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. 2022 Dec 8;12(12):1686.
doi: 10.3390/brainsci12121686.

Experimental Studies of the Attention Processing Model in Multiple Object Tracking Task

Affiliations

Experimental Studies of the Attention Processing Model in Multiple Object Tracking Task

Shuyi Liang et al. Brain Sci. .

Abstract

(1) Background: Attention is an important cognitive process in daily life. However, limited cognitive resources have been allocated to attention, especially for multiple objects and its mechanism is still unclear. Most of the previous studies have been based on the static attention paradigms with relatively lower ecological validity. Thus, we aimed to explore the attention processing mechanism in a multiple object tracking (MOT) task by using a dynamic attention paradigm. Two experiments were conducted to assess whether there was a multi-focus attention processing model, and whether the processing model changes with the number of target balls. (2) Methods: During the experiments, 33 university students completed MOT combined with the simultaneous-sequential paradigm, with tracking accuracy and reaction time of correct reaction as indicators. (3) Results: (i) When there were two target balls, an obvious bilateral field advantage was apparent. (ii) When there were four target balls, participants' performance was significantly better when stimuli were presented simultaneously than when they were presented sequentially, showing a multi-focus attention processing model. (4) Conclusion: Attention processing is characterized by flexibility, providing strong evidence to support the multi-focus theory.

Keywords: attention; multi-focus theory; multiple object tracking (MOT) task; simultaneous–sequential paradigm.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Classical MOT task (target number is four).
Figure 2
Figure 2
Simultaneous–sequential paradigm.
Figure 3
Figure 3
A Combination of MOT task and simultaneous–sequential paradigm.
Figure 4
Figure 4
Examples of four presentations of the target ball.
Figure 5
Figure 5
Comparison of tracing accuracy of different presentation conditions under simultaneous and sequential conditions. Note: *** indicates the significance level is p < 0.001.
Figure 6
Figure 6
Comparison of tracing reaction time of different presentation conditions under simultaneous and sequential conditions. Note: * indicates the significance level is p < 0.05.
Figure 7
Figure 7
Comparison of the accuracy rate of different numbers of target balls in the simultaneous and sequential conditions. Note: *** indicates the significance level is p < 0.001.
Figure 8
Figure 8
Comparison of the accuracy rate of different numbers of target balls in simultaneous and sequential conditions. Note: ** indicates the significance level is p < 0.01.

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References

    1. Peng D.L. General Psychology. 5th ed. Beijing Normal University Press; Beijing, China: 2019. pp. 198–204.
    1. Carrasco M. Visual attention: The past 25 years. Vision Res. 2011;51:1484–1525. doi: 10.1016/j.visres.2011.04.012. - DOI - PMC - PubMed
    1. Yantis S., Serences J.T. Cortical mechanisms of space-based and object-based attentional control. Curr. Opin. Neurobiol. 2003;13:187–193. doi: 10.1016/S0959-4388(03)00033-3. - DOI - PubMed
    1. Assad J.A. Neural coding of behavioral relevance in parietal cortex. Curr. Opin. Neurobiol. 2003;13:194–197. doi: 10.1016/S0959-4388(03)00045-X. - DOI - PubMed
    1. Diab M.S., Elhosseini M.A., El-Sayed M.S., Ali H.A. Brain Strategy Algorithm for Multiple Object Tracking Based on Merging Semantic Attributes and Appearance Features. Sensors. 2021;21:7604. doi: 10.3390/s21227604. - DOI - PMC - PubMed

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