Influence of Color on Perceptual Priming: A Picture ... - ScienceDirect

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Dr. Kobus Maree, University of Pretoria, South Africa. ... bPhysiological Psychology, Bielefeld University, Post Office Box 100131, 33501 Bielefeld, Germany.
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Procedia - Social and Behavioral Sciences 82 (2013) 482 – 486

World Conference on Psychology and Sociology 2012

Influence of Color on Perceptual Priming: A Picture Fragment Completion Paradigm Dennis E. Dal Mas a *, Sina Kühnel a, b, Benjamin Reichelt a, Hans J. Markowitsch a, b, c, Martina Piefke a, b, d a

Center of Excellence in Cognitive Interaction Technology, Bielefeld University, Post Office Box 100131, 33501 Bielefeld, Germany b Physiological Psychology, Bielefeld University, Post Office Box 100131, 33501 Bielefeld, Germany c Hanse Institute for Advanced Study, Post Office Box 1344, 27733 Delmenhorst, Germany d Department of Psychology, Neurobiology and Genetics of Behavior, Witten/Herdecke University, Alfred-Herrhausen-Straße 50, 58448 Witten, Germany

Abstract The role of color in perceptual priming still remains unclear. We investigated the influence of color during the identification of natural images using a perceptual priming paradigm. In a learning phase, two groups of participants were presented with either colored or gray-scaled variants of photos. A control group did not participate in the learning phase. We measured the level of fragmentation by which a stimulus was correctly recognized in a retrieval phase. Results indicate that colored (compared to gray-scaled) stimuli improved subsequent identification performance of colored and gray-scaled stimuli. These findings imply that color enhances the effects of perceptual priming. 2013The The Authors. Published by Elsevier Ltd.access under CC BY-NC-ND license. ©©2013 Authors. Published by Elsevier Ltd. Open Selection and peer review under the responsibility of Prof. Dr. Kobus Maree, University of Pretoria, South Africa.

Selection and peer review under the responsibility of Prof. Dr. Kobus Maree, University of Pretoria, South Africa. Keywords: Perceptual Priming, Color Information, Picture Fragment Completion Paradigm, Object Recognition;

1. Introduction Does color information have an influence on perceptual priming? Can we recognize things faster and more correctly, when we perceive them unconsciously before in their colored instead of gray-scaled form? In experiments using a classic paradigm of perceptual priming, participants recognize stimuli that already occurred in a learning/study phase faster and more accurate in a test/retrieval phase compared with participants who see these stimuli for the first time e.g. see Bargh & Chartrand, 2000; Cermak, Talbot, Chandler, & Wolbarst, 1985; Weldon, 1991; Wiggs & Martin, 1998). Recognition of stimuli in a test phase depends on

* Corresponding author: Dennis E. Dal Mas. Tel.: +49-152-289-69603 E-mail address: [email protected]

1877-0428 © 2013 The Authors. Published by Elsevier Ltd. Open access under CC BY-NC-ND license. Selection and peer review under the responsibility of Prof. Dr. Kobus Maree, University of Pretoria, South Africa. doi:10.1016/j.sbspro.2013.06.296

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several factors. The similarity between first (primes) and second presentation (targets; see Goodglass, Theurkauf, & Wingfield, 2008) as well as the context, in which primes and targets are presented (see Biederman, Mezzanotte, & Rabinowitz, 1982), can affect both: error and recognition rate. Most investigations that were concerned with the influence of color on priming, could only determine slight, non-significant advantages related to color information (Cave, Bost, & Cobb, 1996; Cave & Squire, 1992; Seamon et al., 1997; Srnivias, 1996). Cave et al. (1996) reported no advantages for priming by using colored outline drawings with a naming task. In contrast, Wippich and Mecklenbräuker (1998) found enhanced priming associated with color information. Likewise, Uttl, Graf, and Santacruz (2006) showed that colored compared to gray-scaled photos in different fragmenting stages lead to better recognition. Previously learned primes were earlier recognized when the respective targets were colored. In the experiment of Uttl and colleagues (2006) participants were presented with both colored and different gray-scaled stimuli in the learning phase. At test, participants were either exposed to colored or gray-scaled fragmented photos. Interestingly, previously seen gray-scaled stimuli were recognized earlier in their colored variant than in their original gray-scaled format. Since participants were either exposed to colored or gray-scaled targets during retrieval, the authors could not disentangle the issue whether color information only serves as better recall cue in the test phase or rather shifts information processing already in the learning phase. In the present study, we aimed at examining whether color information already affects unconscious information processing in the learning phase. We assumed that previously seen colored stimuli will increase the subsequent recognition performance of both colored and gray-scaled stimuli. 2. Methods and materials 2.1. Participants and design 33 right-handed undergraduate and graduate students (16 female/17 male, age: mean = 23.15, SD = 1.15) participated in the study. Exclusion criteria were determined in a short screening interview. These criteria were studying psychology as well as a known history of neurological or psychiatric diseases, and psychopharmacological medication. Participants were tested neuropsychologically for cognitive abilities, which were relevant to the experiment. All volunteers gave written-informed consent to participate in the experiment, and the study was approved by the local ethics committee. The experiment consisted of a study phase (~ 10 min) with an interference task (living vs. non-living), a standard neuropsychological testing battery (~ 40 min), and a test phase with a picture fragment completion task (~ 20 min). For the study phase, participants were randomly assigned to one of three groups. One group was presented with colored stimuli (“Color-Group”), the other with gray-scaled ones (“Gray-Group”). The third group did not participate in the study phase (“Control-Group”). 2.2. Materials Four different classes of stimuli were used in the experiment: 42 natural images of animals (14 butterflies, 14 birds, and 14 fish; “living things”), and 42 inanimate objects (e.g. computer, bike; “non-living things”) were presented in the study phase. Animate stimuli were used as targets (“Old stimuli”). To familiarize participants with the stimulus materials, eight practice stimuli were presented at the beginning of the study phase. None of the practice stimuli was included in the main experiment. In the study phase, the first and last three stimuli were identical for all participants. These six stimuli were not used at test to avoid any Primacy-Recency-Effect (Atkinson & Shiffrin, 1968). All other stimuli were randomized in both study- and test phases. In the test phase 36 Old stimuli were used. Additionally, 36 new filler stimuli were presented at test. The program Presentation (Version 14.2, Neurobehavioral Systems) was used to program and run both study- and test phases.

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2.3. Procedure The experiment started with the screening interview. In the following study phase, participants executed 84 trials with the following structure: presentation of a stimulus for 500 ms, a response screen showing the (verbal) options “living” on the left side and “non-living” on the right side of the screen, and a fixation cross for one second in the interstimulus interval. Participants were instructed to respond as early and accurate as possible. The standard neuropsychological testing battery was applied after the study phase. The testing battery did not include tests or stimulus materials, which could have confounded our measures of priming. Thereafter, the test phase was implemented which was identical for all three groups. Half of the stimuli were presented in colored, the other half in gray-scaled format. Each stimulus was shown either in colored or gray-scaled format. All stimuli of the test phase were subdivided into 10 levels of fragmentation by the software "Image Modifier” (Helbach, 2009). The level of fragmentation by which a stimulus was correctly recognized was taken as a measure of perceptual priming (i.e. the recognition stage). Thus, earlier recognition stages indicated better identification performance. The presentation of each stimulus began with its most fragmented degree. The final level of fragmentation was the original image of the corresponding stimulus. Each fragmentation was displayed until a participant pressed the continue-button, indicating that he/she was unable to recognize the stimulus. Immediately after the key-press response, the next lesser degree of fragmentation of the same stimulus appeared. By pressing the recognition-button the participant indicated that he/she recognized the stimulus. The recognition response was followed by a naming screen. Participants were asked to type the name of the recognized stimulus. Naming the stimulus was implemented as a control-measure, to ensure whether participants correctly recognized the stimulus or pressed the recognition-button by mistake. After typing, the participant pressed the enter-button, indicating that he/she would like to continue with the next stimulus. Then a fixation cross appeared for 500 ms, followed by the next stimulus in its most fragmented degree. In case where a participant had pressed the continue-button for all levels of fragmentation of a stimulus, the fixation cross then also appeared, and subsequently the next stimulus was presented. 3. Results Only those stimuli were analyzed, that were correctly identified in the test phase. Altogether, there were less than 1.7% wrong designations and the error rate did not differ between groups (F(2) = 2.36, p = .112, f = .36). There was a main effect of groups (Control vs. Color vs. Gray), Λ = 0.04, F(10, 52) = 20.19, p < .001. Follow-up ANOVAs revealed significant effects of Old (all together; F(2, 30) = 165.12, p < .001, f = .94), colored Old (F(2, 30) = 119.34, p < .001, f = .93), and gray-scaled Old recognition stages (F(2, 30) = 97.22, p < .001, f = .92). All post-hoc tests revealed significant results (p < .001; Table 1). Table 1. Two-tailed Bonferroni analyses for Old stimuli between participant groups.

Old (all)

Colored Old

95% CI Group comparisons Control-Group

Mdiff SD Color-Group

min

max

3.86 0.98 3.32 4.40

Gray-scaled Old

95% CI Mdiff 4.14

SD

min

max

1.27 3.45 4.82

95% CI Mdiff 3.95

SD

min

max

1.31 3.23 4.68

Control-Group

Gray-Group

1.68 0.98 1.14 2.22

1.64

1.27 0.95 2.32

1.77

1.31 1.05 2.49

Color-Group

Gray-Group

-2.18 0.98 -2.72 -1.64

-2.50

1.27 -3.18 -1.82

-2.18

1.31 -2.90 -1.46

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Mdiff = mean difference, SD= standard deviation, CI = confidence interval, min = lower limit, max = upper limit.

Bonferroni analyses showed a significant difference between recognition stages of gray-scaled Old stimuli of the Color-Group (mean = 3.82, SD = 0.87) compared with gray-scaled Old stimuli of the Gray-Group (mean = 6.00, SD = 0.63; meandiff = -2.18, SD = 1.31, p < .001; see Table 1 & Fig. 2). 4. Discussion The primary goal of the present study was to examine the influence of color information on perceptual priming. The results demonstrate that color information of implicitly learned colored photos enhanced the subsequent recognition of the same fragmented photos. Importantly, this was not only the case for stimuli that were presented in color, but also for their gray-scaled variants at test. In contrast, unconsciously learned grayscaled photos led to delayed recognition of the same fragmented photos in both color and gray-scaled variants. Our findings are thus consistent with those of Uttl et al. (2006) and Wippich and Mecklenbräuker (1998) who previously reported that color information may enhance perceptual priming. Our data complement results of these studies in that they provide first evidence that color information may already affect unconscious information processing in the learning phase of a perceptual priming experiment. Most importantly, in the present study, the Color-Group recognized gray-scaled stimuli significantly earlier than the Gray-Group. Even though our study did not address brain activity, this result supports the view that color information leads to a stronger representation of an unconsciously perceived stimulus at encoding. It is thus reasonable to assume that color information may enhance encoding, consolidation processes and/or storage of visual characteristics. Presumably, color information is treated with high priority in implicit visual memory processing. Some investigators did not find a significant advantage of color for perceptual priming (Cave et al., 1996; Cave & Squire, 1992; Seamon et al., 1997; Srnivias, 1996), while our study clearly demonstrates that color may enhance perceptual priming of natural picture stimuli. One reason for the absence of color effects on priming may be related to the use of outline drawings in the above studies. It is likely that outline drawings supply too less color information to cause significant effects on perceptual priming. This assumption needs to be investigated systematically in future studies comparing color effects on perceptual priming across a variety of different stimulus materials. Note that the use of natural images in our study also better relates to perceptual priming functions occurring in everyday life than the use of rather abstract line drawings. Weldon (1991) postulated that perceptual priming can be defined by the similarity between primes and targets such that any change of stimuli between study and test should therefore result in decreased priming. However, the similarity between primes and targets cannot only account for the perceptual priming effects found in our study. If similarity had been the crucial factor, the Color-Group should only have recognized colored photos earlier at test and the Gray-Group only gray-scaled ones. However, the Color-Group identified all photos of the study phase – 50% colored and 50% gray-scaled – at an earlier fragmentation stage than the Gray- or the ControlGroup. It needs to be further clarified how similarities between primes and targets may interact with other features of colored and gray-scaled stimuli (e.g. complexity, contrast) in the context of implicit visual memory processing. Taken together, our results indicate that color information of stimuli enhances perceptual priming of natural pictures. Most importantly, the data strongly suggest that color exerts its effects at encoding in the study phase. This finding may complement the current knowledge of cognitive processes underlying perceptual priming. It needs to be investigated more in future research on priming how encoding, consolidation, and storage processes may differentially be influenced by color information. Acknowledgements

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The work has been supported by German Research Foundation, CITEC – Center of Excellence 277, Cognitive Interaction Technology. References Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), The Psychology of Learning and Motivation: Advances in Research and Theory (pp. 89–195). New York: Academic Press. Bargh, J. A., & Chartrand, T. L. (2000). The mind in the middle: A practical guide to priming and automaticity research. In H. T. Reis & C. M. Judd (Eds.), Handbook of research methods in social and personality psychology (pp. 253–285). Cambridge, England: Cambridge University Press. Biederman, I., Mezzanotte, R. J., & Rabinowitz, J. C. (1982). Scene perception: Detecting and judging objects undergoing relational violations. Cognitive Psychology, 14(2), 143–177. Cave, C. B., & Squire, L. R. (1992). Intact and long-lasting repetition priming in amnesia. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18(3), 509–520. Cave, C. B., Bost, P. R., & Cobb, R. E. (1996). Effects of color and pattern on implicit and explicit picture memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(3), 639–653. Cermak, L. S., Talbot, N., Chandler, K., & Wolbarst, L. R. (1985). The perceptual priming phenomenon in amnesia. Neuropsychologia, 23(5), 615–622. Goodglass, H., Theurkauf, J. C., & Wingfield, A. (2008). Naming latencies as evidence for two modes of lexical retrieval. Applied Psycholinguistics, 5(2), 135–146. Groh-Bordin, C., Zimmer, H. D., & Mecklinger, A. (2005). Feature binding in perceptual priming and in episodic object recognition: Evidence from event-related brain potentials. Cognitive Brain Research, 24(3), 556–567. Helbach, J. (2009). Image Modifier (Version 0.97b) [Computer software]. Bielefeld: Bielefeld University. Seamon, J. G., Ganor-Stern, D., Crowley, M. J., Wilson, S. M., Weber, W. J., O'Rourke, C. M., & Mahoney, J. K. (1997). A mere exposure effect for transformed three-dimensional objects: Effects of reflection, size, or color changes on affect and recognition. Memory & Cognition, 25(3), 367–374. Srinivas, K. (1996). Contrast and illumination effects on explicit and implicit measures of memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(5), 1123–1135. Uttl, B., Graf, P., & Santacruz, P. (2006). Object color affects identification and repetition priming. Scandinavian Journal of Psychology, 47(5), 313–325. Weldon, M. S. (1991). Mechanisms underlying priming on perceptual tests. Journal of Experimental Psychology: Learning, Memory, and Cognition, 17(3), 526–541. Wiggs, C. L., & Martin, A. (1998). Properties and mechanisms of perceptual priming. Current Opinion in Neurobiology, 8(2), 227–233. Wippich, W., & Mecklenbräuker, S. (1998). Effects of color on perceptual and conceptual tests of implicit memory. Psychological Research, 61(4), 285–294.