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Article  |   January 2025
Pupil responds spontaneously to visuospatial regularity
Author Affiliations & Notes
  • Zhiming Kong
    Department of Psychology, Hangzhou Normal University, Hangzhou, Zhejiang, China
    Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, Zhejiang, China
    [email protected]
  • Chen Chen
    Department of Psychology, Hangzhou Normal University, Hangzhou, Zhejiang, China
    Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, Zhejiang, China
    [email protected]
  • Jianrong Jia
    Department of Psychology, Hangzhou Normal University, Hangzhou, Zhejiang, China
    Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, Zhejiang, China
    [email protected]
  • Footnotes
    * ZK and CC contributed equally.
Journal of Vision January 2025, Vol.25, 14. doi:https://doi.org/10.1167/jov.25.1.14
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      Zhiming Kong, Chen Chen, Jianrong Jia; Pupil responds spontaneously to visuospatial regularity. Journal of Vision 2025;25(1):14. https://doi.org/10.1167/jov.25.1.14.

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Abstract

Beyond the light reflex, the pupil responds to various high-level cognitive processes. Multiple statistical regularities of stimuli have been found to modulate the pupillary response. However, most studies have used auditory or visual temporal sequences as stimuli, and it is unknown whether the pupil size is modulated by statistical regularity in the spatial arrangement of stimuli. In three experiments, we created perceived regular and irregular stimuli, matching physical regularity, to investigate the effect of spatial regularity on pupillary responses during passive viewing. Experiments using orientation (Experiments 1 and 2) and size (Experiment 3) as stimuli consistently showed that perceived irregular stimuli elicited more pupil constriction than regular stimuli. Furthermore, this effect was independent of the luminance of the stimuli. In conclusion, our study revealed that the pupil responds spontaneously to perceived visuospatial regularity, extending the stimulus regularity that influences the pupillary response into the visuospatial domain.

Introduction
The environment we perceive is organized in both space and time, and within it, we encounter patterns that repeat themselves. These repeated patterns form regularities that our cognitive systems learn to extract through statistical learning (Fiser & Lengyel, 2022; Forest, Siegelman, & Finn, 2022; Zhao, Al-Aidroos, & Turk-Browne, 2013). This ability to recognize and use regularities allows us to interact with our environment effectively. According to the information theory of sensory systems (Barlow, 2001), our sensory organs play a crucial role in sensing the regularity of environmental information. The pupil, which regulates the amount of light that enters the retina, is the initial stage of visual information processing (Mathôt, 2020). The size of the pupil is modulated by various cognitive factors, such as changes in brain state (Joshi & Gold, 2020; Reimer et al., 2016), the size of the stimulus (Gao, Ko, Yabe, Goodale, & Chen, 2020), and the size of the attentional field (Vilotijević & Mathôt, 2023). These changes in pupil size reveal high-level cognitive processing beyond the light reflex (Joshi & Gold, 2020). Therefore, the pupil's ability to adjust its size in response to the task's demands implies that it may regulate the amount of information it receives. 
The human pupil responds to a range of high-level visual properties (Joshi & Gold, 2020). Interestingly, it has been found that the statistical regularity of stimuli influenced the pupil's response. Previous studies have shown that the precision of the statistical distribution of the stimulus (Silvestrin, Penny, & FitzGerald, 2021), the surprise of the statistical regularity (Alamia, VanRullen, Pasqualotto, Mouraux, & Zenon, 2019), the violation of the temporal regularity of the stimulus (Zhao, Chait, et al., 2019), and the subjective statistical structure of the stimulus sequence (Schwiedrzik & Sudmann, 2020) all affected the pupillary response. Specifically, stimuli that were uncertain, ambiguous, unpredictable, or contained dispersed components resulted in greater cognitive demand and associated mental effort in participants, which resulted in greater pupil dilation (Kraus, Tune, Obleser, & Herrmann, 2023). However, these studies have only used auditory or visual temporal sequences as stimuli, limiting their conclusions’ generalization to more general cognitive processing scenarios. 
In the case of visual stimuli, the spatial arrangement is a common stimulus regularity and can influence stimulus processing (Castaldi, Pomè, Cicchini, Burr, & Binda, 2021). Studies have found that both the perception of numerosity of a visual stimulus (Castaldi et al., 2021) and image understanding (Naber & Nakayama, 2013) can modulate the pupillary response. This study aims to examine pupillary responses to the perceived regularities of stimulus arrangement in spatial vision. We hypothesized that spatially irregular stimuli elicit more pupil dilation than regular stimuli under conditions in which the physical properties of the stimuli are matched. Moreover, recent studies have shown that a variety of visual statistical regularities are represented in human subcortical structures (Zeng, Zhao, Cao, & Jia, 2024; Zhao et al., 2023) that may share control mechanisms with neural circuits controlling the pupillary response (Castaldi et al., 2021; Joshi & Gold, 2020), which supports the hypothesis in this study. 
In three experiments, we presented participants with stimuli of various spatial arrangements while matching the physical regularity and investigated whether pupil size is affected by the perceived regularity of the spatial arrangement. The regularity in this study refers to the organization of stimuli into a whole or the relative consistency (i.e., smaller variance) between stimuli. In Experiments 1 and 2, regular stimuli were organized into a whole, whereas irregular stimuli could not form a whole (Fang, Kersten, & Murray, 2008). In Experiment 3, owing to the Ponzo illusion, the regular condition seemed to have a small variance between stimuli, whereas the irregular condition seemed to have a large variance between stimuli (Rhodes & Luca, 2016). Through our experiments using orientation (Experiments 1 and 2) and size (Experiment 3) as stimuli, we consistently found that perceived irregular stimuli resulted in greater constriction of the pupil compared with regular stimuli. The discrepancies between the results of this study and previous studies were discussed. 
Experiment 1: Pupil responds to perceived visuospatial regularity spontaneously
In Experiment 1, we created 2 types of regular stimuli, a dodecagon and a clock shape consisting of 12 bars. Additionally, we generated irregular versions of these stimuli by randomly shuffling the positions of the bars while keeping their size and orientation consistent with the regular versions. Our goal was to investigate how the statistical regularity of spatial arrangements influences pupillary responses, which we recorded and analyzed for both the regular and irregular stimuli. 
Materials and methods
Participants
Thirty participants (5 males; mean age, 21.24 ± 2.10 years) between 18 and 26 years old were recruited from Hangzhou Normal University. They all had normal or corrected-to-normal vision and were unaware of the purpose of these experiments. To ensure that the observed changes in pupil diameter were not blink-related artifacts, participants were excluded if they blinked in more than 30% of trials. Six participants were excluded from the further data analysis. The sample size was comparable to previous pupil studies with similar experimental designs (Kraus et al., 2023; Liu, Cheng, Yuan, & Jiang, 2023). The research was approved by the local ethics committee (Institutional Review Board #20200629) and was in accordance with the Declaration of Helsinki. All participants gave written informed consent before participating in the research. 
Apparatus and tools
The present experiments used MATLAB (The MathWorks, Natick, MA) and the Psychophysics Toolbox (Brainard, 1997) to present stimuli and to record behavioral responses. The experiments took place in a dimly lit and sound-proof laboratory. The participants were comfortably seated at a viewing distance of approximately 70 cm, with their heads stabilized on a chin rest. The visual stimuli were presented on a CRT monitor (width and height, 40 × 30 cm; resolution, 1,024 × 768; refresh rate, 85 Hz). 
Stimuli
In Experiments 1a and 1b, the visual stimulus array consisted of 12 white bars (1.29° × 0.32°, 104 cd/m2) with different orientations and uniformly distributed on 12 fixed positions of a virtual circle (6° radius) around the white fixation point (Figure 1A). The stimuli were presented on a gray background (23 cd/m2). 
Figure 1.
 
Paradigm and data of Experiment 1. (A and D) Procedure of Experiments 1a and 1b. Each trial began with the presentation of a fixation point followed by a stimulus array. The stimulus array consisted of 12 white bars. The first and second stimuli in each procedure illustrate the regular and irregular stimulus, respectively. The participants were asked to maintain gaze on the fixation point and performed passive viewing tasks. (B and E) Pupillary response to the stimulus array for the two conditions in Experiments 1a and 1b. The shaded areas show the standard error of the mean (SEM). (C and F) The mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) for the two conditions in Experiments 1a and 1b. *p < 0.05, ***p < 0.001.
Figure 1.
 
Paradigm and data of Experiment 1. (A and D) Procedure of Experiments 1a and 1b. Each trial began with the presentation of a fixation point followed by a stimulus array. The stimulus array consisted of 12 white bars. The first and second stimuli in each procedure illustrate the regular and irregular stimulus, respectively. The participants were asked to maintain gaze on the fixation point and performed passive viewing tasks. (B and E) Pupillary response to the stimulus array for the two conditions in Experiments 1a and 1b. The shaded areas show the standard error of the mean (SEM). (C and F) The mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) for the two conditions in Experiments 1a and 1b. *p < 0.05, ***p < 0.001.
In the regular condition of Experiment 1a, the 12 white bars are uniformly arranged around the fixation point and shaped a dodecagon as illustrated by the first stimulus in Figure 1A. In the regular condition of Experiment 1b, the 12 white bars are similarly arranged, but shaped a clock as illustrated by the first stimulus in Figure 1D. In the irregular conditions of Experiment 1a and Experiment 1b, the exactly exact same 12 white bars as the corresponding regular conditions were used, but their positions were shuffled randomly (second stimulus in Figures 1A and 1D). Thus, the participant perceived a spatial regularity (i.e., the shape) in the regular conditions and no discernible pattern in the irregular conditions. 
Procedure
Participants were required to maintain gaze on the fixation point in the center of the screen and perform passive viewing tasks. The stimulus array was presented in the peripheral visual field for 3 seconds with an interval of 2 to 3 seconds between stimuli. The fixation point remained in the center of the screen throughout the experiment. Experiments 1a and 1b each consist of 4 blocks of 40 trials and the regular and irregular conditions were intermixed in each block. Participants could have a rest between blocks and pressed the space key on the keyboard to start the next block. The presentation order of Experiments 1a and 1b was balanced across participants. The whole experiment took about 45 minutes to complete. 
Eye movement recording
Eye movements were recorded binocularly at 1,000 Hz with an EyeLink 1000 eye tracker (SR Research, Ottawa, Canada). The participant's head was stabilized with a chin rest to maintain good tracking accuracy. The tracker was calibrated with a standard nine-point calibration procedure at the beginning of experiment and every block. 
Preprocessing of pupil data
The pupil data were preprocessed using the PuPl toolbox (Kinley & Levy, 2022). It consisted of the following six steps: (1) Removal of outlier values: Pupil data that were too large or too small (outside the mean ± 2 standard deviations) were deleted, and pupil data that dilated too rapidly were deleted (Kret & Sjak-Shie, 2019). Based on this procedure, data islands with a duration of less than 30 ms and an interval of more than 25 ms from the surrounding data were deleted (Lemercier et al., 2014). (2) Removal of blinks: Blinks were identified using the pupillometry noise method (Hershman, Henik, & Cohen, 2018). Because blinks appear as a sharp decrease and then increase in measured pupil sizes, the data 25 ms before and 100 ms after the detected blinks were flagged also as blink data and deleted. (3) Interpolation: The missing pupil data were interpolated using a linear interpolation, where the length of time to insert was within 500 ms and the difference of the pupil sizes between the two ends of the interpolated data was no more than one standard deviation. (4) Filtering and down-sampling: To eliminate high-frequency artifacts in the data, smoothing was performed with a 100-ms Hanning window and down-sampling was performed to 100 Hz. (5) Defining epochs: The data from 500 ms before to 3,000 ms after the presentation of the stimulus array were defined as an epoch. If there was more than 1% of pupil data missing in an epoch, the epoch was deleted. If more than 30% of epochs are rejected, this subject’s data are excluded from further analysis. After that, the data from both eyes were averaged to form a single index. (6) Normalization and baseline correction: To exclude the effect of intersubject differences in pupil sizes on the statistics of the data, the pupil data of each subject were converted to z scores. The post-stimulus data were then baseline-corrected using the pre-stimulus 500 ms data as the baseline. 
Statistics
Paired-sample t tests were used to compare the differences in pupil size between regular and irregular conditions. 
Results
The pupillary response to the subjective visual regularity
For Experiment 1a, pupillary responses to different conditions were shown in Figure 1B. After stimulus onset, the pupil constricted rapidly, exhibiting a typical phasic response to the stimulus presentation. Importantly, pupil constrictions differed between the two conditions, with the irregular stimuli causing greater pupil constriction than the regular stimuli. Based on previous studies (Mathôt, 2018) and visual inspection of the data from this experiment, we selected the mean pupil size during the pupil constriction period (0.3–1.5 seconds) for statistical analysis. As shown in Figure 1C, pupil constriction for the regular condition was significantly lower than for the irregular condition, t(23) = 2.55, p = 0.018, Cohen's d = 0.52. Experiment 1b replicated the results of Experiment 1a, pupillary responses to different conditions were shown in Figure 1E. As shown in Figure 1F, pupil constriction for the regular condition was significantly lower than the irregular condition, t(23) = 4.53, p < 0.001, Cohen's d = 0.93. These results suggest that the pupil responds spontaneously to perceived visuospatial regularity. The less regularity, the greater the pupil constriction. 
Experiment 2: Pupillary response to spatial regularity is independent of stimulus luminance
In Experiment 1, we used the white stimulus presented on a gray background and found that the pupil was slightly dilated followed by a rapid large constriction, after which it returned to near baseline. In previous studies, white stimuli presented on a dark background usually elicit monotonous constriction of the pupil (Castaldi et al., 2021), so we explored whether the pupillary response to spatial regularity observed in Experiments 1 was dependent on stimulus luminance. In Experiment 2, we repeated Experiment 1b using new participants, but changed the white stimuli to black while keeping the background luminance constant (Figure 2A). 
Figure 2.
 
Stimulus and data of Experiment 2. (A) Examples of black stimulus array. (Left) Regular stimulus. (Right) Irregular stimulus. (B) Pupillary response to stimulus array for the two conditions. (C) The mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) for the two conditions. (D) The differences in mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) between Experiment 1b and Experiment 2. The shaded areas show the SEM. *p < 0.05, ***p < 0.001.
Figure 2.
 
Stimulus and data of Experiment 2. (A) Examples of black stimulus array. (Left) Regular stimulus. (Right) Irregular stimulus. (B) Pupillary response to stimulus array for the two conditions. (C) The mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) for the two conditions. (D) The differences in mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) between Experiment 1b and Experiment 2. The shaded areas show the SEM. *p < 0.05, ***p < 0.001.
Materials and methods
Participant
Thirty participants (5 males; mean age 20.77 ± 1.50 years) between 18 and 26 years old were recruited from Hangzhou Normal University. Five participants were excluded from further data analysis because they blinked in more than 30% of trials. The sample size was similar to that of Experiment 1
Stimuli
Experiment 2, as a control experiment, used the same stimuli array and procedure as Experiment 1b, except that the color of the stimulus array was changed from white (104 cd/m2) to black (0 cd/m2). The recording and analysis of pupil data were the same as in Experiment 1
Statistics
A paired-sample t test was used to compare the differences in pupil size between regular and irregular conditions. An independent-sample t test was used to compare the differences in pupil size between Experiment 1b (white stimulus array) and Experiment 2 (black stimulus array). 
Results
The results were similar to Experiment 1, with the pupil dilated and then constricted after stimulus onset, before dilating above baseline (Figure 2B). We also extracted the mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) for statistical analysis. There was a significant difference in the pupillary response for the different conditions (Figure 2C). Pupil constriction for the irregular condition was significantly greater than the regular condition, t(24) = 2.73, p = 0.012, Cohen's d = 0.12. To investigate the influence of luminance on pupil size, we compared the pupil size during the pupil constriction period (0.3–1.5 seconds) between Experiment 1b and Experiment 2. The results showed a significant difference between Experiment 1 and Experiment 2 (Figure 2D). Pupil constriction for the white stimulus was significantly greater than for the black stimulus, t(47) = −3.47, p = 0.001, Cohen's d = −0.99. These results suggest that the luminance of the stimulus only affected the degree of pupil constriction, but did not affect the pupillary response to subjective visual regularity. 
Experiment 3: Pupillary response to perceived regularity is independent of high-order physical regularity
In Experiments 1 and 2, we used the same 12 bars in the regular and irregular conditions, which prevented the effect on pupil size observed from being explained by the distribution of physical features in the stimulus array. However, the regular and irregular conditions of Experiments 1 and 2 were only matched in their first-order physical regularity (i.e., the angles of the bars), and differed in their second-order physical regularity. Specifically, the angular difference between adjacent bars in the regular condition was a fixed 30°, whereas the angular difference between adjacent bars in the irregular condition was random. This leaves a possibility that the difference in pupil size between the regular and irregular conditions observed in Experiments 1 and 2 was due to differences in the higher-order physical regularities of the stimuli in the two conditions. Therefore, in Experiment 3, we designed new stimuli in which the regular and irregular conditions were matched in both first- and second-order physical regularities to examine the effect of perceived regularity on pupillary responses. In addition, Experiment 3 used sizes rather than orientation as the stimulus feature to validate the results of Experiments 1 and 2
Materials and methods
Participants
Thirty participants (11 males; mean age, 21.83 ± 2.10 years) between 18 and 26 years old were recruited from Hangzhou Normal University. Five participants were excluded from further data analysis because they blinked in more than 30% of trials. The sample size was similar to that of Experiment 1
Stimuli
In Experiment 3, we presented six rings along the hallway of a rendered three-dimensional scene (width and height: 16.52° × 12.34°). The rings were at close and far apparent depths in a three-dimensional scene (Figure 3A). The diameters of the rings vary from 1.95° to 3.25° with a constant distance of 0.26°. The closest ring was presented at a fixed depth of 1.14° above the bottom of the scene, and the distance between the midpoint of the closest ring and the farthest ring was fixed at 8.06°. 
Figure 3.
 
Paradigm and data of Experiment 3. (A) Each trial began with the presentation of a fixation point followed by a stimulus array. The first stimulus array was treated as the regular condition owing to its perceived low variability, and the second stimulus array was treated as the irregular condition owing to its perceived high variability. (B) Pupillary response to stimulus array for the two conditions. (C) The mean pupil sizes during the two conditions’ constriction periods (0.3–1.5 seconds). The shaded areas show the SEM. ***p < 0.001.
Figure 3.
 
Paradigm and data of Experiment 3. (A) Each trial began with the presentation of a fixation point followed by a stimulus array. The first stimulus array was treated as the regular condition owing to its perceived low variability, and the second stimulus array was treated as the irregular condition owing to its perceived high variability. (B) Pupillary response to stimulus array for the two conditions. (C) The mean pupil sizes during the two conditions’ constriction periods (0.3–1.5 seconds). The shaded areas show the SEM. ***p < 0.001.
The far ring seemed to be larger than the same-size close ring when participants were fixated on the scene's center, referred to as the Ponzo illusion (Fang, Boyaci, Kersten, & Murray, 2008). In one condition, the six rings were presented from large to small on the depth background from close to far. In the other condition, the six rings are presented from small to large on the depth background from close to far. The first- and second-order physical regularities were the same for both conditions. Because of the effect of the Ponzo illusion, the sizes of the six rings seemed to have small variability in the former condition but to have high variability in the latter condition. Subjectively, the small variability of the stimuli leads to a perception of high regularity (Rhodes & Luca, 2016). Thus, we treated the former condition as regular and the latter as irregular. In Experiment 3, 100 images were used as stimuli with 50 images in each of the two conditions. 
Procedure
The procedure of Experiment 3 was the same as Experiment 1. The whole experiment consisted of 2 blocks of 50 trials and took approximately 17 minutes to complete. The recording and analysis of pupil data were the same as in Experiment 1
Results
Experiment 3 replicated the results of Experiment 1 and showed that pupil constriction was greater in the irregular condition (Figure 3B). We extracted the mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) for statistical analysis. There was a significant difference in the pupillary response for the different conditions (Figure 3C). Pupil constriction for the irregular condition was significantly greater than the regular condition, t(24) = 3.99, p < 0.001, Cohen's d = 0.33. These results suggest that, even if both the low-order and high-order physical regularities are matched, the pupillary responses will still be influenced by the perceived regularity of visuospatial arrangement. 
Discussion
This study investigated whether the pupil responds to the regularity of the spatial arrangement of visual stimuli. In three experiments, we matched the physical properties of perceived regular and irregular stimuli and recorded the pupillary response to the stimuli. Results across three experiments consistently showed that, after stimulus presentation, perceived irregular stimuli elicited greater pupil constriction relative to perceived regular stimuli. This response pattern was independent of the luminance and higher-order physical regularities of the stimuli. Moreover, in all experiments of the present study, participants were only required to passively view the stimuli, suggesting that the pupillary response to the perceived regularities of spatial arrangement was spontaneous. The results of the present study extended the understanding of the properties of pupillary responses. 
The results of the present study are partially consistent with those found in previous studies of pupillary responses to temporal regularities. Previous studies have found that the precision of the statistical distribution of the stimuli (Silvestrin et al., 2021), the surprise of the statistical regularity (Alamia et al., 2019), the violation of the temporal regularity (Zhao, Chait, et al., 2019), and the subjective statistical structure of the stimulus sequence (Schwiedrzik & Sudmann, 2020) could modulate pupil size. The present study extends the scope of regularity to the spatial arrangement of stimuli and similarly found that the pupil could respond to perceived regularity in the spatial arrangement of stimuli. 
The previous studies of temporal regularity (Alamia et al., 2019; Schwiedrzik & Sudmann, 2020; Silvestrin et al., 2021; Zhao, Chait, et al., 2019) showed that irregular stimuli elicit more pupil dilation than regular stimuli. Therefore, we initially hypothesized that the regularity of spatial arrangement would have a similar effect on the pupil size, specifically that the pupil dilates more when viewing irregular stimuli. However, our three experiments consistently showed the opposite results. We suspect two reasons for this. One is that temporal regularity may have a different mechanism for affecting pupil size than spatial regularity. Temporal regularity relies on past stimuli to predict current stimuli, whereas spatial regularity relies on participants’ familiarity with the stimuli and visual Gestalt rules. This difference may lead to different effects of the two regularities on pupil size. Second, in the present study, both white and black stimuli elicited rapid pupil constriction, and the pupil constriction response (relative to baseline) was greater in the irregular condition than in the regular condition. This result leaves the possibility that the irregular stimuli elicited a greater phasic response of the pupil, which was greater dilation in previous studies and greater constriction in the present study. Future studies could further examine the specific reasons for this divergence. 
Given the different spatial arrangements may result in different visual salience (Zhang, Zhaoping, Zhou, & Fang, 2012), the greater constriction of the pupil to the irregular condition observed in the present experiment may simply be due to the high visual salience induced by irregular stimulus arrangement. Previous evidence on whether salience affects pupil size was mixed, with some studies finding an effect (Wang, Boehnke, Itti, & Munoz, 2014) and others finding no effect (Filipowicz, Glaze, Kable, & Gold, 2020; Zhao, Yum, et al., 2019). For the results of the present study, the different visual salience of the different conditions may be one of the reasons for the differences in pupil responses. 
The statistical regularity of a stimulus presented to the visual field is used to automatically form a summary statistical representation in order to compress information (Alvarez, 2011; Jia, Wang, Chen, Ding, & Fang, 2022; Wang, Zhao, & Jia, 2023). Meanwhile, the degree of stimulus variability represents the degree of stimulus regularity and affects the visual system's statistical summarization of the stimulus. Greater stimulus variability, that is, less stimulus regularity, impedes statistical summarization of the stimulus (Semizer & Boduroglu, 2021). This engagement in statistical summarization may be reflected in the pupillary response. The degree of engagement in cognitive processing is one of the main factors influencing pupil size (Kraus et al., 2023). In the present study, statistical summarization of regular stimuli was easier because the regular conditions formed a shape perception. Thus, there is less engagement of cognitive processing and less pupil constriction responses in the regular condition, and conversely, there is more engagement of cognitive processing and more pupil constriction responses in the irregular condition. 
Conclusions
The present study found a new property of pupillary response, that is, that the pupil responds spontaneously to the perceived visuospatial regularity of stimuli. 
Acknowledgments
Supported by the National Natural Science Foundation of China (32371086), Zhejiang Provincial Natural Science Foundation of China (LY23C090001), and Major Project of Philosophy and Social Science Research of the Ministry of Education of China (22JZD044). 
Author contributions: Conceptualization: JJ; Methodology: JJ, ZK, CC; Investigation: ZK, CC; Visualization: JJ, ZK; Supervision: JJ; Writing—original draft: ZK, JJ; Writing—review & editing: JJ, ZK, CC. 
Data availability statements: Data and code have been uploaded to the web: https://osf.io/k4fnp/files/osfstorage
Commercial relationships: none. 
Corresponding author: Jianrong Jia. 
Address: Department of Psychology, Hangzhou Normal University, No. 2318 Yuhangtang Road, Yuhang District, Hangzhou 311121, Zhejiang, China. 
References
Alamia, A., VanRullen, R., Pasqualotto, E., Mouraux, A., & Zenon, A. (2019). Pupil-linked arousal responds to unconscious surprisal. Journal of Neuroscience, 39(27), 5369–5376, https://doi.org/10.1523/JNEUROSCI.3010-18.2019. [CrossRef]
Alvarez, G. A. (2011). Representing multiple objects as an ensemble enhances visual cognition. Trends in Cognitive Sciences, 15(3), 122–131, https://doi.org/10.1016/j.tics.2011.01.003. [CrossRef] [PubMed]
Barlow, H. (2001). Redundancy reduction revisited. Network: Computation in Neural Systems, 12(3), 241–253, https://doi.org/10.1080/net.12.3.241.253.
Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10, 433–436. [CrossRef] [PubMed]
Castaldi, E., Pomè, A., Cicchini, G. M., Burr, D., & Binda, P. (2021). The pupil responds spontaneously to perceived numerosity. Nature Communications, 12(1), 5944, https://doi.org/10.1038/s41467-021-26261-4. [CrossRef] [PubMed]
Fang, F., Boyaci, H., Kersten, D., & Murray, S. O. (2008). Attention-dependent representation of a size illusion in human V1. Current Biology, 18(21), 1707–1712, https://doi.org/10.1016/j.cub.2008.09.025. [CrossRef]
Fang, F., Kersten, D., & Murray, S. O. (2008). Perceptual grouping and inverse fMRI activity patterns in human visual cortex. Journal of Vision, 8(7), 2, https://doi.org/10.1167/8.7.2. [CrossRef]
Filipowicz, A. L., Glaze, C. M., Kable, J. W., & Gold, J. I. (2020). Pupil diameter encodes the idiosyncratic, cognitive complexity of belief updating. eLife, 9, e57872, https://doi.org/10.7554/eLife.57872. [CrossRef] [PubMed]
Fiser, J., & Lengyel, G. (2022). Statistical learning in vision. Annual Review of Vision Science, 8(1), 265–290, https://doi.org/10.1146/annurev-vision-100720-103343. [CrossRef] [PubMed]
Forest, T. A., Siegelman, N., & Finn, A. S. (2022). Attention shifts to more complex structures with experience. Psychological Science, 33(12), 2059–2072, https://doi.org/10.1177/09567976221114055. [CrossRef] [PubMed]
Gao, J., Ko, A., Yabe, Y., Goodale, M. A., & Chen, J. (2020). Pupil size is modulated by the size of equal-luminance gratings. Journal of Vision, 20(8), 4, https://doi.org/10.1167/jov.20.8.4. [CrossRef] [PubMed]
Hershman, R., Henik, A., & Cohen, N. (2018). A novel blink detection method based on pupillometry noise. Behavior Research Methods, 50(1), 107–114, https://doi.org/10.3758/s13428-017-1008-1. [CrossRef] [PubMed]
Jia, J., Wang, T., Chen, S., Ding, N., & Fang, F. (2022). Ensemble size perception: Its neural signature and the role of global interaction over individual items. Neuropsychologia, 173, 108290, https://doi.org/10.1016/j.neuropsychologia.2022.108290. [CrossRef] [PubMed]
Joshi, S., & Gold, J. I. (2020). Pupil size as a window on neural substrates of cognition. Trends in Cognitive Sciences, 24(6), 466–480, https://doi.org/10.1016/j.tics.2020.03.005. [CrossRef] [PubMed]
Kinley, I., & Levy, Y. (2022). PuPl: An open-source tool for processing pupillometry data. Behavior Research Methods, 54(4), 2046–2069, https://doi.org/10.3758/s13428-021-01717-z. [CrossRef] [PubMed]
Kraus, F., Tune, S., Obleser, J., & Herrmann, B. (2023). Neural α oscillations and pupil size differentially index cognitive demand under competing audiovisual task conditions. Journal of Neuroscience, 43(23), 4352–4364, https://doi.org/10.1523/JNEUROSCI.2181-22.2023. [CrossRef]
Kret, M. E., & Sjak-Shie, E. E. (2019). Preprocessing pupil size data: Guidelines and code. Behavior Research Methods, 51(3), 1336–1342, https://doi.org/10.3758/s13428-018-1075-y. [CrossRef] [PubMed]
Lemercier, A., Guillot, G., Courcoux, P., Garrel, C., Baccino, T., & Schlich, P. (2014). Pupillometry of taste: Methodological guide – From acquisition to data processing - And toolbox for MATLAB. Quantitative Methods for Psychology, 10(2), 179–195, https://doi.org/10.20982/tqmp.10.2.p179. [CrossRef]
Liu, W., Cheng, Y., Yuan, X., & Jiang, Y. (2023). Linear integration of multisensory signals in the pupil. Psychophysiology, 61(2), e14453, https://doi.org/10.1111/psyp.14453. [CrossRef] [PubMed]
Mathôt, S. (2018). Pupillometry: Psychology, physiology, and function. Journal of Cognition, 1(1), 16, https://doi.org/10.5334/joc.18. [CrossRef] [PubMed]
Mathôt, S. (2020). Tuning the senses: How the pupil shapes vision at the earliest stage. Annual Review of Vision Science, 6(1), 433–451, https://doi.org/10.1146/annurev-vision-030320-062352. [CrossRef] [PubMed]
Naber, M., & Nakayama, K. (2013). Pupil responses to high-level image content. Journal of Vision, 13(6), 7, https://doi.org/10.1167/13.6.7. [PubMed]
Reimer, J., McGinley, M. J., Liu, Y., Rodenkirch, C., Wang, Q., McCormick, D. A., ... Tolias, A. S. (2016). Pupil fluctuations track rapid changes in adrenergic and cholinergic activity in cortex. Nature Communications, 7(1), 13289, https://doi.org/10.1038/ncomms13289. [PubMed]
Rhodes, D., & Luca, M. D. (2016). Temporal regularity of the environment drives time perception. PLoS One, 11(7), e0159842. [PubMed]
Schwiedrzik, C. M., & Sudmann, S. S. (2020). Pupil diameter tracks statistical structure in the environment to increase visual sensitivity. Journal of Neuroscience, 40(23), 4565–4575, https://doi.org/10.1523/JNEUROSCI.0216-20.2020.
Semizer, Y., & Boduroglu, A. (2021). Variability leads to overestimation of mean summaries. Attention, Perception, & Psychophysics, 83(3), 1129–1140, https://doi.org/10.3758/s13414-021-02269-2. [PubMed]
Silvestrin, F., Penny, W. D., & FitzGerald, T. H. B. (2021). Pupil dilation indexes automatic and dynamic inference about the precision of stimulus distributions. Journal of Mathematical Psychology, 101, 102503, https://doi.org/10.1016/j.jmp.2021.102503.
Vilotijević, A., & Mathôt, S. (2023). Emphasis on peripheral vision is accompanied by pupil dilation. Psychonomic Bulletin & Review, 30(5), 1848–1856, https://doi.org/10.3758/s13423-023-02283-5. [PubMed]
Wang, C.-A., Boehnke, S. E., Itti, L., & Munoz, D. P. (2014). Transient pupil response is modulated by contrast-based saliency. Journal of Neuroscience, 34(2), 408–417, https://doi.org/10.1523/JNEUROSCI.3550-13.2014.
Wang, T., Zhao, Y., & Jia, J. (2023). Nonadditive integration of visual information in ensemble processing. iScience, 26(10), 107988, https://doi.org/10.1016/j.isci.2023.107988. [PubMed]
Zeng, T., Zhao, Y., Cao, B., & Jia, J. (2024). Perception of visual variance is mediated by subcortical mechanisms. Brain and Cognition, 175, 106131, https://doi.org/10.1016/j.bandc.2024.106131. [PubMed]
Zhang, X., Zhaoping, L., Zhou, T., & Fang, F. (2012). Neural activities in v1 create a bottom-up saliency map. Neuron, 73, 183–192, https://doi.org/10.1016/j.neuron.2011.10.035. [PubMed]
Zhao, J., Al-Aidroos, N., & Turk-Browne, N. B. (2013). Attention is spontaneously biased toward regularities. Psychological Science, 24(5), 667–677, https://doi.org/10.1177/0956797612460407. [PubMed]
Zhao, S., Chait, M., Dick, F., Dayan, P., Furukawa, S., & Liao, H.-I. (2019). Pupil-linked phasic arousal evoked by violation but not emergence of regularity within rapid sound sequences. Nature Communications, 10(1), 4030, https://doi.org/10.1038/s41467-019-12048-1. [PubMed]
Zhao, S., Yum, N. W., Benjamin, L., Benhamou, E., Yoneya, M., Furukawa, S., ... Chait, M. (2019). Rapid ocular responses are modulated by bottom-up-driven auditory salience. Journal of Neuroscience, 39(39), 7703–7714, https://doi.org/10.1523/JNEUROSCI.0776-19.2019.
Zhao, Y., Zeng, T., Wang, T., Fang, F., Pan, Y., & Jia, J. (2023). Subcortical encoding of summary statistics in humans. Cognition, 234, 105384, https://doi.org/10.1016/j.cognition.2023.105384. [PubMed]
Figure 1.
 
Paradigm and data of Experiment 1. (A and D) Procedure of Experiments 1a and 1b. Each trial began with the presentation of a fixation point followed by a stimulus array. The stimulus array consisted of 12 white bars. The first and second stimuli in each procedure illustrate the regular and irregular stimulus, respectively. The participants were asked to maintain gaze on the fixation point and performed passive viewing tasks. (B and E) Pupillary response to the stimulus array for the two conditions in Experiments 1a and 1b. The shaded areas show the standard error of the mean (SEM). (C and F) The mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) for the two conditions in Experiments 1a and 1b. *p < 0.05, ***p < 0.001.
Figure 1.
 
Paradigm and data of Experiment 1. (A and D) Procedure of Experiments 1a and 1b. Each trial began with the presentation of a fixation point followed by a stimulus array. The stimulus array consisted of 12 white bars. The first and second stimuli in each procedure illustrate the regular and irregular stimulus, respectively. The participants were asked to maintain gaze on the fixation point and performed passive viewing tasks. (B and E) Pupillary response to the stimulus array for the two conditions in Experiments 1a and 1b. The shaded areas show the standard error of the mean (SEM). (C and F) The mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) for the two conditions in Experiments 1a and 1b. *p < 0.05, ***p < 0.001.
Figure 2.
 
Stimulus and data of Experiment 2. (A) Examples of black stimulus array. (Left) Regular stimulus. (Right) Irregular stimulus. (B) Pupillary response to stimulus array for the two conditions. (C) The mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) for the two conditions. (D) The differences in mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) between Experiment 1b and Experiment 2. The shaded areas show the SEM. *p < 0.05, ***p < 0.001.
Figure 2.
 
Stimulus and data of Experiment 2. (A) Examples of black stimulus array. (Left) Regular stimulus. (Right) Irregular stimulus. (B) Pupillary response to stimulus array for the two conditions. (C) The mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) for the two conditions. (D) The differences in mean pupil sizes during pupil constriction periods (0.3–1.5 seconds) between Experiment 1b and Experiment 2. The shaded areas show the SEM. *p < 0.05, ***p < 0.001.
Figure 3.
 
Paradigm and data of Experiment 3. (A) Each trial began with the presentation of a fixation point followed by a stimulus array. The first stimulus array was treated as the regular condition owing to its perceived low variability, and the second stimulus array was treated as the irregular condition owing to its perceived high variability. (B) Pupillary response to stimulus array for the two conditions. (C) The mean pupil sizes during the two conditions’ constriction periods (0.3–1.5 seconds). The shaded areas show the SEM. ***p < 0.001.
Figure 3.
 
Paradigm and data of Experiment 3. (A) Each trial began with the presentation of a fixation point followed by a stimulus array. The first stimulus array was treated as the regular condition owing to its perceived low variability, and the second stimulus array was treated as the irregular condition owing to its perceived high variability. (B) Pupillary response to stimulus array for the two conditions. (C) The mean pupil sizes during the two conditions’ constriction periods (0.3–1.5 seconds). The shaded areas show the SEM. ***p < 0.001.
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