Статті в журналах: "Attentional tracking"

1

Seiffert, A. E. "Attentional tracking across display translations." Journal of Vision 5, no. 8 (March 17, 2010): 643. http://dx.doi.org/10.1167/5.8.643.

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2

Pichlmeier, Sebastian, and Till Pfeiffer. "Attentional capture in multiple object tracking." Journal of Vision 21, no. 8 (August 11, 2021): 16. http://dx.doi.org/10.1167/jov.21.8.16.

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3

Drew, Trafton, Andrew W. McCollough, Todd S. Horowitz, and Edward K. Vogel. "Attentional enhancement during multiple-object tracking." Psychonomic Bulletin & Review 16, no. 2 (April 2009): 411–17. http://dx.doi.org/10.3758/pbr.16.2.411.

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4

Makin, Simon J., Anthony J. Watkins, and Andrew P. Raimond. "Attentional tracking in real‐room reverberation." Journal of the Acoustical Society of America 129, no. 4 (April 2011): 2623. http://dx.doi.org/10.1121/1.3588717.

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5

Watkins, Anthony J., Simon J. Makin, and Andrew Raimond. "Room‐acoustic factors in attentional tracking." Journal of the Acoustical Society of America 123, no. 5 (May 2008): 2976. http://dx.doi.org/10.1121/1.2932481.

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6

Mounts, J. R. W., B. S. Amos, M. A. Moschetta, and E. C. Page. "Multiple object tracking and attentional capture." Journal of Vision 6, no. 6 (March 24, 2010): 769. http://dx.doi.org/10.1167/6.6.769.

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7

Sears, Christopher R., and Zenon W. Pylyshyn. "Multiple object tracking and attentional processing." Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale 54, no. 1 (2000): 1–14. http://dx.doi.org/10.1037/h0087326.

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8

Tombu, Michael, and Adriane E. Seiffert. "Attentional costs in multiple-object tracking." Cognition 108, no. 1 (July 2008): 1–25. http://dx.doi.org/10.1016/j.cognition.2007.12.014.

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9

Chen, Nigel T. M., Patrick J. F. Clarke, Tamara L. Watson, Colin MacLeod, and Adam J. Guastella. "Attentional bias modification facilitates attentional control mechanisms: Evidence from eye tracking." Biological Psychology 104 (January 2015): 139–46. http://dx.doi.org/10.1016/j.biopsycho.2014.12.002.

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10

Seiffert, A. E. "Dissociating neural correlates of attentional tracking and attention to visual motion." Journal of Vision 3, no. 9 (March 18, 2010): 868. http://dx.doi.org/10.1167/3.9.868.

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11

Reavis, E. A., P. J. Kohler, S. He, and P. U. Tse. "Attentional tracking in the absence of consciousness." Journal of Vision 10, no. 7 (August 3, 2010): 307. http://dx.doi.org/10.1167/10.7.307.

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12

Flombaum, J. I., B. J. Scholl, and Z. W. Pylyshyn. "Attentional high-beams in tracking through occlusion." Journal of Vision 6, no. 6 (March 24, 2010): 765. http://dx.doi.org/10.1167/6.6.765.

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13

Wu, Hefeng, Guanbin Li, and Xiaonan Luo. "Weighted attentional blocks for probabilistic object tracking." Visual Computer 30, no. 2 (May 4, 2013): 229–43. http://dx.doi.org/10.1007/s00371-013-0823-3.

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14

Leblanc, Émilie, David J. Prime, and Pierre Jolicoeur. "Tracking the Location of Visuospatial Attention in a Contingent Capture Paradigm." Journal of Cognitive Neuroscience 20, no. 4 (April 2008): 657–71. http://dx.doi.org/10.1162/jocn.2008.20051.

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Currently, there is considerable controversy regarding the degree to which top-down control can affect attentional capture by salient events. According to the contingent capture hypothesis, attentional capture by a salient stimulus is contingent on a match between the properties of the stimulus and top-down attentional control settings. In contrast, bottom-up saliency accounts argue that the initial capture of attention is determined solely by the relative salience of the stimulus, and the effect of top-down attentional control is limited to effects on the duration of attentional engagement on the capturing stimulus. In the present study, we tested these competing accounts by utilizing the N2pc event-related potential component to track the locus of attention during an attentional capture task. The results were completely consistent with the contingent capture hypothesis: An N2pc wave was elicited only by distractors that possessed the target-defining attribute. In a second experiment, we expanded upon this finding by exploring the effect of target-distractor similarity on the duration that attention dwells at the distractor location. In this experiment, only distractors possessing the target-defining attribute (color) captured visuospatial attention to their location and the N2pc increased in duration and in magnitude when the capture distractor also shared a second target attribute (category membership). Finally, in three additional control experiments, we replicated the finding of an N2pc generated by distractors, only if they shared the target-defining attribute. Thus, our results demonstrate that attentional control settings influence both which stimuli attract attention and to what extent they are processed.

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15

Jovicich, Jorge, Robert J. Peters, Christof Koch, Jochen Braun, Linda Chang, and Thomas Ernst. "Brain Areas Specific for Attentional Load in a Motion-Tracking Task." Journal of Cognitive Neuroscience 13, no. 8 (November 1, 2001): 1048–58. http://dx.doi.org/10.1162/089892901753294347.

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Although visual attention is known to modulate brain activity in the posterior parietal, prefrontal, and visual sensory areas, the unique roles of these areas in the control of attentional resources have remained unclear. Here, we report a dissociation in the response profiles of these areas. In a parametric functional magnetic resonance imaging (fMRI) study, subjects performed a covert motion-tracking task, in which we manipulated “attentional load” by varying the number of tracked balls. While strong effects of attention—independent of attentional load—were widespread, robust linear increases of brain activity with number of balls tracked were seen primarily in the posterior parietal areas, including the intraparietal sulcus (IPS) and superior parietal lobule (SPL). Thus, variations in attentional load revealed different response profiles in sensory areas as compared to control areas. Our results suggest a general role for posterior parietal areas in the deployment of visual attentional resources.

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16

Frielink-Loing, Andrea F., Arno Koning, and Rob van Lier. "Distinguishing influences of overt and covert attention in anticipatory attentional target tracking." Journal of Vision 17, no. 4 (June 12, 2017): 3. http://dx.doi.org/10.1167/17.4.3.

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17

Dunifon, Carolyn M., Samuel Rivera, and Christopher W. Robinson. "Auditory stimuli automatically grab attention: Evidence from eye tracking and attentional manipulations." Journal of Experimental Psychology: Human Perception and Performance 42, no. 12 (2016): 1947–58. http://dx.doi.org/10.1037/xhp0000276.

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18

Indrarathne, Bimali, and Judit Kormos. "ATTENTIONAL PROCESSING OF INPUT IN EXPLICIT AND IMPLICIT CONDITIONS." Studies in Second Language Acquisition 39, no. 3 (June 13, 2016): 401–30. http://dx.doi.org/10.1017/s027226311600019x.

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In this study we examined language learners’ attentional processing of a target syntactic construction in written L2 input in different input conditions, the change in learners’ knowledge of the targeted construction in these conditions, and the relationship between the change in knowledge and attentional processing. One hundred L2 learners of English in Sri Lanka were divided into four experimental groups and control group: input flood, input enhancement, a specific instruction to pay attention to the target grammatical construction in the input, and an explicit metalinguistic explanation of the target construction. Eye tracking was used to collect data on the attentional processing of 45 participants in the sample. The eye-tracking measures of learners who received a specific instruction to pay attention to the target structure and an explicit metalinguistic explanation indicated increased attentional processing. The learners in these groups also improved their knowledge of the target structure significantly. The results suggest that increased attentional processing is needed for development in L2 grammatical knowledge and that explicit instruction to pay attention to the input and metalinguistic explanation are successful in directing learners’ attentional resources toward novel grammatical constructions in the input.

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19

Prinet, Julie C., Alexander C. Mize, and Nadine Sarter. "Triggering and Detecting Attentional Narrowing in Controlled Environments." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 298–302. http://dx.doi.org/10.1177/1541931213601068.

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Attentional narrowing refers to a state in which operators, involuntarily and unconsciously, fail to process a subset of potentially critical information. Little is known about factors that trigger the phenomenon and how to detect and distinguish it from a related state, focused attention, where one deliberately concentrates on one source of information. The objectives of this study were to (1) evaluate the effectiveness of three factors - workload, a novel difficult problem and incentive - for inducing attentional narrowing, and (2) identify markers of attentional narrowing and focused attention. Performance, eye-tracking data and anxiety levels were recorded while participants timeshared numerous tasks. When confronted with a novel problem, participants’ visual attention narrowed towards the affected task, and performance dropped on several tasks when all three factors were present. The findings from this study highlight promising means of inducing narrowing and show that eye-tracking, together with performance data, enable real-time detection of attentional narrowing.

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20

Wang, Zhangdong, Jiaohua Qin, Xuyu Xiang, Yun Tan, and Neal N. Xiong. "Criss-Cross Attentional Siamese Networks for Object Tracking." Computers, Materials & Continua 73, no. 2 (2022): 2931–46. http://dx.doi.org/10.32604/cmc.2022.028896.

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21

Gill, J., and G. Alvarez. "A Cost for Hemifield "Crossover" During Attentional Tracking." Journal of Vision 10, no. 7 (August 3, 2010): 313. http://dx.doi.org/10.1167/10.7.313.

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22

Holcombe, Alex O., Daniel Linares, and Maryam Vaziri-Pashkam. "Perceiving Spatial Relations via Attentional Tracking and Shifting." Current Biology 21, no. 13 (July 2011): 1135–39. http://dx.doi.org/10.1016/j.cub.2011.05.031.

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23

Wang, Qiurui, Chun Yuan, Jingdong Wang, and Wenjun Zeng. "Learning Attentional Recurrent Neural Network for Visual Tracking." IEEE Transactions on Multimedia 21, no. 4 (April 2019): 930–42. http://dx.doi.org/10.1109/tmm.2018.2869277.

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24

KOMADA, Yuichi, Kazumitsu SHINOHARA, and Toshiaki MIURA. "Attentional effects in the multiple object tracking task." Japanese Journal of Cognitive Psychology 5, no. 1 (2007): 43–51. http://dx.doi.org/10.5265/jcogpsy.5.43.

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25

Lu, Shengfu, Jiying Xu, Mi Li, Jia Xue, Xiaofeng Lu, Lei Feng, Bingbing Fu, Gang Wang, Ning Zhong, and Bin Hu. "Attentional bias scores in patients with depression and effects of age: a controlled, eye-tracking study." Journal of International Medical Research 45, no. 5 (June 29, 2017): 1518–27. http://dx.doi.org/10.1177/0300060517708920.

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Objective To compare the attentional bias of depressed patients and non-depressed control subjects and examine the effects of age using eye-tracking technology in a free-viewing set of tasks. Methods Patients with major depressive disorder (MDD) and non-depressed control subjects completed an eye-tracking task to assess attention of processing negative, positive and neutral facial expressions. In this cross-sectional study, the tasks were separated in two types (neutral versus happy faces and neutral versus sad faces) and assessed in two age groups (‘young’ [18–30 years] and ‘middle-aged’ [31–55 years]). Results Compared with non-depressed control subjects ( n = 75), patients with MDD ( n = 90) had a significant reduced positive attentional bias and enhanced negative attentional bias irrespective of age. The positive attentional bias in ‘middle-aged’ patients with MDD was significantly lower than in ‘young’ patients, although there was no difference between the two age groups in negative attentional bias. Conclusions These results confirm that there are emotional attentional biases in patients with MDD and that positive attentional biases are influenced by age.

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26

D'Andrea-Penna, Gina M., Sebastian M. Frank, Todd F. Heatherton, and Peter U. Tse. "Distracting tracking: Interactions between negative emotion and attentional load in multiple-object tracking." Emotion 17, no. 6 (September 2017): 900–904. http://dx.doi.org/10.1037/emo0000329.

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27

Wang, Chundi, Luming Hu, Thomas Talhelm, and Xuemin Zhang. "The effects of colour complexity and similarity on multiple object tracking performance." Quarterly Journal of Experimental Psychology 72, no. 8 (December 12, 2018): 1903–12. http://dx.doi.org/10.1177/1747021818817388.

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Surface features can be used during multiple object tracking (MOT). Previous studies suggested that surface features might be stored in visual working memory to assist object tracking, and attentive tracking and visual working memory share common attentional resources. However, it is still unknown whether features of both the target and distractor sets will be stored, or features of the target and distractor sets are processed differently. Moreover, how feature distinctiveness and similarity between the target and distractor sets affect tracking and allocation of attentional resources are still not clear. First, we manipulated the colour complexity of the target set (CT) and the colour complexity of the distractor set (CD), respectively, in two experiments, where colours of the target and distractor sets were always distinct, to test their effects on tracking performance. If features of the target and distractor sets are stored, manipulating feature complexity of the target and distractor sets would significantly affect tracking performance. Second, this study tested whether tracking performance was affected by different levels of distinctiveness between the target and distractor sets (DTD) and explored how distinctiveness affected tracking and allocation of attentional resources. Results showed that DTD and CT significantly affect tracking performance and allocation of attentional resources, but not CD. These results indicated that when targets and distractors have distinct features, only the surface features of the targets are maintained in visual working memory. And when targets have the same colour with the distractors, they are more difficult and consume more attentional resources to track.

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28

Kuo, Yung-Lung, Jiann-Shu Lee, and Min-Chai Hsieh. "Video-Based Eye Tracking to Detect the Attention Shift." International Journal of Distance Education Technologies 12, no. 4 (October 2014): 66–81. http://dx.doi.org/10.4018/ijdet.2014100105.

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Eye and head movements evoked in response to obvious visual attention shifts. However, there has been little progress on the causes of absent-mindedness so far. The paper proposes an attention awareness system that captures the conditions regarding the interaction of eye gaze and head pose under various attentional switching in computer classroom. Via the algorithm of complexion area detection, eye location and eye tracking, the system detects the shifts of the subject's attention, records it and sends a notification to the class teacher. In five variant experiments of attentional shift, the authors find the cues of subjects when turning to other directions, moving forwards or backwards, and closing eyes. It applies even if the students wear glasses or have hair fringe. The findings of absent-mindedness are very important for psychologists or educators conducting post-hoc analysis. These experimental results show eye tracking are useful for detecting shift of attention.

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29

Issa, Bernard, Kara Morgan-Short, Briana Villegas, and Gary Raney. "An Eye-tracking Study on the Role of Attention and its Relationship with Motivation." EUROSLA Yearbook 15 (July 31, 2015): 114–42. http://dx.doi.org/10.1075/eurosla.15.05iss.

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This study aimed to assess whether attentional allocation to direct object pronouns in L2 Spanish was influenced by external or internal manipulations of attention and whether these manipulations caused learning of the form. Attention was measured by fixation duration and skipping rate on the pronouns, and learning was measured with a sentence interpretation task. Results provided empirical evidence that both types of manipulations direct attention to target forms, but in different ways, and bring about learning. In addition to examining the role of attention, the present study examined how different types of motivation, (i.e., integrative, intrinsic and extrinsic) were related to both attentional allocation and learning and found that intrinsic and extrinsic motivation were related to different attentional manipulations. Results are informative for models of L2 acquisition that posit a role for attention, instructed L2 acquisition and L2 motivation research.

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30

Alós-Ferrer, Carlos, Alexander Jaudas, and Alexander Ritschel. "Attentional shifts and preference reversals: An eye-tracking study." Judgment and Decision Making 16, no. 1 (January 2021): 57–93. http://dx.doi.org/10.1017/s1930297500008305.

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AbstractThe classic preference reversal phenomenon, where monetary evaluations contradict risky choices, has been argued to arise due to a focus on outcomes during the evaluation of alternatives, leading to overpricing of long-shot options. Such an explanation makes the implicit assumption that attentional shifts drive the phenomenon. We conducted an eye-tracking study to causally test this hypothesis by comparing a treatment based on cardinal, monetary evaluations with a different treatment avoiding a monetary frame. We find a significant treatment effect in the form of a shift in attention toward outcomes (relative to probabilities) when evaluations are monetary. Our evidence suggests that attentional shifts resulting from the monetary frame of evaluations are a driver of preference reversals.

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31

Lazarov, Amit, Benjamin Suarez-Jimenez, Amanda Tamman, Louise Falzon, Xi Zhu, Donald E. Edmondson, and Yuval Neria. "Attention to threat in posttraumatic stress disorder as indexed by eye-tracking indices: a systematic review." Psychological Medicine 49, no. 5 (September 4, 2018): 705–26. http://dx.doi.org/10.1017/s0033291718002313.

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AbstractBackgroundCognitive models of posttraumatic stress disorder (PTSD) implicate threat-related attentional biases in the etiology and phenomenology of the disorder. However, extant attentional research using reaction time (RT)-based paradigms and measures has yielded mixed results. Eye-tracking methodology has emerged in recent years to overcome several inherent drawbacks of RT-based tasks, striving to better delineate attentional processes.MethodsA systematic review of experimental studies examining threat-related attention biases in PTSD, using eye-tracking methodology and group-comparison designs, was conducted conforming to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Studies were selected following a systematic search for publications between 1980 and December 2017 in PsycINFO, MEDLINE and the National Center for PTSD Research's Published International Literature on Traumatic Stress (PILOTS) database. Additional records were identified by employing the Similar Articles feature in PubMed, and the Cited Reference Search in ISI Web of Science. Reference sections of review articles, book chapters and studies selected for inclusion were searched for further studies. Ongoing studies were also sought through Clinicaltrials.gov.ResultsA total of 11 studies (n = 456 participants in total) were included in the final review. Results indicated little support for enhanced threat detection, hypervigilance and attentional avoidance. However, consistent evidence emerged for sustained attention on threat (i.e. attention maintenance) in PTSD.ConclusionsThis review is the first to systematically evaluate extant findings in PTSD emanating from eye-tracking studies employing group-comparison designs. Results suggest that sustained attention on threat might serve as a potential target for therapeutic intervention.

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32

Sun, Xinglong, Guangliang Han, Lihong Guo, Hang Yang, Xiaotian Wu, and Qingqing Li. "Two-stage aware attentional Siamese network for visual tracking." Pattern Recognition 124 (April 2022): 108502. http://dx.doi.org/10.1016/j.patcog.2021.108502.

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33

Müller, Hermann J., and Adrian Von Mühlenen. "Attentional tracking and inhibition of return in dynamic displays." Perception & Psychophysics 58, no. 2 (March 1996): 224–49. http://dx.doi.org/10.3758/bf03211877.

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34

Carlisle, Nancy B., and Ziyao Zhang. "Eye tracking supports active attentional suppression from negative templates." Journal of Vision 19, no. 10 (September 6, 2019): 53d. http://dx.doi.org/10.1167/19.10.53d.

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35

Leonard, C., and Z. W. Pylyshyn. "Measuring the attentional demand of multiple object tracking (MOT)." Journal of Vision 3, no. 9 (March 18, 2010): 582. http://dx.doi.org/10.1167/3.9.582.

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36

Sternshein, Heather, Yigal Agam, and Robert Sekuler. "EEG Correlates of Attentional Load during Multiple Object Tracking." PLoS ONE 6, no. 7 (July 26, 2011): e22660. http://dx.doi.org/10.1371/journal.pone.0022660.

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37

Gao, Peng, Ruyue Yuan, Fei Wang, Liyi Xiao, Hamido Fujita, and Yan Zhang. "Siamese attentional keypoint network for high performance visual tracking." Knowledge-Based Systems 193 (April 2020): 105448. http://dx.doi.org/10.1016/j.knosys.2019.105448.

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38

Thompson, T. W., J. D. E. Gabrieli, and G. A. Alvarez. "Adaptive Training in Multiple Object Tracking Expands Attentional Capacity." Journal of Vision 10, no. 7 (August 3, 2010): 308. http://dx.doi.org/10.1167/10.7.308.

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39

Makovski, T., and Y. V. Jiang. "The interdependence between multiple attentional foci in attentive tracking." Journal of Vision 8, no. 6 (March 27, 2010): 503. http://dx.doi.org/10.1167/8.6.503.

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40

Culham, Jody C., Stephan A. Brandt, Patrick Cavanagh, Nancy G. Kanwisher, Anders M. Dale, and Roger B. H. Tootell. "Cortical fMRI Activation Produced by Attentive Tracking of Moving Targets." Journal of Neurophysiology 80, no. 5 (November 1, 1998): 2657–70. http://dx.doi.org/10.1152/jn.1998.80.5.2657.

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Culham, Jody C., Stephan A. Brandt, Patrick Cavanagh, Nancy G. Kanwisher, Anders M. Dale, and Roger B. H. Tootell. Cortical fMRI activation produced by attentive tracking of moving targets. J. Neurophysiol. 80: 2657–2670, 1998. Attention can be used to keep track of moving items, particularly when there are multiple targets of interest that cannot all be followed with eye movements. Functional magnetic resonance imaging (fMRI) was used to investigate cortical regions involved in attentive tracking. Cortical flattening techniques facilitated within-subject comparisons of activation produced by attentive tracking, visual motion, discrete attention shifts, and eye movements. In the main task, subjects viewed a display of nine green “bouncing balls” and used attention to mentally track a subset of them while fixating. At the start of each attentive-tracking condition, several target balls (e.g., 3/9) turned red for 2 s and then reverted to green. Subjects then used attention to keep track of the previously indicated targets, which were otherwise indistinguishable from the nontargets. Attentive-tracking conditions alternated with passive viewing of the same display when no targets had been indicated. Subjects were pretested with an eye-movement monitor to ensure they could perform the task accurately while fixating. For seven subjects, functional activation was superimposed on each individual's cortically unfolded surface. Comparisons between attentive tracking and passive viewing revealed bilateral activation in parietal cortex (intraparietal sulcus, postcentral sulcus, superior parietal lobule, and precuneus), frontal cortex (frontal eye fields and precentral sulcus), and the MT complex (including motion-selective areas MT and MST). Attentional enhancement was absent in early visual areas and weak in the MT complex. However, in parietal and frontal areas, the signal change produced by the moving stimuli was more than doubled when items were tracked attentively. Comparisons between attentive tracking and attention shifting revealed essentially identical activation patterns that differed only in the magnitude of activation. This suggests that parietal cortex is involved not only in discrete shifts of attention between objects at different spatial locations but also in continuous “attentional pursuit” of moving objects. Attentive-tracking activation patterns were also similar, though not identical, to those produced by eye movements. Taken together, these results suggest that attentive tracking is mediated by a network of areas that includes parietal and frontal regions responsible for attention shifts and eye movements and the MT complex, thought to be responsible for motion perception. These results are consistent with theoretical models of attentive tracking as an attentional process that assigns spatial tags to targets and registers changes in their position, generating a high-level percept of apparent motion.

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41

Carment, Loïc, Lucile Dupin, Laura Guedj, Maxime Térémetz, Marie-Odile Krebs, Macarena Cuenca, Marc A. Maier, Isabelle Amado, and Påvel G. Lindberg. "Impaired attentional modulation of sensorimotor control and cortical excitability in schizophrenia." Brain 142, no. 7 (May 17, 2019): 2149–64. http://dx.doi.org/10.1093/brain/awz127.

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Abstract Impairments in attentional, working memory and sensorimotor processing have been consistently reported in schizophrenia. However, the interaction between cognitive and sensorimotor impairments and the underlying neural mechanisms remains largely uncharted. We hypothesized that altered attentional processing in patients with schizophrenia, probed through saccadic inhibition, would partly explain impaired sensorimotor control and would be reflected as altered task-dependent modulation of cortical excitability and inhibition. Twenty-five stabilized patients with schizophrenia, 17 unaffected siblings and 25 healthy control subjects were recruited. Subjects performed visuomotor grip force-tracking alone (single-task condition) and with increased cognitive load (dual-task condition). In the dual-task condition, two types of trials were randomly presented: trials with visual distractors (requiring inhibition of saccades) or trials with addition of numbers (requiring saccades and addition). Both dual-task trial types required divided visual attention to the force-tracking target and to the distractor or number. Gaze was measured during force-tracking tasks, and task-dependent modulation of cortical excitability and inhibition were assessed using transcranial magnetic stimulation. In the single-task, patients with schizophrenia showed increased force-tracking error. In dual-task distraction trials, force-tracking error increased further in patients, but not in the other two groups. Patients inhibited fewer saccades to distractors, and the capacity to inhibit saccades explained group differences in force-tracking performance. Cortical excitability at rest was not different between groups and increased for all groups during single-task force-tracking, although, to a greater extent in patients (80%) compared to controls (40%). Compared to single-task force-tracking, the dual-task increased cortical excitability in control subjects, whereas patients showed decreased excitability. Again, the group differences in cortical excitability were no longer significant when failure to inhibit saccades was included as a covariate. Cortical inhibition was reduced in patients in all conditions, and only healthy controls increased inhibition in the dual-task. Siblings had similar force-tracking and gaze performance as controls but showed altered task-related modulation of cortical excitability and inhibition in dual-task conditions. In patients, neuropsychological scores of attention correlated with visuomotor performance and with task-dependant modulation of cortical excitability. Disorganization symptoms were greatest in patients with weakest task-dependent modulation of cortical excitability. This study provides insights into neurobiological mechanisms of impaired sensorimotor control in schizophrenia showing that deficient divided visual attention contributes to impaired visuomotor performance and is reflected in impaired modulation of cortical excitability and inhibition. In siblings, altered modulation of cortical excitability and inhibition is consistent with a genetic risk for cortical abnormality.

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Gill, J., and G. Alvarez. "Attentional tracking of spatially extended objects: evidence for object-based competition between lateralized attentional systems." Journal of Vision 9, no. 8 (March 21, 2010): 147. http://dx.doi.org/10.1167/9.8.147.

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Störmer, Viola S., Shu-Chen Li, Hauke R. Heekeren, and Ulman Lindenberger. "Normal Aging Delays and Compromises Early Multifocal Visual Attention during Object Tracking." Journal of Cognitive Neuroscience 25, no. 2 (February 2013): 188–202. http://dx.doi.org/10.1162/jocn_a_00303.

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Declines in selective attention are one of the sources contributing to age-related impairments in a broad range of cognitive functions. Most previous research on mechanisms underlying older adults' selection deficits has studied the deployment of visual attention to static objects and features. Here we investigate neural correlates of age-related differences in spatial attention to multiple objects as they move. We used a multiple object tracking task, in which younger and older adults were asked to keep track of moving target objects that moved randomly in the visual field among irrelevant distractor objects. By recording the brain's electrophysiological responses during the tracking period, we were able to delineate neural processing for targets and distractors at early stages of visual processing (∼100–300 msec). Older adults showed less selective attentional modulation in the early phase of the visual P1 component (100–125 msec) than younger adults, indicating that early selection is compromised in old age. However, with a 25-msec delay relative to younger adults, older adults showed distinct processing of targets (125–150 msec), that is, a delayed yet intact attentional modulation. The magnitude of this delayed attentional modulation was related to tracking performance in older adults. The amplitude of the N1 component (175–210 msec) was smaller in older adults than in younger adults, and the target amplification effect of this component was also smaller in older relative to younger adults. Overall, these results indicate that normal aging affects the efficiency and timing of early visual processing during multiple object tracking.

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Dumessa, Nathan, and Leo Gugerty. "Improving hazard perception and tracking through part-task training." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (November 2019): 1565–69. http://dx.doi.org/10.1177/1071181319631419.

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Safe driving requires wisely allocating focal attention among multiple changing events and comprehending events that are attended to. Research suggests that attentional skills can be improved by training. In this experiment, we are using a low-fidelity driving simulator to train participants using part-task training on two attentional subskills: identifying (comprehending) and tracking potential hazards; and detecting and avoiding imminent hazards. Following initial familiarization with the driving simulator, each participant will receive training in one of these two attentional subskills. Scene comprehension probes train (and measure) identifying and tracking potential hazards by having participants watch a moving driving scenario and then select the vehicle that behaved hazardously during the scene. In hazard avoidance probes, participants must make driving responses to avoid imminent hazards without hitting nearby vehicles. After the training phase, there is a test phase measuring near transfer, to hazards similar to training, and far transfer, to untrained hazards. We hypothesize that the participants who receive part-task training on identifying and tracking hazards should perform better at scene comprehension probes than the hazard-avoidance training group in both near and far transfer conditions. We also hypothesize that the group trained on avoiding imminent hazards will perform better on hazard avoidance probes in both near and far transfer conditions.

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Carter, Olivia L., David C. Burr, John D. Pettigrew, Guy M. Wallis, Felix Hasler, and Franz X. Vollenweider. "Using Psilocybin to Investigate the Relationship between Attention, Working Memory, and the Serotonin 1A and 2A Receptors." Journal of Cognitive Neuroscience 17, no. 10 (October 2005): 1497–508. http://dx.doi.org/10.1162/089892905774597191.

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Increasing evidence suggests a link between attention, working memory, serotonin (5-HT), and prefrontal cortex activity. In an attempt to tease out the relationship between these elements, this study tested the effects of the hallucinogenic mixed 5-HT1A/2A receptor agonist psilocybin alone and after pretreatment with the 5-HT2A antagonist ketanserin. Eight healthy human volunteers were tested on a multiple-object tracking task and spatial working memory task under the four conditions: placebo, psilocybin (215 Ag/kg), ketanserin (50 mg), and psilocybin and ketanserin. Psilocybin significantly reduced attentional tracking ability, but had no significant effect on spatial working memory, suggesting a functional dissociation between the two tasks. Pretreatment with ketanserin did not attenuate the effect of psilocybin on attentional performance, suggesting a primary involvement of the 5-HT1A receptor in the observed deficit. Based on physiological and pharmacological data, we speculate that this impaired attentional performance may reflect a reduced ability to suppress or ignore distracting stimuli rather than reduced attentional capacity. The clinical relevance of these results is also discussed.

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Qiu, Fanghui, Yanling Pi, Ke Liu, Xuepei Li, Jian Zhang, and Yin Wu. "Influence of sports expertise level on attention in multiple object tracking." PeerJ 6 (September 28, 2018): e5732. http://dx.doi.org/10.7717/peerj.5732.

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Background This study aimed to investigate whether performance in a multiple object tracking (MOT) task could be improved incrementally with sports expertise, and whether differences between experienced and less experienced athletes, or non-athletes, were modulated by load. Methods We asked 22 elite and 20 intermediate basketball players, and 23 non-athletes, to perform an MOT task under three attentional load conditions (two, three, and four targets). Accuracies were analyzed to examine whether different levels of sports expertise influence MOT task performance. Results The elite athletes displayed better tracking performance compared with the intermediate or non-athletes when tracking three or four targets. However, no significant difference was found between the intermediate athletes and the non-athletes. Further, no differences were observed among the three groups when tracking two targets. Discussion The results suggest that the effects of expertise in team ball sports could transfer to a non-sports-specific attention task. These transfer effects to general cognitive functions occur only in elite athletes with extensive training under higher attentional load.

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Wahn, Basil, Supriya Murali, Scott Sinnett, and Peter König. "Auditory Stimulus Detection Partially Depends on Visuospatial Attentional Resources." i-Perception 8, no. 1 (January 2017): 204166951668802. http://dx.doi.org/10.1177/2041669516688026.

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Humans’ ability to detect relevant sensory information while being engaged in a demanding task is crucial in daily life. Yet, limited attentional resources restrict information processing. To date, it is still debated whether there are distinct pools of attentional resources for each sensory modality and to what extent the process of multisensory integration is dependent on attentional resources. We addressed these two questions using a dual task paradigm. Specifically, participants performed a multiple object tracking task and a detection task either separately or simultaneously. In the detection task, participants were required to detect visual, auditory, or audiovisual stimuli at varying stimulus intensities that were adjusted using a staircase procedure. We found that tasks significantly interfered. However, the interference was about 50% lower when tasks were performed in separate sensory modalities than in the same sensory modality, suggesting that attentional resources are partly shared. Moreover, we found that perceptual sensitivities were significantly improved for audiovisual stimuli relative to unisensory stimuli regardless of whether attentional resources were diverted to the multiple object tracking task or not. Overall, the present study supports the view that attentional resource allocation in multisensory processing is task-dependent and suggests that multisensory benefits are not dependent on attentional resources.

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Lizarán, M., R. Sahuquillo-Leal, P. Navalón, A. Moreno-Giménez, B. Almansa, M. Vento, and A. García-Blanco. "An eye-tracking study for measuring the attentional characteristics towards emotional scenes in children with autism spectrum condition." European Psychiatry 64, S1 (April 2021): S226—S227. http://dx.doi.org/10.1192/j.eurpsy.2021.605.

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IntroductionThe difficulties in social interaction present in individuals with autism spectrum conditions may are related with the abnormal attentional processing of emotional information. Specifically, it has been hypothesized that the hypersensibility to threat shown by individuals with autism may explain an avoidance behaviour. However, this hypothesis is not supported by research and the underlying psychological mechanisms of social interaction in autism still unclear.ObjectivesThe aim of the present study was to examine attentional processing biases by administering a computer-based attentional task in a sample of 27 children with autism spectrum conditions and 25 typically developed participants (age 11-15 years).MethodsThe initial orienting of attention, the attention al engagement, and the attentional maintenance to different emotional scenes in competition (i.e. happy, neutral, threatening and sad) were measured by recording the eye movements during a 20 seconds free-viewing task.Results The main findings were: i) children with autism spectrum conditions showed an initial orientating bias towards threatening stimuli; and ii) while typically developed children revealed an attentional engagement and attentional maintenance bias towards threatening stimuli, children with autism spectrum conditions did not.ConclusionsThe findings of the present study are consistent with the affective information processing theories and shed light on the underlying mechanisms of social disturbances in autism spectrum conditions.

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Szinte, Martin, Marisa Carrasco, Patrick Cavanagh, and Martin Rolfs. "Attentional trade-offs maintain the tracking of moving objects across saccades." Journal of Neurophysiology 113, no. 7 (April 2015): 2220–31. http://dx.doi.org/10.1152/jn.00966.2014.

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In many situations like playing sports or driving a car, we keep track of moving objects, despite the frequent eye movements that drastically interrupt their retinal motion trajectory. Here we report evidence that transsaccadic tracking relies on trade-offs of attentional resources from a tracked object's motion path to its remapped location. While participants covertly tracked a moving object, we presented pulses of coherent motion at different locations to probe the allocation of spatial attention along the object's entire motion path. Changes in the sensitivity for these pulses showed that during fixation attention shifted smoothly in anticipation of the tracked object's displacement. However, just before a saccade, attentional resources were withdrawn from the object's current motion path and reflexively drawn to the retinal location the object would have after saccade. This finding demonstrates the predictive choice the visual system makes to maintain the tracking of moving objects across saccades.

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Kim, Jaewon (Justine), Gi-Eun Lee, and Jang-Han Lee. "The visual attentional pattern toward smoking area signs in legal and illegal cigarette smokers: Preliminary findings." Korean Data Analysis Society 25, no. 1 (February 28, 2023): 25–42. http://dx.doi.org/10.37727/jkdas.2023.25.1.25.

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Attentional patterns towards signs of smoking area might be different on individual levels. This would play a significant role in the decision-making process of illegal smoking behavior. In order to understand and effectively intervene the such behavior, this study aims to investigate the attentional pattern of the legal and illegal smokers toward the area signs (e.g. smoking area vs. no-smoking area) using a free viewing task and eye-tracking method. The participants were grouped into 25 legal smokers groups (LSG) and 15 illegal smokers groups (ISG) based on their usual smoking spots specified in the self-report questionnaire. During the free-viewing task where their visual attentional pattern was measured by an eye-tracking method, the participants were presented with eight pictorial stimuli with the area signs and the smoking-related cues. To examine the initial orientation process, the initial fixation latency, total dwell time, and dwell time by time blocks were analyzed for the smoking area signs. As a result, while LSG showed faster initial fixation toward the smoking area signs than no-smoking area signs, ISG did not. Also, LSG showed higher proportion of initial visual attention to smoking area signs. These findings suggest that the initial orienting attentional pattern of LSG toward the area signs might play a significant role in the legal smoking behavior.

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