Exp Brain Res DOI 10.1007/s00221-014-4187-3

RESEARCH ARTICLE

The prevalence effect in lateral masking and its relevance for visual search B. P. Geelen · A. H. Wertheim 

Received: 6 February 2014 / Accepted: 16 December 2014 © Springer-Verlag Berlin Heidelberg 2014

Abstract  In stimulus displays with or without a single target amid 1,644 identical distractors, target prevalence was varied between 20, 50 and 80 %. Maximum gaze deviation was measured to determine the strength of lateral masking in these arrays. The results show that lateral masking was strongest in the 20 % prevalence condition, which differed significantly from both the 50 and 80 % prevalence conditions. No difference was observed between the latter two. This pattern of results corresponds to that found in the literature on the prevalence effect in visual search (stronger lateral masking corresponding to longer search times). The data add to similar findings reported earlier (Wertheim et al. in Exp Brain Res, 170:387–402, 2006), according to which the effects of many well-known factors in visual search correspond to those on lateral masking. These were the effects of set size, disjunctions versus conjunctions, display area, distractor density, the asymmetry effect (Q vs. O’s) and viewing distance. The present data, taken together with those earlier findings, may lend credit to a causal hypothesis that lateral masking could be a more important mechanism in visual search than usually assumed. Keywords  Lateral masking · Prevalence effect · Visual search

Introduction The term lateral masking—coined by Bouma (1970), who reformulated the original finding of Korte (1923)—means B. P. Geelen · A. H. Wertheim (*)  Department of Psychonomics, Utrecht University, Utrecht, The Netherlands e-mail: [email protected]

that the peripheral perception of a target is impaired when distractors are present in its adjacent surroundings. The impairment becomes more pronounced when distractors are placed more closely together and when the target with its adjacent distractors is positioned further away in the visual periphery (see, e.g. Bouma 1970; Wertheim et al. 2006). In his original paper, Bouma (1970) also provided a method to quantify the strength of lateral masking by measuring how many degrees of visual angle one can divert one’s gaze from the target before one cannot anymore recognize it. This method of maximum gaze deviation implies visually tracking a small fixation point, moving horizontally across the stimulus array away from the target, until the ability to detect or identify the target is lost. Lateral masking—usually called “crowding” in the literature on visual search—is thought as just one of the mechanisms affecting search performance—(see, e.g. Vlaskamp and Hooge 2006). However, Wertheim et al. (2006) (see also Wertheim 2010) have hypothesized that it could be much more important, or even the main mechanism affecting search performance. The reason is that these authors reported a strong correspondence between lateral masking scores, obtained with Bouma’s method of maximum gaze deviation on the one hand, and, on the other hand, visual search performance in search experiments that used the exact same stimulus arrays: stronger lateral masking (i.e. smaller maximum gaze deviation) was always associated with longer visual search times, and weaker lateral masking scores corresponded to shorter search times. This was the case for the factors set size, disjunctions versus conjunctions, display area, distractor density, the asymmetry effect (Q vs. O’s and vice versa) and viewing distance. For this reason, Wertheim and collaborators (Wertheim et al. 2006) suggested that lateral masking might be a much more important mechanism in visual search than generally

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assumed, causing many of the well-known search effects that are traditionally attributed to higher-level cognitive or attentional mechanisms. Of course, the high and consistent correspondence observed between lateral masking scores and visual search times does not necessarily imply that all these visual search effects are caused by the mechanism of lateral masking. But they do at least suggest such a causal relationship. That would be a simple and more elegant hypothesis (albeit a rather unconventional one), to explain the correspondence between lateral masking scores and visual search performance, than assuming that each and every one of these factors just chances to affect lateral masking scores and visual search scores similarly or that some unknown higher-order factor affects both types of scores in a similar way. In fact, the effect viewing distance has on visual search performance can only be explained by lateral masking (see Wertheim et al. 2006 for details). In this respect, it is a problem that there currently is no predictive model that explains how lateral masking comes about, i.e. detailed enough to allow specific predictions, like how exactly search might depend on lateral masking in all the respects mentioned above. Therefore, we could not use such a model as a guiding principle and must adopt a more empirical approach. But we can make one relevant prediction: if this causal hypothesis, as proposed by Wertheim et al. (2006), is valid indeed, other factors known to affect visual search performance (in addition to those already investigated) might also have corresponding effects on lateral masking scores. The present paper investigates this possibility with a factor known as “target prevalence”, the frequency at which targets are presented across search trials. The relevant literature on visual search (Wolfe et al. 2005, 2007; Wolfe and van Wert 2010) shows that in visual search, hit scores on target present trials were slightly but significantly longer when target prevalence is reduced to much lower than 50 % (Wolfe et al. 2007), while no such effects are found when target prevalence increases beyond 50 % (Wolfe and van Wert 2010). If lateral masking is also affected by target prevalence in that same way, this would lend further support to the above-mentioned causal hypothesis. Thus, an experiment was designed to determine whether manipulating target prevalence has an effect on lateral masking scores, which correspond to that reported to occur on hit trial search times in the visual search literature. Three lateral masking tests (to be termed experimental conditions) with different target prevalence were carried out. Although in visual search it is possible to analyse the effects of target prevalence on search times in both target present and target absent trials, this poses a problem for lateral masking tasks. The point is that the method of maximum gaze deviation, as described by Bouma (1970),

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Exp Brain Res

cannot be used with target absent arrays. This is because that method requires from an observer to move the gaze away from a target (pursuing a moving a fixation point) until it cannot anymore be recognized as such. That of course is impossible in target absent arrays, where there is no target. Moreover, when there is no target, one cannot speak of lateral masking of a target. Therefore, Bouma’s method of quantifying lateral masking had to be slightly adapted in the present experiment: Instead of moving the fixation point away from the position of the target until it cannot any more be recognized, we moved the fixation point towards the position of the target, starting from a point greater than maximum gaze deviation. According to the causal hypothesis mentioned above, we then expect maximum gaze deviation to be smallest (lateral masking to be strongest) when target prevalence is reduced, but only in cases where target prevalence is already at low levels, while no effects are expected when target prevalence levels are higher. Of course, a control 100 % target present condition— with Bouma’s standard method to measure lateral masking, i.e. with the fixation point moving away from the target— must be added in order to see whether these control data were within the same range as reported earlier with similar arrays and methodology (Wertheim et al. 2006). But the control condition also served to compare results for moving the fixation point from and towards the target, i.e. to see whether the different methodology between the control and experimental conditions made a difference in the data. It should come as no surprise if it did: maximum gaze deviation is likely to be greatest in this control condition, because here the task is easier, as the target is known to be always present and is already seen at the start of each trial.

Methods Participants Eighteen participants cooperated in this experiment, all students or graduates from Utrecht University (age range 20–28 years, mean age = 23.38 years, SD = 2.15 years; 11 women, 9 men). They were screened for dyslexia since dyslectics might be expected to have atypical lateral masking (Bouma and Leigen 1977). They all had normal or corrected to normal vision. Informed consent was obtained from the participants, and they were either paid or received study credits for their participation. Apparatus Stimulus arrays were generated with MATLAB and the Psychophysics toolbox (Brainard 1997) on a PowerMac

Exp Brain Res

point, the orientation of the little stripe in the target and target position relative to the centre of the screen were equally balanced and randomly presented. Conditions

Fig. 1  Example of a stimulus array with the small fixation mark (which was red in the experiment) on the left and with the target positioned in the centre. At the beginning of an experimental trial, the fixation point moved horizontally towards the centre of the screen. [As one of our referees suggested, this stimulus configuration may imply that near-foveation is required for target identification (but see: Treisman and Souther 1985; Wolfe 2001)] (colour figure online)

G5. They reflected a Q amongst O’s paradigm, from the visual search literature (as in Wertheim et al. 2006). The target present arrays consisted of a field of either 1,644 distractors consisting of the letter O (diameter .7°; centre to centre distance of .81°) and one target which also consisted of the same letter O, but with a small crossing line, making it resemble the letter Q rotated in either one of the four different orientations (45°, 135°, 225° and 315°). The target absent arrays consisted of just 1,645 distractors. The stimuli were arranged regularly in rows and columns, just as in the Wertheim et al. (2006) study (Fig. 1). The illumination of the laboratory was slightly darkened. Target and distractors were white (luminance 90.8 cd/ m2) presented on a grey background (luminance 45.8 cd/ m2). The arrays measured 38.3° by 29.4° and were viewed from a chinrest at 59 cm distance from the screen. In every trial, a small red moving fixation point (14.8 cd/m2, diameter .25°) was made visible, moving horizontally at 1.6°/s either towards the target, from an extreme left or right starting location, or away from the target starting at the target location (control condition). Between trials, targets could be presented in four different positions around the centre of the screen, i.e. the distance between target stimulus position and the centre of the screen varied between 0° and 1.6° between trials. This was done to prevent unconscious learning with respect to where to expect a target and/or to prevent remembering the point of maximum gaze deviation on the screen at consecutive trials. In all arrays, the moving direction of the fixation

Three experimental target prevalence conditions were carried out. Each one included 64 target present trials. The number of target absent trials differed per condition. This yielded the following prevalence conditions: 20 % target present trials (64 target present trials, 256 target absent trials), 50 % target present trials (64 target present trials, 64 target absent trials) and 80 % target present trials (64 target present trials, 16 target absent trials). Finally, there was a fourth condition, a control condition, in which the target was always present (which made it easier and thus qualitatively different, from the experimental conditions). In this control condition, lateral masking was measured with the standard method described by Bouma (1970), i.e. the target moved horizontally away from the target either to the left or to the right until maximum gaze deviation was reached. As mentioned earlier, this control condition was necessary for methodological reasons: to check whether we were measuring performance properly, i.e. to see whether our scores were within the same range as those reported earlier by Wertheim et al. (2006) with similar arrays, in which Bouma’s standard method was also used. To ensure a participant’s ocular fixation on the moving fixation mark with a smooth pursuit eye movement (thus avoiding “sneaky” saccades towards the target that could prematurely reveal the target to the subject), eye movements were recorded for each trial using the Eyelink toolbox (Cornelissen et al. 2002). All eye traces were analysed offline with a threshold consisting of twice the average maximum gaze deviation for target present trials in the collective data set. Trials with at least one horizontal saccade towards the target that passed this threshold were rejected and removed from analysis. Procedure To get familiar with the task, participants started with 10 test trials, sufficient for the experimenter to judge them capable of performing the task correctly. They were told that it was very important to focus on the fixation point and to make sure that no “sneaky” eye movements towards the target were made. After this, the four conditions were offered randomly to the participants. At the start of each condition, the participants were explicitly informed about the target prevalence. Prior to each condition, eye calibration was carried out. A single trial in the experimental conditions began with the appearance of the fixation point, which had to be

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fixated with the eyes. It was presented at 15.8° horizontally from the centre of the screen. This was about 7° further away from the target than the average maximum gaze deviation as measured in a pilot study [using the standard Bouma (1970) method] and about 10° further than the average maximum gaze deviation as measured in the Wertheim et al. (2006) study with a similar set up. When the participants pressed the spacebar on the keyboard of the computer, the screen was filled with the stimulus array and the fixation point began moving horizontally towards the target. An identification criterion was used, i.e. participants pressed the spacebar again as soon as they could identify peripherally the orientation of the stripe in the target while maintaining their gaze on the moving fixation point. Or they pressed the spacebar as soon as they believed there to be no target. These points of maximum gaze deviation were registered by the computer. After this response, crosses appeared over all stimuli in the array (covering all four directions of the target stripe), thus eradicating any difference between target and distractors. This masked the position and nature of the target in iconic memory. After another space bar press, the whole stimulus array was replaced by a text asking the participants to respond in which of the four directions the target stripe had been orientated. This was done by pressing one of four keys on the key board. A fifth key was used to indicate the belief that there had been no target. Trials were given in five blocks, each one representing one experimental condition apart from the 20 % target prevalence condition, which was divided into two blocks because it would otherwise last too long. It took about 25, 20, 12 and 10 min to complete a block of 20, 50 or 80 % target prevalence and the control condition, respectively. After each block, there was a short break of a couple of minutes. Participants were always asked whether they were ready to proceed or whether they needed more time to pause.

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Fig. 2  Group mean lateral masking scores for all target present trials. Thin lines represent one between subject SD

respectively. In the remaining trials, miss errors were very rare, which resulted in a miss error rate of .8, .3 and .9 % in the 20, 50 and 80 % target prevalence conditions, respectively. Out of the remaining 1,611 target absent trials in the 20 % prevalence condition, only one participant responded with a false alarm. False alarms did not occur in the 50 and 80 % prevalence conditions. The individual lateral masking scores for the target present trials of all participants are given in Fig. 2 and Table 1. Analysis of variance showed that there were significant differences between conditions (p 

The prevalence effect in lateral masking and its relevance for visual search.

In stimulus displays with or without a single target amid 1,644 identical distractors, target prevalence was varied between 20, 50 and 80 %. Maximum g...
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