Artists Excel on Image Activation But Not Image Manipulation Tasks

Abstract

The ability to envision what is not directly seen is important in the visual arts, since artists do more than reproduce what they see. Such envisioning requires visual imagery abilities. In this study, we examined whether art students (n = 32) have enhanced visual imagery abilities compared to nonart students (n = 40). We administered four tasks designed to assess visual imagery. Three tasks assessed the ability to activate mental images: vividness of visual imagery, recognition of out-of-focus pictures, and abstraction; the fourth task assessed the ability to manipulate mental images: mental rotation. We also administered a verbal IQ and a creativity test to determine whether these measures should be included as covariates in our analyses. Results showed that art students excelled on two of the three image activation tasks, vividness of visual imagery and abstraction, but did not excel on the image manipulation task of mental rotation.

Keywords

visual imagery drawing artists creativity visualization

Visual imagery involves generating, inspecting, and transforming mental images of scenes, objects, experiences, or events that are not observable—either because they are not present, not available to the naked eye, or because they do not exist (Kosslyn, 1980; Kosslyn, Thompson, & Ganis, 2006). Visual artists provide a clear example of the ability to go beyond the information given. They rarely simply reproduce what they observe, but instead use observation as a jumping off point, or eschew observation entirely to create images entirely from their imagination (Varnedoe, 2006). Artists must conjure up images in their minds (image activation) and must modify these images as they plan their works (image manipulation). We examined how burgeoning visual artists (in the form of art students) perform on three image activation tasks: vividness of visual imagery, recognition of out-of-focus pictures, and envisioning the underlying structure of a drawing (abstraction). We also examined their performance on an image manipulation task: mental rotation. On all of these tasks, visual art students were compared to nonart students.

Vividness of Visual Imagery

By vividness of visual imagery, we refer to the ability to conjure up scenes that are vivid and clear—a skill critically important when artists work from memory. Visual artists report vivid mental imagery (Pérez-Fabello & Campos, 2007), with individuals scoring high on creative behavior in art also scoring high on vividness of imagery (Morrison & Wallace, 2001).

Out-of-Focus Pictures

By recognition of out-of-focus pictures, we refer to the ability to fill in missing visual information by activating the parts that are not seen. This kind of skill should be useful to artists when they glance at a scene far away and are able to imagine (and thus depict) the parts they cannot clearly see. Individuals with art training have also been shown in some studies to have superior image activation abilities: They are able to generate images of named shapes and hold these in mind (Winner & Casey, 1993), identify images with missing parts (Zemore, 1995), and identify objects in blurry photographs (Kozbelt, 2001; but also see Chamberlain et al., 2019 and Chamberlain & Wagemans, 2015 who failed to show an artist superiority on this task).

Abstraction

By abstraction, we refer to the ability to look at a complex scene or object and envision its unseen, underlying, and essential structure. This is an important skill for visual artists, who must grasp the important forms of a subject, noting figure–ground relationships, and the features of objects most critical to identifying them (Seeley & Kozbelt, 2008). Artists and designers are often admired for their creative ability to reduce objects “to a few essential flashes of direction or shape” (Arnheim, 1969, p. 113) and have been shown to excel in tasks that require abstraction compared to nonartists. In a Limited-Line Tracing Task developed by Kozbelt et al. (2010), artists and nonartists were asked to create a rendering of an elderly man’s face using a specific number of thin pieces of tape. The task does not require any drawing or creativity but does require visually selecting the most important features to depict using the pieces of tape. Artists outperformed nonartists on this task when the subject matter to be depicted was a human face (Kozbelt et al., 2010) or an entire animal such as an elephant (Ostrofsky, Kozbelt, & Seidel, 2012).

Mental Rotation

By mental rotation, we refer to the ability to create a mental image of something observed and then to manipulate that image mentally, rotating it in three-dimensional space. Artists have been shown to have superior image transformation abilities, as assessed by the ability to rotate images mentally (Kozbelt, 2001). John Ruskin (1856/2011, p. 25) remarked on British painter J. M. W. Turner’s ability to paint a seascape actually observed from one vantage point and then to “turn it round on the table of his brain, and look at it from the other corner.” Image transformation abilities have been reported to be associated with visual creativity (Palmiero, Nori, Aloisi, Ferrara, & Piccardi, 2015). And high school students after 2 years of intensive art lessons were shown to improve geometric thinking, which often involves mental manipulation of imagery (Goldsmith, Hetland, Hoyle, & Winner, 2016). However, some studies have failed to show superior mental rotation abilities in artists (Casey, Winner, Brabeck, & Sullivan, 1990; Palmiero & Srinivasan, 2015).

Whereas previous research has examined visual imagery skills in artists, no study has examined these components of visual imagery in one study. In addition, previous research has yielded mixed results with some studies finding enhanced visual imagery skills in artists and others finding no difference between artists and nonartists. The goal of our research was to test the hypothesis (supported by the research just reviewed) that artists have stronger capacities in these four areas than do nonartists. We included measures that assessed both image activation and image manipulation to determine whether art students show superiority in both of these areas. As vividness of imagery and creativity are related (Morrison & Wallace, 2001), we assessed overall creativity as well as verbal IQ in order to determine whether these should be controlled for in our analyses.

Methods

Participants

The art students were 32 fourth-year art and design majors (22 females, 9 males, and 1 unspecified; ages 21–26 years, M = 21.1, SD = 1.2) who were recruited from the Pratt Institute in Brooklyn, NY. The Pratt Institute is a highly selective art and design school where students are accepted for admission based on their artistic and drawing abilities. Art students received $40 for their participation. The nonart students were 40 psychology majors (32 females and 8 males; ages 18–21 years, M = 19.1, SD = 0.9) who were recruited from an undergraduate subject pool and received course credit for their participation. The art student group was 46.9% Caucasian, 40.6% Asian, 6.3% Hispanic or Latino, 3.1% Biracial, and 3.1% Black or African American. The nonart student group was 60% Caucasian, 20% Hispanic or Latino, 12.5% Asian, 5.0% Biracial, and 2.5% Black or African American. The racial and gender composition did not differ by group, χ² (4, n = 72) = 8.785, p = .067 and χ² (2, n = 72) = 2.047, p = .359, respectively. A one-way analysis of variance (ANOVA) revealed that the art students were older (M_age = 21.8, SD = 1.3) than the nonart students (M_age = 19.1, SD = 0.9), F(1, 70) = 118.279, p < .001, d = 2.53. When we included age as a covariate in a subsequent analysis, our results did not change. In addition, and not surprisingly, a one-way ANOVA also revealed that art students had completed more years of formal art lessons (M_age = 6.6, SD = 4.2) than the nonart students (M_age = 1.7, SD = 2.7), F(1, 70) = 35.236, p < .001, d = 1.73. We do not view this as a problem, given that our goal was not to determine whether artists’ imagery skills are a function of inborn talent or experience or both. None of the nonart students reported being an art major or minor.

Materials and Measures

We administered four measures of visual imagery and two control measures (verbal IQ and overall creativity). We used measures of visual imagery that were closely related to the kinds of skills that artists possess, including measures that assess image activation (vividness of visual imagery, recognition of out-of-focus pictures, abstraction) and image manipulation (mental rotation). The IQ and creativity measures were administered to determine whether to control for these measures in our statistical analyses.

Visual Imagery Measures

Vividness of visual imagery

To assess vividness of visual imagery, we administered the Vividness of Visual Imagery Questionnaire (VVIQ; Marks, 1973) which is a self-report measure that assesses the ability to conjure up visual images in a clear and vivid way. Participants were presented with 16 items (e.g., “The sun rising above the horizon into a hazy sky”) and were asked to form a visual image of the item. For each image, they rated how vivid they experienced it on a 5-point scale from do not have a visual image to perfectly clear and vivid as real setting. An overall score was computed by averaging the 16 items.

Recognition of out-of-focus pictures

The Out-of-Focus Pictures Task, similar to that used by Kozbelt (2001) and recently used by Chamberlain et al. (2019), assesses the ability to go beyond the information given to identify the object represented in the image. Because this task requires going beyond the information given, we suggest that this task requires filling in what one can see with visual imagery. Participants were presented with 15 gray-scale pictures in a random order on a laptop computer that varied in level of blurriness. The laptop was placed at an arm’s distance from the participant. The pictures were blurred based on a Gaussian blur at 100 pixels at 2, 4, 6, or 8 radii. The Gaussian blur weights pixels that are close in distance to each other. A larger radii has more pixels and therefore blurs out more fine details in the picture (i.e., a higher radius creates a blurrier picture). We selected radii that gave us a range of levels of blurriness. The pictures consisted of animals, scenes, and objects and the picture set contained no duplicate images. Figure 1 presents examples of the blurred pictures at 2, 4, 6, and 8 radii. Each picture was presented for 15 seconds, and participants were instructed to identify what was in each picture by typing a free response after the picture was shown. Participants were given unlimited time to type their free response before moving on to the next picture. Participants first completed two practice items and were given feedback and then proceeded on to 15 test items without feedback. Responses were coded for accuracy independently by two raters. Raters coded the open-ended responses using a key of correct responses developed by Chamberlain et al. (2019). Raters practiced coding using responses from the Chamberlain study, and once 80% agreement was achieved on the practice responses, they coded responses from this study. Responses that named an exemplar or the class of the object (e.g., tulip or flower) were counted as correct. Summed accuracy scores were then calculated for each participant. Two versions of the task were used, randomized by participant.

Figure 1.
Examples of the abstraction task at the four levels of blurriness: 2 radii (a), 4 radii (b), 6 radii (c), and 8 radii (d).

Abstraction

We assessed abstraction through the Limited-Line Tracing Task (Kozbelt et al., 2010; Ostrofsky et al., 2012). Participants were presented with a gray-scale photograph of an elephant on a white piece of letter paper that was placed inside a clear plastic folder. They were asked to create an abstracted drawing of the elephant by tracing over the photo directly onto the folder using 30 short pieces of thin tape (2 cm × 2 mm). Participants were instructed to use all pieces of tape and were told they could bend the pieces of tape but could not tear them into smaller pieces. They were given 10 minutes to complete the task. This task assesses the ability to abstract the essential features of a complex organic form (an elephant) and does not require any free-hand drawing. This task required going beyond the information given to envision the underlying structural forces of the elephant’s body. As in Kozbelt et al., drawings were scored for level of accuracy on an 8-point scale from low to high accuracy by two of the authors of this study (J. E. D. and E. W.). Figure 2 shows tracings rated high in accuracy (top) that represent depth and show the internal structure of the elephant; and tracings rated low in accuracy (bottom) that depict only the outline of the elephant. Tracings in the top row were made by art students and tracings in the bottom row were made by nonart students.

Figure 2.
Tracings by art (top) and nonart students (bottom).

Mental rotation

We assessed image manipulation through a version of a mental rotation task that we designed in which participants were asked to visualize what a scene would look like if viewed from a different vantage point than the one directly observed. This task requires going beyond the information given because one must take what one can see and rotate it in one’s mind, much like Turner was observed to have done. Participants were presented with a target photograph of a still-life consisting of an arrangement of objects on a table, along with four photographs of the same scene, each taken from a different angle (45° to the left or right, 90° to the left or right, or a full 180°; Figure 3). The task was to identify the photograph that showed the scene from one of these three angles. Photographs were presented in a PowerPoint presentation on a lap top computer. Participants were given 5 minutes to complete 20 items. Summed accuracy scores were computed for each participant.

Figure 3.
Target photograph (top) and four possible answer choices (middle and bottom). Participants were instructed to imagine the photograph that was 45° to the left of the target photograph.

Control measures

Our two control measures, described below, examined whether art students and nonart students differed in verbal IQ and overall creativity in case these factors should be controlled for in our analyses.

Verbal IQ

Participants completed the verbal section of the Wechsler Adult Intelligence Scale, Fourth Edition (WAIS-IV; Wechsler, 2008). Participants were presented with a word (e.g., apple) and were asked to provide a definition of that word. Items were scored on a scale from 0 to 2. Using the apple example, a score of 0 would represent an incorrect or vague definition (e.g., put in mouth), 1 a correct response but lacking in content (e.g., food), and 2 a correct definition (e.g., a piece of fruit). The test was discontinued after participants scored 0 on three consecutive items.

Overall creativity

To assess overall creativity, we administered the verbal and figural versions of the Abbreviated Torrance Test of Creative Thinking (ATTA; Goff, 2002). The ATTA consists of three tests (one verbal and two figural) and participants were given a maximum of 3 minutes to complete each test. In the verbal test, they were told the following: “Just suppose you can walk on air or fly without being in an airplane or similar vehicle. What problems might this create? List as many as you can.” In the first figural test, participants were asked to create a drawing from a simple shape presented on a sheet of paper; in the second figural test, participants were presented with a sheet of paper containing nine triangles and were asked to make a series of drawings from the triangles. Participants were instructed to provide titles for their drawings. None of these tasks require the generation of imagery. For all three tests, participants were encouraged to make their responses as novel and as interesting as possible. Two independent raters coded the responses for fluency, originality, flexibility, and elaboration and scaled scores for overall creativity were then computed. The raters first practiced scoring data from the Chamberlain et al.’s (2019) study. Once 80% agreement was achieved on the practice items, the raters scored the data from this study.

Procedure

Participants were tested individually in a quiet room. We administered the measures in the following order: creativity test, four visual imagery measures (mental rotation, abstraction, recognition of out-of-focus pictures, vividness of visual imagery), and verbal IQ. The college’s institutional review board approved the study, and all participants provided written informed consent.

Results

Statistical Analysis

Interrater reliability was calculated as follows: out-of-focus pictures, r = .90; abstraction, r = .64; and overall creativity, r = .66. For these three tasks, disagreements were resolved by discussion between the two raters. Cronbach’s alpha was as follows: vividness of visual imagery, α = .77; mental rotation, α = .628; and overall creativity, α = .655.¹

A homogeneity of variance test revealed equal variances between the two groups on vividness of visual imagery—F(1, 70) = 0.149, p = .701—recognition out-of focus pictures—F(1, 70) = 0.399, p = .529—and mental rotation—F(1, 70) = 3.003, p = .088. These variables were included in a multivariate analysis of variance (MANOVA) by group. The homogeneity of variance was violated for the abstraction task—F(1, 70) = 37.284, p = .001—and we therefore performed a Mann–Whitney test to assess the difference between the two groups on this measure. Because each of the measures had different scales, we converted each raw score to a z score by group and ran the analysis using the z scores.

Visual Imagery Measures

Table 1 presents the means and standard deviations for the visual imagery measures, verbal IQ, and overall creativity by group. A MANOVA by group on verbal IQ and overall creativity, revealed that, surprisingly, the nonart students scored higher in overall creativity than the art students—F(1, 70) = 7.712, p = .007, $η_{p}^{2}$ = .099. There were no differences between the groups in verbal IQ.

Table 1.
Means and Standard Deviations on the Visual Imagery Measures, Verbal IQ, and Overall Creativity by Art Students and Nonart Students.

Highest possible score
Art students
Nonart students

Measure M SD M SD F p

Vividness of visual imagery 5 4.1 0.5 3.6 0.4 23.847* <.001

Recognition out-of-focus pictures 15 6.3 1.9 6.6 2.2 0.500 .482

Abstraction 8 4.0 1.9 3.5 0.8 7.113 .009

Mental rotation 20 12.6 2.9 11.6 3.5 1.567 .215

Verbal IQ 52 28.5 10.8 30.8 7.1 1.114 .295

Overall creativity 76 42.7 16.2 50.9 8.6 7.712** .007

Note. The median is reported for the abstraction task.

p < .01. *p < .001.

As can be seen in Table 1, art students performed significantly better than nonart students on two of the four measures: vividness of visual imagery—F(1, 70) = 23.847, p < .001, $η_{p}^{2}$ = .254—and abstraction (U = 468, p = .047). No differences were found between the two groups on the recognition of out-of-focus pictures and mental rotation. The results remained unchanged when age and overall creativity was included as covariates.

Discussion

The goal of our research was to pinpoint the kinds of visual imagery abilities that were higher in artists than in nonartists. We narrowed our investigation to tasks that assessed image activation (vividness of visual imagery, recognition of out-of-focus pictures, abstraction) and image manipulation (mental rotation). We found that art students outperformed nonart students on two of the three image activation tasks, specifically vividness of visual imagery, and abstraction. We found no difference in performance between art students and nonart students on the image manipulation task.

Surprisingly, nonart students outperformed art students on overall creativity. However, we note that our creativity measure was administered only to determine whether to control for this in our statistical analyses. On the one hand, it is possible that the Torrance measure does not capture the creative abilities of visual artists. Perhaps measures of problem finding in the visual arts developed by Getzels and Csikszentmihalyi (1976) would do a better job at capturing the domain-specific creativity of visual artists. On the other hand, the Pratt curriculum focused more on drawing from observation than drawing from imagery. It may be possible that the Torrance tests were tapping into another aspect of creativity that was not developed in the Pratt curriculum.

Two of our findings are consistent with previous research. First, as reported by Kozbelt et al. (2010) and Ostrofsky et al. (2012), we found that art students excelled at the abstraction task—reducing a scene to its essential features. When drawing, artists must be able to abstract essential details from the vast three-dimensional world and represent these on a small piece of paper (Gombrich, 1960). This skill was called for in our abstraction task: success required viewing a complex organic form (the body of an elephant) and depicting the underlying (unseen) structure of the body. Second, we found that artists have superior visual imagery skills as assessed by a self-report measure. Whereas previous research has demonstrated that art students are better able to generate mental images than nonart students (Winner & Casey, 1993; Zemore, 1995), we showed that the vividness with which these images are mentally generated is also superior in art students compared to nonart students.

On two of our measures, nonart students performed equivalently to art students, mental rotation, and recognition of out-of-focus pictures. Contrary to one previous report (Kozbelt, 2001) but consistent with two others (Casey et al., 1990; Palmiero & Srinivasan, 2015), we found no artist superiority on mental rotation. Our null result cannot be due to the task being too difficult or too easy, as we did not find any floor or ceiling effects. Although Kozbelt used a task in which participants see two forms and must rotate one to determine whether it is the same form as the other, we showed participants a still-life with multiple objects and asked them to show how the scene would look if rotated to a specified angle. We used this task rather than a standard mental rotation task used in previous studies because we wanted a task that seemed closer to what artists actually do as they plan a drawing, that is, like Turner, they look at a scene and rotate it as they decide the angle from which to depict it. We note that previous studies examining whether artists are superior at mental rotation have been mixed, and our study adds to the null findings. Of course to be certain that our null results were not due to the task used, future research should compare artists’ performance on our task and a standard one. We also found no difference on the recognition of out-of-focus pictures, which required participants to visually analyze ambiguous images to determine their subject matter. This result may not be surprising, given the mixed previous evidence on this task. Using the same images, our results are consistent with Chamberlain et al. (2019) who found no difference in performance between art students and nonart students. Kozbelt (2001) found differences in performance between artists and nonartists, but the images he used showed unusual angles and cropping, making the task more difficult, which may have resulted in more striking differences between these two groups.

A limitation to this study is that we did not administer a task to assess the participants’ artistic or drawing abilities or to differentiate between the art and nonart students. The art students were surely not as skilled as professional artists, but it is also possible that some of the nonart students may have been talented in drawing, and this may have explained the null findings on two of our visual imagery measures. The argument against this, however, is that the nonart students reported only a very limited number of years of art lessons, and none of them identified as art majors and minors. In addition, the art students were drawn from a highly selective art school.

In summary, we show here that art students outperform nonart students on some but not all visual imagery tasks. Our art students showed superiority on image activation (albeit in two out of three of our measures) but not image manipulation. Replicating Ostrofsky et al. (2012), we showed that art students were better able to draw the simplified underlying structure of an object as evidenced by their performance on the abstraction task. They also reported a greater ability to visualize complex scenes as evidenced by their performance on a self-report measure assessing vividness of visual imagery. Future research should replicate these findings with a larger battery of imagery tasks with artists.

	Highest possible score	Art students	Nonart students
Vividness of visual imagery	5	4.1	0.5	3.6	0.4	23.847***	<.001
Recognition out-of-focus pictures	15	6.3	1.9	6.6	2.2	0.500	.482
Abstraction	8	4.0	1.9	3.5	0.8	7.113**	.009
Mental rotation	20	12.6	2.9	11.6	3.5	1.567	.215
Verbal IQ	52	28.5	10.8	30.8	7.1	1.114	.295
Overall creativity	76	42.7	16.2	50.9	8.6	7.712**	.007

Footnotes

Acknowledgments

The authors thank Anastasia Lanzara, Elen Zanotti, Nat Rabb, Rachel Chazanoff, Julia Jones, Jemima McLean, and Sarah Mochkin for their help with conducting this research. The authors also thank Kim Sloane for his assistance with recruitment and his input on the project.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported with a Grant from the Imagination Institute of The John Templeton Foundation to Jennifer E. Drake.

Note

Author Biographies

Jennifer E. Drake is an assistant professor in the Psychology Department at Brooklyn College, City University of New York, USA.

Seymour Simmons is a retired associate professor in the Fine Arts Department at Winthrop University, USA.

Seth Rouser is an assistant professor in the Fine Arts Department at Winthrop University, USA.

Isabella Poloes received her BA in Psychology from Brooklyn College, City University New York, USA.

Ellen Winner is a professor in the Psychology Department at Boston College, USA.

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	Highest possible score	Art students		Nonart students
Measure	Highest possible score	M	SD	M	SD	F	p
Vividness of visual imagery	5	4.1	0.5	3.6	0.4	23.847***	<.001
Recognition out-of-focus pictures	15	6.3	1.9	6.6	2.2	0.500	.482
Abstraction	8	4.0	1.9	3.5	0.8	7.113**	.009
Mental rotation	20	12.6	2.9	11.6	3.5	1.567	.215
Verbal IQ	52	28.5	10.8	30.8	7.1	1.114	.295
Overall creativity	76	42.7	16.2	50.9	8.6	7.712**	.007