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Transferability of target prevalence effect across two dissociable-prevalence visual search tasks

The Korean Journal of Cognitive and Biological Psychology / The Korean Journal of Cognitive and Biological Psychology, (P)1226-9654; (E)2733-466X
2016, v.28 no.2, pp.349-365
https://doi.org/10.22172/cogbio.2016.28.2.008



Abstract

In our real-world visual searches, a target object is present with varied probability rather than with even probability. Recent studies have reported that the proportion of target presentation affects visual search performance via a shift of decision criteria. The present study investigated the transferability of this target prevalence effects across two dissociable-prevalence search tasks concurrently performed within a period. We examined this by conducting two separate visual searches where one emerge a varied-prevalence (10, 50, or 90%; prevalence task) whereas the other has a fixed-prevalence at 50% (neutral task). Each task was presented at the unihemifield in a random-order in whole trials. In addition, we assumed that the transferability of prevalence effect may depend on the perceptual similarity across the tasks. The results showed that search performance for the neutral task followed that for the prevalence task when the search stimuli set was perceptually identical across the tasks (Experiment 1B), whereas was independent from the prevalence task when the stimuli were perceptually distinct across the tasks (Experiment 1A). These results indicate that observers could fail to adaptively separate their decision criteria when they engaged in multiple-visual searches each has different probability of target presentation, at least under circumstances in which interferences on perceptual separation across the tasks exist.

keywords
시각탐색, 표적 출현확률, 의사결정 기준, visual search, target prevalence, decision criteria

Reference

1.

박형범, 손한결, 현주석 (2015). 표적 출현확률에 따른 시각탐색 정보처리 특성. 인지과학, 26(3), 357-375.

2.

Brockmole, J. R., & Henderson, J. M. (2006). Using real-world scenes as contextual cues for search. Visual Cognition, 13(1), 99-108.

3.

Bundesen, C. (1990). A theory of visual attention. Psychological review, 97(4), 523-547.

4.

Chen, X., & Zelinsky, G. J. (2006). Real-world visual search is dominated by top-down guidance. Vision research, 46(24), 4118-4133.

5.

Chun, M. M., & Wolfe, J. M. (1996). Just say no: How are visual searches terminated when there is no target present?. Cognitive psychology, 30(1), 39-78.

6.

Cosman, J. D., & Vecera, S. P. (2011). The contents of visual working memory reduce uncertainty during visual search. Attention, Perception, & Psychophysics, 73(4), 996-1002.

7.

Courtney, S. M. (2004). Attention and cognitive control as emergent properties of information representation in working memory. Cognitive, Affective, & Behavioral Neuroscience, 4(4), 501-516.

8.

Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual review of neuroscience, 18(1), 193-222.

9.

Fleck, M. S., & Mitroff, S. R. (2007). Rare targets are rarely missed in correctable search. Psychological Science, 18(11), 943-947.

10.

Godwin, H. J., Menneer, T., Cave, K. R., & Donnelly, N. (2010). Dual-target search for high and low prevalence X-ray threat targets. Visual Cognition, 18(10), 1439-1463.

11.

Godwin, H. J., Menneer, T., Cave, K. R., Helman, S., Way, R. L., & Donnelly, N. (2010). The impact of relative prevalence on dual-target search for threat items from airport X-ray screening. Acta psychologica, 134(1), 79-84.

12.

Godwin, H. J., Menneer, T., Cave, K. R., Thaibsyah, M., & Donnelly, N. (2014). The effects of increasing target prevalence on information processing during visual search. Psychonomic bulletin & review, 22(2), 469-475.

13.

Gur, D., Sumkin, J. H., Rockette, H. E., Ganott, M., Hakim, C., Hardesty, L., Poller, W. R., Shah, Ratan., & Wallace, L. (2004). Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system. Journal of the National Cancer Institute, 96(3), 185-190.

14.

Hollingworth, A., Richard, A. M., & Luck, S. J. (2008). Understanding the Function of Visual Short-Term Memory: Transsaccadic Memory, Object Correspondence, and Gaze Correction. Journal of Experimental Psychology: General, 137(1), 163-181.

15.

Ishibashi, K., Kita, S., & Wolfe, J. M. (2012). The effects of local prevalence and explicit expectations on search termination times. Attention, Perception, & Psychophysics, 74(1), 115-123.

16.

Itti, L., & Koch, C. (2001). Computational modelling of visual attention. Nature reviews neuroscience, 2(3), 194-203.

17.

Kane, M. J., & Engle, R. W. (2003). Working-memory capacity and the control of attention: the contributions of goal neglect, response competition, and task set to Stroop interference. Journal of Experimental Psychology:General, 132(1), 47-70.

18.

Menneer, T., Barrett, D. J., Phillips, L., Donnelly, N., & Cave, K. R. (2007). Costs in searching for two targets: Dividing search across target types could improve airport security screening. Applied Cognitive Psychology, 21(7), 915-932.

19.

Nakayama, K., & Silverman, G. H. (1986). Serial and parallel processing of visual feature conjunctions. Nature, 320(6059), 264-265.

20.

Reynolds, J. H., & Chelazzi, L. (2004). Attentional modulation of visual processing. Annual review of neuroscience, 27(1), 611-647.

21.

Rich, A. N., Kunar, M. A., Van Wert, M. J., Hidalgo-Sotelo, B., Horowitz, T. S., & Wolfe, J. M. (2008). Why do we miss rare targets? Exploring the boundaries of the low prevalence effect. Journal of Vision, 8(15), 15-15.

22.

Soto, D., Humphreys, G. W., & Heinke, D. (2006). Working memory can guide pop-out search. Vision research, 46(6), 1010-1018.

23.

Stroud, M. J., Menneer, T., Cave, K. R., & Donnelly, N. (2012). Using the Dual-Target Cost to Explore the Nature of Search Target Representations. Journal of Experimental Psychology: Human Perception and Performance, 38(1), 113-122.

24.

Torralba, A., Oliva, A., Castelhano, M. S., & Henderson, J. M. (2006). Contextual Guidance of Eye Movements and Attention in Real-World Scenes: The Role of Global Features in Object Search. Psychological Review, 113(4), 766-786.

25.

Treisman, A. M., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12(1), 97-136.

26.

Treisman, A. (1988). Features and objects: The fourteenth Bartlett memorial lecture. The Quarterly Journal of Experimental Psychology, 40(2), 201-237.

27.

Wolfe, J. M. (1994). Guided search 2.0 a revised model of visual search. Psychonomic Bulletin &Review, 1(2), 202-238.

28.

Wolfe, J. M., & Horowitz, T. S. (2004). What attributes guide the deployment of visual attention and how do they do it?. Nature Reviews Neuroscience, 5(6), 495-501.

29.

Wolfe, J. M., Horowitz, T. S., & Kenner, N. M. (2005). Cognitive psychology: rare items often missed in visual searches. Nature, 435(7041), 439-440.

30.

Wolfe, J. M., Horowitz, T. S., Van Wert, M. J., Kenner, N. M., Place, S. S., & Kibbi, N. (2007). Low target prevalence is a stubborn source of errors in visual search tasks. Journal of Experimental Psychology: General, 136(4), 623-638.

31.

Wolfe, J. M., & Van Wert, M. J. (2010). Varying target prevalence reveals two dissociable decision criteria in visual search. Current Biology, 20(2), 121-124.

32.

Woodman, G. F., & Arita, J. T. (2011). Direct electrophysiological measurement of attentional templates in visual working memory. Psychological Science, 22(2), 212-215.

The Korean Journal of Cognitive and Biological Psychology