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Abstract

Visual regularities activate the visual cortex and generate an Event Related Potential (ERP) called the Sustained Posterior Negativity (SPN). Previous research suggests that aesthetic preference and SPN amplitude correlate: People like the visual regularities that generate a large SPN. We found further evidence from a new study, which built on SPN results from previous research. As predicted, participants preferred reflection, circular and radial Glass patterns to translational Glass patterns (reflection = circular = radial >> translation). These results support the perceptual fluency model and suggest that preference for abstract symmetry is not predominantly a side effect of innate attraction to symmetrical faces.

Keywords

symmetry Glass patterns aesthetics beauty Sustained Posterior Negativity

Introduction

Humans are attracted to symmetry in faces (Rhodes et al., 1998) and abstract symmetrical patterns (Birkhoff, 1932; Boselie & Leeuwenberg, 1985; Makin et al., 2012). Symmetry preference has been observed in mammals, birds, and insects (Grammer et al., 2003; Møller, 1992; Møller & Thornhill, 1998; Wignall et al., 2006).

In fMRI studies, visual symmetry activates the extrastriate cortex, including shape-sensitive lateral occipital complex (Keefe et al., 2018; Kohler et al., 2016; Sasaki et al., 2005; Tyler et al., 2005; Van Meel et al., 2019; Zamboni et al., 2024). In EEG studies, symmetrical and random patterns both generate Event Related Potentials (ERPs) at posterior electrodes. After the initial P1 and N1 peaks, amplitude is lower for symmetry (Figure 1). The symmetry-random difference wave is called the Sustained Posterior Negativity (SPN). Many studies have identified systematic effects on SPN amplitude (Höfel & Jacobsen, 2007; Jacobsen et al., 2018; Jacobsen & Höfel, 2003; Makin et al., 2016, 2022). For example, the SPN becomes larger (more negative) as we increase the proportion of symmetry in symmetry plus noise displays (Makin et al., 2020).

Figure 1.

The parametric Sustained Posterior Negativity (SPN) response to 20, 40, 60, 80 and 100% symmetry. A) Event Related Potentials (ERPs) from posterior electrodes. After the P1 and N1 peaks, amplitude is lower for symmetrical patterns. B) The SPNs as a difference from the random wave with 95% CI Ribbon. The traditional 300-1000 ms SPN interval is highlighted . A large SPN is a difference wave that falls a long way below zero during this interval. C) Topographic difference maps, aligned with example stimuli. Here the SPN appears darker at the back of the head. In A, B and C, we can see that the SPN scales with the amount of symmetry in the stimulus. Data from Makin et al. (2020). Figure adapted from those in Makin et al. (2022) and Karakashevska et al. (2025).

Glass patterns are another kind of visual regularity. These were first described by Glass (1969) and have been widely studied since (Clifford & Weston, 2005; Dakin, 1997; Glass & Pérez, 1973; Krekelberg et al., 2005; Seu & Ferrera, 2001; Wilson & Wilkinson, 1998). In Glass patterns, dot pairs form oriented dipoles. Local orientation signals must be pooled over a large area to detect the global Moiré structure. Glass patterns have approximately the same visual salience as reflectional symmetry, even though they do not have the same ecological significance (van der Helm & Leeuwenberg, 1996). Circular, radial and translational Glass patterns are shown in Figure 2, along with matched random and reflection patterns composed of the same dot dipoles. The five stimulus types were used in Rampone and Makin (2020).

Figure 2.

Example Glass Patterns (Circular, Radial and Translation) along with random and reflection patterns.

Previous work has shown that SPN amplitude correlates with subjective beauty, both in the UK and Egypt (Makin et al., 2018). Put simply, humans like the kinds of visual regularity that produce large brain responses. In the current study, we tested this theory again with a new stimulus set. We tested whether the SPN amplitudes measured by Rampone and Makin (2020) predict preference for the stimuli used by Rampone and Makin (2020). SPNs for circular Glass patterns, radial Glass patterns and reflectional symmetry were all around −2 microvolts. The SPN for translational Glass patterns was around 1 microvolt (Figure 3). Therefore, translation should theoretically be liked less than the other three regularities.

Figure 3.

SPN responses for Glass patterns and reflectional symmetry. Results from Rampone and Makin (2020).

Glass patterns are an interesting stimulus class because they like reflectional symmetry in some ways but very different in other ways. Like reflection, local information must be pooled to detect the global gestalt. Unlike reflection, Glass patterns do not signal health in potential mates or rivals, and Glass patterns are not a property of beautiful faces. Therefore, Glass patterns may help elucidate the relationship between visual processing and visual preference .

Current Study

We ran a new between subject's experiment with 4 groups of 24 participants. Each participant was presented with examples of one regular pattern type (circular, radial, reflection or translation) and matched random patterns. The study had three parts, as shown in Figure 4. Thes are called the art engagement question, discrimination task, and evaluation task.

Figure 4.

Screenshots from the three parts of the online experiment. Participants completed the art engagement question, then discrimination task, and then the evaluation task. In this example, the patterns are Circular Glass.

We first collected Art engagement ratings from each participant. Using a sliding scale, participants answered the following question:

How much do you engage with visual art and art history? For example, painting, visiting museums and art galleries, taking courses in art and art history?

The exploratory art engagement aspect was inspired by Leder et al. (2019). These authors found that most people like symmetry, but art experts sometimes preferred asymmetry. Art engagement may negatively correlate with preference for reflectional symmetry in the current study.

In the Discrimination task, participants viewed the patterns and judged if they were regular or random as quickly and accurately as possible. Error rate and response time provide a direct measure of visual salience. We predicted that performance would be worse for translation patterns than the other three regularities.

In the Evaluation task, participants evaluated the same patterns with a continuous sliding scale, ranging from ugly to beautiful. We predicted that preference for circular, radial and reflection patterns would be larger than preference for translation.

Our predictions and analysis plan were pre-registered on aspredicted.org.

Method

Participants

A sample of 96 participants was collected with the online Gorilla platform (age 18 to 30, 8 handed, 7 male). The study had local ethics committee approval and was conducted in accordance with the declaration of Helsinki (revised 2008).

Procedure

Each participant first completed the art engagement question, then the discrimination task, then the evaluation task. Participants were presented with the same regularity type in both tasks (e.g., circular Glass patterns, Figure 4). In the discrimination task, there were 60 exemplars in each condition (120 trials in total). Participants pressed the A key to report ‘no regularity’, and the L key to report ‘some regularity’. In the evaluation task, there were 20 exemplars in each condition (40 trials in total). All participants were shown the same exemplars in different randomized orders.

Details about the stimuli are reported in Rampone and Makin (2020) section 2.1.3. Key details are repeated here. Information about degrees of visual angle has been omitted, because viewing distance was variable in this online study. The stimuli were generated a priori and saved as .png image files. Consequently, the seed information described in Rampone and Makin (2020) is also omitted.

There were 200 dipoles in each pattern. The dipole position was restricted to a circular region with a large outer perimeter and small inner perimeter to avoid overlap with the central red fixation cross. In all pattens there were 100 dipoles on either side of a central meridian. For the radial Glass patterns, the angle for each dipole was set so orientation was always orthogonal to the circumference of the circular region. For the circular Glass patterns, the dipoles were positioned tangentially to the circumference. For the translation Glass patterns, the orientation of the dipoles ranged between 0° and 180° in steps of 18°. Here there were 10 different translation orientations, each used an equal number of times. In a random pattern, dipole orientation ranged randomly and independently from 0° and 180°. Finally, for the reflection patterns, the orientation of the dipoles was assigned randomly for the left half of the pattern (in the same way as for the random patterns) and then mirrored on the right, giving one fold vertical reflection.

PsychoPy code for stimulus generation, along with images used in the experiment, are available on open science framework. The size of the stimuli varied depending on the participant's monitor, browser window, and viewing distance. For most participants, stimuli would have been at least 10 degrees wide.

Analysis

From the discrimination task, we computed error rate and median response time (RT) on regular trials.

Analysis of the evaluation task was slightly more complicated. We obtained ratings from the 0–100 scale for all regular and random patterns. We then computed mean ratings for regular, and mean rating for random. Finally, we computed relative preference for each participant. This is mean rating for the regular patterns – mean rating for the random patterns. A positive relative preference score indicates that the participant preferred regular to random. This relative preference score was also used in Makin et al. (2018).

Predicted results for error rate, response time and relative preference were tested with three separate Univariate ANOVAs. Each ANOVA had one between subjects’ factor [Regularity type, (circular, radial, reflection, translation)]. Pairwise differences were examined with independent sample's t tests.

For error rate and response time, at least one variable violated the assumption of normality (Shapiro-Wilk test, p < 0.05). Results were replicated with non-parametric Kruskal-Wallis tests (smallest effect, Kruskal Wallis H = 18.256, p < 0.001). Relative preference scores did not significantly violate the normality assumption (Shapiro-Wilk tests >> 0.05).

Results

Results are shown in Figure 5. As expected, translation patterns differed from the other three regularity types. They were detected less accurately and less quickly in the discrimination task. They were also liked less in the evaluation task.

Figure 5.

Results from the discrimination task (error rate and median response time), and evaluation task (relative preference). Each dot corresponds to one participant. Boxplot and distribution features are also included in the same order.

These impressions were confirmed by a significant effect of Regularity type on error rate (F (3,92) = 15.826, p < 0.001, η² = 0.340), response time (F (3,92) = 6.717, p < 0.001, η² = 0.180) and relative preference (F (3,92) = 8.737, p < 0.001, η² = 0.222). In all cases, translation was significantly different to the other three types (smallest effect, t (48) = 2.437, p = 0.019, d_s = 0.704).

Relative preference was significantly greater than 0 in the circular (t (23) = 7.657, p < 0.001, d_z = 1.563), radial (t (23) = 9.344, p < 0.001, d_z = 1.907) and reflection groups (t (23) = 7.813, p = < 0.001, d_z = 1.595), but not in the translation group (t (23) = 1.817, p = 0.082, d_z = 0.371).

Of the 24 participants in the circular group, 23 evaluated circular patterns as more beautiful than random. The figure was 24/24 in the radial group and 23/24 in the reflection group (p < 0.001, binomial test). However, only 16/24 evaluated translation as more beautiful than random in the translation group (p = 0.152, binomial test).

No Correlation with Art Engagement

There were no significant correlations involving art engagement in any group (Figure 6A). Most strikingly, we found almost no correlation between art engagement and preference for reflectional symmetry (r = 0.024, p = 0.910, Figure 6B). While non-significant results are inconclusive, we confirmed the absence of a correlation with Bayesian correlation analysis (BF01 = 3.926). Furthermore, art engagement did not correlate with preference across the full sample of 96 participants, when controlling for group mean preference (r = 0.048, p = 0.641, BF01 = 7.042, Figure 6C).

Figure 6.

A) Correlations between art engagement, error rate, response time and preference for each regularity type. B) More detailed visualization of art engagement vs. preference correlation the reflection Group (N=24). C) More detailed visualization art engagement vs. normalized preference for all groups (N=96). There was no relationship between preference and art engagement. In Panels B and C, curves show distribution of individual data points on the x and y axes, and the grey ribbon shows 95% confidence interval around the Linear trend line. All panels produced in JASP version 0.19.1.

Discussion

Previous work has found that SPN amplitude predicts preference for different kinds of visual regularity (Makin et al., 2018). We found further evidence by measuring preferences for stimuli used in Rampone and Makin (2020). Rampone and Makin (2020) found that SPNs were large and similar for circular Glass patterns, radial Glass patterns and reflectional symmetry, but smaller for translational Glass patterns. We thus predicted that participants would find circular, radial and reflection patterns more beautiful than translation patterns. This prediction was confirmed. Our study again shows that preference for regularity is closely related to the size of the brain response to regularity in the extrastriate visual cortex.

ERPs are electrophysiological signatures of distinct perceptual and cognitive operations in the brain. We found that one such ERP - the SPN - predicts preference. Other negative ERPs, such as the N1, the Mismatch Negativity (MNN) or Error Related Negativity (ERN) may or may not be systematically correlated with preference. They are generated by different neural populations and were not tested in this study. Most importantly, we note that this research does NOT tell us whether the Stimulus Preceding Negativity (also abbreviated SPN) predicts preference.

The results areconsistent with the fluency account of aesthetics. This account claims that people are sensitive to the speed and efficiency of their own perceptual processes. Fluent processing has a positive hedonic tone, so people tend to like stimuli that are processed fluently (Reber, 2012). In support, we found that participants preferred the patterns that were detected quickly (circular, radial and reflection) more than those that were detected slowly (translation).

There are also evolutionary considerations. It is potentially adaptive to be attracted to symmetrical faces and bodies, because phenotypic symmetry could be a truthful indicator of health (Møller & Thornhill, 1998). This innate attraction may overgeneralize onto abstract symmetrical patterns (Ramachandran & Hirstein, 1999). Such overgeneralization might be a ubiquitous phenomenon: For example, our innate reactions to babies may cause miniature objects to look cute. However, this overgeneralization account only applies to reflectional symmetry. We found that circular and radial Glass patterns are just as subjectively beautiful as reflection, but they are not at all face like. We propose that the beauty of reflectional symmetry is NOT primarily a side effect of innate attraction to symmetrical faces.

Additional exploratory analysis found no correlation between art engagement and preference. This was surprising, because previous work has found that art experts sometimes acquire an unusual taste for asymmetry (Leder et al., 2019). However, our participants were psychology students, and few were highly engaged with visual art (see distributions in Figure 6B and C). It is likely that none of our participants engaged with art as deeply as the people recruited from art and art history departments recruited by Leder et al. (2019). It remains a possible that SPN amplitude predicts preference in lay people, but not in experts, who may cultivate more subtle tastes. The public SPN catalogue database can facilitate this future work.

In summary, we found further evidence that people like the most fluently processed patterns that produce the largest brain response. Future work should seek exceptions to the rule. It would be interesting to discover a type of abstract visual regularity for which preference was not predicted by SPN amplitude. Such an outlier might have special aesthetic significance.

Furthermore, psychological states which require deeper stimulus processing and elaboration, rather than mere viewing and rating, might decouple preference and SPN amplitude. Such psychological states might also have special aesthetic significance.

Footnotes

Acknowledgements

This study was covered by an ESRC proposal awarded to Alexis Makin (ES/S014691/1).

ORCID iDs

Alexis D.J. Makin

Farah Akthar

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the , (grant number ES/S014691/1).

Declaration of Conflicting Interests

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

Data Availability Statement

All stimuli, codes for generating stimuli, datasets, and analysis codes are available on open science framework (https://osf.io/8cmks/). EEG data from Rampone and Makin (2020) is available in the project 15 subfolder of the complete Liverpool SPN catalogue on open science framework ().

Author Biographies

Alexis D. J. Makin is a Lecturer in Psychology at the University of Liverpool. His area of research is visual neuroscience focusing on symmetry perception.

Farah Akthar is a Lecturer in Psychology at the University of Liverpool. Her area of research is clinical vision, forcusing on degenerative eye disorders.

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Aesthetic Preference for Glass Patterns is Predicted by Known Activations of the Extrastriate Visual cortex

Abstract

Keywords

Introduction

Current Study

Method

Participants

Procedure

Analysis

Results

No Correlation with Art Engagement

Discussion

Footnotes

Acknowledgements

ORCID iDs

Funding

Declaration of Conflicting Interests

Data Availability Statement

Author Biographies

References