良好的动态视觉注意能力是保障飞行安全的关键。受限于生态效度不足及缺乏交互性操作,传统多目标追踪范式难以准确评估真实情境中的视觉注意能力。研究开发了MOT情景交互测验,招募民航飞行员和普通大学生被试,通过行为和近红外指标验证其信效度,并比较了两组被试在情景测验上的差异。结果发现,情景测验内部一致性与区分度良好;情景测验得分与传统多目标追踪范式任务、连线测验、注意力转移测验得分相关性显著;飞行员在情景测验得分上显著高于大学生,且内侧额上回产生显著负激活。结果表明MOT情景交互测验具有良好的信效度,可作为评估动态视觉注意的有效工具。
Abstract
Dynamic visual attention is a crucial cognitive skill that involves focusing on multiple moving objects in an ever-changing environment. In occupations such as Air Traffic Control (ATC), pilots, and Unmanned Aerial Vehicle pilots, operators are required to perform numerous search tasks with high speed and accuracy, requiring strong dynamic tracking abilities. In fact, the effectiveness of task performance and hazard detection in specialized occupations, including aviation, relies heavily on dynamic visual attention capabilities. Therefore, enhancing methods for selecting and assessing dynamic visual attention is a critical issue in psychological research and a vital aspect of safety management. Multiple object tracking (MOT), which refers to the simultaneous tracking of multiple targets in a dynamic environment while minimizing interference, is a widely used paradigm in dynamic visual attention research. However, previous MOT tasks have predominantly been developed for laboratory settings, often consisting of meaningless elements lacking interactivity. These tasks often focus on minimizing inter-individual differences and systematically controlling for condition variables. Consequently, conducting assessments of individual differences using traditional MOT tasks, which may not accurately reflect real-world visual attention abilities, becomes challenging. Mainstream research has highlighted the importance of cognitive tests that assess situational interaction, emphasizing the need to develop ecologically valid multi-object tracking tests.
In this study, we developed an MOT situational interaction test. The test was conducted with a grassy field as a background, viewed from an oblique top-down angle, where participants were tasked with tracking butterflies within a designated space, incorporating interactive manipulations during the process. The test comprised three distinct phases. In the cue phase, the target butterfly was identified by its wing flapping. During the tracking phase, all butterflies flapped their wings simultaneously and began flying. In this period, participants were required to continuously track the position of the target butterfly. In the reaction phase, all butterflies returned to the grass and remained stationary. Participants were required to select all target butterflies using the mouse. The accuracy of target selection during the reaction phase was recorded. To increase interaction with the scene elements, a detection task was introduced within the first two seconds of the tracking phase. At the beginning of the tracking phase, a flower bloomed on the grass, and a butterfly landed on it. If the butterfly landing on the flower was the target, participants were instructed to press the spacebar to repel it; otherwise, no action was required.
Experiment 1 examined the internal consistency, discriminant, and construct validity of the situational test. A total of 115 undergraduate students were recruited to complete the traditional multiple objects tracking task, the situational test, the trail making test, and the attention-shifting test. Experiment 2 assessed the discriminant validity of the situational test using a known-groups methodology, combined with near-infrared spectroscopy (NIRS) to measure brain function. A total of 139 male participants were recruited. Of these, 67 participants were undergraduate students from a university, majoring in science disciplines at both the high school and university levels. The remaining 72 participants were pilots from a Chinese airline company, with an average flight experience of 772 hours. Participants were asked to complete the situational test, during which behavioral data and cortical oxygenation data were recorded.
The results revealed that the situational test exhibited strong internal consistency and discriminant validity. The correlation between scores on the situational test and those on the traditional MOT, connectivity, and attentional distraction tests was significant. Pilot participants scored significantly higher than university students, and the oxygen concentration in the medial superior frontal gyrus of the pilot participants was also significantly greater. This evidence suggests that the situational test possesses strong reliability and validity, making it a valuable tool for assessing individual differences in visual attention.
关键词
多目标追踪 /
动态注意 /
情景交互测验
Key words
multiple object tracking /
dynamic attention /
situational interaction test
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 胡传鹏, 孔祥祯, Wagenmakers, E. J., Ly A., 彭凯平. (2018). 贝叶斯因子及其在JASP中的实现. 心理科学进展, 26(6), 951-965.
[2] 金鹏, 张建辉. (2022). 民航飞行学员视觉注意分配特征研究. 空军航空医学, 39(5), 230-233.
[3] 李泰安, 张禹, 李杰. (2019). 多目标追踪在各类人群评价与训练中的应用. 心理科学进展, 27(9), 1585-1595.
[4] 李苑, 姬鸣, 兰继军, 常明, 游旭群. (2017). 从航空驾驶到工业设计: 情境意识研究的拓展. 心理科学, 40(2), 263-268.
[5] 刘煜, 潘盈朵, 李萌, 李晨麟, 王新野, 游旭群. (2023). 近红外光谱技术在航空心理学研究中的应用与展望. 心理科学, 46(6), 1518-1528.
[6] 卢天娇, 汤梦晗, 江涛, 周晨琛, 游旭群. (2020). 飞行员情景意识的影响因素剖析: 基于Endsley的三级理论. 应用心理学, 26(3), 195-207.
[7] 魏柳青, 张学民. (2019). 多目标追踪的神经机制. 心理科学进展, 27(12), 2007-2018.
[8] 魏柳青, 张学民, 刘冰, 鲁学明, 李迎娣. (2010). 多目标视觉追踪的现象、规律和认知加工机制. 心理科学进展, 18(12), 1919-1925.
[9] 姚丹旭. (2022). 基于情景-交互特征的多目标追踪能力测试研究 (硕士学位论文). 陕西师范大学, 西安.
[10] 殷恒婵. (2003). 青少年注意力测验与评价指标的研究. 中国体育科技, 39(3), 51-53.
[11] 殷恒婵, 张锋周, 宋湘勤, 陈培林. (2006). 优秀运动员注意力测量与评价研究. 体育科学, 26(3), 58-63, 69.
[12] Alnæs D., Sneve M. H., Richard G., Skåtun K. C., Kaufmann T., Nordvik J. E., & Westlye L. T. (2015). Functional connectivity indicates differential roles for the intraparietal sulcus and the superior parietal lobule in multiple object tracking. NeuroImage, 123, 129-137.
[13] Baldauf, D., & Deubel, H. (2010). Attentional landscapes in reaching and grasping. Vision Research, 50(11), 999-1013.
[14] Blumberg E. J., Peterson M. S., & Parasuraman R. (2015). Enhancing multiple object tracking performance with noninvasive brain stimulation: A causal role for the anterior intraparietal sulcus. Frontiers in Systems Neuroscience, 9, Article 3.
[15] Cak S., Say B., & Misirlisoy M. (2020). Effects of working memory, attention, and expertise on pilots'situation awareness. Cognition, Technology and Work, 22(1), 85-94.
[16] Callan, D. E., & Naito, E. (2014). Neural processes distinguishing elite from expert and novice athletes. Cognitive and Behavioral Neurology, 27(4), 183-188.
[17] de Sant, D. A. L. M., & de Hilal, A. V. G. (2021). The impact of human factors on pilots'safety behavior in offshore aviation companies: A Brazilian case. Safety Science, 140, Article 105272.
[18] Dørum E. S., Alnæs D., Kaufmann T., Richard G., Lund M. J., Tønnesen S., & Westlye L. T. (2016). Age-related differences in brain network activation and co-activation during multiple object tracking. Brain and Behavior, 6(11), Article e00533.
[19] Endsley, M. R. (2021). Situation awareness. In G. Salvendy & W. Karwowski (Eds.), Handbook of human factors and ergonomics (pp. 434-455). John Wiley & Sons, Inc.
[20] Esterman M., Noonan S. K., Rosenberg M., & DeGutis J. (2013). In the zone or zoning out? Tracking behavioral and neural fluctuations during sustained attention. Cerebral Cortex, 23(11), 2712-2723.
[21] Faubert, J. (2013). Professional athletes have extraordinary skills for rapidly learning complex and neutral dynamic visual scenes. Scientific Reports, 3, Article 1154.
[22] Faul F., Erdfelder E., Lang A. G., & Buchner A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191.
[23] Gaudino E. A., Geisler M. W., & Squires N. K. (1995). Construct validity in the trail making test: What makes Part B harder? Journal of Clinical and Experimental Neuropsychology, 17(4), 529-535.
[24] Guo Z. P., Li A. M., & Yu L. (2017). “Neural efficiency” of athletes'brain during visuo-spatial task: An fMRI study on table tennis players. Frontiers in Behavioral Neuroscience, 11, Article 72.
[25] Han S., Ji E., Choe E., Kim D., & Kim M. S. (2020). Simple action planning can affect attentional allocation in subsequent visual search. Psychonomic Bulletin and Review, 27(5), 1014-1024.
[26] Hedge C., Powell G., & Sumner P. (2018). The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences. Behavior Research Methods, 50(3), 1166-1186.
[27] Huang L. Q., Mo L., & 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), 414-428.
[28] Kelly, A. M. C., & Garavan, H. (2005). Human functional neuroimaging of brain changes associated with practice. Cerebral Cortex, 15(8), 1089-1102.
[29] Kelly, D., & Efthymiou, M. (2019). An analysis of human factors in fifty controlled flight into terrain aviation accidents from 2007 to 2017. Journal of Safety Research, 69, 155-165.
[30] Kerick S. E., Douglass L. W., & Hatfield B. D. (2004). Cerebral cortical adaptations associated with visuomotor practice. Medicine and Science in Sports and Exercise, 36(1), 118-129.
[31] Kristjánsson, Á., & Draschkow, D. (2021). Keeping it real: Looking beyond capacity limits in visual cognition. Attention, Perception, and Psychophysics, 83(4), 1375-1390.
[32] Lee S. S. Y., Wood J. M., & Black A. A. (2020). Impact of glaucoma on executive function and visual search. Ophthalmic and Physiological Optics, 40(3), 333-342.
[33] Li F. Z., Liu Q. H., Lu H. J., & Zhu X. (2020). Attentional blink in pilots and its relationship with flight performance. Frontiers in Psychology, 11, Article 1696.
[34] Lin, C. H., & Chen, C. M. (2016). Developing spatial visualization and mental rotation with a digital puzzle game at primary school level. Computers in Human Behavior, 57, 23-30.
[35] Ludyga S., Gronwald T., & Hottenrott K. (2016). The athlet's brain: Cross-sectional evidence for neural efficiency during cycling exercise. Neural Plasticity, 2016, Article 4583674.
[36] Ma, Z., & Flombaum, J. I. (2013). Off to a bad start: Uncertainty about the number of targets at the onset of multiple object tracking. Journal of Experimental Psychology: Human Perception and Performance, 39(5), 1421-1432.
[37] Maxwell H., Weaver B., Gagnon S., Marshall S., & Bédard M. (2020). The validity of three new driving simulator scenarios: Detecting differences in driving performance by difficulty and driver gender and age. Human Factors, 63(8), 1449-1464.
[38] Meyerhoff, H. S., & 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.
[39] Noland, R. M. (2017). Intelligence testing using a tablet computer: Experiences with using Q-interactive. Training and Education in Professional Psychology, 11(3), 156-163.
[40] O'Donnell J. P., Macgregor L. A., Dabrowski J. J., Oestreicher J. M., & Romero J. J. (1994). Construct validity of neuropsychological tests of conceptual and attentional abilities. Journal of Clinical Psychology, 50(4), 596-600.
[41] Patel R., Spreng R. N., & Turner G. R. (2013). Functional brain changes following cognitive and motor skills training: a quantitative meta-analysis. Neurorehabilitation and Neural Repair, 27(3), 187-199.
[42] Petrini K., Pollick F. E., Dahl S., McAleer P., McKay L., Rocchesso D., & Puce A. (2011). Action expertise reduces brain activity for audiovisual matching actions: An fMRI study with expert drummers. NeuroImage, 56(3), 1480-1492.
[43] Pylyshyn, Z. W., & Storm, R. W. (1988). Tracking multiple independent targets: Evidence for a parallel tracking mechanism. Spatial Vision, 3(3), 179-197.
[44] Qiu F. H., Pi Y. L., Liu K., Zhu H., Li X. P., Zhang J., & Wu Y. (2019). Neural efficiency in basketball players is associated with bidirectional reductions in cortical activation and deactivation during multiple-object tracking task performance. Biological Psychology, 144, 28-36.
[45] Rolfs M., Lawrence B. M., & Carrasco M. (2013). Reach preparation enhances visual performance and appearance. Philosophical Transactions of the Royal Society B: Biological Sciences, 368(1628), Article 20130057.
[46] Scholl B. J.(2009). What have we learned about attention from multiple-object tracking (and vice versa)? In D. Dedrick & L. Trick (Eds.), Computation, cognition, and pylyshyn (pp. 49-77). MIT Press.
[47] Singh T., Fridriksson J., Perry C. M., Tryon S. C., Ross A., Fritz S., & Herter T. M. (2017). A novel computational model to probe visual search deficits during motor performance. Journal of Neurophysiology, 117(1), 79-92.
[48] Tomasi D., Ernst T., Caparelli E. C., & Chang L. (2004). Practice-induced changes of brain function during visual attention: A parametric fMRI study at 4 Tesla. NeuroImage, 23(4), 1414-1421.
[49] van Benthem, K., & Herdman, C. M. (2020). The importance of domain-dependent cognitive factors in GA safety: Predicting critical incidents with prospective memory, situation awareness, and pilot attributes. Safety Science, 130, Article 104892.
[50] Voyer D., Jansen P., & Kaltner S. (2017). Mental rotation with egocentric and object-based transformations. The Quarterly Journal of Experimental Psychology, 70(11), 2319-2330.
[51] Weigelt, M., & Memmert, D. (2021). The mental rotation ability of expert basketball players: Identifying on-court plays. Research Quarterly for Exercise and Sport, 92(1), 137-145.
[52] Xie X. D., Li T. T., Xu S., Yu Y. Y., Ma Y. F., Liu Z., & Ji M. (2024). The effects of auditory working memory task on situation awareness in complex dynamic environments: An eye-movement study. Human Factors, 66(7), 1844-1859.
[53] Yang H. L., Chu H., Kao C. C., Miao N. F., Chang P. C., Tseng P., & Chou K. R. (2020). Construction and evaluation of multidomain attention training to improve alertness attention, sustained attention, and visual-spatial attention in older adults with mild cognitive impairment: A randomized controlled trial. International Journal of Geriatric Psychiatry, 35(5), 537-546.
[54] Zelinsky, G. J., & Neider, M. B. (2008). An eye movement analysis of multiple object tracking in a realistic environment. Visual Cognition, 16(5), 553-566.
基金
*本研究得到陕西师范大学研究生领航人才培养项目（LHRCTS23104,LHRCTS23108）的资助
PDF(1586 KB)
