Journal of Vision (2014) 14(3):27, 1–15 http://www.journalofvision.org/content/14/3/27 1

The impact of predictive cues and visual working on dynamic oculomotor selection Center for Mind/Brain Sciences, University of Trento, Matthew D. Weaver Trento, Italy $

Center for Mind/Brain Sciences, University of Trento, Davide Paoletti Trento, Italy $ Center for Mind/Brain Sciences, University of Trento, # Wieske van Zoest Trento, Italy $

Strategic use of advanced information about search any given time, can vary markedly between individuals. display properties can benefit covert attentional Most models of attentional control consider oculomo- selection. However, little work has investigated this tor and visual selection to be determined by the benefit on overt selection. The present study examined interplay between goal-directed processes, representing how cued information impacts oculomotor selection current observer selection goals, and stimulus-driven over time and the role played by individual differences in processes determined by the physical salience of visual (VWM) capacity in utilizing such elements in the visual environment (e.g., Bundesen, cues. Participants searched for a specific orientation 1998; Desimone & Duncan, 1995; Egeth & Yantis, target in a saccade localization search task. Prior to each 1997; Folk, Remington, & Johnston, 1992; Itti & Koch, trial, additional information regarding secondary display 2000; Treisman & Sato, 1990; Wolfe, 1994, 2007; but features (color singleton identity) was either provided by see Awh, Belopolsky, & Theeuwes, 2012). By extension, a word cue or not. The cue increased accuracy performance from the earliest saccadic responses. VWM saccades (i.e., rapid eye movements) used for oculo- capacity was measured via a change-detection task and motor selection are generally considered to result from results showed that individuals’ VWM capacity scores the combination of stimulus-driven and goal-directed were associated with cue impact, whereby participants processes (e.g., Godijn & Theeuwes, 2002). Although it with higher capacity derived an increased cue is accepted that goal-directed strategies can use performance benefit. These findings suggest that advanced information about the properties of a search strategic use of cue information to select and reject display to directly influence covert attentional selection, salient singletons can develop very early following relatively little work has investigated this benefit on display presentation and is related to an individual’s overt saccadic selection. The aim of the present study VWM capacity. This research indicates that stimulus- was twofold: first, to explore how the impact of driven and goal-directed processes are not simply advanced knowledge provided by a preceding cue additive in oculomotor selection, but instead exhibit a develops over time to influence oculomotor selection distinct and dynamic profile of interaction. and second, to investigate the role that individual differences play in utilizing this cue to benefit selection performance. The first focus of the present study specifically Introduction concerned the impact of nonspatial (cf. spatial) information provided by endogenous (cf. exogenous) We are constantly inundated by sensory informa- cues, that is, those cues which require the information tion, which competes for selection from limited- to be used in a goal-directed manner to assist selection. capacity attentional resources. However, the ability to While previous research demonstrates that knowing efficiently and effectively select those subsets of what features to expect can improve information, which are most behaviorally relevant at performance (Mu¨ller, Reimann, & Krummenacher,

Citation: Weaver, M. D., Paoletti, D., & van Zoest, W. (2014). The impact of predictive cues and visual working memory on dynamic oculomotor selection. Journal of Vision, 14(3):27, 1–15. http://www.journalofvision.org/content/14/3/27, doi: 10.1167/ 14.3.27.

doi: 10.1167/14.3.27 Received December 19, 2013; published March 24, 2014 ISSN 1534-7362 Ó 2014 ARVO

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2003; Wolfe, Horowitz, Kenner, Hyle, & Vasan, 2004), cue itself; see also Theeuwes et al., 2006; Theeuwes & the developmental time-course by which this influence Van der Burg, 2007). The purpose of the present study operates to guide selection remains unclear. Given was to explore the dynamics of how and when sufficient time to apprehend the cue, some research nonspatial information provided by endogenous cues would indicate that advanced nonspatial information impact oculomotor selection during visual search. In should have an immediate or early influence on doing so, we sought to extend existing research by attentional selection (Adams & Chambers, 2012; Bravo examining cue impact across the latency distribution of & Nakayama, 1992; Hillstrom, 2000; Lamy, Carmel, oculomotor responses, using a mixed design that Egeth, & Leber, 2006; Lamy & Yashar, 2008; Leonard allowed measurement of intertrial effects. & Egeth, 2008; Mu¨ller & Krummenacher, 2006; Mu¨ller Because eye movements determine the quality of early et al., 2003; Treisman, 1988; Wolfe, Butcher, Lee, & visual information processing, they represent a form of Hyle, 2003; Zhang & Luck, 2009), while other findings behavior more implicit and sensitive than manual would suggest an influence only later, following initial button-press responses, effectively reflecting a real-time stimulus-driven selection processes (Cave & Pashler, measure of the overt allocation of visual . 1995; Hochstein & Ahissar, 2002; Kim & Cave, 2001; Recent research on oculomotor selection in visual search Nothdurft, 2002; Theeuwes, Reimann, & Mortier, has highlighted the importance of examining when a 2006; Theeuwes & Van der Burg, 2007, 2011; Tsal & response is made relative to stimulus onset. Early Lavie, 1988; van Zoest, Donk, & Theeuwes, 2004). saccades following a display presentation are more likely In addition, more recently, it has been increasingly to be made to the most physically salient stimuli argued that many findings supporting a role for early regardless of task-relevance (Godijn & Theeuwes, 2002; goal-directed guidance by nonspatial information can Ludwig & Gilchrist, 2002; Mulckhuyse, van Zoest, & also be explained by passive bottom-up intertrial Theeuwes, 2008). As saccade latency increases, so, too, priming (see Awh et al., 2012; Lamy & Kristjansson, does the likelihood that the saccade is directed to the 2013; Theeuwes, 2013, for recent reviews). For example, task-relevant item (Donk & van Zoest, 2008; van Zoest & repeating versus switching a target dimension or feature Donk, 2005, 2008; van Zoest et al., 2004; see also Hickey, value across trials can also lead to significant improve- van Zoest, & Theeuwes, 2010, for complementary results ment in terms of speed and accuracy of visual selection, with covert attentional shifts). Using this approach, van a phenomenon termed priming of pop-out (PoP) Zoest and Donk (2008) interestingly demonstrated a (Maljkovic & Nakayama, 1994). In paradigms where benefit of task instructions on the earliest 20% of advanced knowledge of target properties is manipulated saccadic responses in a search task requiring discrimi- by holding properties constant (‘‘blocked’’) versus nation of targets from unique distractors based on color. varying them (‘‘mixed’’) across trials, any evidence that While these data suggest a potentially early role for goal- attentional settings for a specific target feature can guide directed guidance based on advanced nonspatial infor- attention then becomes confounded with intertrial mation, such conclusions are precluded by use of a repetition effects (e.g., Belopolsky, Schreij, & Theeuwes, blocked (rather than mixed) design which could not rule 2010; Maljkovic & Nakayama, 1994; Pinto, Olivers, & out a bottom-up intertrial priming account of the Theeuwes, 2005). One way to disentangle these effects is findings. By examining saccadic accuracy as a function of by using cues to provide advance knowledge on a trial- saccade latency, the present study will add a further layer by-trial basis. Leonard and Egeth (2008) used a mixed of understanding to the dynamic nature of when and design to compare word cues that either provided 100% how cue information influences selection, providing valid information about an upcoming target color (‘‘red’’ greater scope to reconcile existing findings. or ‘‘green’’) or were noninformative (‘‘either’’) in a The second motivation of the present study was to singleton search, while concurrently measuring impact investigate how individual differences in visual working of repeating versus switching target colors on successive memory (VWM) capacity influences overt selection trials. While similar search performance benefits from performance. VWM is broadly considered to be a both advanced feature cuing and target repetition were capacity-limited cognitive resource involved in the observed, the results indicated these were separable and active ‘‘on-line’’ maintenance of information to per- independent effects. However, along with other research form current tasks (Cowan, 2001). Within the context (Mu¨ller & Krummenacher, 2006; Mu¨ller et al., 2003), of visual search, VWM has been implicated as a crucial these findings contrast with those of Theeuwes and Van mechanism that defines and maintains active represen- der Burg (2011) who found evidence that advanced tations of task-relevant items, creating feature tem- feature information affected early attentional selection plates necessary to select task-relevant targets and only when target features repeated across trials (attri- reject task-irrelevant distractors (e.g., Bundesen, Ha- buted to intertrial priming) or when the actual search bekost, & Kyllingsbaek, 2005). feature (and not a symbolic word) was presented as a cue Stable differences in VWM capacity across healthy (attributed to automatic bottom-up priming from the individuals are highly correlated with higher order

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cognitive functioning (Cowan et al., 2005; Fukuda, with stimulus-driven processes); identifying the dis- Vogel, Mayr, & Awh, 2010), and a wealth of research tractor as a color singleton indicated the need to guide has found significant differences between individuals selection away from the most salient feature (requiring with high versus low VWM capacity in a wide range of the override of stimulus-driven processes). Given these cognitive tasks where attentional control was necessary cues could vary trial by trial, ongoing and active for successful performance (e.g., Bleckley, Durso, attentional control became necessary to derive benefit Crutchfield, Engle, & Khanna, 2003; Heitz & Engle, from them. In order to maximize impact, cues not only 2007; Poole & Kane, 2009; Sobel, Gerrie, Poole, & identified the status of the singleton (target vs. Kane, 2007; Vogel, McCollough, & Machizawa, 2005). distractor), but also the dimension (color) and feature Consequently, it has been posited that VWM is closely value (red) of the singleton, with 100% accuracy. linked with attentional processes and that an individ- Therefore cues were highly informative and useful for ual’s VWM capacity reflects the degree to which efficient selection of the target. attentional control can be exerted in order to select and A mixed design was used by varying (rather than maintain task-relevant information in the presence of holding constant) the status of the color singleton distraction. Individual differences in VWM capacity (target-color singleton, distractor-color singleton, or would thus be expected to predict differential perfor- no-color singleton) across trials within cued and mance in a cognitive task requiring attentional control. uncued conditions. Consequently, the average likeli- In the present experiment we used a color change- hood of target status as a color singleton repeating detection task to estimate VWM capacity (as in Luck & versus changing on consecutive trials was equal across Vogel, 1997) and correlated performance in this task both cued and uncued conditions, ensuring that with the main oculomotor search task. potential effects of intertrial priming were matched The primary experiment involved a modified visual between cue conditions. Symbolic word cues were used search task where eye movements were recorded while to avoid bottom-up priming from presenting the participants searched for a specific orientation target. feature itself as a cue. This design also allowed In the uncued half of the experiment, participants were independent investigation into the dynamic contribu- not provided with any additional information regard- tions of passive intertrial priming, by comparing the ing the secondary features of the display (i.e., basic time-course of performance on trials where target replication of van Zoest & Donk, 2008, experiment 1). singleton status had repeated versus switched from In the cued half of the experiment, participants were previous trials. Taken together, it could be examined given specific information regarding a secondary how the dual contributions of stimulus-driven intertrial feature of the upcoming display by means of a word priming and goal-directed use of cue information cue. Thus, while the primary search task was alike in combine to guide selection. both experimental sessions, participants received more It was predicted that when the target was a color or less relevant information regarding the additional singleton, the presence of a valid cue would result in features in the display. superior task performance (i.e., response speed and/or More specifically, the basic experiment instructed accuracy). Again, the idea being that goal-directed participants to select a particular line orientation in a guidance would further benefit selection of the salient visual search task by making an eye movement to its color target. Stimulus-driven control accounts of location. In addition to the target, a second uniquely oculomotor selection would suggest that initial selec- oriented singleton was always present in the search tion is guided only by stimulus-driven processes and so display. Target and distractor lines were equally salient would predict an additional accuracy benefit from the in terms of orientation-contrast relative to the non- cue to be observed only for later saccadic responses targets. The target line or the distractor line could also (i.e., following initial attentional selection). However, be unique in color (creating a salient color singleton) or goal-directed control accounts would indicate that when no extra color was applied, could both be equally initial selection can be guided by goal-directed pro- salient. In the uncued part of the experiment, partic- cesses, such that a cue accuracy benefit would be ipants were solely provided with the word ‘‘ready.’’ In observed from the earliest saccadic responses (e.g., the cued part of the experiment, the singleton identity Wolfe, 1994, 2007). Regardless, once this influence was (target-color singleton, distractor-color singleton, or observed, it was expected to rapidly asymptote to a no-color singleton) was validly cued prior to each trial. maximum level of accuracy performance over the Importantly, these cues provided additional informa- remaining time-course of saccadic responses. tion allowing the use of the more salient dimension of Regarding distractor as a color singleton, the color to assist selection in a goal-directed manner. research is mixed as to whether a cue informing Whereby identifying the target in advance as a color participants of the to-be-ignored feature could be singleton effectively indicated oculomotor selection expected to result in a performance benefit (Arita, could be guided to the most salient feature (in concert Carlisle, & Woodman, 2012; Carlisle & Woodman,

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2011; Munneke, Van der Stigchel, & Theeuwes, 2008; run on a Pentium III Dell Precision T1600 PC (Dell, Sawaki & Luck, 2011; Theeuwes & Burger, 1998; Ło´dz´, Poland) and displayed on a 19-inch ViewSonic Woodman & Luck, 2007) or cost (Moher & Egeth, G90fB CRT monitor (ViewSonic, Munich, Germany) 2012; Soto, Heinke, Humphreys, & Blanco, 2005; Soto, at a 100 Hz refresh rate and 1024 · 768 resolution. Humphreys, & Heinke, 2006). A primary question Participants were seated approximately 57 cm from the underlying these discrepant predictions concerns the monitor and eye movements were measured using the degree to which goal-directed processes can overcome EyeLink II Desktop Mount (SR Research, Ltd., an initial bias to attend to the to-be-ignored distractor Mississauga, Canada). features matching WM content. Examining accuracy performance as a function of saccade latency may provide valuable insights to this question. An immedi- Stimuli, procedure, and design ate and consistent accuracy benefit from the cue over the latency distribution of saccadic responses would Oculomotor search task indicate an ability to suppress distractor activation Stimuli consisted of a 17 · 17 rectangular matrix of without first requiring attentional selection, while an line elements (approximate length of 0.688 visual angle) accuracy cost, particularly for early saccadic responses, presented on a black background, subtending 29.118 · would suggest attentional selection may be prerequisite. 21.868. Target and distractor line elements were Regarding the predictions concerning VWM capac- angularly oriented 458 to either the left or right. On ity, Woodman, Luck, and Schall (2007) demonstrated every trial a target and a distractor were presented at that increasing VWM load disrupted visual search two of four equidistant locations at the vertices of an when implementing trial-by-trial cuing of feature imaginary square (approximately 10.758 · 10.758) representations using the target stimulus itself as a cue. surrounding fixation, embedded within the matrix of An important role by VWM was similarly predicted for vertical white nontargets. Angular distance between the present experiment when semantically cuing feature both target and distractor elements from central representations using symbolic word cues, particularly fixation was always 908. given the task effectively required participants to Trial procedure is presented in Figure 1. Each trial generate, maintain, and coordinate feature templates began with a drift correction. A central fixation point with attentional deployment on a trial-by-trial basis. was presented for 200 ms, then replaced by a word cue To this end, it was expected that individual differences in 17-point Arial font for 1000 ms. A fixation point was in VWM capacity would predict differences in the shown again for 400 to 600 ms, followed by the matrix, ability to make use of the cues to control oculomotor presented for 1500 ms. Participants were instructed to selection, such that individuals with a higher VWM make a speeded saccade to the tilted element defined as capacity would benefit more from the cue than those the target (e.g., right-tilted) while ignoring the dis- with lower VWM capacity. tractor defined by the opposite-tilted line element (e.g., left-tilted). Three singleton conditions (target-color singleton, distractor-color singleton, or no-color sin- Method gleton) were presented with equal probability. Color singleton elements were red, while all other elements were white. For the cued condition, the word cue Participants (‘‘target,’’ ‘‘distractor,’’ or ‘‘nessun’’) validly indicated which of either the target or distractor would be red in Twenty-seven participants completed the experiment the subsequent matrix. For the uncued condition the in exchange for payment. All gave their informed word ‘‘pronto’’ (‘‘ready’’ in Italian) was presented. consent but were na¨ıve to specific experimental Feedback was provided by warning tones signaling hypotheses. Data from two participants were excluded anticipative (,80 ms) or late (.600 ms) saccades and from primary analyses due to high error rates (.30% by presenting average reaction times at the end of each for either experimental session; cf. error criteria below). block. Of the remaining 25 participants (mean age ¼ 23.92 Participants completed two approximately 1-hr years), 18 were female and all were right-handed with experimental sessions on different days. Each session normal or corrected-to-normal vision. consisted of one cuing condition (cued or uncued) made up of 24 practice trials followed by 456 analyzable trials separated into 12 blocks. Location of targets and Apparatus distractors, and singleton condition were counterbal- anced within participants and presented in a random The experiment was programmed using Matlab order within an experimental session. Target (and (version 7.11.1, The MathWorks, Inc., Natick, MA), complementary distractor) orientation (left vs. right)

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Figure 1. Trial sequence. Participants executed a speeded saccade to the uniquely oriented target line element, pictured here as tilting 458 to the right relative to vertical nontarget elements. Additionally, a uniquely oriented distractor line element was always presented (pictured here as tilting 458 to the left). The target, distractor, or neither element could be colored red on any trial, potentially creating a color singleton. In the cued condition, the word cue validly identified the upcoming color singleton as either the target, distractor, or neither element. In the uncued condition, the word ‘‘pronto’’ (‘‘ready’’ in Italian) was presented as a cue. Note that stimuli were not drawn to scale.

and experimental session order were counterbalanced was also randomized. Using the formula by Cowan across participants. (2001) a measure of working memory capacity, K, was derived for each of the three array sizes, where K ¼ set size · (hit rate þ false alarm rate), and then averaged Visual working memory capacity task together to give a single estimate of VWM capacity. At the beginning of the second session, participants also completed a brief color change detection task of 192 trials (preceded by 24 practice trials) to provide a Results measure of VWM capacity. Based on the same design as Luck and Vogel (1997), participants were briefly Saccade reaction time (RT) was measured as the time presented an array of four, six, or eight colored squares taken to initiate the first saccade greater than 38 (each 1.38 · 1.38) on a gray background for 100 ms. following presentation of the matrix. Saccades were After a 900-ms interval, a second array was presented defined when eye movement velocity exceeded 308/s or that could be either identical to the initial array or acceleration exceeded 80008/s2. The initial saccade was differed in the color of one square, with equal assigned to either the target or distractor if it landed probability. Participants made a key press to indicate within 48 of their respective positions. Trials were whether the two arrays differed or were the same. excluded if the first saccade was launched more than 38 Accuracy was stressed and the second display remained from central fixation (2.50% of trials), did not land at until a response was made. Square locations were either target or distractor locations (5.61%), was randomized within a 19.68 · 15.68 region and separated anticipative (,60 ms; 0.29%) or late (. 2.5 standard from each other by at least 4.08 center-to-center. deviations later than a participant’s mean saccadic Squares could randomly be one of seven possible colors latency; 2.53%). Combined, these criteria led to the with no more than two squares sharing a color. The overall exclusion of 10.07% of trials from the 25 location and new color of the square on change trials participants included in the primary analyses.

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The ANOVA for correct saccade RTs showed a significant main effect of cue condition, F(1, 24) ¼ 12.56, MSE ¼ 1138.89, p , 0.002, g2 ¼ 0.34, indicating that the presence of a cue resulted in faster RTs overall (M ¼ 224 ms vs. 243 ms). A significant main effect of singleton condition, F(2, 48) ¼ 91.08, MSE ¼ 145.83, p , 0.001, g2 ¼ 0.79, was revealed by Bonferroni- corrected comparisons to reflect faster RTs for singleton targets (M ¼ 215 ms), SE ¼ 2.37, p , 0.001, and slower RTs for singleton distractors (M ¼ 247 ms), SE ¼ 2.32, p , 0.02, relative to when both elements were white (M ¼ 239 ms). No significant interaction was found (F , 0.9).

Time-course analyses

To examine the impact of the cue on performance over time, saccadic accuracy was examined as a function of saccade latency. Participants’ distribution of saccadic responses (to both targets and distractors) was individually separated evenly into quintiles according to response latency. Mean proportion of Figure 2. (a) Mean proportion of saccades correctly directed to correct saccades and mean saccadic RT were then the target, and (b) mean saccade RTs for correct responses (ms); calculated within each quintile per participant. See presented for cued and uncued trials as a function singleton Figure 3 for mean proportion of correct saccades condition. Error bars reflect standard errors. (across participants) as a function of saccade latency bins for each cue · singleton condition. A three-way repeated measures ANOVA was conducted on mean Proportions and correct saccade reaction times proportion of correct saccades, using within-partici- pants factors of cue condition, singleton condition, Figure 2 presents the mean proportion of saccades and saccade RT bin. All main effects and two-way correctly directed to the target (saccades to targets interactions were significant ( ps , 0.02). Most divided by total saccades to targets and distractors) and importantly for the present analyses, a significant latency of correct saccades as a function of cue and three-way interaction was observed, F(4.41, 105.89) ¼ singleton conditions. Two two-way repeated measures 3.23, MSE ¼ 0.02, p , 0.02, g2 ¼ 0.12, prompting three ANOVAs were conducted using cue condition (cued vs. further two-way ANOVAs (cue condition · saccade uncued) and singleton condition (target-color vs. no- RT bin) to be conducted separately for each singleton color vs. distractor-color) as within-participants fac- condition. For the target-color singleton condition, significant main effects of cue condition, F(1, 24) ¼ tors. The ANOVA for proportion of correct saccades 2 revealed significant main effects of cue, F(1, 24) ¼ 76.55, 136.81, MSE ¼ 0.03, p , 0.001, g ¼ 0.85, and saccade MSE ¼ 0.01, p , 0.001, g2 ¼ 0.76, and singleton RT bin, F(2.32, 55.57) ¼ 18.74, MSE ¼ 0.03, p , 0.001, g2 ¼ 0.44, were qualified by an interaction, F(2.38, condition, F(1.30, 31.13) ¼ 45.08, MSE ¼ 0.03, p , 2 2 57.13) 5.63, MSE 0.03, p , 0.01, g 0.19. 0.001, g ¼ 0.65. These main effects were qualified by a ¼ ¼ ¼ Intriguingly, follow-up one-way ANOVAs showed significant interaction, F(2, 48) ¼ 50.01, MSE ¼ 0.01, p 2 significant main effects of saccade RT bin for both , 0.001, g 0.68, which planned paired-samples t tests 2 ¼ cued, F(4, 96) ¼ 6.43, MSE ¼ 0.01, p , 0.002, g ¼ 0.21, showed to be driven by an accuracy benefit in the cued and uncued target singleton conditions, F(2.05, 49.11) (vs. uncued) trials when the target (accuracy difference ¼ 13.64, MSE ¼ 0.06, p , 0.001, g2 ¼ 0.36. These of 0.2553), t(24) ¼ 11.65, SE ¼ 0.22, p , 0.001, d ¼ 3.01, results indicate that proportion of correct saccades or distractor (0.0806), t(24) ¼ 3.64, SE ¼ 0.22, p , decreased as saccade latency increased when target- 0.002, d ¼ 0.51, was a color singleton, but not in the no- color singletons were present, and that this seeming color singleton condition when both elements were deterioration of accuracy performance over time was white (t , 0.35). These results demonstrate that the cue reduced, but not eliminated, when following cues. For was utilized by participants and improved accuracy the no-color singleton condition, a significant main performance. effect of saccade RT bin was observed, F(4, 96) ¼

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Figure 3. Mean proportion of correct saccades and standard errors as a function of mean saccade RT latency bins. (a) Plotted separately for each singleton condition in uncued (upper panel) and cued (lower panel) trials. (b) The same data plotted separately for each cuing condition in target-color (upper panel), no-color (middle panel), and distractor-color (lower panel) singleton conditions.

12.50, MSE ¼ 0.01, p , 0.001, g2 ¼ 0.34, whereby influenced oculomotor selection from the earliest 20% accuracy performance increased as a function of of saccadic responses analyzed. saccade latency. There was no significant main effect of cue, nor a cue · saccadic RT interaction (remaining F values , 0.7). For the distractor-color singleton Correlations with visual working memory condition, significant main effects were observed of capacity cue, F(1, 24) ¼ 13.48, MSE ¼ 0.03, p , 0.002, g2 ¼ 0.36, and saccade RT bin, F(2.59, 62.04) ¼ 73.35, MSE ¼ To explore the role that individual differences might 0.04, p , 0.001, g2 ¼ 0.75, the latter reflecting play in the utilization of the cue to benefit performance, increased performance accuracy with later saccades. two-tailed correlational analyses were conducted on the No cue · saccadic RT interaction was observed (F , relationship between participants’ individual VWM 1.2), indicating a consistent benefit of cue on capacity estimates and the benefits conferred by the cue performance accuracy across the distribution of in terms of saccadic accuracy and RT for each of saccadic responses when the distractor was the color target-color and distractor-color singleton conditions. singleton. Estimates of VWM capacity (K) ranged from 1.63 to Planned contrasts using two paired-samples two- 4.38, with a mean of 3.10. tailed t tests showed increased performance accuracy For suitable comparison, a simple logistic regression for cued versus uncued trials in the earliest saccade RT was conducted to transform accuracy proportions into bin, both when target-color (M ¼ 0.9478 vs. 0.8370), log odds of a correct saccade for each participant. t(24) ¼ 4.28, SE ¼ 0.03, p , 0.001, d ¼ 1.24, and Figures 4a and 4b present these correlations. A positive distractor-color (M ¼ 0.2697 vs. 0.2086), t(24) ¼ 2.37, correlation was found between VWM capacity scores SE ¼ 0.03, p , 0.03, d ¼ 0.36, singletons were present in and cue impact on saccade accuracy (cued minus the search display. These contrasts indicate that cues uncued log odds) for singleton targets, r(25) ¼ 0.47, p ,

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Figure 4. Correlation across participants between accuracy benefit (cued – uncued log odds of proportion correct) and visual working memory capacity (K) for (a) target-color singletons, and (b) distractor-color singletons. Panel (c) presents a correlation between saccade RT benefit (uncued – cued RTs; ms) and visual working memory capacity (K), collapsed across both target-, and distractor-, color singletons.

0.02, indicating that those participants with higher intertrial priming effects was examined by making VWM capacity estimates tended to have greater comparisons between performances on trials where a improvements in saccadic accuracy from the cue when target-color singleton had repeated versus switched the target was a color singleton. A similar relationship from a distractor-color singleton in the previous trial. was absent for distractor-color singletons ( p . 0.05). The mean proportion and latency of correct saccades as Positive correlations were found between VWM a function of each cue · priming condition are capacity and cue impact on saccade RTs (uncued minus presented in Figures 5a and 5b, respectively. A two-way cued mean RT) for both singleton targets, r(25) ¼ 0.48, repeated-measures ANOVA using cue condition and p , 0.02, and singleton distractors, r(25) ¼ 0.50, p , priming condition (repeat vs. switch) on correct saccade 0.02, showing that participants with higher estimates of proportion yielded main effects of cue, F(1, 24) ¼ VWM capacity tended to receive greater RT benefits 132.81, MSE ¼ 0.01, p , 0.001, g2 ¼ 0.85, and priming, from the presence of the cue (see Figure 4c). F(1, 24) ¼ 30.73, MSE ¼ 0.04, p , 0.001, g2 ¼ 0.56. Comparing the size of these latter two correlation Importantly, the interaction did not approach signifi- coefficients using a method based on Meng, Rosenthal, cance (F , 1.0), indicating that the relative contribu- and Rubin (1992) did not reveal a significant difference tions to accuracy from the cue (0.2559) and intertrial (z ¼ 0.23, p . 0.05). The no-color singleton condition priming (0.0741) were additive. The same ANOVA on was not submitted to further analyses due to the null saccade RTs revealed a significant main effect of cue, results obtained in the time-course analyses. F(1, 24) ¼ 16.19, MSE ¼ 873.68, p , 0.001, g2 ¼ 0.40, indicating faster saccades were made to target single- tons when preceded by a valid cue (M ¼ 204 ms vs. 227 Intertrial priming analyses ms). There was no significant main effect of priming, nor a cue · priming condition interaction (remaining F The extent to which the cue impact on selection values , 1.9). Together, these results indicate that both speed and accuracy for target-color singletons reflected bottom-up intertrial priming and goal-directed cuing

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Figure 5. (a) Mean proportion of correct saccades, and (b) mean correct saccade RTs (ms) to target-color singletons; presented for repeat (trial n-1 ¼ target-color singleton) and switch (trial n-1 ¼ distractor-color singleton) trials as a function of cuing condition. Panel (c) presents mean proportion of correct saccades as a function of mean saccade RT latency bins. These were plotted separately for each cuing · priming (repeat vs. switch) condition. Error bars reflect standard errors.

effects significantly contribute to visual search perfor- priming effects did not interact with cue effects, and so mance (at least in terms of accuracy), but do so in an could not account for the observed dynamic effects additive, not interactive, manner. from the cue. To explore the time-course of intertrial priming effects, a three-way repeated-measures ANOVA was conducted on proportion of accurate saccades to target-color singletons (Figure 5c). Within-participants Discussion factors included cue condition, priming condition, and saccade RT bin. The three levels of the saccade RT bin Several important findings emerged from the results. factor consisted of separating participants’ saccadic A cue providing advanced knowledge about the color- response distribution for each cue · priming condition singleton status in a search display facilitated speed into tertiles according to response latency. A tertile, (across all conditions) and accuracy (for target and rather than quintile, split was necessary to maintain distractor-color singletons) of oculomotor selection. sufficient statistical power (M ¼ 15.22 trials per bin). The cue influenced dynamic oculomotor selection in Main effects of cue, priming condition, and RT bin, as three specific ways: (1) it increased accuracy perfor- well as a cue · RT bin interaction were all significant mance from the earliest 20% of saccadic responses; (2) ( ps , 0.01). A priming · RT bin interaction was also this accuracy benefit increased with later saccadic significant, F(2, 48) ¼ 3.70, MSE ¼ 0.01, p , 0.05, g2 ¼ responses to target-color singletons; (3) this increasing 0.13, suggesting that the effect of priming increased as benefit was sufficient to only reduce, and not eliminate, saccadic response latency increased. More important an overall decrease in accuracy performance as a was the lack of a significant three-way interaction function of response latency towards target-color between priming condition, cue and RT bin (remaining singletons. Overall cue impact on performance was F values , 1.1). These findings demonstrate that even correlated with individual VWM capacity scores, such over the time-course of saccadic responding, intertrial that higher VWM capacity scores were associated with

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increased cue benefits in terms of accuracy (for target- (2008) who similarly observed with singleton targets, color singletons) and response speed (for target and which were already the most salient element in the distractor singletons). Importantly, while intertrial display, that providing advanced knowledge of target priming effects on accuracy were observed when target features resulted in an additional attentional selection singleton status was repeated, these effects were benefit separable from intertrial priming. Here we minimal and did not interact with the overall or extend their findings to oculomotor selection, using dynamic effects from the cue. response measures and analyses that provide a more In line with previous findings (e.g., Mu¨ller et al., sensitive and dynamic picture than what could be 2003; Wolfe et al., 2004), cuing nonspatial information derived from mean manual-motor RTs. In this regard, about upcoming properties of a search display was our results showed that intertrial priming effects observed to enhance visual search performance. These increased as a function of response latency, suggesting endogenous cues provided an additional selection that such priming effects, if anything, might be less benefit by cuing the presence of a target-color automatic and bottom-up than previously argued (e.g., singleton, indicating that goal-directed processes guid- Theeuwes, 2013) and instead may be more strategic ed selection over and above a stimulus-driven bias (e.g., Wolfe et al., 2003). It could be that the target resulting from target salience. That cuing the upcoming representation takes time to develop following its presence of a to-be-ignored salient distractor-color presentation, so that little representation would have singleton also benefited target selection similarly developed at the earliest saccades where salience indicated a role for goal-directed processes in improv- information dominates, whereas greater modulation of ing selection of the less-salient target when competing target-relevant information by priming occurs with with a stimulus-driven bias towards selection of the later saccades, once a sufficient target representation salient distractor. The key result was observing that has built up. More research would, however, be cues influenced such selection from the earliest saccadic required to further substantiate this claim, particularly responses (M ¼ 167 ms, for earliest 20% of analyzed in light of recent research that suggests incidental trial saccades). This finding demonstrates that strategic use factors may result in an under estimation of distractor of cue information to select and reject salient singletons interference (thereby artificially reducing priming ef- can develop very early following display presentation, fects) in the fastest saccade bins (Leber, Lechak, & suggesting an immediate or early role for goal-directed Tower-Richardi, 2013). guidance in early oculomotor selection. While this The present results are inconsistent with those of finding contrasts with previous research claiming that Theeuwes and Van der Burg (2011), who did not rapid saccades are purely stimulus-driven (Godijn & observe an effect of cuing feature information on visual Theeuwes, 2002; Ludwig & Gilchrist, 2002; Mulck- selection separable from priming. Several methodo- huyse et al., 2008), it is consistent with recent logical differences may account for these discrepant observations that VWM content can modulate speed results. The current paradigm employed a cue that and accuracy of rapid saccades (, 200 ms) in the provided additional information about upcoming absence of competition (Hollingworth, Matsukura, & target and distractor features, whereas Theeuwes and Luck, 2013). Our findings align with theories that Van der Burg used cues that defined the target singleton implicate a role for goal-directed pre-attentive guidance itself, making it difficult to ascertain in their study on the basis of nonspatial information, that is, where whether cuing nonspatial information benefits selection certain features or dimensions can be actively priori- relative to a control baseline where no additional tized in advance, which can then be voluntarily used to information is provided. Other differences included our pre-attentively guide selection to features across the focus on overt (vs. covert) attentional selection and use visual field (Bundesen, 1998; Duncan & Humphreys, of a simple saccadic localization task rather than a 1989; Folk et al., 1992; Mu¨ller et al., 2003; Serences & compound manual discrimination task where target- Boynton, 2007; Treisman & Sato, 1990; Wolfe, 1994, defining features (color) were dissociated from those 2007). defining the discrimination response (orientation). Our findings rule out intertrial priming as an These differences mean that, while we can comment on alternative explanation and so build on existing how the cue influenced overt attentional selection, it is research observing early goal-directed impacts of more difficult to convincingly distinguish between nonspatial information (e.g., Treisman, 1988; van Zoest accounts regarding whether the cue enhanced percep- & Donk, 2008; Wolfe et al., 2003; Zhang & Luck, tual sensitivity (i.e., by enhancing perception of red 2009). With respect to priming, the present results favor elements a priori) or biased oculomotor responding an additive interpretation, whereby goal-directed and (i.e., by reducing uncertainty about whether to saccade passive priming processes appear to operate indepen- towards the salient red singleton element) in the current dently to influence initial oculomotor selection. Our task. While beyond the scope of our study, replicating results are consistent with those of Leonard and Egeth the present modulatory effects from cuing when

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measuring the N2pc ERP component preceding ocu- made prior to applied suppression are influenced by lomotor responses or when measuring initial saccadic saliency information (Godijn & Theeuwes, 2002, 2004; responses in a compound search task would provide McSorley, Haggard, & Walker, 2006; Theeuwes, evidence in support of a pre-attentive locus of cue Kramer, Hahn, & Irwin, 1998). Our results support the influence. former explanation by demonstrating that even when Advanced knowledge about the saliency and features observers had prior knowledge that the target would be of to-be-ignored distractors helped observers guide a color singleton, selection accuracy performance still selection away from the distractor and toward the declined (albeit less so) as a function of saccade latency. target. These results are consistent with the results of That such a transient selection benefit observed when work by Arita et al. (2012), who similarly found a target saliency was incidental (i.e., one-third of trials) performance benefit suggesting observers could use was only attenuated, and not eliminated, when target feature precues (they used the physical feature itself) to saliency was known in advance, indicates that such direct attention away from nontarget items during saliency information was less available to be used in a visual search. However, their task involved a more goal-driven manner to enhance later selection. The complex manual-motor discrimination task producing transient nature of saliency activity then appears to much longer response times (cue benefits were only have a role in the observed performance decline of observed with mean RTs . 900 ms), which cannot rule selecting salient targets over time. out initial selection of the to-be-ignored feature prior to Individual variation on the size of the cue impact on its rejection/suppression. A performance benefit was performance was predicted by individual VWM ca- observed in the present study from the earliest saccadic pacity scores. Participants with higher VWM capacity responses (, 200 ms), providing more convincing scores tended to receive a greater RT benefit from the evidence that an initial bias toward attending to to-be- cue for both target and distractor singletons, and a ignored features matching WM representations could greater accuracy benefit for target singletons. These be overridden without their first being selected. Our results indicate that the ability to strategically use cue results might be explained by the signal suppression information to improve efficiency and effectiveness of hypothesis as proposed by Sawaki and Luck (2010, oculomotor selection appears to be related to VWM 2011), which posits that attentional selection is the capacity. VWM capacity has been considered to reflect competitive outcome between an ‘‘attend-to-me’’ pri- ability to control which information accesses VWM oritization signal, which may be automatically gener- (e.g., Vogel et al., 2005), indicating that individuals ated by a to-be-ignored object’s stimulus-driven with higher VWM capacity should be better able to use saliency and/or top-down matching with WM content, attentional control to select task-relevant information and a goal-directed control signal aiming to suppress while filtering out task-irrelevant information. Because such activity. Cuing to-be-ignored features of the attentional control was required to derive a selection distractor in the current paradigm would have then benefit from the trial-by-trial cuing, the present results served to boost the top-down control signal thereby support the view that the greater cue benefit enjoyed by increasing the likelihood that saccades were directed individuals with higher VWM capacity was a result of away from the distractor. superior attentional control. The present findings add The present experiment effectively replicated previ- to a growing literature finding that individual differ- ous observations that saccades to the most salient ences in VWM capacity measures can predict individ- element in a search display, whether target or ual differences in performance on tasks requiring distractor, became less likely as latency increased attentional control (Luck & Vogel, 2013). (Donk & van Zoest, 2008; van Zoest & Donk, 2008). However, while we found a reliable correlation with Why a lower proportion of later saccades should be target selection and VWM capacity, we did not obtain made to a target when it is the most salient element in a a similar relationship with VWM capacity and dis- display is an intriguing question not easily explained by tractor inhibition. Previous research has implicated either a stimulus-driven or goal-directed process orienting (specifically, disengagement from to-be-ig- account. One explanation is that the drop in selection nored elements; Fukuda & Vogel, 2011) or executive accuracy is the consequence of a rapid passive decay of control (e.g., Hiebel & Zimmer, 2013; Sobel et al., 2007) early stimulus-driven activity (Cheal & Lyon, 1991; as the attentional mechanisms underlying VWM Donk & van Zoest, 2008; Nakayama & Mackeben, capacity. However, whereas with higher VWM capacity 1989; Nothdurft, 2002; Yantis & Jonides, 1990), such scores we observed both a greater speed and accuracy that the high target saliency is unable to influence later cue benefit for salient target singletons, orienting or selection. An alternative explanation is that observers executive control accounts would predict the greatest actively suppress salience activity (i.e., from color differences when cuing the to-be-ignored salient dis- singletons) to be more in line with task instructions tractor, where we observed only a greater benefit for (i.e., attend to orientation), such that only saccades speed. The increased speed benefit observed from all

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cues as a function of VWM capacity may instead Sciences, 16(8), 437–443, doi:10.1016/j.tics.2012.06. suggest that alerting mechanisms of attention were 010. differentially affected in the present task, whereby cues Belopolsky, A. V., Schreij, D., & Theeuwes, J. (2010). more greatly increased alertness for higher VWM What is top-down about contingent capture? capacity individuals. The present findings, however, Attention, Perception, & Psychophysics, 72(2), 326– cannot realistically specify which mechanisms of 341, doi:10.3758/APP.72.2.326. attentional control were indexed by VWM capacity in the current task and distinguishing between hypotheses Bleckley, M. K., Durso, F. T., Crutchfield, J. M., regarding the roles of alerting, orienting, and executive Engle, R. W., & Khanna, M. M. (2003). Individual attentional control mechanisms in VWM capacity differences in working memory capacity predict might be better achieved in future research by utilizing visual attention allocation. Psychonomic Bulletin & the Attentional Network Test (ANT; Fan, McCandliss, Review, 10(4), 884–889, doi:10.3758/Bf03196548. Sommer, Raz, & Posner, 2002). Bravo, M. J., & Nakayama, K. (1992). The role of Taken together, the current research demonstrates attention in different visual-search tasks. Perception that strategic use of cue information to select and reject & Psychophysics, 51(5), 465–472. salient singletons can develop very early following Bundesen, C. (1998). A computational theory of visual display presentation. The efficiency and effectiveness of attention. Philosophical Transactions of the Royal such strategic use is related to an individual’s visual Society B: Biological Sciences, 353(1373), 1271– working memory capacity and develops independently 1281, doi:10.1098/rstb.1998.0282. of bottom-up priming processes. This research indi- cates that stimulus-driven and goal-directed processes Bundesen, C., Habekost, T., & Kyllingsbaek, S. (2005). are not simply additive in oculomotor selection, but A neural theory of visual attention: Bridging instead exhibit a distinct and dynamic profile of cognition and neurophysiology. Psychological Re- interaction. view, 112(2), 291–328, doi:10.1037/0033-295x.112.2. 291. Keywords: eye movements, visual search, oculomotor selection, individual differences, visual working memory Carlisle, N. B., & Woodman, G. F. (2011). Automatic capacity and strategic effects in the guidance of attention by working memory representations. Acta Psycholog- ica (Amsterdam), 137(2), 217–225, doi:10.1016/j. actpsy.2010.06.012. Acknowledgments Cave, K. R., & Pashler, H. (1995). Visual selection mediated by location: Selecting successive visual Commercial relationships: none. objects. Perception & Psychophysics, 57(4), 421– Corresponding author: Matthew D. Weaver. 432. Email: [email protected]. Cheal, M. L., & Lyon, D. R. (1991). Central and Address: Center for Mind/Brain Sciences, University of peripheral precuing of forced-choice discrimina- Trento, Trento, Italy. tion. Quarterly Journal of Experimental Psychology Section A: Human Experimental Psychology, 43(4), 859–880. References Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental Adams, R. C., & Chambers, C. D. (2012). Mapping the capacity. Behavioral and Brain Sciences, 24(1), 87– timecourse of goal-directed attention to location 185, doi:10.1017/S0140525x01003922. and colour in human vision. Acta Psychologica Cowan, N., Elliott, E. M., Saults, J. S., Morey, C. C., (Amsterdam), 139(3), 515–523, doi:10.1016/j. Mattox, S., Hismjatullina, A., & Conway, A. R. A. actpsy.2012.01.014. (2005). On the capacity of attention: Its estimation Arita, J. T., Carlisle, N. B., & Woodman, G. F. (2012). and its role in working memory and cognitive Templates for rejection: Configuring attention to aptitudes. , 51(1), 42–100, doi: ignore task-irrelevant features. Journal of Experi- 10.1016/j.cogpsych.2004.12.001. mental Psychology: Human Perception and Perfor- Desimone, R., & Duncan, J. (1995). Neural mecha- mance, 38(3), 580–584, doi:10.1037/A0027885. nisms of selective visual-attention. Annual Review Awh, E., Belopolsky, A. V., & Theeuwes, J. (2012). of Neuroscience, 18, 193–222, doi:10.1146/annurev. Top-down versus bottom-up attentional control: A neuro.18.1.193. failed theoretical dichotomy. Trends in Cognitive Donk, M., & van Zoest, W. (2008). Effects of salience

Downloaded from jov.arvojournals.org on 09/27/2021 Journal of Vision (2014) 14(3):27, 1–15 Weaver, Paoletti, & van Zoest 13

are short-lived. Psychological Science, 19(7), 733– Training Group Adaptive Minds & Department of 739. doi:10.1111/j.1467-9280.2008.02149.x Psychology, Brain and Cognition. Saarbru¨cken, Duncan, J., & Humphreys, G. W. (1989). Visual search Germany: Saarland University. and stimulus similarity. Psychological Review, Hillstrom, A. P. (2000). Repetition effects in visual 96(3), 433–458. search. Perception & Psychophysics, 62(4), 800–817, Egeth, H. E., & Yantis, S. (1997). Visual attention: doi:10.3758/Bf03206924. Control, representation, and time course. Annual Hochstein, S., & Ahissar, M. (2002). View from the top: Review of Psychology, 48, 269–297, doi:10.1146/ Hierarchies and reverse hierarchies in the visual annurev.psych.48.1.269. system. Neuron, 36(5), 791–804, doi:10.1016/ Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & S0896-6273(02)01091-7. Posner, M. I. (2002). Testing the efficiency and Hollingworth, A., Matsukura, M., & Luck, S. J. (2013). independence of attentional networks. Journal of Visual working memory modulates rapid eye Cognitive Neuroscience, 14(3), 340–347, doi:10. movements to simple onset targets. Psychological 1162/089892902317361886. Science, 24(5), 790–796, doi:10.1177/ Folk, C. L., Remington, R. W., & Johnston, J. C. 0956797612459767. (1992). Involuntary covert orienting is contingent Itti, L., & Koch, C. (2000). A saliency-based search on attentional control settings. Journal of Experi- mechanism for overt and covert shifts of visual mental Psychology: Human Perception and Perfor- attention. Vision Research, 40(10-12), 1489–1506. mance, 18(4), 1030–1044. Kim, M. S., & Cave, K. R. (2001). Perceptual grouping Fukuda, K., Vogel, E., Mayr, U., & Awh, E. (2010). via spatial selection in a focused-attention task. Quantity, not quality: The relationship between Vision Research, 41(5), 611–624. fluid intelligence and working memory capacity. Psychonomic Bulletin & Review, 17(5), 673–679, doi: Lamy, D., Carmel, T., Egeth, H. E., & Leber, A. B. 10.3758/17.5.673. (2006). Effects of search mode and intertrial priming on singleton search. Perception & Psycho- Fukuda, K., & Vogel, E. K. (2011). Individual physics, 68(6), 919–932. differences in recovery time from attentional capture. Psychological Science, 22(3), 361–368, doi: Lamy, D., & Kristjansson, A. (2013). Is goal-directed 10.1177/0956797611398493. attentional guidance just intertrial priming? A review. Journal of Vision, 13(3):14, 1–19, http:// Godijn, R., & Theeuwes, J. (2002). Programming of www.journalofvision.org/content/13/3/14, doi:10. endogenous and exogenous saccades: Evidence for 1167/13.3.14. [PubMed] [Article] a competitive integration model. Journal of Exper- imental Psychology-Human Perception and Perfor- Lamy, D., & Yashar, A. (2008). Intertrial target-feature mance, 28(5), 1039–1054, doi:10.1037//0096-1523. changes do not lead to more distraction by 28.5.1039. singletons: Target uncertainty does. Vision Re- search, 48(10), 1274–1279, doi:10.1016/j.visres. Godijn, R., & Theeuwes, J. (2004). The relationship 2008.02.021. between inhibition of return and saccade trajectory deviations. Journal of Experimental Psychology: Leber, A. B., Lechak, J. R., & Tower-Richardi, S. M. Human Perception and Performance, 30(3), 538– (2013). What do fast response times tell us about 554, doi:10.1037/0096-1523.30.3.538. attentional control? Journal of Vision, 13(3):31, 1– 12, http://www.journalofvision.org/content/13/3/ Heitz, R. P., & Engle, R. W. (2007). Focusing the 31, doi:10.1167/13.3.31. [PubMed] [Article] spotlight: Individual differences in visual attention control. Journal of Experimental Psychology: Gen- Leonard, C. J., & Egeth, H. E. (2008). Attentional eral, 136(2), 217–240, doi:10.1037/0096-3445.136.2. guidance in singleton search: An examination of 217. top-down, bottom-up, and intertrial factors. Visual Hickey, C., van Zoest, W., & Theeuwes, J. (2010). The Cognition, 16(8), 1078–1091, doi:10.1080/ time course of exogenous and endogenous control 13506280701580698. of covert attention. Experimental brain research. Luck, S. J., & Vogel, E. K. (1997). The capacity of Experimentelle Hirnforschung. Experimentation visual working memory for features and conjunc- cerebrale, 201(4), 789–796, doi:10.1007/ tions. Nature, 390(6657), 279–281, doi:10.1038/ s00221-009-2094-9. 36846. Hiebel, N., & Zimmer, H. D. (2013). Individual Luck, S. J., & Vogel, E. K. (2013). Visual working differences in filtering efficiency and resistance to memory capacity: From psychophysics and neuro- attention capture. The International Research biology to individual differences. Trends in Cogni-

Downloaded from jov.arvojournals.org on 09/27/2021 Journal of Vision (2014) 14(3):27, 1–15 Weaver, Paoletti, & van Zoest 14

tive Sciences, 17(8), 391–400, doi:10.1016/j.tics. uncertainty does not lead to more distraction by 2013.06.006. singletons: Intertrial priming does. Perception & Ludwig, C. J. H., & Gilchrist, I. D. (2002). Stimulus- Psychophysics, 67(8), 1354–1361. driven and goal-driven control over visual selec- Poole, B. J., & Kane, M. J. (2009). Working-memory tion. Journal of Experimental Psychology: Human capacity predicts the executive control of visual Perception and Performance, 28(4), 902–912, doi:10. search among distractors: The influences of sus- 1037//0096-1523.28.4.902. tained and selective attention. Quarterly Journal of Maljkovic, V., & Nakayama, K. (1994). Priming of Experimental Psychology, 62(7), 1430–1454, doi:10. pop-out .1. Role of features. Memory & Cognition, 1080/17470210802479329. 22(6), 657–672, doi:10.3758/Bf03209251. Sawaki, R., & Luck, S. J. (2010). Capture versus McSorley, E., Haggard, P., & Walker, R. (2006). Time suppression of attention by salient singletons: course of oculomotor inhibition revealed by sac- Electrophysiological evidence for an automatic attend-to-me signal. Attention Perception & Psy- cade trajectory modulation. Journal of Neurophys- chophysics, 72(6), 1455–1470, doi:10.3758/App.72. iology, 96(3), 1420–1424, doi:10.1152/jn.00315. 6.1455. 2006. Sawaki, R., & Luck, S. J. (2011). Active suppression of Meng, X. L., Rosenthal, R., & Rubin, D. B. (1992). distractors that match the contents of visual Comparing correlated correlation-coefficients. working memory. Visual Cognition, 19(7), 956–972, Psychological Bulletin, 111(1), 172–175, doi:10. doi:10.1080/13506285.2011.603709. 1037/0033-2909.111.1.172. Serences, J. T., & Boynton, G. M. (2007). Feature- Moher, J., & Egeth, H. E. (2012). The ignoring based attentional modulations in the absence of paradox: Cueing distractor features leads first to direct visual stimulation. Neuron, 55(2), 301–312, selection, then to inhibition of to-be-ignored items. doi:10.1016/j.neuron.2007.06.015. Attention Perception & Psychophysics, 74(8), 1590– 1605, doi:10.3758/s13414-012-0358-0. Sobel, K. V., Gerrie, M. P., Poole, B. J., & Kane, M. J. (2007). Individual differences in working memory Mulckhuyse, M., van Zoest, W., & Theeuwes, J. (2008). capacity and visual search: The roles of top-down Capture of the eyes by relevant and irrelevant and bottom-up processing. Psychonomic Bulletin & onsets. Experimental brain research. Experimentelle Review, 14(5), 840–845, doi:10.3758/Bf03194109. Hirnforschung. Experimentation cerebrale, 186(2), 225–235, doi:10.1007/s00221-007-1226-3. Soto, D., Heinke, D., Humphreys, G. W., & Blanco, M. J. (2005). Early, involuntary top-down guidance Mu¨ller, H. J., & Krummenacher, J. (2006). Locus of of attention from working memory. Journal of dimension weighting: Preattentive or postselective? Experimental Psychology: Human Perception and Visual Cognition, 14(4-8), 490–513, doi:10.1080/ Performance, 31(2), 248–261, doi:10.1037/ 13506280500194154. 0096-1523.31.2.248. Mu¨ller, H. J., Reimann, B., & Krummenacher, J. Soto, D., Humphreys, G. W., & Heinke, D. (2006). (2003). Visual search for singleton feature targets Working memory can guide pop-out search. Vision across dimensions: Stimulus- and expectancy-driv- Res, 46(6-7), 1010–1018, doi:10.1016/j.visres.2005. en effects in dimensional weighting. Journal of 09.008. Experimental Psychology: Human Perception and Theeuwes, J. (2013). Feature-based attention: It is all Performance, 29(5), 1021–1035, doi:10.1037/ bottom-up priming. Philosophical Transactions of 0096-1523.29.5.1021. the Royal Society B: Biological Sciences, 368(1628), Munneke, J., Van der Stigchel, S., & Theeuwes, J. 20130055, doi:10.1098/rstb.2013.0055. (2008). Cueing the location of a distractor: An Theeuwes, J., & Burger, R. (1998). Attentional control inhibitory mechanism of spatial attention? Acta during visual search: The effect of irrelevant Psychologica (Amst), 129(1), 101–107, doi:10.1016/ singletons. Journal of Experimental Psychology: j.actpsy.2008.05.004. Human Perception and Performance, 24(5), 1342– Nakayama, K., & Mackeben, M. (1989). Sustained and 1353, doi:10.1037//0096-1523.24.5.1342. transient components of focal visual attention. Theeuwes, J., Kramer, A. F., Hahn, S., & Irwin, D. E. Vision Research, 29(11), 1631–1647. (1998). Our eyes do not always go where we want Nothdurft, H. C. (2002). Attention shifts to salient them to go: Capture of the eyes by new objects. targets. Vision Research, 42(10), 1287–1306, doi:10. Psychological Science, 9(5), 379–385, doi:10.1111/ 1016/S0042-6989(02)00016-0. 1467-9280.00071. Pinto, Y., Olivers, C. N., & Theeuwes, J. (2005). Target Theeuwes, J., Reimann, B., & Mortier, K. (2006).

Downloaded from jov.arvojournals.org on 09/27/2021 Journal of Vision (2014) 14(3):27, 1–15 Weaver, Paoletti, & van Zoest 15

Visual search for featural singletons: No top-down differences in controlling access to working mem- modulation, only bottom-up priming. Visual Cog- ory. Nature, 438(7067), 500–503, doi:10.1038/ nition, 14(4-8), 466–489, doi:10.1080/ nature04171. 13506280500195110. Wolfe, J. M. (1994). Guided search 2.0 a revised model Theeuwes, J., & Van der Burg, E. (2007). The role of of visual search. Psychonomic Bulletin & Review, spatial and nonspatial information in visual selec- 1(2), 202–238, doi:10.3758/BF03200774. tion. Journal of Experimental Psychology: Human Wolfe, J. M. (2007). Guided search 4.0: Current Perception and Performance, 33(6), 1335–1351, doi: progress with a model of visual search. In W. Gray 10.1037/0096-1523.33.6.1335. (Ed.), Integrated models of cognitive systems (pp. Theeuwes, J., & Van der Burg, E. (2011). On the limits 99–119). New York: Oxford. of top-down control of visual selection. Attention Perception & Psychophysics, 73(7), 2092–2103, doi: Wolfe, J. M., Butcher, S. J., Lee, C., & Hyle, M. (2003). 10.3758/s13414-011-0176-9. Changing your mind: On the contributions of top- down and bottom-up guidance in visual search for Treisman, A. (1988). Features and objects: The feature singletons. Journal of Experimental Psy- fourteenth Bartlett memorial lecture. Quarterly chology: Human Perception and Performance, 29(2), Journal of Experimental Psychology A, 40(2), 201– 483–502. 237. Wolfe, J. M., Horowitz, T. S., Kenner, N., Hyle, M., & Treisman, A., & Sato, S. (1990). Conjunction search revisited. Journal of Experimental Psychology: Vasan, N. (2004). How fast can you change your Human Perception and Performance, 16(3), 459– mind? The speed of top-down guidance in visual 478. search. Vision Research, 44(12), 1411–1426, doi:10. 1016/j.visres.2003.11.024. Tsal, Y., & Lavie, N. (1988). Attending to color and shape: The special role of location in selective visual Woodman, G. F., & Luck, S. J. (2007). Do the contents processing. Perception & Psychophysics, 44(1), 15– of visual working memory automatically influence 21. attentional selection during visual search? Journal of Experimental Psychology: Human Perception and van Zoest, W., & Donk, M. (2005). The effects of Performance, 33(2), 363–377, doi:10.1037/ salience on saccadic target selection. Visual Cogni- tion, 12(2), 353–375, doi:10.1080/ 0096-1523.33.2.363. 13506280444000229. Woodman, G. F., Luck, S. J., & Schall, J. D. (2007). van Zoest, W., & Donk, M. (2008). Goal-driven The role of working memory representations in the modulation as a function of time in saccadic target control of attention. Cerebral Cortex, 17 Suppl, 1, selection. Quarterly Journal of Experimental Psy- i118–124, doi:10.1093/cercor/bhm065. chology, 61(10), 1553–1572, doi:10.1080/ Yantis, S., & Jonides, J. (1990). Abrupt visual onsets 17470210701595555. and selective attention - voluntary versus automatic van Zoest, W., Donk, M., & Theeuwes, J. (2004). The allocation. Journal of Experimental Psychology: role of stimulus-driven and goal-driven control in Human Perception and Performance, 16(1), 121– saccadic visual selection. Journal of Experimental 134, doi:10.1037//0096-1523.16.1.121. Psychology: Human Perception and Performance, Zhang, W., & Luck, S. J. (2009). Feature-based 30(4), 746–759. attention modulates feedforward visual processing. Vogel, E. K., McCollough, A. W., & Machizawa, M. Nature Neuroscience, 12(1), 24–25, doi:10.1038/nn. G. (2005). Neural measures reveal individual 2223.

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