsy.2010.09.001.

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35

Xia, Ru Ting, and Xiao Yan Zhou. "Measurement on Reaction Time of Visual Attention in Depth during Driving." Applied Mechanics and Materials 319 (May 2013): 343–47. http://dx.doi.org/10.4028/www.scientific.net/amm.319.343.

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This research aimed to reveal characteristics of visual attention of low-vision drivers. Near and far stimuli were used by means of a three-dimensional (3D) attention measurement system that simulated traffic environment. We measured the reaction time of subjects while attention shifted in three kinds of imitational peripheral environment illuminance (daylight, twilight and dawn conditions). Subjects were required to judge whether the target presented nearer than fixation point or further than it. The results showed that the peripheral environment illuminance had evident influence on the react

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36

Roberts, Ian D., Yi Yang Teoh, and Cendri A. Hutcherson. "Time to Pay Attention? Information Search Explains Amplified Framing Effects Under Time Pressure." Psychological Science 33, no. 1 (2021): 90–104. http://dx.doi.org/10.1177/09567976211026983.

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Decades of research have established the ubiquity and importance of choice biases, such as the framing effect, yet why these seemingly irrational behaviors occur remains unknown. A prominent dual-system account maintains that alternate framings bias choices because of the unchecked influence of quick, affective processes, and findings that time pressure increases the framing effect have provided compelling support. Here, we present a novel alternative account of magnified framing biases under time pressure that emphasizes shifts in early visual attention and strategic adaptations in the decisi

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37

Viau-Quesnel, Charles, Rémi Gaudreault, Andrée-Anne Ouellet, and Claudette Fortin. "Making Sense of Timing and Attention: Modality Effect in Timing with a Break." Timing & Time Perception 2, no. 2 (2014): 129–44. http://dx.doi.org/10.1163/22134468-00002019.

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Tones are perceived longer than visual stimuli of same durations. One interpretation of this modality effect is that auditory stimuli capture attention more easily than visual stimuli, resulting in more efficient temporal processing. During a time interval production, expecting a break signal lengthens the produced interval, an effect explained by attention sharing between timing and monitoring for the signal occurrence. In the present study, participants produced a brief time interval defined by a visual or an auditory stimulus and in most trials, there was a break in stimulus presentation. T

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38

Kashiwase, Yoshiyuki, Kazumichi Matsumiya, Ichiro Kuriki, and Satoshi Shioiri. "Time Courses of Attentional Modulation in Neural Amplification and Synchronization Measured with Steady-state Visual-evoked Potentials." Journal of Cognitive Neuroscience 24, no. 8 (2012): 1779–93. http://dx.doi.org/10.1162/jocn_a_00212.

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Endogenous attention modulates the amplitude and phase coherence of steady-state visual-evoked potentials (SSVEPs). In efforts to decipher the neural mechanisms of attentional modulation, we compared the time course of attentional modulation of SSVEP amplitude (thought to reflect the magnitude of neural population activity) and phase coherence (thought to reflect neural response synchronization). We presented two stimuli flickering at different frequencies in the left and right visual hemifields and asked observers to shift their attention to either stimulus. Our results demonstrated that atte

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39

Li, Ning, and Linda Ng Boyle. "Allocation of Driver Attention for Varying In-Vehicle System Modalities." Human Factors: The Journal of the Human Factors and Ergonomics Society 62, no. 8 (2019): 1349–64. http://dx.doi.org/10.1177/0018720819879585.

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Objective This paper examines drivers’ allocation of attention using response time to a tactile detection response task (TDRT) while interacting with an in-vehicle information system (IVIS) over time. Background Longer TDRT response time is associated with higher cognitive workload. However, it is not clear what role is assumed by the human and system in response to varying in-vehicle environments over time. Method A driving simulator study with 24 participants was conducted with a restaurant selection task of two difficulty levels (easy and hard) presented in three modalities (audio only, vis

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40

Xia, Ru Ting, Jian Fan, and Bai Shao Zhan. "Measure Method on Reaction Time of Visual Attention Using a New-Style Mechatronic Measurement System." Applied Mechanics and Materials 55-57 (May 2011): 838–42. http://dx.doi.org/10.4028/www.scientific.net/amm.55-57.838.

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In this paper, a new measure method was suggested to examine the reaction time of visual attention of drivers using a new-style mechatronic visual attention measurement system. The system can control the peripheral environment illuminance and the present of stimulus at the start locations, and change the color of stimulus in terms of visual attention shift theory in three-dimensional (3D) space. The measurement system included the setting of observation location, stimuli location, moving speed, environment illuminance. The paper introduced the test method of visual function and the test proced

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41

Hoang Dinh, Thang, Tuan Do Ngoc, Kien Thai Trung, and Long Tran Quoc. "Real-time Siamese visual object tracking using attention and anchor-free mechanism." Journal of Military Science and Technology, no. 80 (June 28, 2022): 132–41. http://dx.doi.org/10.54939/1859-1043.j.mst.80.2022.132-141.

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Trackers based on Siamese have consistently demonstrated superior performance in tracking visual objects. The majority of existing trackers calculate the features of the target template and search image independently and then estimate the target's scale and aspect ratio using either a multi-scale searching scheme or pre-defined anchor boxes. This paper proposed a Siamese attention network for tracking visual objects. An attention fusion mechanism is generated using pixel-level matching of template and search features. The framework proposed is anchor-free, making it both simple and effective.

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42

Kida, Tetsuo, Koji Inui, Toshiaki Wasaka, Kosuke Akatsuka, Emi Tanaka, and Ryusuke Kakigi. "Time-Varying Cortical Activations Related to Visual–Tactile Cross-Modal Links in Spatial Selective Attention." Journal of Neurophysiology 97, no. 5 (2007): 3585–96. http://dx.doi.org/10.1152/jn.00007.2007.

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The neural mechanisms underlying unimodal spatial attention have long been studied, but the cortical processes underlying cross-modal links remain a matter of debate. To reveal the cortical processes underlying the cross-modal links between vision and touch in spatial attention, we recorded magnetoencephalographic (MEG) responses to electrocutaneous stimuli when subjects directed attention to an electrocutaneous or visual stimulus presented randomly in the left or right space. Neural responses recorded around the bilateral sylvian fissures at 85 and 100 ms after the electrocutaneous stimulus w

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43

Mason, Deanna J., Glyn W. Humphreys, and Lindsey S. Kent. "Exploring selective attention in ADHD: visual search through space and time." Journal of Child Psychology and Psychiatry 44, no. 8 (2003): 1158–76. http://dx.doi.org/10.1111/1469-7610.00204.

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44

Wei, Chun-Chun, and Min-Yuan Ma. "Influences of Visual Attention and Reading Time on Children and Adults." Reading & Writing Quarterly 33, no. 2 (2016): 97–108. http://dx.doi.org/10.1080/10573569.2015.1092100.

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45

Blough, Donald S. "Reaction time drifts identify objects of attention in pigeon visual search." Journal of Experimental Psychology: Animal Behavior Processes 19, no. 2 (1993): 107–20. http://dx.doi.org/10.1037/0097-7403.19.2.107.

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46

Ekanayake, Jinendra, Chloe Hutton, Gerard Ridgway, Frank Scharnowski, Nikolaus Weiskopf, and Geraint Rees. "Real-time decoding of covert attention in higher-order visual areas." NeuroImage 169 (April 2018): 462–72. http://dx.doi.org/10.1016/j.neuroimage.2017.12.019.

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47

Moya, L., S. Shomstein, A. Bagic, and M. Behrmann. "The time course of neural activity in object-based visual attention." Journal of Vision 8, no. 6 (2010): 549. http://dx.doi.org/10.1167/8.6.549.

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48

Ewen, JB, DM Caggiano, BM Lakshmanan, H. Rosen, and S. Yantis. "Time-Course of Top-Down Shifts of Covert Visual Spatial Attention." NeuroImage 47 (July 2009): S66. http://dx.doi.org/10.1016/s1053-8119(09)70361-1.

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49

deBettencourt, M. T., R. F. Lee, J. D. Cohen, K. A. Norman, and N. B. Turk-Browne. "Externalizing internal states with real-time neurofeedback to train visual attention." Journal of Vision 13, no. 9 (2013): 1132. http://dx.doi.org/10.1167/13.9.1132.

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50

Danno, Mikio, Matti Kutila, and Juha M. Kortelainen. "Measurement of Driver’s Visual Attention Capabilities Using Real-Time UFOV Method." International Journal of Intelligent Transportation Systems Research 9, no. 3 (2011): 115–27. http://dx.doi.org/10.1007/s13177-011-0033-1.

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