Short article Visual similarity at encoding and retrieval in an item recognition task

THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY 2009, 62 (7), 1277 1284 Short article Visual similarity at encoding and retrieval in an item recognition task Judit Mate and Josep Baqués Laboratori de Memòria, Departament de Psicologia Bàsica, Evolutiva i de l Educació, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain The aim of this experiment was to examine the effects of shape similarity in visual working memory using a six alternative recognition task of Chinese characters. Shape similarity among items was manipulated at both encoding and retrieval in order to assess in which phase similarity impairs recognition to a greater degree. Results revealed that performance is particularly facilitated by high discriminability at retrieval but also by the presence of similar items at encoding, as similarity simplifies the global representation of the display and reduces memory load. Moreover, results provide further evidence that the classical similarity effect can be reversed in the visual domain when item memory (as opposed to order) is assessed. Keywords: Visual working memory; Visual short-term memory; Similarity effects; Recognition; Relational processing. Visual information the physical properties of objects, such as shape, colour, or brightness can be retained for a brief period of time in visual working memory (VWM), and its representation implies the retention of objects structure and the relation between parts of different items (Logie, 1995). VWM maintains perceptual continuity of natural scenes, and one of its most notable characteristics is that storage capacity is highly limited (Luck & Vogel, 1997). In comparison with verbal working memory, the visual domain has received less attention and is not as well understood. Nevertheless, some researchers have focused on establishing parallelisms between these domains by trying to replicate well-known verbal effects such as the influence of similarity, suppression, or simultaneous presentation of irrelevant material. Our work focuses on the effect of similarity. Visual similarity plays a crucial role in our Correspondence should be addressed to Judit Mate, Dept. Psicologia Bàsica, Evolutiva i de l Educació, Facultat de Psicologia Edifici B, Campus de la UAB, 08193 Bellaterra (Cerdanyola del Vallès), Spain. E-mail: judit.mate@uab.cat This research was supported by a Formación de Profesorado Universitario grant from the Spanish Ministry of Science and Innovation (MCINN) to Judit Mate. We thank Laurence White, Guillermo Campoy, and the reviewers for their useful comments. http://www.psypress.com/qjep # 2009 The Experimental Psychology Society 1277 DOI:10.1080/17470210802680769

MATE AND BAQUÉS representation of the world since it is involved in object recognition, generalization, and the creation of categories and concepts. Understanding the influence of similarity effects in visual working memory is of great interest because it addresses the question of whether information can be represented in a purely visual code in working memory and may also explain how internal descriptions of objects are encoded. With regard to similarity in the verbal domain, phonological similarity refers to the robust, replicated finding that similar-sounding items are less accurately recalled in immediate serial recall tasks than are dissimilar-sounding items (Conrad & Hull, 1964). However, several further studies have indicated that the effect reverses for item identity (as opposed to order) in immediate serial recall tasks when the words of the similar list rhyme (Fallon, Groves, & Tehan, 1999; Gathercole, Gardiner, & Gregg, 1982) and also when nonwords are used (Karlsen, Gravir, Johannessen, Endestad, & Lian, 2007). A positive similarity effect has also been found in free recall of words (Fournet, Juphard, Monnier, & Roulin, 2003). Fallon et al. (1999) have suggested that this reversal can be explained because rhyme and shared phonemes serve as an effective category cue that facilitates item recall. Immediate serial recall has also been the most widely used task in research on similarity within the visual domain. For example, Wolford and Hollingsworth (1974) found several visual, but not acoustic, confusions in a letter serial recall task, suggesting that letters were not encoded phonologically but visually. Hue and Erickson (1988) also reported a visual similarity effect in an immediate recall task of Chinese characters. Hitch, Halliday, Schaafstal, and Schraagen (1988) found that 5-year-old children showed visual confusions in serial recall of similar drawings while the effect disappeared in older children. The authors hypothesized that young children rely on visual codes due to the fact that verbal codes and subvocalization are not well developed yet, while older children rely on verbal codes except when articulation is suppressed. These findings suggest that the visual similarity effect arises from confusions within storage codes rather than from perceptual errors. Avons and Mason (1999) tested serial recall of novel and repeated patterns and reported a robust visual similarity effect, which they attributed to structural similarity among items. Logie, Della Sala, Wynn, and Baddeley (2000) also found a strong effect in serial recall of words and letters with and without a concurrent articulatory suppression task. However, a few studies have focused on how similarity influences item memory regardless of order, and while some of them have used paradigms that do not imply item memory exclusively (Jalbert, Saint-Aubin, & Tremblay, 2008), others have failed to obtain the effect both in a recognition task (Avons & Mason, 1999) and in the item-based score ignoring order in a serial recall task (Saito, Logie, Morita, & Law, 2008). Taken together, the results show the classical similarity effect in the visual domain that is, an impairment in serial recall performance due to similarity among items but little is known about this effect in item memory and especially under a recognition paradigm. Recent work has employed a variant of the Sternberg recognition paradigm in which a list of visual items is followed by an old or a new probe that can be either similar or dissimilar to the previously presented stimuli (Hay, Smyth, Hitch, & Horton, 2007; Kahana & Sekuler, 2002; Nosofsky & Kantner, 2006). Hay et al. (2007) manipulated similarity in the study list and found that faces were better discriminated when a similar list was tested with a dissimilar foil. Mewhort and Johns (2000) also found that the difficulty of rejecting a negative probe increased as similarity to the studied list increased. As in those studies, in the present experiment we use a recognition task in which similarity among target and lures is manipulated at both encoding and retrieval to test the effect of similarity in each phase. However, the specific procedure used here has not, to our knowledge, been used before in assessing visual similarity effects. Participants are shown 2, 3, 4, or 5 similar or dissimilar items simultaneously at encoding in a random manner, one of which appears again among six similar or dissimilar alternatives at recognition. We employ Chinese 1278 THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2009, 62 (7)

VISUAL SIMILARITY IN ITEM RECOGNITION characters that do not have a previous mental representation for our participants and that do not rely on spatial memory (compared to visual stimuli such as matrix patterns). Although similarity effects have been found mainly with the use of figurative stimuli like drawings or pictures of known objects (Poirier, Saint-Aubin, Musselwhite, Mohanadas, & Mahammed, 2007), we suggest that using novel visual material provides a better way of studying how visual information is represented, because the contribution of longterm memory is minimized. Furthermore, in order to avoid verbal rehearsal we have added a concurrent articulatory suppression task. In sum, the aim of the present experiment is to observe whether recognition declines as an effect of similarity among items at encoding or at retrieval using an open set of nonfamiliar visual items. Considering the fact that order memory, which is known to be especially affected by similarity, is not assessed in this study, a facilitating effect of similarity at encoding could occur. This pattern would be consistent with the finding that similarity seems to enhance item memory in the verbal domain. Method Participants A total of 48 undergraduate students (mean age 20.28 years, SD ¼ 3.97) from the Autonomous University of Barcelona participated in the experiment for course credit. All reported having normal or corrected-to-normal visual acuity. Apparatus and stimuli The experiment was conducted on a computer with a Pentium IV processor and a 21 00 monitor. The software DMDX (Forster & Forster, 2003) was used for stimulus presentation and registration of responses. Stimuli were 1,520 Chinese characters from the Chinese character database, developed by the Research Centre for the Humanities Computing. Chinese characters consist of combinations of 20 basic strokes and a radical, which provides the meaning. In order to control orthographic complexity, characters with fewer than 6 and more than 12 strokes were excluded (mean of 10 strokes). Two characters were defined as similar if they contained the same radical and number of strokes. This approach is supported by the study of Yeh, Li, and Chen (1997) in which the authors carried out multidimensional analysis and concluded that similarity among participants who do not know the language is judged by these two factors, while experienced readers rely on how the attributes are distributed. Design The dependent variable was the proportion of correct recognition. A correction was applied to raw data: hits (errors/5). The independent variables were: set size, with four levels (2, 3, 4, and 5 items); similarity at encoding, with two levels (similar and dissimilar items); and similarity at retrieval, with two levels (similar and dissimilar items). The combination of these variables resulted in four experimental conditions within each set size, so trials could contain similar items at both encoding and retrieval (SS), similar items at encoding and dissimilar items at retrieval (SD), dissimilar items at encoding and similar items at retrieval (DS), and dissimilar items at both encoding and retrieval (DD), resulting in a 4 2 2 within-subjects design. All items appeared the same number of times in each experimental condition, so the complete rotation of material was guaranteed. The position of the target was also counterbalanced: It appeared the same number of times in each of the four coordinates (right, left, up, and down) in each condition at encoding and the same number of times in each of the six alternatives at recognition. The total number of trials was 80, 20 in each set size (2, 3, 4, and 5 items), of which 5 corresponded to each of the four different conditions of similarity among encoding and retrieval. Trials were presented randomly. Procedure Participants carried out the experiment individually in a dark room. The task consisted in the presentation of 2, 3, 4, or 5 black Chinese characters THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2009, 62 (7) 1279

MATE AND BAQUÉS Figure 1. Example display of the recognition task used. distributed on an invisible circular pattern against a white background (see Figure 1). The duration of each display was proportional to the number of items (1 second per item); thus it could range from 2 to 5 seconds. Participants were instructed to memorize all the items. After a blank interval of 900 milliseconds, six alternatives were presented, and participants had to decide which one had appeared previously by pressing the corresponding number. The test items remained on the screen for 10 seconds or until response, whichever was the sooner. After each trial, participants were asked for a confidence judgement, which ranged from 1 (guessing) to 5 (high confidence). The experiment ran for 22 minutes. In all of the trials, participants suppressed articulation at encoding by saying aloud one, two, three, four at a rate of approximately two digits per second. An instruction to start counting appeared on the screen before each trial. Results Mean proportion of correct recognition (see Table 1) was submitted to a 2 2 4 repeated measures within-subjects analysis of variance (ANOVA): Similarity at Encoding (similar, dissimilar) Similarity at Retrieval (similar, dissimilar) Set Size (2, 3, 4, 5). The results of this analysis revealed that all three main effects were significant. Recognition was more enhanced by similar items at encoding (M ¼.65) than by dissimilar items (M ¼.40): F(1, 47) ¼ 182.83, p,.001, MSE ¼ 0.065, h 2 ¼.79. The opposite pattern was found at retrieval, with recognition higher when dissimilar items were shown (M ¼.69) than when similar items were shown Table 1. Mean proportion of correct recognition as a function of set size and similarity Similarity at encoding/similarity at retrieval Set size SS SD DS DD 2.57 (.27).91 (.14).39 (.27).70 (.24) 3.43 (.27).81 (.18).29 (.23).54 (.23) 4.46 (.25).84 (.16).18 (.21).50 (.26) 5.39 (.24).79 (.19).20 (.23).39 (.26) Note: Standard deviations in parentheses. S ¼ similar items, D ¼ dissimilar items. 1280 THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2009, 62 (7)

VISUAL SIMILARITY IN ITEM RECOGNITION (M ¼.37): F(1, 39) ¼ 352.71, p,.001, MSE ¼ 0.056, h 2 ¼.88. The main effect of set size, F(3, 141) ¼ 24.71, p,.001, MSE ¼ 0.056, h 2 ¼.55, indicated that participants performed worse as set size increased. However, this effect was mediated by the interaction between similarity at encoding and set size, F(3, 141) ¼ 3.42, p ¼.019, MSE ¼ 0.048, h 2 ¼.07. Additional analyses indicated that the source of the interaction was that the difference between similarity and dissimilarity at encoding was greater in set sizes 4 and 5 than in set sizes 2 and 3 (p,.05). Moreover, in both similar and dissimilar conditions, comparisons between the means showed that there was significantly better performance only in set size 2 when compared to the other set sizes (p,.05). In addition, the interaction between similarity at encoding and similarity at retrieval was also significant: F(1, 47) ¼ 6.52, p ¼.014, MSE ¼ 0.078, h 2 ¼.12. Further analysis of this interaction showed that the differences produced by similarity at encoding were greater when items were dissimilar at retrieval. As can be seen in Figure 2, condition SD obtained the highest proportion of correct recognition (.84), followed by DD (.54) and SS (.46). DS obtained the lowest proportion (.27). All post hoc Bonferroni-adjusted pairwise comparisons were significant (p,.001). The other interactions did not reach significance. Table 2. Mean response time as a function of set size and similarity Similarity at encoding/similarity at retrieval Set size SS SD DS DD 2 5.36 (1.51) 4.03 (1.19) 5.84 (1.96) 5.22 (1.91) 3 6.05 (1.81) 4.49 (1.54) 6.01 (1.92) 5.63 (2.14) 4 6.06 (1.99) 4.63 (1.22) 6.62 (2.06) 5.83 (1.69) 5 6.29 (1.72) 5.12 (1.91) 6.64 (2.27) 5.92 (1.92) Note: Standard deviations in parentheses. Response time in s. S ¼ similar items, D ¼ dissimilar items. Response times are shown in Table 2. A 2 2 4 repeated measures within-subjects ANOVA revealed that all three main effects were significant: similarity at encoding, F(1, 47) ¼ 37.82, p,.001, MSE ¼ 2.546, h 2 ¼.45; similarity at retrieval, F(1, 47) ¼ 136.83, p,.001, MSE ¼ 1.396, h 2 ¼.74; set size, F(3, 141) ¼ 20.98, p,.001, MSE ¼ 1.315, h 2 ¼.31. The two-way interaction between similarity at encoding and similarity at retrieval was also significant: F(1, 47) ¼ 15.68, p,.001, MSE ¼ 1.695, h 2 ¼.25. Response times were higher as set size increased, but as in the recognition results the difference between set sizes 3 and 4 and set sizes 4 and 5 did not prove to be significant (p ¼.30 and p ¼.17, respectively). In addition, as can be seen in Table 2, response times were faster in the conditions with higher proportion of correct recognition and increased significantly as a function of condition complexity. Regarding confidence judgements, there was a main effect of set size, F(3, 141) ¼ 43.65, p,.001, MSE ¼ 0.339, h 2 ¼.48, indicating that participants were more confident of their choices when fewer items were presented at encoding. Comparisons of mean confidence ratings replicate the main findings insofar as participants reported higher confidence in the conditions that produced greater recognition accuracy. Figure 2. Mean proportion of correct recognition as a function of similarity at both memory phases. S ¼ similar items, D ¼ dissimilar items. Bars represent standard error. Discussion The aim of the present experiment was to assess the visual similarity effect in the recognition of THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2009, 62 (7) 1281

MATE AND BAQUÉS Chinese characters: stimuli that did not have a previous representation in participants long-term memory. Similarity among items was manipulated at both encoding and retrieval in order to evaluate the specific effects of similarity in each phase. In contrast with previous studies, a multiple-choice recognition task was used so that performance relied specifically on memory for item identity. Our results showed a robust impact of visual similarity on performance, as demonstrated by the significant differences among the four conditions. In addition, recognition scores were consistent with response times and confidence judgements, with poorer recognition being accompanied by higher latency and lower confidence rates. Results indicated an interactive effect of similarity at encoding and retrieval on memory performance. Similarity at encoding resulted in better performance with both similar and dissimilar stimuli at retrieval, with the interaction being a consequence of a greater positive effect when recognition involved dissimilar items. The mechanism underlying this pattern could be interpreted in terms of discrimination processes at retrieval combined with relational processing at encoding, which refers to the processing of dimensions common to all items in terms of shared features within an event (Einstein & Hunt, 1980; Hunt & Einstein, 1981; Hunt & Worthen, 2006). It has been suggested that recognition accuracy increases when dissimilar alternatives are presented at test because distinctiveness effects occur at this phase, and discrimination is facilitated (Hunt, 2003; Tulving, 1981). Indeed, the beneficial role of dissimilarity at retrieval can be observed in the two conditions that obtained the highest scores (SD and DD), although the former, which involved the presence of similar items at encoding, resulted in a particularly good performance. Similarity can be considered as relational information that facilitates the abstraction of the common elements by creating a global scheme of the whole display. The emergence of a common schema reduces memory load by simplifying the global representation of the to-beremembered items. Evidence supporting this fact comes from organizational theories that emphasize the importance of encoding information common to the input elements (Puff, 1979) and also from perceptual similarity studies such as the one from Goldstone and Barsalou (1998), which indicated that similarity implies integration of different sources of information rather than focusing on single attributes. Goldstone and Barsalou argued that holistic processing of similarity seems to be a more primitive computation, which could have derived from perception in order to optimize categorization processes. Visual search tasks have also demonstrated that similarity among distractors can contribute to better performance through facilitation of perceptual grouping strategies (Humphreys, Quinlan, & Riddoch, 1989). So, on the one hand, the encoding of information concerning the general pattern abstracted from the items presented may serve as a useful retrieval cue (Einstein & Hunt, 1980), and on the other hand, showing dissimilar items at retrieval makes it easier to discriminate the target between the alternatives, which explains the greater performance of SD relative to the others. However, in this condition participants only needed to discriminate which alternative was similar to any of the previously presented items. So, one might argue that correct responses did not necessarily imply target recognition. Performance in the remaining conditions can also be explained on the basis of the differential effects that similarity has upon the type of processing engaged at encoding combined with discrimination difficulties at retrieval. A striking finding is that similarity at encoding still had a positive effect when items were similar at retrieval (SS) compared with DS. SS condition involved lures that were similar to all previously shown items so a worse performance should be expected. The assumption that similarity helps performance by simplifying the structural descriptions of the to-be-remembered items can be put forward to explain this phenomenon. When similar items are shown at encoding, the common reference trace makes it possible to disregard shared features and focus on those that distinguish one item from another (Tulving, 1981). This additional individual-item 1282 THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2009, 62 (7)

VISUAL SIMILARITY IN ITEM RECOGNITION processing of distinct attributes provides discriminative information during retrieval, as it allows participants to reject the alternatives that do not possess a critical item-specific detail. On the contrary, in the DS condition, the greater amount of elements to be encoded makes selective attention to particular features more difficult, with a consequent poor ability to discriminate among similar alternatives presented at retrieval. This reasoning could also be applied to explain why similarity had a greater effect as set size increased. It is possible to argue that, when few items are shown, participants are capable of maintaining all features. However, when set size increases to a certain point, visual working memory capacity is overloaded (Luck & Vogel, 1997), and encoding a common schema of the display and focusing attention on distinctive elements become more efficient, with the consequence of similarity having a greater positive effect. The general pattern of results could also be accounted for by two-process models of recognition memory. According to these models, an item can be recognized as old because it evokes a feeling of familiarity or because it has been consciously recollected. Familiarity and recollection play qualitatively different roles for the recognition decision process: While familiarity is assumed to be a rapid and automatic process that involves low demands on cognitive resources, recollection is a slower process that places greater demands (for a review, see Yonelinas, 2002). In the SD condition, response times were faster; thus it is plausible that participants relied on an assessment of familiarity, as they only needed to discriminate which alternative was more similar to any of the previously presented items. The higher difficulty in the remaining conditions, as shown by slower response times and lower recognition scores, makes it less probable to choose the correct item by relying on a feeling of familiarity alone, so recollection could have occurred and dominated recognition decision. Nevertheless, although plausible, this interpretation is somewhat speculative as the present experiment does not address this question directly. Moreover, the fact that familiarity is faster than recollection has been questioned by other researchers (cf. Dewhurst, Holmes, Brandt, & Dean, 2006). In summary, our results indicate that similarity manipulations have a major impact at retrieval but that discrimination in this phase is moderated by the type of processing engaged at encoding. However, when retrieval is held constant, the two conditions in which similar items are presented at encoding have obtained higher scores than those in which items are dissimilar. Therefore, the results are partly consistent with those studies that have focused on item memory regardless of order in the verbal domain, in which the similarity effect reverses and thus facilitates performance (Fallon et al., 1999; Fournet et al., 2003; Gathercole et al., 1982; Karlsen et al., 2007). In the verbal domain, the most widely accepted explanation is that phonological similarity in terms of rhyme or shared phonemes provides an efficient retrieval cue (Fallon et al., 1999). In our experiment the facilitation could come from the structural configuration of visual material in terms of shared attributes that make relational processing possible and thus reduce memory load. However, the present experiment has shown that when similarity is manipulated in a visual recognition task, performance depends on both phases, and it is particularly facilitated by combining high discriminability at retrieval with information simplification at encoding. REFERENCES Original manuscript received 28 July 2008 Accepted revision received 4 December 2008 First published online 18 February 2009 Avons, S. E., & Mason, A. (1999). Effects of visual similarity on serial report and item recognition. The Quarterly Journal of Experimental Psychology, 52A, 217 240. Conrad, R., & Hull, A. J. (1964). Information, acoustic confusion and memory span. British Journal of Psychology, 55, 429 432. Dewhurst, S. A., Holmes, S. J., Brandt, K. R., & Dean, G. M. (2006). Measuring the speed of the conscious THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2009, 62 (7) 1283

MATE AND BAQUÉS components of recognition memory: Remembering is faster than knowing. Consciousness and Cognition, 15, 147 162. Einstein, G. O., & Hunt, R. R. (1980). Levels of processing and organization: Additive effects of individual-item and relational processing. Journal of Experimental Psychology: Human Learning and Memory, 6, 588 598. Fallon, A. B., Groves, K., & Tehan, G. (1999). Phonological similarity and trace degradation in the serial recall task: When CAT helps RAT, but not MAN. International Journal of Psychology, 34, 301 307. Forster, K. I., & Forster, J. C. (2003). DMDX: A Windows display program with millisecond accuracy. Behavior Research Methods, Instruments & Computers, 35, 116 124. Fournet, N., Juphard, A., Monnier, C., & Roulin, J. L. (2003). Phonological similarity in free and serial recall: The effect of increasing retention intervals. International Journal of Psychology, 38, 384 389. Gathercole, S. E., Gardiner, J. M., & Gregg, V. H. (1982). Modality and phonological similarity effects in serial recall: Does one s own voice play a role? Memory & Cognition, 10, 176 180. Goldstone, R. L., & Barsalou, L. (1998). Reuniting perception and conception. Cognition, 65, 231 262. Hay, D. C., Smyth, M. M., Hitch, G. J., & Horton, N. J. (2007). Serial position effects in short-term visual memory: A SIMPLE explanation? Memory & Cognition, 35, 176 190. Hitch, G. J., Halliday, M. S., Schaafstal, A. M., & Schraagen, J. M. (1988). Visual working memory in young children. Memory & Cognition, 16, 120 132. Hue, C. W., & Erickson, J. R. (1988). Short-term memory for Chinese characters and radicals. Memory & Cognition, 16, 196 205. Humphreys, G. W., Quinlan, P. T., & Riddoch, M. J. (1989). Grouping processes in visual search: Effects with single and combined-feature targets. Journal of Experimental Psychology: General, 118, 258 279. Hunt, R. R. (2003). Two contributions of distinctive processing to accurate memory. Journal of Memory & Language, 48, 811 825. Hunt, R. R., & Einstein, G. O. (1981). Relational and item-specific information in memory. Journal of Verbal Learning and Verbal Behavior, 20, 497 514. Hunt, R. R., & Worthen, J. B. (2006). Distinctiveness and memory. New York: Oxford University Press. Jalbert, A., Saint-Aubin, J., & Tremblay, S. (2008). Visual similarity in short-term recall for where and when. The Quarterly Journal of Experimental Psychology, 61, 353 360. Kahana, M. J., & Sekuler, R. (2002). Recognizing spatial patterns: A noisy exemplar approach. Vision Research, 42, 2177 2192. Karlsen, P. J., Gravir, A. G., Johannessen, K., Endestad, T., & Lian, A. (2007). Why does the phonological similarity effect reverse with nonwords? Psychological Research, 71, 448 457. Logie, R. H. (1995). Visuo-spatial working memory. Hove, UK: Lawrence Erlbaum Associates. Logie, R. H., Della Sala, S., Wynn, V., & Baddeley, A. D. (2000). Visual similarity effects in immediate serial recall. The Quarterly Journal of Experimental Psychology, 53A, 626 646. Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390, 279 281. Mewhort, D. J. K., & Johns, E. E. (2000). The extralistfeature effect: Evidence against item matching in short-term recognition memory. Journal of Experimental Psychology: General, 129, 262 284. Nosofsky, R., & Kantner, J. (2006). Exemplar similarity, study list homogeneity, and short-term perceptual recognition. Memory & Cognition, 34, 112 124. Poirier, M., Saint-Aubin, J., Musselwhite, K., Mohanadas, T., & Mahammed, G. (2007). Visual similarity effects on short-term memory for order: The case of verbally labeled pictorial stimuli. Memory & Cognition, 35, 711 723. Puff, C. R. (1979). Memory organization and structure. New York: Academic Press. Saito, S., Logie, R. H., Morita, A., & Law, A. (2008). Visual and phonological similarity effects in verbal immediate serial recall: A test with kanji materials. Journal of Memory and Language, 59, 1 17. Tulving, E. (1981). Similarity relations in recognition. Journal of Verbal Learning and Verbal Behavior, 20, 479 496. Wolford, G., & Hollingsworth, S. (1974). Evidence that short-term memory is not the limiting factor in the tachistoscopic full-report procedure. Memory & Cognition, 2, 796 800. Yeh, S. L., Li, J. L., & Chen, I. P. (1997). The perceptual dimensions underlying the classification of the shapes of Chinese characters. Chinese Journal of Psychology, 39, 47 74. Yonelinas, A. P. (2002). The nature of recollection and familiarity: A review of 30 years of research. Journal of Memory and Language, 46, 441 512. 1284 THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2009, 62 (7)