Cognitive control of fixation duration in visual search - Semantic Scholar

Visual Cognition, 2014 Vol. 22, Nos. 3–4, 610–634, http://dx.doi.org/10.1080/13506285.2014.881443

Cognitive control of fixation duration in visual search: The role of extrafoveal processing Eyal M. Reingold1 and Mackenzie G. Glaholt2 1 2

University of Toronto, Mississauga, Canada University of California, San Diego

(Received 1 August 2013; accepted 7 January 2014)

Participants’ eye movements were monitored in two visual search experiments that manipulated target-distractor similarity (high vs. low) as well as the availability of distractors for extrafoveal processing (Free-Viewing vs. No-Preview). The influence of the target-distractor similarity by preview manipulation on the distributions of first fixation and second fixation duration was examined by using a survival analysis technique which provided precise estimates of the timing of the first discernible influence of targetdistractor similarity on fixation duration. We found a significant influence of targetdistractor similarity on first fixation duration in normal visual search (Free Viewing) as early as 26–28 ms from the start of fixation. In contrast, the influence of target-distractor similarity occurred much later (199–233 ms) in the No-Preview condition. The present study also documented robust and fast acting extrafoveal and foveal preview effects. Implications for models of eye-movement control and visual search are discussed.

Keywords: Eye movements; Visual search; Fixation duration; Peripheral vision; Parafoveal preview; Top-down.

INTRODUCTION Over the past several decades, the visual search paradigm has become increasingly influential in the study of visual attention (for reviews see Chan & Hayward, 2013; Wolfe, 1998). In a typical search task, observers are required to

Please address all correspondence to Eyal Reingold, University of Toronto at Mississauga, Department of Psychology, 3359 Mississauga Road N. RM2037B, Mississauga, Ontario, Canada L5L 1C6. E-mail: [email protected] This research was supported by an NSERC grant to Eyal Reingold. The author is grateful to Gregory Zelinsky, Kyle Cave, Denis Drieghe, Heather Sheridan, and Keith Rayner, for their comments on an earlier draft of this manuscript. © 2014 Taylor & Francis

EYE-MOVEMENT CONTROL OF VISUAL SEARCH FIXATIONS

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look for a target item in a multi-element visual display that also includes distractor (non-target) items. In a complex search display containing several types of distractors, participants typically have to make several saccades before a decision on target presence can be made (for reviews see Rayner, 1998, 2009; Zelinsky, 2008). In such multiple fixation searches, the eyes move three to four times per second enabling the encoding of fine visual details by aligning the fovea (the central 2° of vision in which visual acuity is at a maximum) with display items. Given this critical role of eye movements in selecting the locations in the search display to be foveated (i.e., fixation position) as well as in determining the duration of each foveation (i.e., fixation duration), it is surprising that until recently, factors that influence when the eyes move as well as where they move to remained largely unexplored within the research and theorizing on visual search (see Findlay & Gilchrist, 2003). The importance of exploring eye-movement control in visual search might be best conceptualized in the context of the broader controversy concerning the eye–mind link in visual cognition. Of particular relevance to the present investigation is the debate concerning the extent to which the influence of cognitive processing is rapid enough to produce an immediate fixation-byfixation adjustment of the timing of the saccade terminating the fixation (i.e., fixation duration). Specifically, the cognitive control hypothesis states that the processing of the properties of the fixated stimulus influences fixation duration, regardless of whether this processing was initiated while this stimulus was first foveated or when it was processed extrafoveally (i.e., via parafoveal or peripheral vision) prior to the first fixation on the stimulus (for a review see Reingold, Reichle, Glaholt, & Sheridan, 2012). There is a curious discrepancy between the intense focus on the examination of the cognitive control hypothesis in the domain of reading (see Rayner, 1998, 2009) and the absence of a similar effort in the domain of visual search. Consequently, the main goal of the present research was to explore the cognitive control of fixation duration in visual search by employing several innovative techniques that were recently introduced in the context of the study of eyemovement control in reading. Accordingly, we begin by briefly outlining the possible relevance of the cognitive control hypothesis to the debate concerning the role of top-down influences in visual search. Next, we review prior studies that investigated the control of fixation duration in visual search. We then outline the rationale of the present methodology and report on the findings from two visual search experiments that manipulated the target-distractor similarity as well as the availability of peripheral display items for extrafoveal processing. Finally, we explore the implications of our results for models of eye-movement control of fixation times in visual search. Current conceptualizations of visual search often distinguish between two different tasks that are integral to visual search performance: (1) the peripheral selection task, which determines the destination of an upcoming saccade (i.e., the

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saccadic endpoint) based in part on extrafoveal processing that was initiated during the preceding fixation, and (2) the central discrimination task, which requires observers to determine if the foveated item is the target or a distractor (see Hooge & Erkelens, 1999; Shen, Reingold, Pomplun, & Williams, 2003). More specifically, it is commonly assumed that a pre-attentive process, which extracts basic stimulus features (e.g., colour, shape, orientation) in a spatially parallel manner, influences peripheral selection while being insufficient for supporting the identification of display items (see Rayner & Fisher, 1987; Treisman, 1996; Wolfe, 1998; Wolfe & Bennett, 1997). In contrast, the postselection central discrimination is assumed to require focal attention and involves integrating stimulus features into a complete object (e.g., Navon & Pearl, 1985; Rayner & Fisher, 1987; Treisman, 1988; Wolfe, 1998; Wolfe & Bennett, 1997). Furthermore, since the introduction of the influential guided search model by Wolfe and his colleagues (Wolfe, 1994; Wolfe, Cave, & Franzel, 1989), visual search efficiency has been typically conceptualized with reference to the combined effect of bottom-up and top-down processes. Specifically, according to this model, during visual search, pre-attentive processes guide shifts of attention by pinpointing stimulus locations likely to contain the target. This preattentive information encompasses both bottom-up (i.e., the physical distinctiveness of each item as compared to other display items) and top-down influences (i.e., how closely the features of a given item match those characterizing the target). These sources of information combine to form an “activation map”, which contains peaks of activity at likely target locations. During the search process, the focus of attention is directed at the stimulus location showing the most activity. If this location contains the target, the participant responds that the target is present and the search terminates; otherwise, the attentional focus is directed to the next most active location. This process continues until the target is found, until all of the stimuli with activations above a particular threshold have been analysed, or until search extends beyond a certain time limit; the latter two conditions typically result in negative responses. As reviewed by Chen and Zelinsky (2006), there is an ongoing intense debate concerning the relative contributions to search efficiency by bottom-up versus top-down factors. In particular, some researchers (e.g., Theeuwes, Reimann, & Mortier, 2006) argue that the rapid influence of bottom-up factors precedes the slower subsidiary influence of top-down factors. To further explore this issue, a main goal of the present investigation was to examine the magnitude and time course of top-down influences on fixation duration in visual search. In addition, we expected the present study to contribute to the broader exploration of the cognitive control hypothesis in visual cognition in general, and visual search in particular. The investigation of the cognitive control of eye-movements in reading has often involved the manipulation of lexical and/or linguistic variables such as word frequency, predictability, and lexical ambiguity (see Rayner, 2009 for a review). Similarly, an important variable used to study top-down influences in visual


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search is target-distractor similarity. Specifically, a growing number of recent studies employed search displays containing several types of distractors with different levels of target-distractor similarity, and have convincingly demonstrated a bias towards fixating distractors that are similar to the target as compared to dissimilar distractors (e.g., Alexander & Zelinsky, 2011, 2012; Bichot & Schall, 1998; Findlay, 1997; Findlay, Brown & Gilchrist, 2001; Findlay & Gilchrist, 1998; Hooge & Erkelens, 1999; Motter & Belky, 1998; Pomplun, 2006; Pomplun, Reingold, & Shen, 2001a, 2003; Pomplun, Reingold, Shen, & Williams, 2000; Scialfa & Joffe, 1998; Shen, Elahipanah, & Reingold, 2007; Shen & Reingold, 1999; Shen, Reingold, & Pomplun, 2000; Shen et al., 2003; Tavassoli, van der Linde, Bovik, & Cormack, 2009; Williams & Reingold, 2001; Xu, Higgins, Xiao, & Pomplun, 2007; Zelinsky, Peng, Berg, & Samaras, 2013). This phenomenon that is commonly referred to as saccadic selectivity strongly indicates, in line with current visual search theories (e.g., Duncan & Humphreys, 1989; Treisman & Sato, 1990; Wolfe, 1994; Wolfe et al., 1989), that extrafoveal processing and top-down factors at least in part determine saccadic endpoints. In contrast to the well-documented influence of target-distractor similarity on the spatial distribution of saccadic endpoints, the impact of this variable on fixation durations in visual search has been rather controversial. While it is generally accepted that fixation durations in visual search increase as a function of task difficulty (e.g., Gould, 1967; 1973; Jacobs, 1986; Jacobs & O’Regan, 1987; Hooge & Erkelens, 1996, 1998, 1999; Moffitt, 1980; Nattkemper & Prinz, 1984; Phillips, 1981; Rayner & Fisher, 1987; Shen et al., 2003; Trukenbrod & Engbert, 2007; Williams, Reingold, Moscovitch, & Behrmann, 1997; Zelinsky & Sheinberg, 1997), the eye-movement control mechanism mediating this effect is unclear. For example, Hooge and Erkelens, (1996, 1998) proposed a control mechanism of fixation times in visual search (see also Graefe & Vaughan, 1978; Vaughan, 1982, 1983; Vaughan & Graefe, 1977), according to which the average processing difficulty encountered in several previous fixations, rather than the difficulty of the foveal analysis that is in progress, determines the duration of the current fixation. Note that such a control mechanism involves a delayed adjustment of fixation duration based on the difficulty of the search task as compared to the immediate fixation-by-fixation adjustment that is hypothesized by the cognitive control view (see Henderson & Smith, 2009 for a related discussion). As part of their argument in favour of delayed control of fixation times, Hooge and Erkelens (1996, 1998) considered the temporal constraints imposed by neural delays in the perceptual and oculomotor system. Specifically, given the minimum oculomotor latency (the interval between the initiation and the execution of saccades) required to programme a saccade, foveal processing occurring during the final 100–150 ms of the fixation duration could have no impact on fixation duration (see also Reichle & Reingold, 2013; Sereno & Rayner, 2003). Thus, if foveal analysis is required for triggering the programming of the saccade

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that terminates a fixation, it must occur prior to this “dead time” at the end of fixation. Consequently, Hooge and Erkelens (1996, 1998) argued that the remaining time in the average visual search fixation that typically lasts 200–250 ms does not appear sufficient for accomplishing this task. However, this analysis ignores the fact that the processing of the fixated item is likely to begin in advance of the start of fixation via extrafoveal processing. The finding of saccadic selectivity as a function of target-distractor similarity constitutes strong evidence for extrafoveal processing of visual features of subsequently fixated items. Consequently, it is possible that in a visual search task in which distractor items vary in terms of their similarity to the target, extrafoveal processing enables the extraction of information that is required to reject distractors. Such extrafoveal processing might in turn influence the duration of the first fixation on the distractor. The investigation of this important, but as of yet unexplored issue constitutes a major goal of the present study. Accordingly, we focused on the examination of the magnitude and time course of target-distractor similarity effects on fixation duration during visual search both in the standard Free-Viewing condition as well as in a No-Preview condition in which all items except for the fixated item were masked, thereby preventing extrafoveal processing of a display item prior to the first fixation on that item. In addition, the present study was designed to extend prior investigations by primarily focusing on analysing the differences in the distributions of first fixation duration across the target-distractor similarity (similar vs. dissimilar) by preview availability (Free-Viewing vs. No-Preview) conditions. Note that distributional analyses are inherently more suitable than the analysis of mean fixation durations for determining the time course of the influence of targetdistractor similarity. This is because the same effect size in mean fixation durations might reflect a rapid influence of this variable producing a small but consistent increase in the duration of most of the fixations or a slow influence of the variable producing a very strong influence on a few long fixations. Recently, a growing number of studies successfully employed distributional analysis techniques to study eye-movement control in reading (e.g., McConkie & Dyre, 2000; McConkie, Kerr, & Dyre, 1994 ; Reingold et al., 2012; Sheridan, Rayner, & Reingold, 2013; Sheridan & Reingold, 2012a, 2012b; Staub, 2012; Staub, White, Drieghe, Hollway, & Rayner, 2010; White & Staub, 2012; White, Staub, Drieghe, & Liversedge, 2011; White, Warren, Staub, & Reichle, 2011; Yang & McConkie, 2001), and scene processing (e.g., Glaholt & Reingold, 2012; Glaholt, Rayner, & Reingold, 2013; Luke, Nuthmann, & Henderson, 2013). In the present study we applied a survival analysis technique that was introduced by Reingold et al. (2012). This paradigm is designed to identify the earliest discernable influence of a stimulus property on the duration of the first fixation on that stimulus (first fixation duration). Specifically, in two search tasks (see Figure 1) we examined the distributions of first fixation duration that were


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Figure 1. The top part of the figure illustrates the stimuli used in Experiments 1A and 1B. The bottom part of the figure illustrates two successive displays seen by a participant in the gaze contingent No-Preview condition in Experiment 1B. In Display 1 the participant was fixating near a Low Similarity (LS) distractor, which was visible while all other display items were masked. During a saccade (represented by the arrow) this display was changed such that the item nearest to the eventual saccadic endpoint became visible, in this case a High Similarity (HS) distractor, while the previously visible display item was masked (see Display 2). Throughout the trial, such a display change occurred during each saccade (except for saccades which produced immediate refixations of the same display item). Note, in this figure, in order to make the gap in the Landolt C distractors (Experiment 1B) visible, we enlarged it substantially as compared to the size used in the actual trials (see method section for details).

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produced when participants attempted to locate the target that was embedded in an array containing an equal number of high similarity (HS) and low similarity (LS) distractors. Survival curves were then produced for first-fixations on HS and LS distractors. In plotting survival curves, for a given time, t, the percentage of first fixations with a duration greater than t are referred to as the percent survival at time t. Thus, when t equals zero, survival is at 100%, but then declines as t increases, and approaches 0% as t approaches the duration of the longest observed first fixation. Following Reingold et al. (2012, see also Glaholt & Reingold, 2012; Sheridan et al., 2013; Sheridan & Reingold, 2012a, 2012b), we expected that the earliest point in time at which the HS and LS survival curves begin to significantly diverge (henceforth referred to as the divergence point) might provide a promising and unique estimate for the earliest significant influence of target-distractor similarity on first fixation durations. In addition, in order to investigate the role of extrafoveal processing in enabling top-down control, we also manipulated the extent to which stimuli were available for extrafoveal processing during fixations prior to the first fixations on these stimuli. While in the Free-Viewing condition search displays were presented normally, in the No-Preview condition we masked the identity, but not the location, of all display items except for the fixated item. In the latter condition, using a variant of the gaze contingent window paradigm (McConkie & Rayner, 1975; Rayner, 1975), the search display was updated dynamically such that only the display item nearest to the gaze position at a start of every fixation was visible (for other examples of studies that used gaze contingent techniques to explore visual search see Bertera & Rayner, 2000; Cornelissen, Bruin, & Kooijman, 2005; Greene & Rayner, 2001; Pomplun, Reingold, & Shen, 2001a, 2001b; Reingold, Charness, Pomplun, & Stampe, 2001). By comparing the time-course of the target-distractor similarity effects as a function of preview availability, we hoped to shed light on the influence of extrafoveal processing on the control of fixation times in visual search. Finally, we primarily focused on analysing the distribution of the very first fixation on distractor items because such an analysis affords a straightforward opportunity for examining the immediate fixation-by-fixation adjustment of the timing of the saccade terminating the fixation (i.e., fixation duration). This is because an influence of target-distractor similarity on the first fixation on a display item (Stimlusn) could only be due to either: (1) foveal analysis of Stimlusn during the very same fixation, and/or (2) extrafoveal processing of Stimlusn during a fixation on the previous display item (Stimlusn-1). It is important to note that in the No-Preview condition only foveal analysis of Stimlusn could produce a target-distractor similarity effect on the first fixation on that stimulus. Consequently, contrasting the influence of target-distractor similarity across the FreeViewing and No-Preview condition could be used to investigate the role of extrafoveal processing in modulating the time course of this effect. Specifically, we predicted that the first discernible influence of target-distractor similarity


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(i.e., the divergence point between the LS and HS survival curves) would occur earlier in the Free-Viewing than the No-Preview condition, reflecting the contribution of extrafoveal processing of Stimlusn. In addition to first fixation duration, we also conducted survival analyses of immediate refixations on Stimlusn. The survival analysis of this measure, referred to as second fixation duration, was used as a potentially interesting contrast to the first fixation analysis. In particular, we reasoned that the No-Preview second fixation condition might resemble the Free-Viewing first fixation condition. This is because in both of these conditions processing of Stimlusn occurred in the previous fixation (fixationn-1). During fixationn-1, Stimlusn was processed foveally in the NoPreview second fixation condition, and extrafoveally in Free-Viewing first fixation condition. In other words, in terms of the cognitive control of fixation duration, the No-Preview second fixation condition provides “foveal preview” that might be similar in its impact to the extrafoveal preview in the Free viewing condition. Thus, we conducted survival analyses to investigate the time course of target-distractor similarity effects and preview effects in both first fixation and second fixation duration.

METHOD Participants In both Experiments 1A and 1B, 12 undergraduate students were tested at the University of Toronto. None of the participants in Experiment 1A were included in Experiment 1B. All participants had normal or corrected-to-normal vision. They were naïve with respect to the purpose of the experiment and received course credit for their participation.

Apparatus Eye movements were measured with an SR Research EyeLink 1000 system with high spatial resolution and a sampling rate of 1000 Hz. Viewing was binocular, but only the right eye was monitored. A chin rest and forehead rest were used to minimize head movements. Following calibration, average gaze-position error was less than 0.5°. The search displays were presented on a 21 inch ViewSonic monitor with a refresh rate of 150 Hz and a screen resolution of 1024 × 768 pixels (38° × 28.5°). Participants were seated 60 cm from the monitor. All display items were presented in black (4.7 cd/m2) on a white background (56 cd/m2). In the No-Preview condition, the display was updated dynamically using a gaze contingent display paradigm. Dual velocity thresholds were used for saccade detection and the triggering of display changes. Specifically, the first trigger occurred when eye velocity first exceeded a threshold of 50°/s during the acceleration phase of the saccade. The second trigger occurred during the

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deceleration phase of the saccade when eye velocity first decreased below a threshold of 30°/s. During the next screen refresh following the second trigger (average delay of 3.33 ms; maximum delay of 6.7 ms), the display item nearest to the gaze position at the time of the trigger was made visible, and the previously visible item was masked. Given the sparse search displays used in the present experiments (minimum distance of 4.5° between adjacent items), this saccade contingent procedure reliably ensured that for any given fixation all display items except the nearest one were masked (see Figure 1). In debriefing, participants reported that they did not perceive any flicker associated with display changes.

Stimuli and design As shown in Figure 1, in both Experiments 1A and 1B there were three types of display items: Target, High Similarity (HS) distractor, and Low Similarity (LS) distractor. The stimuli in Experiment 1A (see Figure 1) were similar to those used by von Grünau, Dubé, and Galera (1994) and Shen et al. (2003) and subtended 2° both horizontally and vertically. In experiment 1B the target was a 1.75° diameter circle, and the distractors were Landolt Cs of the same diameter with 0.03° gap size. Line-width of the target and the HS distractors (thin Cs) was 0.18° and the line-width of the LS distractors (fat Cs) was 0.56°. The anticipated effectiveness of the target-distractor similarity manipulation in both experiments was based on findings from prior studies (e.g., Hooge & Erkelens, 1999; Shen et al., 2003; von Grünau et al., 1994) demonstrating strong differences across distractor type (HS vs. LS) in search efficiency and saccadic selectivity. In Experiment 1A each search display contained a target item and 9 HS and 9 LS distractors for a total display size of 19 items. In Experiment 1B each search display contained a target item and 8 HS and 8 LS distractors for a total display size of 17 items. For both HS and LS distractors in Experiment 1B, the orientation of the Landolt Cs was chosen equally often (two per display) from the directions up, down, left and right. To create the search displays in both experiments, the stimuli were randomly placed within a 28° × 28° area in the centre of the monitor with a minimum distance of 4.5° between adjacent items. In addition, the target was presented equally often in each of the four quadrants of the display and was centred at least 5° away from the vertical meridian. In Experiment 1A, each participant performed 432 experimental trials in six blocks of 72 trials. In Experiment 1B, each participant performed 504 experimental trials in seven blocks of 72 trials. In each block, there were twice as many Free-Viewing trials as No-Preview trials. We included more trials in the former than the latter condition in order to obtain a comparable number of fixations across these conditions for the distributional analyses by offsetting the anticipated longer average trial duration in the No-Preview than Free-Viewing condition. The order of stimulus displays was randomized with a restriction that


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no more than four consecutive displays of a given type would occur. In addition, at the beginning of the experiment, participants received eight Free-Viewing practice trials followed by eight No-Preview practice trials.

Procedure In both Experiments 1A and 1B, a 9-point calibration procedure was performed at the beginning of the experiment, followed by a 9-point calibration accuracy test. Calibration was repeated if any point was in error by more than 1° or if the average error for all points was greater than 0.5°. Prior to the experiment participants were shown the target as well as the two possible distractors. Participants were told that a target was present in every search display. At the beginning of each trial, participants were instructed to fixate a black dot in the centre of the computer screen and then press a start button to initiate a trial. They were asked to search for the target item and indicate whether the target was presented on the left or the right side of the display by pressing an appropriate button as quickly and as accurately as possible. In the Free-Viewing trials all display items were visible from display onset and until the response. In contrast, in the No-Preview trials only the display item nearest to the fixation position was visible during the fixation and all other stimuli were masked. Consequently, in the latter condition, participants were required to fixate display items in order to view them, and they had to continue doing so until they located the target.

RESULTS Our main focus involved contrasting the distributions of first fixation duration across experimental conditions by employing a survival analysis technique that provided an estimate of the earliest influence of target-distractor similarity (LS vs. HS) and preview availability (Free-Viewing vs. No-Preview) on first fixation duration (Reingold et al., 2012). However, in order to facilitate comparison with prior studies, we first examined the impact of the present manipulation on global search performance and on several measures of eye movements. As shown in Table 1, while accuracy was very high, and did not vary as a function of preview availability, the No-Preview condition resulted in substantially longer reaction times (RTs) and more fixations per trial than the Free-Viewing condition. The superior search performance in the Free-Viewing condition as compared to the No-Preview condition was also reflected in saccadic selectivity in the former, but not the latter condition. Specifically, in the Free-Viewing condition across both experiments approximately 85% of first fixations on distractor items landed on HS distractors. In marked contrast, in the No-Preview condition, the absence of visual guidance by extrafoveal processing resulted in an equal likelihood of first fixations landing on HS distractors and LS distractors.

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TABLE 1 Accuracy (proportion correct), reaction time (S), number of fixations and saccadic selectivity by preview availability in Experiments 1A and 1B (standard errors in parentheses) Experiment 1A Variable Accuracy Reaction time (RT) Number of fixations Saccadic selectivity

Experiment 1B

FreeViewing

NoPreview

Preview benefit

FreeViewing

Nopreview

Preview benefit

.97 (.005) 3.69 (.27) 14.4 (1.2) .87 (.008)

.98 (.004) 5.83 (.36) 20.1 (1.1) .50 (.002)

−.01 n.s. 2.14 *** 5.7 *** .37 ***

.99 (.003) 2.55 (.09) 9.2 (.17) .84 (.010)

.98 (.005) 4.94 (.18) 14.1 (.25) .50 (.002)

.01 n.s. 2.39 *** 4.9 *** .34 ***

For t tests df = 11, *** p < .001, n.s. p > .1; HS = High Similarity distractor; LS = Low Similarity distractor; Preview benefit = No-Preview – Free-Viewing for RT, number of fixations; and Preview benefit = Free-Viewing – No-Preview for accuracy and saccadic selectivity. Saccadic selectivity = the number of first fixations on HS distractors divided by the total number of first fixations on distractors.

In addition, several fine-grained eye-movement measures were analysed in order to examine the influence of the present manipulation on viewing behaviour during the first dwell on distractor items (where a dwell was defined as a run of one or more consecutive fixations on a display item prior to a saccade to another display item). Specifically, as summarized in Tables 2 and 3, the following measures were computed: (1) first fixation duration (i.e., the duration of the first fixation during the first dwell on distractor items), (2) second fixation duration (i.e., for first dwells with more than one fixation, the duration of the second fixation), (3) probability of single fixation (i.e., the proportion of first dwells with only one fixation), and (4) dwell duration (i.e., the sum of the duration of all fixations during the first dwell on a distractor). For all of these dependent measures, 2 × 2 × 2 analyses of variance (ANOVAs) were carried out on the data with target-distractor similarity (HS vs. LS) and preview availability (FreeViewing vs. No-Preview) as within-participant variables, and Experiment (1A vs. 1B) as a between-participant variable (see Table 2 for the means and standard errors and Table 3 for the significance of main effects and interactions). Furthermore, as shown in Table 2, for both Experiment 1A and 1B, we conducted two types of planned comparisons in order to evaluate: (1) the targetdistractor similarity effects in the Free-Viewing and No-Preview conditions, and (2) the preview benefits for HS distractors and LS distractors (i.e., the decrease in fixation times and the increase in the probability of single fixation dwells due to the availability of distractors for extrafoveal processing). As can be seen by an inspection of these tables, for all experiments, conditions and measures there

TABLE 2 First fixation duration (ms), second fixation duration (ms), the probability of single fixation dwell, and dwell duration (ms) on both High Similarity (HS) and Low Similarity (LS) distractors in both the Free-Viewing and the No-Preview condition in Experiments 1A and 1B (standard errors in parentheses) Free-Viewing

No-Preview

Preview benefit

First Fixation 1A 1B Second Fixation 1A 1B Prob. of a Single Fixation 1A 1B Dwell Duration 1A 1B

HS

LS

diff.

HS

LS

diff.

HS

LS

238 (9.2) 200 (5.1)

170 (5.8) 165 (6.5)

68 *** 35 ***

304 (11.5) 271 (8.6)

246 (6.5) 235 (7.3)

58 *** 36 ***

66 *** 71 ***

76 *** 70 ***

231 (14.0) 145 (4.3)

113 (7.4) 115 (7.0)

118 *** 30 ***

278 (14.7) 191 (9.0)

159 (6.7) 157 (9.8)

119 *** 34 ***

47 *** 46 ***

46 *** 42 ***

.569 (.025) .755 (.022)

.804 (.026) .845 (.018)

.235 *** .090 **

.406 (.024) .698 (.032)

.714 (.022) .823 (.014)

.308 *** .125 ***

.163 *** .057 p = .07

.090 * .022 n.s.

354 (20.7) 237 (5.4)

193 (7.2) 183 (7.5)

161 *** 54 ***

527 (28.0) 335 (14.3)

294 (9.9) 266 (9.9)

233 *** 69 ***

173 *** 98 ***

101 *** 83 ***

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For t tests df = 11; *** p < .001; ** p < .01; * p < .05; n.s. p > .1; HS = High Similarity distractor; LS = Low Similarity distractor; diff. = HS – LS = targetdistractor similarity effect; Preview benefit = No-Preview – Free-Viewing for First Fixation, Second Fixation, and Dwell Duration; and Preview benefit = FreeViewing – No-Preview for Probability of a Single Fixation.


Experiment

First Fixation Duration Second Fixation Duration Probability of Single Fixation Dwell Duration

df = F (1, 22).

Exp.

Preview

Similarity

Preview x Similarity

Exp. x Preview

Exp. x Similarity

Exp. x Preview x Similarity

F = 5.1, p < .05 F = 16.9, p < .001 F = 40.6, p < .001 F = 28.9, p < .001

F = 584.8, p < .001 F = 120.5, p < .001 F = 37.8, p < .001 F = 273.6, p < .001

F = 152.1, p < .001 F = 109.9, p < .001 F = 188.5, p < .001 F = 153.2, p < .001

F = 1.1, n.s. F < 1, n.s. F = 5.5, p < .05 F = 22.9, p < .001

F < 1, n.s. F < 1, n.s. F = 10.4, p < .01 F = 11.4, p < .01

F = 12.8, p < .01 F = 36.4, p < .001 F = 35.3, p < .001 F = 42.0, p < .001

F = 1.7, n.s. F < 1, n.s. F < 1, n.s. F = 9.2, p < .01


Variable

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TABLE 3 The significance of main effects and interactions from the analysis of first fixation duration (ms), second fixation duration (ms), the probability of single fixation dwell, and dwell duration (ms) by Experiment (1A vs. 1B), Preview (Free-Viewing vs. No-Preview), and Similarity (High Similarity vs. Low Similarity)


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were robust target-distractor similarity effects and preview benefits. This was due to longer fixation times (first fixation, second fixation, and dwell duration) and lower probability of single fixation dwells on HS distractors than LS distractors and in the No-Preview as compared to the Free-Viewing condition. While the magnitude of the preview benefit was stronger for the first fixation duration than the second fixation duration, for both of these measures the preview benefit did not vary as a function of target-distractor similarity. In contrast, a stronger preview benefit for HS distractors than LS distractors was observed for the dwell duration measure and the probability of single fixation measure. It is also interesting to compare search performance across experiments. The search task used in Experiment 1A resulted in longer RTs and more fixations per trial as compared to the search task that was employed in Experiment 1B (see Table 1). Based on the analysis of the eye-movement measures, the difference in performance between experiments was not due to the efficiency of selecting display items for foveal analysis (i.e., a comparable level of saccadic selectivity was observed across experiments). In addition, the examination of fixation time measures revealed similar performance across experiments for dwells on LS distractors. Rather, the main difference appears to be caused by longer dwell duration on HS distractors in Experiment 1A than Experiment 1B, resulting in larger target-distractor similarity effects in the former than the latter experiment. Furthermore this interaction between Experiment and target-distractor similarity was more pronounced in the No-Preview than the Free-Viewing condition as reflected by a significant three-way interaction (see Table 3). Thus, it is likely that the discrimination between the HS distractor and the target was more challenging in Experiment 1A than Experiment 1B, and this difficult discrimination in Experiment 1A was further exacerbated when extrafoveal processing of display items was rendered ineffective in the No-Preview condition. The specificity of the difference in the pattern of eye movements across experiments nicely illustrates the advantage of using fine-grained eye-movement measures to supplement the standard RT and accuracy measures of search performance.

Survival analyses As discussed earlier, our main goal in the present study involved testing the cognitive control hypothesis, in general and the influence of extrafoveal processing, in particular. The primary tool we used for that purpose was a survival analysis technique that was introduced by Reingold et al. (2012). We begin by examining survival analyses of first fixation and second fixation duration investigating the first discernible influence of target-distractor similarity, followed by analyses exploring the onset of preview effects. Across participants in Experiment 1A, there were 22,801 and 17,005 first fixations in the FreeViewing and No-Preview conditions, respectively. The corresponding numbers of first fixations in Experiment 1B were 21,571 (Free-Viewing) and 17,669 (No-

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Preview). The number of second fixations in Experiment 1A was 9180 in the FreeViewing condition and 7481 in the No-Preview condition. The corresponding numbers in Experiment 1B were 4887 (Free-Viewing) and 4191 (No-Preview). Target-distractor similarity effects. To explore the time-course of the influence of target-distractor similarity (LS vs. HS) on first fixation and second fixation duration, we computed LS and HS survival curves in both the FreeViewing and No-Preview conditions. For each 1-ms time bin t (t was varied from 0–600 ms), the percentage of fixations with a duration greater than t constituted the percent survival at time t. The survival curve for each condition was computed separately for each participant, and then averaged across participants. In order to estimate the divergence point between the LS and HS survival curves, we employed a bootstrap re-sampling procedure (Efron & Tibshirani, 1994). On each iteration of this procedure, the set of observations (first fixation or second fixation durations) for each participant and condition was randomly re-sampled with replacement. Individual participant’s survival curves were then computed and averaged. Next, the value for each 1-ms bin in the LS survival curve was subtracted from the corresponding value in the HS survival curve. This procedure was repeated 1000 times, and the obtained differences for each 1-ms bin were then sorted in order of magnitude. Bins in which the smallest difference between the HS and LS survival rate was greater than zero were defined as significant difference points. The divergence point was then defined as the earliest significant difference point that was part of a run of five consecutive significant difference points. Each panel in Figure 2 displays the LS and HS survival curves, the divergence point (indicated by the vertical dashed line), and an inset histogram of the corresponding fixation distributions. As can be seen in Figure 2 (Panels a and c), for first fixation in the Free-Viewing condition the LS and HS survival curves significantly diverged at a duration of 28 ms in Experiment 1A and 26 ms in Experiment 1B. In marked contrast, in the No-Preview condition (Figure 2, Panels b and d), the LS and HS survival curves for first fixation significantly diverged at 233 ms in Experiment 1A and 199 ms in Experiment 1B. Furthermore, these divergence points also define the percentage of first fixations with durations that were too short to exhibit an influence of target-distractor similarity. In the Free-Viewing condition only very few first fixations had durations that were shorter than the divergence point (Exp. 1A: < 1%; Exp. 1B: < 1%). In contrast, the corresponding percentages in the No-Preview condition were 42% in Experiment 1A and 25% in Experiment 1B. Thus, a comparison of the divergence point across preview conditions indicates a dramatic impact of extrafoveal processing on the onset of the target-distractor similarity effect on first fixation duration. An inspection of the LS and HS survival curves for second fixation duration (Figure 2, Panels e–h) reveals a qualitatively different pattern. Not surprisingly,


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Figure 2. Survival curves contrasting fixation duration on High Similarity (HS) versus Low Similarity (LS) distractors for both first fixation (Exp. 1A in Panels a–b, Exp. 1B. in Panels c–d), and second fixation (Exp. 1A in Panels e–f, Exp. 1B. in Panels g-h). Results from the Free-Viewing condition are shown in the left column (Exp. 1A in Panel a and Panel e, Exp. 1B. in Panel c and Panel g), and results from the NoPreview condition are displayed in the right column (Exp. 1A in Panel b and Panel f, Exp. 1B. in Panel d and Panel h). In each panel, the divergence point is marked by the vertical dashed line, and the histogram of fixation durations by target-distractor similarity is shown in the top right section of the panel. See text for details.

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early divergence points were obtained for second fixation in the Free-Viewing condition (Exp. 1A = 26 ms – Figure 2, Panel e; Exp. 1B = 48 ms – Figure 2, Panel g). However, in the No-Preview condition, unlike the late divergence points for first fixation, second fixation divergence points (Exp. 1A = 34 ms – Figure 2, Panel f; Exp. 1B = 55 ms – Figure 2, Panel h) were only slightly longer than the divergence points for second fixation in the Free-Viewing condition. These early divergence points delimit the small percentage of second fixations that were too short to exhibit an influence of target-distractor similarity (Exp. 1A: Free-Viewing < 1%, No-Preview < 1%; Exp. 1B: Free-Viewing < 5%, NoPreview < 7%). The present findings are consistent with our hypothesis that the time course of the target-distractor similarity effect for second fixation in the NoPreview condition might be similar to the time course of the influence of this variable on first fixation in the Free-Viewing condition. Importantly, for both types of fixations, the processing of the fixated display item might have been initiated during the previous fixation (i.e., extrafoveally in the Free-Viewing first fixation condition, and foveally in the No-Preview second fixation condition). Preview effects. To further investigate the onset of extrafoveal and foveal preview effects we conducted two additional sets of survival analyses (see Figure 3). Specifically, survival curves of first fixation in the No-Preview condition were contrasted with: (1) survival curves of first fixation in the Free-Viewing condition in order to determine the onset of the extrafoveal preview effect (Figure 3, Panels a–d), and (2) survival curves of second fixation in the NoPreview condition in order to determine the onset of the foveal preview effect (Figure 3, Panels e–h). To the extent that foveal or extrafoveal preview enables the extraction of more of the information that is required to reject target-dissimilar than target-similar distractors, such differential processing might in turn be reflected in earlier preview effects for fixations on LS than HS distractors. Consistent with this prediction, the onset of the extrafoveal preview effect (i.e., Free-Viewing vs. NoPreview) occurred earlier in first fixation on LS distractors than HS distractors (Exp. 1A: LS = 29, HS = 66 ms – Figure 3, Panels a–b; Exp. 1B: LS = 27, HS = 42 ms – Figure 3, Panels c–d). A similar pattern was observed for the onset of the foveal preview effect (i.e., No-Preview: first fixation vs. second fixation) in Experiment 1A (LS = 31, HS = 75 ms –- Figure 3, Panels e–f) but not in Experiment 1B (LS = 37, HS = 34 ms – Figure 3, Panels g–h). This difference between experiments with regard to the onset of the foveal preview effect is consistent with the findings discussed above, which suggested that the manipulation of target-distractor similarity was more extreme in Experiment 1A than in Experiment 1B. Finally, across all of the survival analyses shown in Figure 3, less than 2% of fixations had durations that were shorter than the divergence point and consequently were too short to exhibit a preview effect.


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Figure 3. Survival curves contrasting fixation duration in: (1) the Free-Viewing versus the No-Preview condition (Exp. 1A in Panels a–b, Exp. 1B in Panels c–d), and (2) first fixation versus second fixation in the No-Preview condition (Exp. 1A in Panels e–f, Exp. 1B in Panels g–h). Results for fixations on low similarity distractors are shown in the left column (Exp. 1A in Panel a and Panel e, Exp. 1B in Panel c and Panel g), and results for fixations on high similarity distractors are displayed in the right column (Exp. 1A in Panel b and Panel f, Exp. 1B in Panel d and Panel h). In each panel, the divergence point is marked by the vertical dashed line, and the histogram of the distribution of fixation durations is shown in the top right section of the panel. See text for details.

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DISCUSSION The present results are consistent with a growing literature demonstrating a variety of saccadic selectivity effects in visual search (e.g., Bichot & Schall, 1998; Findlay, 1997; Findlay et al., 2001; Findlay & Gilchrist, 1998; Hooge & Erkelens, 1999; Motter & Belky, 1998; Pomplun, 2006; Pomplun et al., 2000, 2001a, 2003; Scialfa & Joffe, 1998; Shen & Reingold, 1999; Shen et al., 2000, 2003, 2007; Tavassoli et al., 2009; Williams & Reingold, 2001; Xu et al., 2007). Taken together, these findings clearly demonstrate the critical role of extrafoveal processing in biasing the distribution of saccadic endpoints towards distractors that share certain visual features with the target. The present study also provided convergent evidence for prior demonstrations that, in visual search, the degree of difficulty associated with the processing of a fixated display item is positively correlated with fixation times on this item (e.g., Gould, 1967; 1973; Jacobs, 1986; Jacobs & O’Regan, 1987; Hooge & Erkelens, 1996, 1998, 1999; Moffitt, 1980; Nattkemper & Prinz, 1984; Phillips, 1981; Rayner & Fisher, 1987; Shen et al., 2003; Trukenbrod & Engbert, 2007; Williams et al., 1997; Zelinsky & Sheinberg, 1997). However, the most important contribution of the present study was related to the findings from the survival analyses concerning the onset of the targetdistractor similarity and preview effects on fixation duration. Consider first the results from the No-Preview condition in which extrafoveal processing was rendered ineffective for the purpose of the discrimination between HS and LS distractors. The survival curves for first fixation in this condition (Figure 2, Panels b and d) indicated that the earliest discernable influence of targetdistractor similarity on first fixation duration occurred 199–233 ms from the beginning of fixation. Importantly, when taking into account approximately 50 ms neural delay associated with visual input (i.e., the retina–brain lag; Clark, Fan, & Hillyard, 1995; Foxe & Simpson, 2002; Mouchetant-Rostaing, Giard, Bentin, Aguera, & Pernier, 2000; Van Rullen & Thorpe, 2001; see Reichle & Reingold, 2013), and a minimum of 125 ms neural delay associated with oculomotor output (i.e., saccadic programming lag; Becker & Jürgens, 1979), the present findings indicate an extremely rapid differentiation between LS and HS distractors, requiring as little as 24–58 ms of cortical processing time (i.e., the divergence point for No-Preview minus 175 ms corresponding to the sum of input and output delays). We can now turn to the consideration of the timing constraints that operate in the Free-Viewing condition (i.e., in normal visual search). As indicated by our survival analysis (see Figure 2, Panels a and c), an effect of target-distractor similarity on first fixation duration in the Free-Viewing condition is evident as early as 26–28 ms after the onset of the fixation and consequently only very few fixations were too short to be impacted by target-distractor similarity. The fast


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acting influence of this variable is clearly consistent with the hypothesis of cognitive control of fixation times in visual search. However, given neural delays in the perceptual and oculomotor systems, it is evident that such a rapid influence of target-distractor similarity on first fixation duration cannot be due to foveal analysis during that fixation. Consequently, our results suggest that extrafoveal processing had a vital role in enabling an immediate fixation-byfixation adjustment of the duration of foveation. This conclusion is further bolstered by the finding that the onset of the targetdistractor similarity effect on first fixation in the Free-Viewing condition (a condition which provided extrafoveal preview) was comparable to the onset of the influence of this variable on second fixation in the No-Preview condition (a condition which provided foveal preview). Thus, although foveal analysis is clearly superior to extrafoveal analysis for the purpose of encoding fine perceptual detail, at least with robust manipulations of target-distractor similarity such as the ones that were employed in the present experiments, extrafoveal processing had a powerful influence on the timing and efficiency of targetdistractor discrimination. Furthermore, the present survival analyses demonstrated a rapid onset of the influence of extrafoveal preview and foveal preview on fixation duration, but also revealed an interesting difference between these effects. Specifically, the onset of the extrafoveal preview effect occurred earlier for fixations on LS than HS distractors, and this finding suggests that more of the information required for rejecting the LS than HS distractors was obtained extrafoveally. In contrast, for the foveal preview effect, a similar pattern only occurred in Experiment 1A in which the discrimination between the target and the HS distractor was very challenging. Future research is required in order to systematically investigate variation in the timing of preview effects as a function of target-distractor similarity. More generally, the survival analysis and the preview availability manipulation that were employed in the present study constitute a promising method for deriving precise quantitative estimates of the time-course of the influence of targetdistractor similarity on fixation durations. Consequently, an important direction for future research would involve applying the present paradigm to study the timecourse of more subtle manipulations of target-distractor similarity as well as other variables that are known to impact visual search fixation times. Such estimates would in turn provide potentially important temporal constraints that could be used to inform models of eye-movement control of fixation times in visual search. Finally, the extremely fast-acting influence of target-distractor similarity that was demonstrated in the present study is clearly inconsistent with any conceptualization of visual search that argues for a secondary influence of slow acting top-down factors on search efficiency (e.g., Theeuwes et al., 2006; see Chen & Zelinsky, 2006 for a review). In addition, as argued by Zelinsky, Peng, Berg, and Samaras (2013), models of visual search typically focus on explicating the nature of peripheral selection rather than central discrimination.

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In particular, most theoretical frameworks do not clearly specify how selected display items are identified and the possible contributions of extrafoveal processing to the eventual recognition of these objects. It seems counterintuitive that efficient selection of relevant display items, as measured by the wellestablished finding of saccadic selectivity, would not also translate into a processing advantage when these items are later foveated. The present findings that extrafoveal processing of target-distractor similarity had robust effects on peripheral selection (i.e., saccadic selectivity) as well as on the time course of the central discrimination (i.e., the divergence point between LS and HS survival curves) calls into question the degree to which these aspects of visual search performance are truly as independent and dissociable as suggested by most accounts of this phenomenon.

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