A standardized set of 200 full color, real world pictures for use in psychology research.
The development of a scientifically useful picture set is quite labor intensive. The 260 Snodgrass and Vanderwart (S&V) concepts were required to meet three criteria before they were accepted into the picture pool. Each image had to be: easily identifiable, a category exemplar, and had to be a concept at the basic level of categorization. These criteria ensured that the selected concepts were generally agreed upon objects, and thus scientifically useful.
Once the concepts were determined, representational line drawings were created. Each line drawing was subsequently standardized on multiple variables: name agreement, image agreement, familiarity, and visual complexity (Snodgrass & Vanderwart, 1980). In the name agreement condition each stimulus was individually presented to participants who were instructed to identify each image by writing down its name. The image agreement condition required participants to form a mental representation of each concept prior to viewing it. Participants were then instructed to rate how closely the stimulus matched their previously formed mental image. The familiarity and visual complexity conditions required participants to rate how usual/unusual the stimulus was based upon their own experiences and the amount of detail or intricacy each object possessed respectively.
In the intervening years since the creation of this valuable picture set, scores of scientists have used these line drawings in a wide assortment of research projects. A literature search in Web of Science (March, 2014) revealed that the S&V picture set has been cited in excess of 3,000 times. Cognitive researchers have made use of the S&V stimulus set to differentiate the activity associated with spatial and object-based working memory (Singhal, 2006) as well as the role of priming in object recognition (Kennedy, Rodrigue, & Raz, 2007). Furthermore, this picture set has been used to examine disorders, such as speech deficits found in aphasia (Rose & Douglas, 2008) and factors associated with developmental dyslexia (Zoccolotti, De Luca, Judica, & Spinelli, 2008). Neuroscientists have also employed this picture set to investigate neurobiological concepts such as episodic encoding in relation to object recognition (Hofer, et al., 2007) and the neural activity associated with repetition effects (Guo, Lawson, & Jiang, 2007).
The S&V picture set has proven to be a useful stimulus set in non-English speaking cultures as well, being similarly normed in France (Alario & Ferrand, 1999), Italy (Nisi, Longoni, & Snodgrass, 2000), Iceland (Pind, Jonsdottir, Gissurardottir, & Jonsson, 2000), Britain (Barry, Morrisson, & Ellis, 1997) and Spain (Sanfeliu, & Fernandez, 1996). By norming the stimuli in different languages and cultures the stimulus set has developed a much wider range of application. Not only has it been normed in a variety of languages, since its inception the S&V picture set has been augmented and updated. Rossion and Pourtois (2004) were interested in the role of surface detail in object processing and were in need of a stimulus set to tease apart these differences. As a result two additional picture sets were fashioned out of the existing S&V picture set, one by adding color to each line drawing, the other by adding color and texture to each picture. In compliance with Snodgrass and Vanderwart, each picture was again subjected to strict standardizing measures. Normative data for each picture was acquired on a naming task, familiarity, visual detail, imagery agreement, and appropriateness of the color (Rossion & Pourtois, 2004).
In addition to these altered versions of the S&V picture set, several additional sets have been developed and normed over the years. Dell'Acqua, Lotto, and Job (2000) published an extensive picture set consisting of 266 black line drawings. Given the utility of good visual stimuli, this picture set has also been employed in a variety of studies, including neuroimaging investigations of conceptual knowledge (Zannino et al., 2006), crossmodal processing (Sestieri, et al., 2006), degradation in aphasic patients (Lesk, Womble, & Rumiati, 2007), category specific deficits (Siri, Kensinger, Cappa, Hood, & Corkin, 2003), and impairment in Alzheimer's (Zannino, Perri, Caltagirone, & Carlesimo, 2007) and schizophrenia (Anselmetti et al., 2007). In 2003 another novel set of objects was normed on a French sample. Each picture corresponded to the style of those produced by Snodgrass and Vanderwart, in being a line drawing with the necessary detail of the concept, but was intended to depict concepts that were more culturally relevant as well as those not well represented in the current picture bank (e.g. football helmet was eliminated, parchment and sphinx were added) (Bonin, Peereman, Malardier, Meot, & Chalard, 2003). This aforementioned picture set has also been employed in many experiments, for example: how planning interacts with spelling out picture names (Bonin, Malardier, Meot, & Fayol, 2006); how phonological encoding is influenced by literacy (Ventura, Kolinsky, Querido, Fernandes, & Morais, 2007); the role of spelling in the verbal production of picture names (Alario, Perre, Castel, & Ziegler, 2007); and the effect of encountering relevant visual characteristics in picture memory (Pecher, Zanolie, & Zeelenberg, 2007).
Although the database of visual stimuli has grown substantially, Snodgrass and Vanderwart's technique and method of developing and standardizing useable visual stimuli remain ubiquitous. Bates et. al. (2003) standardized 520 existing black-and-white line drawings (including 174 from Snodgrass and Vanderwart) in seven different languages (English, Spanish, Italian, Bulgarian, Hungarian, Chinese, and German) using the criteria originated by Snodgrass-Vanderwart. These established norming categories: name agreement, familiarity, and visual complexity, reappear again when 388 black-and-white line drawings from the European Standardized Picture Pool for Oral Naming were normed in Canadian French (Sirois, Kremin, & Cohen, 2006). Such examples suggest that some of the methods originally developed by Snodgrass and Vanderwart over 30 years ago are essential ingredients in the development of a scientifically useful picture set.
Aside from the picture sets previously mentioned, there are several stimulus sets that are primarily used as assessment tools, for example the Peabody Picture Vocabulary Test (Dunn & Dunn, 1981) and Boston Naming Test (BNT) (Kaplan, Goodglass, & Weintraub, 1983). These particular sets are of a more specialized nature, the Peabody, for example assesses verbal ability, while the BNT is primarily concerned with word retrieval. Neither is necessarily intended for a wide range of experimental purposes.
Although the current stimulus sets are extremely valuable and have provided enormous scientific benefit, not all questions concerning object processing can be answered with the majority of stimulus sets currently available. Specifically, how are real-world objects processed? This question is a natural precursor to how scenes are processed. To begin to answer such questions a standardized set of real world images is required. In the ongoing effort toward a comprehensive understanding of object and scene processing, a picture set composed of real world images will provide another avenue for investigating these unanswered questions. To date there are only two known picture sets that offer such an advantage: the BOSS (Brodeur, Dionne-Dostie, Montreuil & Lepage, 2010) and An Ecological Alternative to Snodgrass and Vanderwart (Moreno-Martlnez & Montoro, 2012). Both sets have provided the scientific community with valuable research tools for visual object processing, but have not been normed on color diagnosticity or by an American sample.
Development of this real world picture set utilized many of the methods employed during the creation of the groundbreaking Snodgrass and Vanderwart (1980) stimulus set. Each of our real world images was normed on four of the S&V criteria: name agreement, image agreement, familiarity, and complexity. However, we also collected normative data on the color diagnosticity of each picture. Where possible we also adhered to S&V orientation guidelines: animals were seen from the side, functional ends of objects faced down, and long, thin pictures were positioned at a 45[degrees] angle; however, good pictures were not eliminated if these criteria were not able to be met. It was our belief that if an image was easily identifiable and closely resembled the mental representations of our sample there was no need to remove it from our picture set, especially since objects are often encountered and recognized from a variety of different viewpoints.
Our picture norming project sought to improve the current picture database with the addition of a set of real world images that roughly correspond to the concepts established by Snodgrass and Vanderwart, while also providing current normative data based on an American sample. Providing the scientific community with a stimulus set composed of real world images and modernized conceptual names will offer a new tool to refine our knowledge of how humans process their visual environment. Many researchers appreciate the advantages of using stimulus sets possessing not only color and texture, but photographic detail as well. The demand for new, more realistic stimuli results from the distinct possibility that line drawings are likely to differ from real world images in the manner in which they are processed. Line drawings may be perceived as a concept instead of a specific instance of a category. If this is the case then real world pictures may be a necessary substitution for line drawings when investigating how objects are naturally processed. Another contribution of this project was to update the names associated with many of the concepts the research relies on. Each concept used in the project has been given the name agreed upon by at least 75% of the participants sampled. Given that picture sets are frequently used to investigate many topics within the realm of language processing it is imperative to continually update the colloquial name given to many of the standard concepts used in such research. Behavioral, neuropsychological, and neuroimaging researchers are likely to find a picture set of this nature to be a valuable tool in the ongoing investigation of object processing.
A total of 1200 students from the University of Nevada volunteered or received class credit for their participation in the various stages of this study (35 participants were also obtained from Truckee Meadows Community College). Participants were all undergraduate students whose ages ranged from 17 to 54 (mean: 20.85 yrs) and had normal or corrected to normal vision. Approximately half of the participants were randomly assigned to the name agreement/familiarity conditions (532) with the other half being assigned to the image agreement/familiarity conditions (522). Once the pictures set was complete we had another 83 participants assess each image on object complexity and color diagnosticity.
All efforts were made during stimulus collection to adhere to the image presentation strategies set forth by Snodgrass and Vanderwart. Pictures were displayed in an easily identifiable and prototypical view agreed upon by a panel of 2 graduate and 2 undergraduate students. This resulted in a picture set commonly displaying animals from the side and man made objects from a familiar point of view. The size of each real world picture is roughly 2.5 x 2.5 inches. The background of each picture was removed using Adobe Photoshop CS or GraphicConverter, and replaced with a uniform gray (rgb values: 128) 5 x 5 background (360 x 360 pixels; 72 pixel per inch resolution). The word stimuli used in the image agreement conditions was presented in 44 inch Arial font (each word was underlined and formatted with a bold font). All visual stimuli during the standardization tasks were presented on an EPSON 3LCD PowerLite 7900p projector. Stimulus presentation was automated and timed using Microsoft PowerPoint such that each stimulus remained visible for several seconds, allowing participants time to respond before moving onto the next trial. All pictures can be obtained from http:/ericclapham.wix.com/cognitionlab.
The first phase of standardizing this picture set was carried out in two complementary conditions: name agreement and image agreement. Participants, who were randomly assigned to each condition, were run in a group setting ranging roughly from 10 to 50 people. Once all participants had arrived they were provided with an answer sheet and given verbal instructions about each aspect of their involvement. Participants in the name agreement conditions were instructed to view each picture and, if possible, name it using the most common and straightforward language. Participants wrote this name in the space provided during the specified time. Image agreement conditions directed participants to develop a mental image of a specified object (initially displayed as a word to cue imagery) and indicate how closely this mental representation resembled the picture that subsequently followed. Furthermore, participants from both groups were also instructed to indicate how familiar they were with the pictured objects. Familiarity refers to how common or uncommon the object is in their experiences. Participants were to rate the concept, not the picture.
The various norming conditions contained between 25-110 pictures that eventually added up to the 200 pictures comprising this set. Each picture was ultimately assessed by a minimum of 50 participants. Throughout the process pictures were removed, due to lack of name agreement, image agreement, or familiarity, as well as added to the set until we had normed 200 pictures. If a picture failed to reach the predetermined criterion (75% name agreement across a minimum of 50 participants) for acceptance into the picture set one of two solutions was employed. The picture was either replaced with a different exemplar for the same concept and re-normed or a new concept was adopted and normed in its place. When a picture received poor feedback on a second occasion we did not hesitate to acquire a picture from a new concept as long as it met the fixed standards. In other words the picture needed to be of a familiar, highly recognizable object.
In the final phase of the norming process we collected information pertaining to the complexity and color diagnosticity for each picture. This information was obtained in a separate norming session once our picture set was complete. Therefore the participants that completed this aspect of the process viewed and evaluated all 200 pictures on one of the two measures.
Name Agreement Condition. Name agreement data were collected by sequentially presenting each object and requiring participants to write down its most common name. Participants were instructed to identify each object as briefly and unambiguously as possible. Each object was presented for 12 seconds after which a tone was sounded and the picture was replaced by the next image in the sequence. The tone was presented to alert the participants to the subsequent stimulus presentation. Participant also rated the familiarity of each object during the 12- second presentation time. This process continued until all pictures were presented.
Image Agreement Condition. This condition required participants to compare our pictures to their prototypical mental representation of each specific concept. Participants were first presented with a printed word accompanied by a soft tone to draw attention to the screen. Each printed word was presented for a duration of 4 seconds, allowing the participants time to develop a mental image of the object represented by the word. After the four-second word display the corresponding picture was then presented for comparison. Eight seconds was allotted for viewing the picture, making the comparison, and indicating how similar the pictured object was to the mental image created moments earlier. Participants indicated their similarity response using a 5-point Likert type scale where 1 indicated "not similar" and 5 "very similar." Each participant also rated the familiarity of each object during the four-second presentation time. The beginning of the next trial was signaled by the soft tone and appearance of a new word.
Familiarity. Familiarity ratings were obtained during both the image and name agreement conditions. Familiarity was defined as the extent to which one is exposed to the concept, the degree to which one thinks about or comes in contact with the concept during daily life. Participants were simply instructed to indicate how familiar the object is in their world. Ratings were made using a 5-point Likert type scale with 1 indicating "not familiar" and 5 "very familiar."
Object Complexity. Object complexity and color diagnosticity information was collected during the same norming sessions. Participants viewed each of the 200 pictures for 8 seconds, during which they were to indicate the complexity and color diagnosticity of each stimulus. The object complexity aspect of the norming session instructed participants to rate the complexity of each picture on a 5-point Likert type scale, where 1 indicated that the object pictured was "not complex" and 5 "very complex." Complexity was defined as the amount of detail or intricacy found in the picture. Participants were further instructed that they were to rate each specific picture, not the concept portrayed.
Color Diagnosticity. This portion of the project instructed participants to rate the color diagnosticity of each picture on a 5-point Likert type scale, where 1 indicated "not very diagnostic" and 5 "very diagnostic." Color diagnosticity was defined as the degree to which the primary color of the picture is associated with the particular object found in the image.
All normative data for the 200 real world pictures can be found at http:/ericclapham.wix.com/cognitionlab. Only pictures that met a 75% name agreement criterion were accepted into the picture set. In fact, the average name agreement score reached an impressive 95%. Additionally, image agreement and familiarity for each picture needed to average a 3 or greater on the associated 5 point Likert-type scale to be allowed into the set, averaging a 4.08 and 4.42 respectively. The average object complexity score was 2.8, while the color diagnosticity averaged a 3.46 on a 5 point scale.
Naming discrepancies that occurred over the norming process can also be found at http:/ericclapham.wix.com/cognitionlab. Included is the number of participants for each picture who did not know object (DKO), did not know name of object but recognized it (DKN), did not know the object in the familiarity conditions (FDKO), and alternative nondominant names and their frequencies.
A series of correlational analyses were also run to better understand how the five measures relate to one another. The correlational analysis of the five different measures revealed interesting yet predictable findings. Not only were image agreement and name agreement positively correlated (r = .296, p < .001) but familiarity was positively correlated with both name agreement (r = .344, p < .001) and image agreement (r = .211, p = .003), indicating that the concepts people are most familiar with tend to have a commonly agreed upon name and also elicit fairly precise mental representations. Furthermore, as the amount of detail and intricacy of the stimuli increased one's familiarity decreased (r = -.485, p <.001). Not surprisingly, color diagnosticity was positively correlated with image agreement (r = .352, p < .001); meaning that one's mental representation of an object likely possesses color, and if that color is highly diagnostic of that object (i.e. banana) the representation has a better chance of matching our stimuli and thus increases the image agreement rating. (See Table One for the correlation matrix.)
Our effort to establish a parallel between our picture set and the concepts of the S&V picture set appears to have been successful. When we analyzed the 177 concepts that are in both sets, relatively strong relationships were uncovered across all 4 shared measures: name agreement (r = .335, p < .001); image agreement (r = .390, p < .001); familiarity (r = .796, p < .001); and complexity (r = .669, p < .001). The strength of these correlations demonstrate that our picture set did follow the outline for creating stimulus sets put forth by Snodgrass and Vanderwart over 30 years ago.
The present work will provide the scientific community with a relatively novel and useful stimulus set. Up to this point researchers have primarily had access only to line drawings, and over the years these have proven to be extremely vital resources. However, there is a wealth of research suggesting that surface features play an essential role in object processing (Callaghan, 1984; Rossion & Pourtois, 2004; Tanaka, Weiskopt, & Williams, 2001; Troscianko & Harris, 1988). Therefore, a stimulus set consisting of photographic object representations, complete with all the surface characteristics indicative of each object (e.g. color, texture, and shading), will be especially valuable.
Our pictures set was intended to approximate many of the same concepts initially established by Snodgrass and Vanderwart over 30 years ago. As a result, many of their concepts are also represented here as well. However, because many of the pictured concepts taken from S&V did not reach an acceptable standard on name agreement, image agreement, or familiarity some had to be reexamined (e.g. alligator) and eventually replaced (e.g. lizard). Due to the photographic nature of this set, the addition of new concepts, and the empirically driven conceptual naming updates this set is fundamentally different from the current standard.
Given that the present picture set is created from real world color images based closely on the S&V picture set we expected to obtain similar agreement ratings with many of the stimulus sets composed entirely of line drawings. The familiarity ratings obtained here surpassed that obtained in previous work, the one measure that is independent of the actual pictures, and instead is intended to express the degree of experience with the concept. Because the familiarity measure does not rely on the pictures themselves, some comparisons between the current and previous picture sets seem acceptable. Familiarity has been reported at 3.29 (on a scale from 1 to 5, with high scores indicating more familiarity) for the Snodgrass and Vanderwart picture set and 3.59 for the Rossion and Pourtois set (as reported in Rossion & Pourtois, 2004), but the familiarity reported here averaged 4.42. This is likely the consequence of a variety of variables.
Throughout the development of this picture set a number of pictures did not norm well, as they lacked consistency on name or image agreement and were at times updated with more recognizable pictures. As a result of this method many of the newly added pictures were quality images that resulted in high scores across all measures. Furthermore, in order to assess familiarity, participants needed to be cued to the concept of interest. This was done by first presenting the participants with the actual pictures. Even though the task was to indicate how familiar the concept, not the picture, was, the images might have inflated familiarity responses. The real world images used here may have led to a greater sense of familiarity within our sample, as our pictures more closely resemble the objects we encounter in our daily lives. Whereas line drawings that lack the photographic detail offered in this set, might not trigger such episodic familiarity. As a result of this effect our pictures may cue a more specific memory representation than would a line drawing, leading to the higher, and perhaps more accurate familiarity scores. Also, these familiarity scores were collected during the same norming sessions as name agreement and image agreement. It is therefore possible that because we had our participants recall additional information (the name or physical characteristics) prior to indicating how familiar they were with the concept, that a more encompassing concept was actually rated on familiarity. In any effect it appears that this picture set contains relevant and recognizable images that are good examples of objects found within our everyday environment.
Participants also provided homogenous feedback in the image and name agreement conditions. An average name agreement of 95% was obtained, suggesting that pictures in this set are good exemplars of the selected concepts. This further demonstrates that this picture set offers quality images that a vast majority of English speakers will identify by the same linguistic tag. Furthermore, because the object names offered here are taken directly from the name agreement data, it is fair to say we have also provided updated labels for these concepts. We accomplished such positive results by using many of the concepts originally established in the Snodgrass and Vanderwart picture set (1980), and substituting other well-known concepts for those that were not easily recognized by our modern sample. Because our real world images purposely maintained distinguishing surface details and colors, image agreement averaged a respectable 4.08 out of a possible 5.
The object sets currently available are, for the most part, comprised of line drawings. This has allowed researchers ample control of many variables that are otherwise inherently linked to the object. Line drawings offer the opportunity to remove, for example, color from the recognition process, providing valuable insights into the role that other physical characteristics play in object identification. However, there are many unanswered questions that will require the use of real life images in order to address them appropriately.
One such example is research that relies on briefly presented stimuli. Such research often addresses how the seemingly irrelevant information that enters the visual system affects subsequent behavior. In such situations stimuli that provide the full compliment of characteristics, similar to those our visual system evolved to process, would be a great benefit in the exploration of such sensitive effects (Gegenfurtner & Rieger, 2000). Furthermore, real world images are essential when attempting to dissociate different types of common cognitive processing. A great deal of research tells us that there are often important differences in how distinctive categories are processed; often times these differences are both functional and cortical. We know, for example, that emotionally negative stimuli are processed differently than those that elicit a more positive emotion (Morel, Ponz, Mercier, & Vuilleumier, George, 2009); a variety of other types of categorical information may also vary in priority of processing, especially those that evoke strong emotional responses. Dissociating these processes requires both behavioral and neuroimaging evidence, both of which would profit from visual stimuli that reflect real life objects, allowing for the most ecologically relevant processing.
The present project offers an additional picture set that is fundamentally different from most available stimulus sets currently available. This paper also provides the normative data to accompany this high-quality full color pictorial set providing the reader with information characterizing the quality and familiarity of each pictorial representation. It is our hope that this picture set will become a valuable investigative tool in the cognitive and brain sciences, aiding in the exploration of numerous phenomena.
Alario, F. X., & Ferrand, L. (1999). A set of 400 pictures standardized for French: Norms for name agreement, image agreement, familiarity, visual complexity, image variability, and age of acquisition. Behavior Research Methods, Instruments, & computers, 31, 531-552. doi:10.3758/BF03200732
Alario, F. X., Perre, L., Castel, C., & Ziegler, J. (2007). The role of orthography in speech production revisited. Cognition, 102, 464-475. doi:10.1016/ j.cognition.2006.02.002
Anselmetti, S., Cavallaro, R., Bechi, M., Angelone, S. M., Ermoli, E., Cocchi, F., et al. (2007). Psychopathological and neuropsychological correlates of source monitoring impairment in schizophrenia. Psychiatry Research, 150, 51-59. doi: 10.1016/j.psychres.2005.12.004
Barry, C., Morrison, C. M., & Ellis, A. W. (1997). Naming the Snodgrass and Vanderwart pictures: Effects of age of acquisition, frequency, and name agreement. Quarterly Journal of Experimental Psychology, 50A, 560-585. doi: 10.1080/027249897392026
Bates, E., D'Amico, S., Jacobsen, T., Szekely, A., Andonova, E., & Devescovi, A. (2003). Timed picture naming in seven languages. Psychonomic Bulletin & Review, 10(2), 344-380. doi:10.3758/BF03196494
Bonin, P., Malardier, N., Meot, A., & Fayol. (2006). The scope of advance planning in written picture naming. Language and Cognitive Processes, 21, 205-237. doi:10.1080/01690960400002141
Bonin, P., Peereman, R., Malardier, N., Meot, A., & Chalard, M. (2003). A new set of 299 pictures for psycholinguistic studies: French norms for name agreement, image agreement, conceptual familiarity, visual complexity, image variability, age of acquisition, and naming latencies. Behavior Research Methods, Instruments, & Computers, 35, 158-167. doi:10.3758/ BF03195507
Brodeur, M. B., Dionne-Dostie, E., Montreuil, T., & Lepage, M. (2010). The Bank of Standardized Stimuli (BOSS), a new set of 480 normative photos of objects to be used as visual stimuli in cognitive research. PLoS ONE, 5, e10773.doi:10.1371/journal.pone.0010773
Callaghan, T. (1984). Dimensional interaction of hue and brightness in preattentive field segregation. Perception & Psychophysics, 36(1), 25-34. doi:10.3758/BF03206351
Dell'Acqua, R., Lotto, L., & Job, R. (2000). Naming times and standardized norms for the Italian PD/DPSS set of 266 pictures: direct comparisons with American, English, French, and Spanish published databases. Behavioral Research Methods, Instruments, & Computers, 32, 588-615. doi:10.3758/ BF03200832
Dunn, L. M., & Dunn, L. M. (1981). Peabody picture vocabulary test-revised. Circle Pines, MN: American Guidance Service.
Gegenfurtner, K. R., & Rieger, J. (2000). Sensory and cognitive contributions of color to the recognition of natural scenes. Current Biology, 10(13), 805-808. doi: 10.1016/S0960-9822(00)00563-7
Guo, C., Lawson, A. L., & Jiang, Y. (2007). Distinct neural mechanisms for repetition effects of visual objects. Neuroscience, 149, 747-759. doi:10.1016/j.neuroscience. 2007.07.060
Hofer, A., Siedentopf, C. H., Ischebeck, A., Rettenbacher, M. A., Widschwendter, C. G., Verius, M., et al. (2007). The neural regions sustaining episodic encoding and recognition of objects. Brain and Cognition, 63, 159-166. doi: 10.1016/j.bandc.2006.11.001
Kennedy, K. M., Rodrigue, K. M., & Raz, N. (2007). Fragmented pictures revisited: Long-term changes in repetition priming, relation to skill learning, and the role of cognitive resources. Gerontology, 53(3), 148-158. doi: 10.1159/000098029
Kaplan, E. F., Goodglass, H., & Weintraub, S. (1983). Boston naming test. Philadelphia: Lea & Febiger.
Lesk, V., Womble, S. P., & Rumiati, R. I. (2007). Testing graceful degradation in a patient with aphasia. Neurocase, 13, 248-255. doi:10.1080/13554790701595489
Morel, S. Ponz, A., Mercier, M., Vuilleumier, P., & George, N. (2009). EEG-MEG evidence for early differential repetition effects for fearful, happy and neutral faces. Brain Research, 1254, 84-98. doi:10.1016/ j.brainres.2008.11.079
Moreno-Martinez, F. J., & Montoro, P. R. (2012). An ecological alternative to Snodgrass & Vanderwart: 360 high quality colour images with norms for seven psycholinguistic variables. PloS ONE, 7, e37527. doi:10.1371/ journal.pone.0037527
Nisi, M., Longoni, A. M., & Snodgrass, J. G. (2000). Italian measurement on the relation of name, familiarity, and acquisition age for the 260 figures of Snodgrass and Vanderwart. Giornale Italiano di Psicologia, 27, 205-218.
Pecher, D., Zanolie, K., & Zeelenberg, R. (2007). Verifying visual properties in sentence verification facilitates picture recognition memory. Experimental Psychology, 54(3), 173-179. doi:10.1027/1618-3126.96.36.199
Pind, J., Jonsdottir, H., Gissurardottir, H., & Jonsson, F. (2000). Icelandic norms for the Snodgrass and Vanderwart (1980) pictures: Name and image agreement, familiarity, and age of acquisition. Scandinavian Journal of Psychology, 41, 41-48. doi:10.1111/1467-9450.00169
Rose, M., & Douglas, J. (2008). Treating a semantic word production deficit in aphasia with verbal and gesture methods. Aphasiology, 22(1), 20-41. doi: 10.1080/02687030600742020
Rossion, B., & Pourtois, G. (2004). Revisiting Snodgrass and Vanderwart's object pictorial set: the role of surface detail in basic-level object recognition. Perception, 33, 217-236. doi:10.1068/p5117
Sanfeliu, M. C., & Fernandez, A. (1996). A set of 254 Snodgrass-Vanderwart pictures standardized for Spanish: Norms for name agreement, image agreement, familiarity, and visual complexity. Behavior Research Methods, Instruments, & Computers, 28, 537-555. doi:10.3758/BF03200541
Sestieri, C., Di Matteo, R., Ferretti, A., Del Gratta, C., Caulo, M., Tartaro, A., et al. (2006). "What" versus "Where" in the audiovisual domain: An fMRI study. NeuroImage, 33, 672-680. doi:10.1016/j.neuroimage.2006.06.045
Siri, S., Kensinger, E. A., Cappa, S. F., Hood, K. L., & Corkin, S. (2003). Questioning the living/nonliving dichotomy: evidence from a patient with an unusual semantic dissociation. Neuropsychology, 17(4), 630-645. doi:10.1037/ 0894-4188.8.131.520
Singhal, A. (2006). Differentiating between spatial and object-based working memory using complex stimuli: an ERP study. International Journal of Neuroscience, 116, 1457-1469. doi:10.1080/00207450500514342
Sirois, M., Kremin, H., & Cohen, H. (2006). Picture-naming norms for Canadian French: name agreement, familiarity, visual complexity, and age of acquisition. Behavior Research Methods, 38(2), 300-306. doi:10.3758/ BF03192781
Snodgrass, J. G., & Vanderwart, M. (1980). A standardized set of 260 pictures: Norms for name agreement, image agreement, familiarity, and visual complexity. Journal of Experimental Psychology: Human Learning & Memory, 6, 174-215. doi:10.1037/0278-73184.108.40.206
Tanaka, J, Weiskopf, D., & Williams, P. (2001). The role of color in high-level vision. Trends in cognitive Sciences, 5(5), 211-215. doi:10.1016/ S13646613(00)01626-0
Troscianko, T., & Harris J. (1988). Phase discrimination in chromatic compound gratings. Vision Research, 28(9), 1041-1049. doi:10.1016/0042 6989(88)90081-8
Ventura, P., Kolinsky, R., Querido, J. L., Fernandes, S., & Morais, J. (2007). Is phonological encoding in naming influenced by literacy? Journal of Psycholinguist Research, 36, 341-360. doi:10.1007/s10936-006-9048-1
Zannino, G. D., Perri, R., Caltagirone, C., & Carlesimo, G. A. (2007). Category-specific naming deficit in Alzheimer's disease: The effect of a display by domain interaction. Neuropsychologia, 45, 1832-1839. doi:10.1016/ j.neuropsychologia.2006.12.011
Zannino, G. D., Perri, R., Pasqualetti, P., Di Paola, M., Caltagirone, C., & Carlesimo, G. A. (2006). The role of semantic distance in category-specific impairments for living things: evidence from a case of semantic dementia. Neuropsychologia, 44, 1017-1028. doi:10.1016/ j.neuropsychologia. 2005.11.006
Zoccolotti, P., De Luca, M., Judica, A., & Spinelli. (2008). Isolating global and specific factors in developmental dyslexia: a study based on the rate and amount model. (RAM). Experimental Brain Research, 186, 551-560. doi:10.1007/s00221-007-1257-9
Note: The norming data and the 200-item picture set can be found at: http://ericclapham.wix.com/cognitionlab
Eric S. Clapham
Black Hills State University
Aaron T. Karst
University of Wisconsin, Oshkosh
C. Mark Wessinger
CogNeuro Learning, Inc.
Author info: Correspondence should be sent to: Eric Clapham, Ph.D., Psychology Department, Black Hills State University, 1200 University St., Unit 9004, Spearfish, SD 57799
TABLE 1 Correlation Matrix IA IC CD Fam NA 0.293 * (<.001) -0.156 * (.028) 0.037 (.599) 0.355 * (<.001) IA -0.188 * (.008) 0.352 * (<.001) 0.211 * (.003) IC 0.211 * (.003) 0.211 * (<.001) CD -0.133 (.06) Note: NA: name agreement; IA: image agreement; IC: image complexitiy; CD: color diagnosticity; Fam: familiarity. Image Complexity correlations with NA & IA remained significant when Bonferroni corrected.
|Printer friendly Cite/link Email Feedback|
|Author:||Clapham, Eric S.; Karst, Aaron T.; Wessinger, C. Mark|
|Publication:||North American Journal of Psychology|
|Date:||Dec 1, 2014|
|Previous Article:||Correlations and sex differences in seven sensory modalities of imagery.|
|Next Article:||Five-factor personality and cooperative behavior.|