The target effect: visual memory for unnamed search targets.

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The target effect: Visual memory for unnamed search targets a

a

Mark D. Thomas & Carrick C. Williams a

Psychology, Mississippi State University, Mississippi State, MS, USA Accepted author version posted online: 01 Apr 2014.Published online: 16 Apr 2014.

Click for updates To cite this article: Mark D. Thomas & Carrick C. Williams (2014) The target effect: Visual memory for unnamed search targets, The Quarterly Journal of Experimental Psychology, 67:11, 2090-2104, DOI: 10.1080/17470218.2014.905611 To link to this article: http://dx.doi.org/10.1080/17470218.2014.905611

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THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2014 Vol. 67, No. 11, 2090–2104, http://dx.doi.org/10.1080/17470218.2014.905611

The target effect: Visual memory for unnamed search targets Mark D. Thomas and Carrick C. Williams

Downloaded by [Michigan State University] at 10:57 06 March 2015

Psychology, Mississippi State University, Mississippi State, MS, USA

Search targets are typically remembered much better than other objects even when they are viewed for less time. However, targets have two advantages that other objects in search displays do not have: They are identified categorically before the search, and finding them represents the goal of the search task. The current research investigated the contributions of both of these types of information to the long-term visual memory representations of search targets. Participants completed either a predefined search or a unique-object search in which targets were not defined with specific categorical labels before searching. Subsequent memory results indicated that search target memory was better than distractor memory even following ambiguously defined searches and when the distractors were viewed significantly longer. Superior target memory appears to result from a qualitatively different representation from those of distractor objects, indicating that decision processes influence visual memory. Keywords: Visual search; Visual memory; Target memory; Eye movements.

When searching for a known target (e.g., my blue coffee cup), the searcher knows several things about the target that could aid search before ever beginning the search. In the case of the cup, colour and shape can be inferred from the label “blue coffee cup”, but there also might be visual memories of the cup from previous searches that could be used to search more efficiently than using the semantic label alone. Although general semantic knowledge and expectations about coffee cups, such as that they normally rest on top of something, can help guide search (Torralba, Oliva, Castelhano, & Henderson, 2006; Võ & Wolfe, 2012, 2013), more precise target information typically produces more efficient searches than less precise target information (Vickery, King, & Jiang, 2005; L. G. Williams, 1967). Schmidt and Zelinsky (2009) investigated how

various levels of knowledge about search targets influenced selection and found that knowing the visual details of search targets (e.g., the precise object category or colour) benefited search more than only knowing abstract target categories. Knowledge of target identities is not only advantageous for search, but may also provide a longterm visual memory advantage for search targets. Konkle, Brady, Alvarez, and Oliva (2010) have claimed that one reason visual memory tends to be incredibly accurate, even after the presentation of thousands of pictures (e.g., Standing, 1973; Standing, Conezio, & Haber, 1970), is that semantic category information supports visual memory. In a series of studies, Williams and colleagues (C. C. Williams, 2010a, 2010b; C. C. Williams, Henderson, & Zacks, 2005; C. C. Williams, Zacks, & Henderson, 2009) examined visual

Correspondence should be addressed to Mark D. Thomas, Department of Psychology, University of Wisconsin–Whitewater, Whitewater, WI 53190, USA. E-mail: [email protected] Mark D. Thomas is now at the University of Wisconsin–Whitewater.

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memory for over 350 unique objects encountered during visual search. Participants searched for an identified target (e.g., yellow bird) in search displays of 12 photographs of real-world objects with distractors that could be related to the search target’s colour or category (e.g., yellow objects that were not birds and birds that were not yellow) or be unrelated to the search target (e.g., objects that were neither birds nor yellow). In each of these studies, identified search targets were remembered better than related distractors, which in turn were remembered better than unrelated distractors. Interestingly, the memory advantage for target objects was found even for a subset of targets that was fixated for less time than the distractors (also see C. C. Williams, 2010b) or when the viewing of the targets and distractors was equated (C. C. Williams, 2010a). Because the objects were fully counterbalanced, the superior memory for objects when they were the targets of visual search could not be attributed to any unique physical characteristics of the objects. Why then, even when viewing differences were accounted for, were the target objects remembered best? Although previous research (C. C. Williams, 2010a, 2010b) has addressed some possible explanations for superior memory, such as the use of a counting task and that most targets were viewed more than the distractors in C. C. Williams et al. (2005), targets continued to be remembered better than distractors. Because viewing factors do not account for the fact that targets and distractors are remembered differently, there may be visual memory representational differences for objects that result from the role the object plays during the search. Previously, Konkle et al. (2010) found that category similarity was more important than visual similarity in producing retroactive interference in visual memories, leading them to claim that visual memories were categorically organized. Extending this concept to a search paradigm, providing target category labels before searching could be critical to a target memory advantage because targets would benefit from categorical organization resulting from the activation of the appropriate semantic category information prior to seeing the object whereas the distractor objects would not.

In our previous studies, when we found a target memory advantage, the search target label was provided prior to search. However, in one experiment (C. C. Williams, 2010a, Experiment 4) the search target label was presented after the search items were presented (e.g., How many yellow birds were there?), and target memory was equivalent to the memory for the distractors. Thus, it is possible that the target memory advantage is simply a case of extra information provided for one type of object compared to other objects in the field when the object is viewed. Although it is possible that the search label could fully account for the target memory advantage, there is another difference between the target object(s) and the distractor objects in a search: Finding the target object is the goal of the search. When searching for a target, a searcher encounters many objects for which he or she is not searching. However, upon encountering the target object, the searcher could have the thought “There is what I am looking for!”. The finding of the target represents a distinct episode in the search and thus could be encoded into a more durable or precise representation than the distractors that were seen prior to or following the target. (C. C. Williams, 2010a, demonstrated through controlled presentation of the search objects that the target being the final object viewed in the display was not necessary for producing a target memory advantage.) In most searches, knowing the search label prior to the search and the distinct episode of finding the search target are confounded—one knows one has found the target because it matches the search target label. However, there is a class of searches that we refer to as undefined searches that do not provide a precise search target label prior to searching but still have the moment of discovery that the target has been found. For example, baggage screeners search for weapons and contraband without knowing precise descriptions, and factory quality control inspectors routinely search for errors in products that may not be clearly predefined. Even though well-defined searches are more efficient than less precisely defined searches (e.g., Schmidt & Zelinsky, 2009), it is not known

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whether finding an undefined target leads to a target memory advantage in the same manner as finding a defined target. In other words, will finding undefined targets produce the same more durable episodic traces as those described by C. C. Williams (2010b), or is the memory advantage only the result of knowing target category label identities when targets are viewed? The current study used two types of visual search tasks to explore the factors that contribute to the long-term visual memory representations of search targets. Participants either searched for targets that were not defined by categorical semantic labels or searched for targets that were defined by categorical semantic labels prior to search. In order to guide search without using category labels, we used a unique object search task (UO) in which participants searched for an object that did not have an exact match (see Figures 1 and 2). If

the episode of identifying the target (the “there it is!” moment) is critical to the target memory advantage, valid undefined search targets should be better remembered than the same objects when they are not targets. In addition, undefined targets should be better remembered than distractors that are also not defined because finding an undefined target would constitute a distinct episode in the search, which would give them an advantage over the distractors. For comparison, a separate group of participants performed a complex conjunction search through the same search displays, and they were provided with target labels that included target colour and category (predefined target search, PT) before performing each search. If predefined targets are better remembered than undefined targets, the memory difference can be attributed to having the category labels before searching.

Figure 1. An example of a one-target search array. The target was the yellow bird in the lower left-hand corner. The category distractors were white birds and green birds. The colour distractors were the yellow hat, yellow pitcher, and yellow leaf. The unrelated distractors were the blue iron and brown fish. All images were full colour with a neutral grey (RGB = 120) background. To view this figure in colour, please visit the online version of this Journal.

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Figure 2. An example of a two-target search array. The two-target arrays were constructed by replacing one of the unrelated triplet distractors from the one-target array with a second exemplar of the target object. In this case, the green pipe at the bottom-center of the search array was replaced with the yellow bird target exemplar. To view this figure in colour, please visit the online version of this Journal.

EXPERIMENTAL STUDY Method Participants Seventy-two Mississippi State University undergraduate students participated for partial course credit. All reported normal, or corrected-tonormal, visual acuity and were naïve to the purpose of the experiment. One participant reported abnormal colour vision, but inclusion of his data did not affect the results, and, thus, his data were retained. Design and materials The experiment had two main phases: a search phase and memory test phase. Within the search phase, two between-participant searches were completed that differed only in the instructions to participants. One group of participants (N = 24) searched for a predefined target (PT) in a

complex conjunction search, and the other group of participants (N = 48) searched for a unique object (UO). Specifically, PT search participants determined whether one or two predefined targets (e.g., yellow bird) were present in the search display, whereas UO search participants were not provided with target labels, but rather they were asked to determine whether all objects in a search display had at least one identical match. The number of targets present in the search array was manipulated within participants (half having one target) and was counterbalanced across participants. Critically, even though the instructions were different between the two search types, the search stimuli were identical. Examples of the search stimuli for the one and two target conditions can be found in Figures 1 and 2. Because we were interested in the longterm memory of the objects in the search, each object’s role in the search display had to be


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consistent throughout the search portion of the experiment. In other words, if a particular object was a target for a participant, it had to be a target every time that participant saw it during the search portion of the experiment. To maintain this consistency within the search, we used the search category structure and objects from C. C. Williams et al. (2005) with a few category substitutions to eliminate categories that could be defined by object parts (e.g., knife handles). Each participant searched 32 different displays with each display containing 21 objects that subtended 2.37° of visual angle along the longer dimension (horizontal or vertical). Within each search array, object roles were defined with relation to the PT search target’s colour category. In the one-target search arrays (UO present; Figure 1), 1 target (e.g., yellow bird), 6 category distractors (3 matching pairs; e.g., white birds), 6 colour distractors (3 matching pairs; e.g., yellow leaves), and 8 unrelated distractors (1 matching pair and 2 sets of matching triplets; e.g., blue irons) were present. The twotarget search displays (UO absent condition; Figure 2) were created by replacing one of the unrelated triplet objects with a duplicate of the UO target (a second instance of the PT target yellow bird). The remainder of the display was unchanged. By using two sets of unrelated triplets in the single target/UO present condition, and a single unrelated triplet in the two target/UO absent condition, the presence of a triplet would not signal target presence or absence. Objects were presented on a neutral grey background (RGB = 120), and each search array appeared in one of eight possible spatial configurations. Objects were not presented in the centre of the search arrays. For both search tasks, the stimuli were presented in two blocks of 32 search trials, each with half of the displays containing one search target (UO present condition) and the other half containing two search targets (UO absent condition). Each search array was presented in both search blocks. Each of the 32 trials used a different target, and the number of targets present in a search display was the same for both presentations of the search array. The memory test phase immediately followed the completion of the search phase. The

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unannounced memory test used a two-alternative forced-choice token discrimination task and was identical for both search conditions. Participants were tested on one target and one of each distractor type (colour, category, and unrelated) from each search display for a total of 128 tested objects. Foil objects were novel object tokens matching the colour and category of the presented objects counterbalanced across participants. Apparatus Search arrays were displayed at a resolution of 800 × 600 pixels and 16-bit colour and subtended 35.43° × 26.47° at a 75-cm viewing distance. All responses were input via a button box, and EPrime software (Schneider, Eschman, & Zuccolotto, 2002) controlled stimuli presentation. Right eye position was recorded using an ISCAN ETL-400 eye tracker sampling at 240 Hz during UO searches. Eye movements were not recorded for PT searches. Procedure For the PT search condition, participants completed an informed consent form and a demographic questionnaire, and then they were seated at a computer station. Prior to beginning the experimental trials, PT search participants were instructed to indicate whether there were one or two predefined targets in the search arrays by pressing the appropriately labelled button on a button box. Each PT trial consisted of a screen identifying the target object label (e.g., “yellow bird”) that was presented until the participant pressed a button indicating that he or she knew the search target. Immediately following that button press, the search array was presented until the participant pressed the button indicating the number of targets in the display, terminating the search display and initiating the presentation of the next search target label. This sequence repeated until all 64 search trails were completed. Two practice trials using novel stimuli were shown to participants prior to the experimental trials. Feedback was provided for the practice trials only. For the UO participants, after consenting, they completed a demographic questionnaire and were




seated at a computer station. Because eye movements were monitored during UO searches, those participants also used a chin rest to minimize head movements. Search instructions were presented on the monitor at the beginning of each trial block. Participants were asked to determine whether each object in a search array had an exact match. Participants were not told target identities or the number of targets that would be presented. A button box was used for all participant responses with the left button labelled “NO”, indicating that there was a unique object in the display, and the right button labelled “YES”, indicating that all objects had a match. As with the PT searches, two practice trials with feedback were provided before beginning the experimental trials, and no other feedback was provided. In order to use the eye tracker, a calibration sequence was performed after the instruction screen. A 9-point calibration sequence covering the entire screen area was used. Following calibration, the experimental trials began. A UO trial began with a fixation cross screen (replacing the target label screen in the PT search task), followed by a search array. UO searches were paced by the researcher in that once the researcher verified that the participant was looking at the fixation cross, the researcher initiated search array presentation. When the participant input a response, it initiated the presentation of the next fixation cross. This sequence was repeated until all 64 UO search trials had been presented. Eye tracker recalibration was performed when judged necessary. For both PT and UO conditions, an unannounced two-alternative forced-choice memory test was administered immediately after completing the search portion of the experiment. Two objects with identical semantic labels were presented for each memory trial (e.g., two yellow birds). One object had been presented during search array presentation, and the foil object was a nonpresented novel token with the same semantic label. Participants were asked to select the object that had been presented during searches by pressing the button on the button box that corresponded with the test object locations (left or right). Participants were encouraged to guess if they were

uncertain. The same memory test was used for both searches, and no eye tracking occurred during memory testing.

Results Overall, the results indicate that both target labels and the episode of the target being found contribute separately to the target memory advantage. Importantly, we found that even in the absence of a target label and when fixated for less time, a valid UO target had a target memory advantage over distractors. This finding indicates that the episode of finding a target is important to producing superior target memory. Although the target memory advantage for UO targets is reliable, it does not equal the memory performance of PT targets, indicating that having the target label prior to searching provides another slight memory advantage for targets. Overall, these results show that the target memory advantage is not the result of a single organizing strategy or specific episode in memory, but rather the combination of visual and nonvisual factors, and may provide insight into the structure of visual memories. Excluded participants Seven UO search participants did not meet a minimum search accuracy of 75% for inclusion; no PT search participants failed to meet the criterion. Three additional UO search participants were excluded due to failing to maintain sufficient eye tracker calibration. The reported analyses are for 24 PT and 38 UO search participants. Search accuracy and response times Consistent with previous findings that more precise target information leads to more efficient searches than less precise target information (e.g., Schmidt & Zelinsky, 2009), PT searches were more accurate than UO searches, F(1, 60) = 21.35, p , .001, η2p = .26 (see Table 1 for search accuracies and response times). In addition, two-target searches were more accurate than one-target searches, F(1, 60) = 40.35, p , .001, η2p = .40, and there was an interaction between the number of targets and the search condition, F(1, 60) = 13.50, p = .001,


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Table 1. Mean search accuracies and response times Search accuracies (% Correct)

Reaction times (in ms)

Condition

1 Target

2 Targets

1 Target

2 Targets

PT search UO search

92.6 (1.9) 80.3 (1.5)

96.2 (1.3) 93.9 (1.0)

4827 (556) 11,034 (442)

3485 (662) 15,069 (532)


Note. PT search refers to the predefined target search. UO search refers to the unique object search. The numbers in parentheses are standard errors. Although the “target” object during the two-target UO search was the same exemplar as the valid UO search target, it was not a valid target during two-target UO searches because it had an exact match.

η2p = .19; search accuracy was worse when a valid UO target was present than in other conditions. With respect to search response times, participants responded more quickly for second presentations of a search array than for first presentations, F (1, 60) = 38.78, η2p = .39, p , .001. In addition, there was a main effect for number of targets, F (1, 60) = 40.43, η2p = .40, p , .001, and PT searches were faster than UO searches, F(1, 60) = 138.73, p , .001, η2p = .70 (see Figure 3). Importantly, there was an interaction between the number of targets and search type, F(1, 60) =

154.64, p , .001, η2p = .72, such that two-target PT searches were faster than one-target PT searches, but one-target UO present searches were faster than two-target UO absent searches. Presumably, finding the unique object terminated UO searches because the one-target UO searches (M = 11,034 ms, SE = 531) were faster than paired UO searches (15,069 ms, SE = 453). Conversely, because PT search participants were informed that one or two targets would always be present, finding the second target terminated PT searches, leading to faster two-target PT searches

Figure 3. Mean search response times. PT search is the predefined target search, and UO search is the unique object search. Error bars represent the standard error.

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(M = 3360 ms, SE = 571) than one-target searches (M = 4952 ms, SE = 668).

Eye movement analyses Due to the structure of the UO search, we expected that distractors would be fixated more than valid UO targets. Thus, if valid UO targets were better remembered than distractors, that memory difference could not be due to quantitative viewing behaviours alone. We collected three eye movement measures—total fixation time, total fixation count, and number of separate viewings—to determine whether valid UO targets were viewed more than the same objects when they were paired (not valid search targets). The target object was present in both trials for all conditions, but it was not a valid target in the paired condition. Reported eye movement data are only for the objects that were tested for memory and are conditionalized on search accuracy. To be included, responses to a search display had to be correct for both presentations.

Because object memory is probably the result of the accumulation of the fixations on the object and the presentation of the stimuli (C. C. Williams, 2010b), we combined the viewing measures for identical exemplars both within a trial (i.e., for paired objects) and across presentations (i.e., first and second presentations). For example, total time was calculated by summing viewing time for an object across both exemplars in each search array and across both array presentations for that object. Similarly, fixation counts were pooled as well as the separate views, and means were calculated for each object type, but there were no significant differences (ps . .2) in these latter measures, and they are not discussed further. Target object viewing behaviours were of particular interest because different viewing behaviours could indicate quantitative differences in object processing. Analyses of variance (ANOVAs) were calculated to examine the differences in total fixation times for object types. There was a main effect for total time on the number of target

Figure 4. Unique object (UO) mean total fixation times for memory test objects from search arrays. The fixation times are pooled across exemplars in the array and across array presentations. Although the “target” object during the two-target UO search was the same exemplar as the valid UO search target, it was not a valid target during UO absent searches because it had an exact match. Error bars represent the standard error. THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2014, 67 (11)

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objects, F(1, 37) = 54.82, η2p = .60, p , .001, and there was a main effect for object type, F(3, 111) = 12.08, η2p = .25, p , .001. There was an interaction for total time between the number of targets and object type, F(3, 111) = 2.83, η2p = .07, p = .041 (Figure 4). Paired-sample ttests were used to examine the differences between total viewing times for object types by search condition. There was no difference between valid target viewing times and category or colour distractor viewing times in the UO present condition, ps . .20. All object types in the UO absent searches were viewed longer than their respective counterparts in the UO present searches, all ts(37) . 3.8, ps ≤ .001. Most importantly for the current project was the analysis of fixation time on the valid UO targets compared to the other objects in the display. Valid UO targets were fixated for less total fixation time than the same objects in the two-target (UO absent) condition, t(37) = −3.81, p = .001. In addition, valid UO targets were also fixated for less time than the category distractors, t(37) = −3.33, p = .002, and colour distractors, t(37) = −4.48, p , .001, from the two-target– UO absent condition. Thus, if a target memory advantage is found for valid UO targets, the advantage cannot be attributed to additional fixation time during the search phase.

Visual memory Because correctly identifying search targets is critical to examining visual memory for targets, all memory analyses were conditionalized on accurate search responses to both search presentations. Eight percent of the one-target PT searches, 4% of the two-target PT searches, 20% of the UO present searches, and 6% of the UO absent searches were eliminated from the memory analyses due to inaccurate search responses.

We first examined PT searches to determine whether there was a target memory advantage because it used standard search instructions with these materials.1 As can be seen in Figure 5, PT targets were remembered much better than the distractor objects in the PT searches [one-target, all ts (23) . 8.47, all ps , .001; two-target, all ts(23) . 11.83, all ps , .001]. Thus, even though the procedure and search arrays were different than those of C. C. Williams et al. (2005, 2009), the target memory advantage was present in the PT searches. Given that the search displays used in the present research produced a target memory advantage when a standard predefined search paradigm was used, we then examined the memory results for the UO searches to determine whether the act of finding a target could also produce a target memory advantage. There are two critical comparisons. The first key comparison is between valid UO targets and distractors from the same trials. Valid UO targets were remembered better than all types of distractors from one-target/valid UO searches, all ts(37) . 3.30, all ps ≤ .002, demonstrating a target memory advantage without a colour-category label being provided prior to searching. The second key, and probably more compelling, comparison is between valid UO targets and the same objects in the UO absent condition (one yellow bird vs. two yellow birds in Figures 1 and 2). The only difference between these conditions is the fact that in the UO absent condition, there was a second instance of the “target” object in the search display. Thus, there was more visual information presented in the search display containing the “target” object in the UO absent condition than in the UO present condition. Although valid UO targets were fixated for approximately 300 ms less time, paired-samples tests indicated that they were remembered about 6% better than the “target” objects in the UO absent condition, t(37) = 2.38, p = .02. To extend this result,

1 Although our primary concern was target memory, we also examined distractor memory differences between PT and UO searches. For all distractor types, memory for the UO distractors exceeded that of the PT distractors [all Fs(1, 60) ≥ 4.13, .065 ≤ η2p ≤ .099, ps ≤ .042]. The distractor memory differences between the two conditions can probably be attributed to search time differences. Overall, UO searches averaged more than twice as long as PT searches. The greater search time probably allowed for more fixation time on the UO distractor objects improving distractor memory accuracy (see Williams, 2010b, for discussion of predictions of memory given additional distractor viewing).

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Figure 5. Memory test accuracy for object types by search condition. PT = predefined target; UO = unique object. Error bars represent the standard error.

memory for valid UO targets was compared to that for all distractor types in the UO absent condition. The relationship between memory and total viewing time for UO search objects is illustrated in Figure 6. Once again, valid UO targets were remembered better than the UO distractors, all ts (37) . 1.93, all ps ≤ .048. The target memory advantage for valid UO targets demonstrates that even in the absence of specific categorical information about targets, the act of finding the search target leads to better memory. If that is the case, then the opposite should also hold: If an object is not identified as a target, it would not be remembered better than the distractors in the search array. In essence, the object is simply another distractor. C. C. Williams (2010b) found this pattern when memorization encoding instructions were used rather than search encoding like that in the current experiment. Within the context of the current project, we have two instances where we would expect to find that the objects that could have been targets were treated as distractors. The first place is the “target” objects in the UO absent searches. These objects were not valid targets and thus were just another object to reject during UO

searches. As expected, memory performance for all object types in the UO absent condition was equivalent (all pairwise ps . .35), supporting the notion that all objects were evaluated equally. The second place in our data where one could look for this pattern of no difference is instances where participants failed to correctly identify the valid UO target. As previously noted, 20% of the UO present trials were excluded from analyses because participants failed to find the targets during both searches. It was assumed that correctly identifying an object as a search target causes it to be processed differently than distractors. If participants failed to correctly identify the UO target, that object would be thought of by the participant as just another distractor. Out of the 608 possible UO targets across all participants, only 55 targets (9%) were missed on both search array presentations. Pooled across all participants, these missed UO targets were remembered at a rate of 70.2% (SD = 2.1). Due to having such a low rate of misses not equally distributed across participants, a statistical analysis was not prudent. However, when participants missed both targets, memory for the target object was remarkably similar to category distractor memory in the UO present


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Figure 6. Memory accuracy by total fixation times for unique object (UO) searches. Error bars represent the standard error. Open markers represent valid UO searches, and the filled markers represent the invalid paired-object UO searches. Unlike standard line graphs, such as a series across time, the dotted lines are used only to link object types in order to clearly illustrate the relationships between viewing time and memory. Valid targets (open circle) were viewed for less time than the same objects paired (closed circle), but valid targets were remembered best.

condition (72.1%), indicating that the missed target was essentially processed as another distractor by the participant. One final comparison is relevant to the question of the contribution to semantic labels and the event of finding the target. By comparing the memory for search targets in the one-target PT condition and the valid UO condition, we could examine whether the addition of the semantic label promoted even better target memory above and beyond the event of finding a target. A betweenparticipants ANOVA indicated that one-target PT targets (88%) were remembered marginally better, F(1, 60) = 3.07, p = .085, than valid UO targets (81%). Thus, providing labels prior to search may improve memory beyond the event of finding the target. However, as we have already demonstrated, the label is not required to create a target memory advantage.

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Discussion Past research has provided evidence that search targets are remembered much better than distractors even when viewing differences have been taken into account (C. C. Williams, 2010a, 2010b). The superior memory of targets could point to a difference in the encoding and representation of visual memories that indicate a goal has been achieved. Although this is a possibility, up to now, it has been impossible to determine whether the target memory advantage that has been observed (C. C. Williams, 2010a, 2010b; C. C. Williams et al., 2005, 2009) was the result of the episodic event of finding the target or the extra information necessary to identify what one was looking for (the search label). The primary purpose of the current study was to evaluate whether a target memory advantage could be




found independent of knowing the semantic identity of the target prior to the search. The current research clearly demonstrates that even when targets were not defined with semantic category labels (valid UO targets), target memory was better than memory for other objects from the same search arrays. The finding of superior memory for UO targets extended to all objects from the all-paired UO search trials even though the valid UO targets were fixated for less time (at least 174 ms less and as much as 300 ms less) than all of the objects in the UO all-paired condition. In other words, finding what one is looking for without knowing its identity in advance created a more durable memory than simply looking at the same object without it being a search target. Although we demonstrated a target memory advantage with an undefined target, memory for the same target objects in predefined one-target searches (PT targets) marginally improved by an additional 7% compared to the UO targets. In other words, when the target objects had both the distinct episodic information of the target being found and the semantic label, memory was even better. Thus, both the semantic label and the event of finding the target contribute to the target memory advantage. This finding is critical because it demonstrates unique components of visual memory that arise from different aspects of the encoding episode. The results of the current study show that target visual memories contain information that distractor visual memories lack (the finding event and, normally, the semantic label), indicating that the representations of the targets and distractors differ. How might these differences manifest? Are the target memories and distractor memories the product of a common system, and are they quantitatively different from each other, or does the fact that the target represents the goal of the search make it so that target memories are represented by a qualitatively separate system from that for the distractor memories? The first possibility is that target memories differ quantitatively in the information that they contain from distractors; in other words, target

and distractor memories lay on a continuum with distractors at one end and targets at the other end (e.g., a levels of processing proposition; Craik & Lockhart, 1972). Within this explanation, all visual memories are the product of a common system, but targets gain more information when they are found. In essence, the moment that a search target is identified, the visual memory system collects more information about the target, encoding it at a greater depth and possibly with a higher resolution than distractors, leading to superior target memory. The event of finding the target could result in focused encoding that allows visual information about the target to be more rapidly accumulated than information about distractors. On the other hand, when distractor objects are viewed, they are more quickly rejected and thus have memories that are less deeply encoded with lower resolution and subsequently are remembered worse than targets. In other words, target and distractor memories would be all of the same general type of memory, but they would differ in the amount of visual information encoded. Another option for the difference between the targets and distractor memory representations is that superior target memories are the result of being coded into a qualitatively different system from that of the distractor memories. If so, how would this different class of memory operate? Target memories could be encoded into a separate visual memory system that is reserved for critical decision information, similar to the neuroimaging differences observed for memories formed at decision points in mazes (Janzen & van Turennout, 2004). A separate system would operate for either our PT or UO targets because they represent the goal of the particular search task. Distractor objects, on the other hand, are not encoded into this critical decision system because they lack the event code of finding the goal of the search. Alternatively, targets could be tagged as decision-related memories (i.e., possessing an extra piece of information), making them easier to retrieve, in the same way that pictures are claimed to have an additional code in dualcode theory (Paivio & Csapo, 1973), making


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them easier to retrieve than words. In either case, a target memory possesses information that is qualitatively different from the visual memories for distractors, and it is the additional or different information that permits the superior memory of target objects. Although both qualitative and quantitative differences are possible, we believe that our results, when considered in combination with the converging evidence from previous research (C. C. Williams, 2010a, 2010b), indicate a qualitative difference between targets and distractors rather than a quantitative difference. Specifically, one would expect that quantitative differences in the quality of visual memories would be tied to viewing time. The more an object was viewed, the better memory would be. In the current study, we found that the valid UO targets were viewed less than all of the UO absent object types, but were still remembered better than those objects. Even with more standard searches than the UO search used in the present research, C. C. Williams (2010b) and C. C. Williams et al. (2005) both found that when targets were fixated for much less time than distractors, targets were remembered better than distractors. In addition, C. C. Williams (2010a) held encoding time equivalent between distractors and targets and found the same target memory advantage as that observed in the current study. Finally, C. C. Williams (2010b) found that visual memory for distractors was best predicted by fixation time or count, but target memory was best predicted by number of searches (a nonvisual factor). All of these findings considered together appear to point to a change in memory type rather than a shift along the same continuum. Another piece of evidence from previous research that points to a qualitative change in memory was the age-related differences in visual memory observed by C. C. Williams et al. (2009). In their study, they found expected agerelated differences in visual memory, with younger adults outperforming older adults (e.g., Zacks, Hasher, & Li, 2000) for target objects. However, they failed to find significant agerelated memory differences for distractors. If targets and distractors were on a single all-inclusive

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continuum, one would expect that any age-related differences would be the same for all object types because all memory would result from the same process. Regardless of the mechanism responsible for the target memory advantage, clearly visual memories are influenced by nonvisual factors. We found that knowing categorical information about the search target before searching (PT search) led to marginally better visual memory than our valid UO targets, indicating that knowing the semantic label of the category before searching provides an additional benefit to visual memory. However, even when the label was not provided, target memory was better for valid UO targets than for the same objects when they were paired. One could argue that participants may have silently named the objects during the UO searches as they looked for matching objects (e.g., “I am looking for another yellow bird”). However, if participants used an object naming search strategy, they probably would have named ALL of the objects in the display, not just the target, and any memory increase due to using the object label should have been similar across all object types. Given that valid targets were remembered better than other objects during UO searches, it is unlikely that category naming alone caused better target memory. Thus, it appears that categorical semantic information plays a role in visual memory as claimed by Konkle et al. (2010), but other nonvisual factors also impact visual memory. Our claim of a nonvisual component affecting visual memory is not new. As previously noted, Paivio and Csapo (1969, 1973) claimed that pictures were remembered better than words due to the possibility that pictures contained dual codes (verbal and imagery) that permitted the pictures to be remembered better than verbal material alone. Standing (1973) found that “interesting” pictures were remembered better than noninteresting pictures. Konkle et al. (2010) demonstrated that visual memories appeared to be organized by preexisting semantic categories rather than by visual details. In each of these cases, the added information was not necessarily tied to the visual complexity or nature of the stimulus, but rather to




a name or interpretation of the image independent of the visual details. In the context of the current study, the additional information is decidedly episodic in that it is part of the event of finding the target object, making this component different from those found in other studies. The act of fixating the object is not sufficient to add this component; one must separate the object from the remaining objects as special in the moment. In conclusion, our results indicate that the episodic aspect of completing a search task—“There it is!”—enhances the encoding of targets, even when the searcher is not provided with semantic labels for targets prior to searching. Whether this enhancement is purely a quantitative shift in the amount of visual information a memory contains, or whether targets are encoded into a separate memory system reserved for goal-related information, remains a question. Although the argument we presented was in favour of a qualitative difference, an interpretation based on quantitatively more information via attentional focus is also consistent with the current data. Regardless, it is clear that the superior memory performance for unnamed targets indicates that the encoding of visual memories is influenced by multiple sources of information, including information that is not visual in nature. Original manuscript received 2 August 2013 Accepted revision received 12 November 2013 First published online 16 April 2014

REFERENCES Craik, F. L. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behavior, 11, 671–684. doi:10.1016/S0022-5371(72)80001-X Janzen, G., & van Turennout, M. (2004). Selective neural representation of objects relevant for navigation. Nature Neuroscience, 7, 673–677. doi:10.1038/ nn1257 Konkle, T., Brady, T. F., Alvarez, G. A., & Oliva, A. (2010). Scene memory is more detailed than you think: The role of categories in visual long-term

memory. Psychological Science, 21, 1551–1556. doi:10.1177/0956797610385359 Paivio, A., & Csapo, K. (1969). Concrete image and verbal memory codes. Journal of Experimental Psychology, 80, 279–285. doi:10.1037/h0027273 Paivio, A., & Csapo, K. (1973). Picture superiority in free recall: Imagery or dual coding? Cognitive Psychology, 5, 176–206. doi:10.1016/0010-0285(73) 90032-7 Schmidt, J., & Zelinsky, G. J. (2009). Search guidance is proportional to the categorical specificity of a target cue. Quarterly Journal of Experimental Psychology, 62, 1904–1914. doi:10.1080/17470210902853530 Schneider, W., Eschman, A., & Zuccolotto, A. (2002). E-Prime user’s guide. Pittsburgh, PA: Psychology Software Tools Inc. Standing, L. (1973). Learning 10000 pictures. Quarterly Journal of Experimental Psychology, 25, 207–222. doi:10.1080/14640747308400340 Standing, L., Conezio, J., & Haber, R. N. (1970). Perception and memory for pictures: Single-trial learning of 2500 visual stimuli. Psychonomic Science, 19, 73–74. Torralba, A., Oliva, A., Castelhano, M. S., & Henderson, J. M. (2006). Contextual guidance of eye movements and attention in real-world scenes: The role of global features on object search. Psychological Review, 113, 766–786. doi:10.1037/ 0033-295X.113.4.766 Vickery, T. J., King, L.-W., Jiang, Y. (2005). Setting up the target template in visual search. Journal of Vision, 5, 81–92. doi:10.1167/5.1.8 Võ, M. L.-H., & Wolfe, J. M. (2012). When does repeated search in scenes involve memory? Looking at versus looking for objects in scenes. Journal of Experimental Psychology: Human Perception and Performance, 38, 23–41. doi:10.1037/a0024147 Võ, M. L.-H., & Wolfe, J. M. (2013). The interplay of episodic and semantic memory in guiding repeated search in scenes. Cognition, 126, 198–212. doi:10. 1016/j.cognition.2012.09.017 Williams, C. C. (2010a). Incidental and intentional visual memory: What memories are and are not affected by encoding tasks? Visual Cognition, 18, 1348–1367. doi:10.1080/13506285.2010.486280 Williams, C. C. (2010b). Not all visual memories are created equal. Visual Cognition, 18, 201–228. doi:10. 1080/13506280802664482 Williams, C. C., Henderson, J. M., & Zacks, R. T. (2005). Incidental visual memory for targets and


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Williams, L. G. (1967). The effects of target specification on objects fixated during visual search. Acta Psychologica, 27, 355–360. doi:10.1016/0001-6918 (67)90080-7 Zacks, R. T., Hasher, L., & Li, K. Z. H. (2000). Human memory. In F. I. M. Craik & T. A. Salthouse (Eds.), The handbook of aging and cognition (2nd ed., pp. 293– 357). Mahwah, NJ: Lawrence Erlbaum Associates.


distractors in visual search. Perception and Psychophysics, 67, 816–827. doi:10.3758/ BF03193535 Williams, C. C., Zacks, R. T., & Henderson, J. M. (2009). Age differences in what is viewed and remembered in complex conjunction search. Quarterly Journal of Experimental Psychology, 62, 946–966. doi:10.1080/17470210802321976

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The role of memory for visual search in scenes.

Is construction reserved for the target during visual search?

Target grouping in visual search for multiple digits.

Understanding the contribution of target repetition and target expectation to the emergence of the prevalence effect in visual search.

Is a search template an ordinary working memory? Comparing electrophysiological markers of working memory maintenance for visual search and recognition.

Visual search with embedded targets: color and texture differences.

Visual search for oriented lines: the role of angular relations between targets and distractors.

Searching for the right word: Hybrid visual and memory search for words.

Memory search for the first target modulates the magnitude of the attentional blink.

Memory and visual search in naturalistic 2D and 3D environments.

A working memory account of refixations in visual search.

Selective scanpath repetition during memory-guided visual search.

Age differences in visual search: target and distractor learning.

Predictive saccade target selection in superior colliculus during visual search.

Use of constant target sets in visual search tasks.

The influence of working memory on visual search for emotional facial expressions.

Comparing target detection errors in visual search and manually-assisted search.

Searching while loaded: Visual working memory does not interfere with hybrid search efficiency but hybrid search uses working memory capacity.

More target features in visual working memory leads to poorer search guidance: evidence from contralateral delay activity.

One visual search, many memory searches: An eye-tracking investigation of hybrid search.

Asymmetry in visual search for targets defined by differences in movement speed.

Training and transfer of training in rapid visual search for camouflaged targets.

Statistical templates for visual search.

Target features and target-distractor relation are both primed in visual search.