시각탐색에서 표적 출현 빈도와 보상에 따른 위치 확률 학습 = Location Probability Learning depending on the Frequency of Target Appearance and the Monetary Reward in Visual Search

다국어 초록 (Multilingual Abstract)

The present study aimed to examine the strong influence of location probability learning(LPL) depending on the frequency of target appearance in various visual search environments. Experiment 1 confirmed the effect of controlling the expected value on the spatial attentional biases by target prevalence. The target is always frequently presented at a specific quadrant. Experiment 1A(Reward Value Control) was constructed that the expected value was manipulated to increase in the high-frequency quadrant by presenting high and low rewards with even distribution in all quadrants. Meanwhile, Experiment 1B(Expected Value Control) was constructed to control the expected value in all quadrants by presenting a lower reward when the target appeared in the high-frequency quadrant compared to the low-frequency quadrant. The difference in the visual search task of Experiment 2 was that reward cues were provided before beginning the search array to enhance the prospect of reward. In Experiment 3, the multi-target detection task was used to manipulate the induced situation with attentional competition among to-be-detected targets. As a result, all experiments showed that the reaction time in the high-frequency quadrant was significantly faster than in the low-frequency quadrant. These results suggest that the effect of LPL affected by the target prevalence is consistently robust in visual search environments with the controlled expected value and high reward prospect or increase of attentional competition.

국문 초록 (Abstract)

본 연구는 다양한 시각탐색 상황에서 표적 출현 빈도에 의한 강력한 위치 확률 학습 효과를 확인하고자 수행되었다. 실험 1에서는 기댓값의 통제 여부가 표적 출현 빈도에 의한 공간주의 편향에 미치는 영향을 확인해보았다. 표적은 항상 특정 사분면에 높은 빈도로 출현하도록 조작하며 실험 1A(보상값 통제)는 모든 사분면에 높은 보상과 낮은 보상이 동일한 확률로 출현하여 고빈도 사분면에서 기댓값이 커지도록 조작하였다. 한편, 실험 1B(기댓값 통제)는 표적이 고빈도 사분면에 출현할 때 저빈도 사분면에 출현할 때에 비해 낮은 보상을 제공함으로써 전체적인 사분면에서 획득하는 기댓값이 동일하도록 통제하였다. 실험 2에서는 보상의 예측력을 높이기 위해 탐색 배열이 제시되기 이전에 보상 단서를 제공한다는 것에서만 차이가 있으며, 실험 3에서는 다중표적 탐지 과제를 통해 탐지해야 할 표적들 간 주의 경쟁이 발생하도록 하였다. 실험 결과, 일련의 실험 모두 고빈도 사분면에서의 반응 속도가 저빈도 사분면에 비해 빨랐다. 본 결과는 기댓값이 통제되고 보상 예측력이나 주의 경쟁이 증가하는 시각탐색 상황에서 일관되게 표적 출현 빈도에 의한 위치 확률 학습이 강력하게 발생한다는 것을 시사한다.

참고문헌 (Reference)

1 Jiang, Y. V., "Visual search and location probability learning from variable perspectives" 13 (13): 13-13, 2013

2 Egeth, H. E., "Visual attention: Control, representation, and time course" 48 (48): 269-297, 1997

3 Anderson, B. A., "Value-driven attentional priority is context specific" 22 (22): 750-756, 2015

4 Anderson, B. A., "Value-driven attentional capture" 108 (108): 10367-10371, 2011

5 Awh, E., "Top-down versus bottom-up attentional control : A failed theoretical dichotomy" 16 (16): 437-443, 2012

6 Kim, M. -S., "Top-down and bottom-up attentional control : On the nature of interference from a salient distractor" 61 : 1009-1023, 1999

7 Brainard, D. H., "The psychophysics toolbox" 10 (10): 433-436, 1997

8 Cristofori, I., "The effects of expected reward on creative problem solving" 18 (18): 925-931, 2018

9 Pelli, D. G., "The VideoToolbox software for visual psychophysics : Transforming numbers into movies" 10 (10): 437-442, 1997

10 Schapiro, A., "Statistical learning" 3 : 501-506, 2015

11 Shomstein, S., "Shaping attention with reward : Effects of reward on space-and object-based selection" 24 (24): 2369-2378, 2013

12 Failing, M., "Selection history : How reward modulates selectivity of visual attention" 25 (25): 514-538, 2018

13 Whitton, A. E., "Reward processing dysfunction in major depression, bipolar disorder and schizophrenia" 28 (28): 7-, 2015

14 Metin, B., "Reward processing deficits during a spatial attention task in patients with ADHD : an fMRI study" 22 (22): 694-702, 2018

15 Levari, D. E., "Prevalence-induced concept change in human judgment" 360 (360): 1465-1467, 2018

16 Anderson, B. A., "Persistence of value-driven attentional capture" 39 (39): 6-, 2013

17 Kehoe, E. J., "Overshadowing and summation in compound stimulus conditioning of the rabbit's nictitating membrane response" 8 (8): 313-, 1982

18 Shaw, M. L., "Optimal allocation of cognitive resources to spatial locations" 3 (3): 201-211, 1977

19 Anderson, B. A., "On the feature specificity of valuedriven attention" 12 (12): e0177491-, 2017

20 Desimone, R., "Neural mechanisms of selective visual attention" 18 (18): 193-222, 1995

21 Liesefeld, H. R., "Modulations of saliency signals at two hierarchical levels of priority computation revealed by spatial statistical distractor learning" 150 (150): 710-, 2021

22 Jiang, Y. V., "Modulation of spatial attention by goals, statistical learning, and monetary reward" 77 (77): 2189-2206, 2015

23 Anderson, B. A., "Mechanisms of valuelearning in the guidance of spatial attention" 178 : 26-36, 2018

24 Sauter, M., "Learning to suppress salient distractors in the target dimension:Region-based inhibition is persistent and transfers to distractors in a nontarget dimension" 45 (45): 2080-, 2019

25 Jiang, Y. V., "Implicit guidance of attention in contextual cueing : Neuropsychological and developmental evidence" 105 : 115-125, 2019

26 Frober, K., "How sequentially changing reward prospect modulates meta-control: Increasing reward prospect promotes cognitive flexibility" 21 (21): 534-548, 2021

27 Won, B. Y., "How do magnitude and frequency of monetary reward guide visual search?" 78 (78): 1221-1231, 2016

28 Zhang, P., "High reward enhances perceptual learning" 18 (18): 11-11, 2018

29 Hong, I., "Habit-like attentional bias is unlike goal-driven attentional bias against spatial updating" 7 (7): 1-10, 2022

30 Jiang, Y. V., "Habit-like attention" 29 : 65-70, 2019

31 Wolfe, J. M., "Guided search : an alternative to the feature integration model for visual search" 15 (15): 419-, 1989

32 Anderson, B. A., "Generalization of value-based attentional priority" 20 (20): 647-658, 2012

33 Lucas, N., "Gambling against neglect : Unconscious spatial biases induced by reward reinforcement in healthy people and brain-damaged patients" 49 : 2616-, 2013

34 Faul, F., "G*Power 3 : A flexible statistical power analysis program for the social, behavioral, and biomedical sciences" 39 (39): 175-191, 2007

35 Don, H. J., "Frequency effects in action versus value learning" 2021

36 Lyu, W., "Feedback moderates the effect of prevalence on perceptual decisions" 28 (28): 1906-1914, 2021

37 Chun, M. M., "Contextual cueing : Implicit learning and memory of visual context guides spatial attention" 36 (36): 28-71, 1998

38 Hong, I., "Context affects implicit learning of spatial bias depending on task relevance" 82 (82): 1728-1743, 2020

39 Miller, J., "Components of the location probability effect in visual search tasks" 14 (14): 453-, 1988

40 Posner, M. I., "Components of attention" 78 (78): 391-408, 1971

41 Kim, H., "Combined influence of valence and statistical learning on the control of attention : Evidence for independent sources of bias" 208 : 104554-, 2021

42 Mine, C., "Awareness is necessary for attentional biases by location-reward association" 1-15, 2021

43 Chelazzi, L., "Altering spatial priority maps via reward-based learning" 34 (34): 8594-8604, 2014

44 Anderson, B. A., "A value-driven mechanism of attentional selection" 13 (13): 7-7, 2013

45 Sisk, C. A., "A spatial bias toward highly rewarded locations is associated with awareness" 46 (46): 669-, 2020