We also collected ratings of fear and disgust in this experiment in an effort to corroborate the pupillary data. After rating images for arousal, participants rated each image (randomized order) on fear and disgust with the questions, “How fearful does this image make you feel?” and “How disgusted does this image make you feel?” on a 7-point scale ranging from 1 (“not at all”) to 7 (“extremely”).

In this experiment, participants also rated the images for level of arousal. Participants provided ratings of their subjective arousal to each image following the free viewing phase. Each image was presented onscreen (randomized order) with the question, “how does this image make you feel overall?” Participants responded on a 7-point scale ranging from -3 (“very negative”) to 3 (“very positive”). Arousal was calculated as the absolute value of the rating, regardless of valence ( Bradley & Lang, 2007 ; but see, Kuppens et al., 2013 , for alternative perspectives on measuring arousal).

All aspects of image presentation were identical to Experiment 1. In particular, each trial began with the baseline phase (6 s) and was followed by the image phase (6 s). Images were presented in a randomized order. Any trials where participants did not fixate to the screen (during baseline or image phase) were excluded from statistical analyses (1.6% of trials). Participants were tested in a brightly lit room, seated in a chinrest 60 cm from the computer monitor. Eye gaze was calibrated using a 5-point calibration routine, and pupil area was recorded using an Eyelink-1000 plus eye-tracker (SR-Research) recording at 1,000 Hz.

Stimulus presentation consisted of 60 images (512 × 512 px; 13.5°× 13.5°): 20 images of holes, 20 images of threatening animals (i.e., spiders and snakes), and 20 non-hole control images (see Fig. 1 ). The images of holes and threatening animals were identical to those used in Experiment 1. The non-hole control images consisted of individual objects or patterns with contrasting textures (e.g., checkerboard; see Fig. 1D ). As in Experiment 1, all images were gray-scaled and equated for luminance using the SHINE toolbox for Matlab (mean luminance = 115.17; Mathworks; Willenbockel et al., 2010 ).

Forty-four undergraduate students ( M age = 19.80 years; 30 females) participated for course credit. None of the participants in the current experiment participated in the previous experiment. Two participants from the current sample were removed from the results reported below because of a failure to fixate on the images for at least half of the experiment. In this experiment, participants also completed the trypophobia questionnaire designed by Le, Cole & Wilkins (2015) . The questionnaire was completed after participants viewed all of the images during which their pupillary responses were recorded. Participants’ scores on the trypophobia questionnaire ( M = 25.5, Mdn = 20, range = 17–83) fell within the normal range of the population who experience aversion to the images of holes but who may not self-identify as trypophobes ( Le, Cole & Wilkins, 2015 ).

Results

As discussed above, the relatively greater pupillary constriction to images of holes could reflect high contrast, HSF information in these images. To address this possibility, we included control images with similar repetitive features and we then conducted an analysis of spatial frequency on the three image categories (holes, threat, and control) to ensure that the images were comparable. Images were analyzed for spatial frequency at five contrast energy levels (10%, 30%, 50%, 70%, and 90%; Bainbridge & Oliva, 2015). A Pearson correlation analysis revealed a negative relation between spatial frequency and pupil size, rs(58) = − 0.415 to −0.616 (across energy levels), such that images with higher spatial frequencies elicited a smaller pupil, consistent with the pupil grating response (Barbur & Thomson, 1987; Cocker et al., 1994). Next, we compared stimulus categories across contrast energy levels with a 5 × 3 repeated-measures ANOVA with contrast energy (10%, 30%, 50%, 70%, and 90%) as the within-subjects factor and stimulus type (holes, threat, and control) as the between-subjects factor. This analysis revealed a main effect of contrast energy, F(4, 228) = 217.220, p < 0.001, η p 2 = 0 . 792 , such that spatial frequency increased with contrast energy, as expected for this image set. But, critically, there was no main effect of stimulus type (p = 0.213, η p 2 = 0 . 053 ), nor a contrast energy by stimulus type interaction (p = 0.189, η p 2 = 0 . 047 ), demonstrating that spatial frequency was comparable across the image categories. However, because this analysis relies on the interpretation of a null effect, we also computed the expected power of this image set (Cohen, 1992), as well as the Bayes factor (BF 10 ; Rouder et al., 2012) for the contrast energy by stimulus type interaction. These analyses revealed that with 60 images we had 99% power (1-β) to detect a medium-sized effect, and that the posterior distribution was in favor of the null hypothesis, BF 10 = 0.220. Thus, although a pupil grating response was evident in our data, these analyses suggest that spatial frequency was comparable across the image categories at all contrast energy levels.

As in the previous experiment, we then tested for an effect of stimulus type (i.e., holes, threat, and control) on pupillary size by conducting a repeated measures ANOVA with the dependent variable of percent pupil-size change. There was a significant main effect of stimulus type, F(2, 82) = 15.469, p < 0.001, η p 2 = 0 . 274 (see Fig. 3). Post-hoc tests (Holm-Bonferroni corrected) revealed that pupil-size change was, again, greater for holes than threatening images (p < 0.001), replicating the effect of Experiment 1. Moreover, and crucially, pupil-size change was also greater for holes than the control images (p < 0.001), which, in this experiment, consisted of high contrast repetitive patterns similar to holes, and which we confirmed were comparable in spatial frequency. Finally, there was a non-significant trend in the expected direction for the difference between threatening images and the control images (p = 0.085), with greater pupil dilation to spiders and snakes than control images. These findings replicate those of Experiment 1 by demonstrating a dissociation between pupillary responses to holes compared with threatening animals. They also demonstrate that the pupillary response to holes is not identical to that of other high-contrast, repetitive stimuli, thereby providing additional support for a parasympathetic response to holes and consistent with our hypothesis that holes elicit a disgust reaction.

Figure 3: Pupillary waveforms across time for each stimulus type in Experiment 2. The x-axis reflects trial time in seconds (s) and the y-axis reflects the percentage of pupil-size change from baseline, such that greater percent change corresponds to a smaller pupil size. Shaded colors represent SEM.

However, an alternative possibility for these findings is that the images differed in arousal level. To address this possibility, we first conducted a one-way ANOVA on stimulus type (holes, threat, and control), which yielded a significant main effect of stimulus type on participants’ arousal ratings, F(2, 57) = 162.780, p < 0.001, η p 2 = 0 . 851 . Post-hoc tests (Holm-Bonferroni corrected) revealed significant differences for all pairwise comparisons (ps < 0.001). Specifically, control images induced the least arousal, followed by holes, followed by the threatening category (see Table 1). Given these differences in arousal level, we conducted an additional analysis of stimulus type (holes, threat, and control) on pupil-size change while controlling for the effects of arousal. Participants’ pupil measurements for each image were regressed on arousal level, and a repeated-measures ANOVA was conducted on the residual values. This analysis yielded a significant main effect of stimulus type, F(2, 82) = 13.373, p < 0.001, η p 2 = 0 . 246 . Post-hoc tests (Holm-Bonferroni corrected) revealed significant differences between holes and threatening images (p < 0.001), as well as between holes and controls (p < 0.001; no difference between threatening images and controls, p = 0.663), generally consistent with the analyses above. Taken together, the results from this experiment suggest that greater pupil constriction is specific to images of holes and not more generally applicable to non-hole repetitive images. Moreover, these results demonstrate that pupillary constriction to holes cannot be accounted for by differences in arousal level.

Stimulus type Rating Arousal Fear Disgust Holes 0.91 (0.96) 1.94 (1.53) 2.47 (1.85) Control 0.42 (0.79) 1.11 (0.50) 1.09 (0.44) Threat 1.51 (1.06) 3.58 (2.19) 3.57 (2.24) DOI: 10.7717/peerj.4185/table-1