Gender-Specific Patterns in Social Visual Attention Among Individuals with Autistic Traits

doi:10.21203/rs.3.rs-5222509/v1

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Research Article

Gender-Specific Patterns in Social Visual Attention Among Individuals with Autistic Traits

https://doi.org/10.21203/rs.3.rs-5222509/v1

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Background

Autism is a neurodevelopmental condition with more prevalent in males, and its gender differences emerge in prevalence and core symptoms. However, most studies investigating the behavioral and cognitive features of autism tend to include more male samples, leading to a male-biased understanding. The gender imbalance limits the specificity of these features, especially considering female individuals with autism. Hence, it is necessary to explore gender-related differences with behavioral–cognitive traits linked to autism in the general population.

Methods

In this study, we designed a dynamic emotion-discrimination task to investigate gender differences in attention to emotional stimuli in general population with autistic traits. Behavioral and eye movement data were recorded during the task, and the Autism-Spectrum Quotient (AQ) was used to assess autistic traits. We drew heat maps and quantified the proportion of fixation time to analysis the gaze patterns of male and female groups.

Results

It was observed that there were significant differences in attention to the eye regions, particularly with females focus more to eyes than males. Moreover, we conducted correlation analyses between AQ scores and proportional fixation time to the eye region in two groups separately. Lower eye-looking was associated with higher level of autistic traits in males, but not in females.

Conclusions

Overall, the above results reveal the pattern of scanning faces differed in females and males, and autistic traits predicted trend of eye-looking in males. These findings suggest that the gender-related stratification in social attention among individuals with autistic traits, and these differences need to be considered during clinical diagnosis.

Autistic traits

Emotional faces

Eye-tracking

Gender differences

Social attention

The autism spectrum condition (henceforth “autism”) is a neurodevelopmental condition with more prevalent in males [1]. In addition to prevalence, gender differences emerge across multiple levels of autism, including its core symptoms [2]. Autism clinical studies have found differences in behavioral symptoms between females and males: Males typically exhibit poorer language and motor function and increased hyperactivity and aggressive behavior. Females demonstrate better visual reception and facial attention skills and exhibit more tendency to be depressed and anxious [3]. However, the existing diagnostic criteria may define autism at an abstract level, irrespective of gender differences [1, 3, 4]. Hence, understanding the behavioral/cognitive differences between males and females contributes to clinical diagnosis and support. Despite the increasing recognition of the importance of gender differences in autism, but longstanding research and clinical practice include more male samples [1]. This tendency has led to a male-biased understanding of autism, and poses challenges for the effective support of females. The relatively smaller male bias in recent research is therefore important. In the general population, there distribute autistic-like behavioral and cognitive traits (autistic traits), corresponding to milder levels of autistic symptoms [5]. Quantifying the gender-related differences associated with autistic traits can provide an alternative for understanding the gender differences of autism [6].

Social attention is critical in social skills development. Atypical attention can hinder the processing of social information, resulting in social difficulties, which has been well-documented in individuals with autism [7]. As extensions of autistic-like features within the general population, individuals with autistic traits may exhibit similarities with clinical autism [8]. Research in the general population has found that alterations in attention are associated with reduced social skills performance [9] and increased autistic traits [10, 11]. Individuals with high autistic traits may struggle with social attention, and they have difficulty orienting to social targets [12]. However, there is heterogeneity in the findings regarding the link between autistic traits and atypical visual attention in the general population when processing emotional stimuli. Recent studies have found that autistic traits do not affect visual attention [13, 14].

We suggest that the inconsistent results may be related to a gender effect. Firstly, researchers have acknowledged the potential influence of gender in the discussion section of these studies, because the participants were not evenly distributed by gender. Additionally, gender differences in processing of social cues in the general population are also evident, especially in the emotional information processing. Indeed, gender influences attentional levels of the information processing system when dealing with emotional stimuli [15]. In the infant period, female infants spent more time looking at the eyes to acquire emotional information in dynamic facial stimuli than male infants [16]. In the adult group, compared with males, females generally gave higher attention to emotional faces, both positive and negative. Men may respond more to specific emotional faces, such as threatening ones [15]. The difference persisted as people grew older. Older females performed significantly better than older males in identifying the angry expression. This could be attributed to their different face exploration patterns, where females tended to explore the upper part of the face more than males [17].

Research related to autistic traits has also revealed such gender differences. Notably, autistic traits may have different normative distribution in the general population between males and females [18]. According to the extreme male brain theory and evidence, typical male neurobiology is more likely to be associated with autism and tends to exhibit more autistic traits on scales than females [19–21]. Furthermore, studies have revealed gender differences in the correlation between autistic traits and the comprehension of social cues, despite the existence of inconsistencies in the results. Rhodes et al. [22] found a significant relationship between the autistic traits subcluster and face recognition among males, whereas Davis et al. [9] reported a similar significance among females. Moreover, it was discovered that males exhibited a negative correlation between autistic traits and the ability to read eyes, but the correlation among females was less pronounced [23].

To ensure that each autistic individual receives appropriate clinical support, it is crucial to understand gender-related differences in core symptoms and behavioral patterns. In the present study, we investigate gender differences in social visual attention among individuals with autistic traits to overcome gender bias in clinical settings. We have designed a facial emotion discrimination task that employs eye-tracking technology. Additionally, by utilizing the Autism Spectrum Quotient (AQ), we separately analyze the correlation between autistic traits and visual attention in the two gender groups. This study contributes to exploring the role of gender in social attention and its association with autistic traits, providing a perspective of general population traits to understand gender differences in autism.

Participants

Fifty-eight typically developing Chinese adults participated in this study, comprising 31 males and 27 females. Ten participants were excluded from the analysis due to insufficient raw data collection (n = 7) or poor eye movement data quality (n = 3). Eventually, 48 participants, 24 males and 24 females were included in the final sample, aged 19–30 years. All participants are free from mental disorders and have normal or corrected-to-normal vision. This study was approved by the Ethics Committee of Tianjin Children's Hospital, and written informed consent was obtained from all participants.

The measure of Autistic Traits

The participants’ autistic traits were evaluated based on the Chinese version Autism Spectrum Quotient (AQ). The AQ is widely used for self-assessment of autistic traits, consisting of 50 items, covering five aspects of autism symptoms: social skills, attention switching, attention to detail, communication, and imagination. The total score of AQ is 50, with 10 scores for each aspect. The higher the AQ score, the stronger abnormality or autism-like performance [18]. In our sample, AQ total score ranged from 9–32, with two participants scoring the cut-off score of 32. Given that there was insufficient evidence that these two participants had autism, they were retained.

Stimuli

Ten males and ten females’ colored facial photographs of neutral, happy, sad, and angry expressions were selected from the Karolinska Directed Emotional Faces (KDEF) database [24], including three views: 0° (left or right), 45° (left or right), and 90°. All photographs were the same size (Width:17° visual angle, Height:23° visual angle), and the critical face features were standardized to the same location. To enhance ecological validity, two dynamic presentation sequences of expression photographs were designed that simulate real-life observation. Order 1 presents photographs from view 0° to 90° to 0°, and order 2 presents photographs from 90° to 0° to 90°. The experimental paradigm was written and presented by MATLAB software supplemented with Psychtoolbox.

Procedure

Participants were guided to a quiet, soft lightroom, sitting approximately 60cm away from a 27-inch monitor (1920*1080 pixels) to complete an emotion-discrimination task. Eye movement data were recorded by Tobii Pro Spectrum eye tracker; the sampling rate is 1200Hz.

After completing the AQ scale, the experimenter explained the task to ensure the participants fully understood and calibrated participants’ eye movement with the 5-point calibration procedure in Tobii Pro Lab software. And then, the experiment task was started by the experimenter pressing the space key.

The task contains 5 blocks; there were 16 trials in each block, a total of 80 trials. During each trial, as shown in Fig. 1, a cartoon character was presented for 3s first to attract participants’ attention to the center of the screen. Subsequently, five photographs of the same actor’s facial expressions were presented in a particular order (order 1 or order 2), each lasting for 2s. These presentation sequences contained different views, visually as a face was rotating. The participants were required to distinguish the expression presented by the actor or actress within 10s of the five face photographs being presented, and gave feedback with the mouse by clicking the corresponding icon on the screen at the moment of recognition. At the same time, the computer recorded the participants’ reaction time and accuracy but did not inform the participants. Then the subsequent trial started, presenting five new photographs. There was no interval between the 16 trials in a block. Each actor's photographs of a specific expression were presented only once across the 80 trials. The two presentation orders and the four emotional conditions were balanced in number and presented in random order.

Data Analysis

Behavioral data were exported for offline analysis with MATLAB. The average accuracy rate and average response time (in the case of correct discrimination) of two gender groups were calculated, respectively.

The raw data of eye movement were extracted from Tobii Pro Lab software. Fixation data were defined using the Tobii IV-T filter with the default preset. Trials with a total fixation duration < 4000ms were excluded, and if the number of invalid trials is more than 20% of total trials, this participant was excluded. Three participants were eventually excluded from further analyses.

To visually observe the differences in gaze patterns between genders, we created heat maps for each gender and calculated difference maps between groups. Referring to the iMAP4 toolbox [25], we wrote our own code for analysis. Heat maps were created based on the ratio of the duration of fixation points at each location in the stimulus pictures to the total duration of stimulus presentation (2s). Then, we applied a Gaussian kernel to smooth each map spatially. Finally, the heat maps of the male group were subtracted from the female group to obtain the difference maps.

We defined the eye region of interest (ROI) for each face stimuli (0°: 9.96°* 4.23° visual angle, 45°: 8.48°* 3.84° visual angle, 90°: 5.78°* 3.69° visual angle). The ROIs of the left and right faces were symmetrical. Further, the proportional fixation duration was calculated for eye ROIs.

In this article, for participants' age, AQ scores, and behavioral performance, we used the two-sample t-test for normally distributed data or the Mann-Whitney U test for non-normally distributed data. As the partial eye movement characteristics did not follow the normal distribution, statistical analysis was performed using the generalized estimating equation (GEE). The significance level of 0.05, adjusting for multiple comparisons using the Bonferroni method.

Participants’ Essential Information

Table 1 presents information on male and female participants, including their age, total score and subscale scores of the AQ scale, and behavioral performance in the task. Statistical analysis showed no significant differences between male and female groups in age, AQ total score, AQ subscales scores, and emotion discrimination task accuracy. Overall, essential information and task performance were comparable between the two groups. However, males had significantly slower reaction times than females (p = 0.027) in the emotion discrimination task, indicating that males took longer to make judgments.

Table 1

Essential Information of Participants
	Male (n = 24)	Female (n = 24)	Test statistic	p-value
Age (year)	22.57 ± 2.51	22.84 ± 2.06	t(46)=-0.413	p = 0.681
AQ-Total	20.08 ± 5.40	20.46 ± 5.95	t(46)=-0.229	p = 0.82
AQ-Social skill	3.54 ± 0.61	3.63 ± 0.47	Z=-0.135	p = 0.893
AQ-Attention switching	5.54 ± 2.21	5.96 ± 2.35	t(46)=-0.633	p = 0.53
AQ-Attention to detail	5.58 ± 2.19	5.46 ± 2.04	t(46) = 0.205	p = 0.839
AQ-Communication	2.25 ± 0.40	2.92 ± 0.46	Z=-1.13	p = 0.258
AQ- Imagination	3.17 ± 0.34	2.50 ± 0.26	Z=-0.996	p = 0.319
Accuracy (%)	92.89 ± 0.76	93.96 ± 0.81	Z=-1.199	p = 0.231
Response Time (s)	2.94 ± 0.94	2.44 ± 0.48	t(46) = 2.286	p = 0.027

Gender Differences in Gaze Pattern

We used heat maps to visually display how males and females allocate their attention to faces. And highlight the gender differences by subtracting the fixation map for males from females. Figure 2 illustrates the differences in fixation distributions across images with varied emotional conditions and views. The warmer the color, the higher the duration females fixate on this region than males. We adopted the same scale for all subfigures. Female and male groups differed in their gaze patterns to emotional faces, particularly in their attention to the eye region. When observing faces, we found that females tend to fixate on the eyes for a longer duration than males.

To further quantify this difference, we calculated the proportional fixation durations of eye ROIs. Due to the multiple factors involved, the analysis is divided into different situations here. In this study, we focus on the role of gender factors. In each presentation order condition (1 or 2), we set the proportional fixation durations of eye ROIs as dependent variables, gender as a between-group variable, expressions (neutral, happy, sad, angry), and pictures (photographs 1 to 5) as within-group variables. For the order 1 condition, the interaction effects of gender*emotion (Wald chi-square = 11.573, p = 0.009) and gender*picture (Wald chi-square = 10.822, p = 0.029) were significant, and the main effects of the three factors were significant (Gender: Wald chi-square = 9.586, p = 0.002; Expression: Wald chi-square = 30.574, p < 0.001; Picture: Wald chi-square = 183.551, p < 0.001). After controlling for other variables, it was found that females tend to fixate more on the eye region than males when looking at faces with different expressions and views, as shown in the subgraphs in the upper row of Fig. 3. This gender difference was statistically significant under most conditions (Details in Table 2).

Table 2

In order 1, statistical results of gender differences after controlling for other variables (Significant differences are highlighted in bold)
	photographs 1	photographs 2	photographs 3	photographs 4	photographs 5
Neutral	p < 0.001	p = 0.005	p = 0.001	p = 0.002	p = 0.001
Happy	p = 0.003	p = 0.002	p = 0.014	p < 0.001	p < 0.001
Sad	p < 0.001	p = 0.031	p = 0.058	p = 0.005	p = 0.006
Angry	p = 0.005	p = 0.055	p = 0.044	p = 0.014	p = 0.004

For the order 2 condition, a complex interactive effect of three factors was found (Wald chi-square = 43.730, p < 0.001). The main effects of the three factors were significant (Gender: Wald chi-square = 10.397, p = 0.001; Expression: Wald chi-square = 17.448, p = 0.001; Picture: Wald chi-square = 159.443, p < 0.001). When controlling for other variables, females still exhibited a significant advantage in eye fixation over males. This is shown in the lower row of Fig. 3. This gender difference was statistically significant in all cases (Details in Table 3).

Table 3

In order 2, statistical results of gender differences after controlling for other variables (Significant differences are highlighted in bold)
	photographs 1	photographs 2	photographs 3	photographs 4	photographs 5
Neutral	p = 0.011	p < 0.001	p = 0.001	p = 0.001	p = 0.007
Happy	p = 0.003	p = 0.004	p = 0.001	p < 0.001	p = 0.001
Sad	p = 0.006	p = 0.009	p = 0.008	p = 0.001	p = 0.002
Angry	p = 0.010	p = 0.010	p = 0.005	p = 0.032	p = 0.020

Gender Difference in Relationship between Proportional Fixation Duration to Eye Region and Autistic Traits

Additionally, we examined the correlation between the proportional fixation duration on the eye region and levels of autistic traits. In two gender groups, the proportional fixation duration of different expressions was used as the dependent variable, and the total and subscale AQ scores as independent variables performed correlation analyses separately. As depicted in Fig. 4, the results showed a clear gender difference: only males had negative correlations between AQ score and proportional fixation duration of neutral, sad, and angry expressions. Further, linear regression was significant, indicating AQ total scores of males have negative linear correlations with the proportional fixation duration of neutral (r² = 0.246, p = 0.014), sad (r² = 0.220, p = 0.021), and angry (r² = 0.219, p = 0.021). Similarly, across the above three emotion conditions, we also found a significant negative linear relationship between males’ AQ-social skill scores and proportional fixation time to the eye region (Neutral: r² = 0.222, p = 0.020; Sad: r² = 0.195, p = 0.031; Angry: r² = 0.235, p = 0.016). These results indicate an association between higher AQ-total and AQ-social skill with less fixation duration to eyes for males, but not for females.

In this study, we investigate gender differences in social visual attention among individuals with autistic traits. To this end, we designed a facial emotion discrimination task and recorded the eye movement data of participants during the task, comparing the fixation patterns of males and females during the processing of emotional faces. Furthermore, we explored the association between visual attention and autistic traits in male and female groups. The results show that females tend to fixate more on the eye region of faces than males, which is critical for the interpretation of emotional information. Moreover, we discovered significant gender differences in the correlation between visual attention and autistic traits. Only in males did higher levels of autistic traits (AQ-Total) and social skill relevant autistic traits (AQ-Social Skill) tend to predict less looking at eyes. Our findings suggest the gender-related stratification in social attention, indicating that there are different social behavioral and cognitive patterns between male and female individuals with autistic traits. Expanding from this, it is necessary to consider gender-specific characteristics to provide more personalized clinical support to autistic individuals.

In line with previous research [26], we found that females recognized facial expressions faster and tended to focus on the eyes more than males. Given that both general [27, 28] and autistic [7, 29] studies suggest the importance of eye contact, and the studies have found that increased use of eye region information related to better face recognition and expression recognition ability [30, 31]. Our findings indicate that increased attention to the eyes may be a source of females' greater sensitivity to emotional stimuli. Neuroimaging studies show females have greater limbic system activation in the facial perception stage, which includes the amygdala, an important structure [32]. The amygdala participates in processing information about the eye region of faces [33], and the research has confirmed that emotion-selective neuronal responses in the amygdala are modulated by information from the eye region of faces [34]. Thus, increased attention to the eye region of faces in females may drive higher amygdala activation, contributing to their processing of emotional information conveyed by facial expressions more effectively than in males.

In addition, we observed gender differences in the relationship between autistic traits and visual attention. Specifically, in males, there was a negative correlation between autistic traits and fixation duration on eyes. But in females, such correlation was not observed. Similarly, previous studies have found a negative link between autistic traits and behavior performance on the eye-reading task in males [23], whereas our results provide more direct evidence in eye movement data. Note that, in our study, there were no significant differences between the two gender groups in either the total AQ scores or the subscale scores. In this case, we still found that the autistic traits significantly reduced males’ eye attention, indicating that males were more affected by the autistic traits. Moreover, our study has implications for gender differences in autism emotional processing. Many theoretical models of autism only consider the physiological differences caused by gender [3]. Here we speculate that gender does confer inherent physiology differences (As our results reveal, females exhibit better social attention to eyes compared to males). In addition, with the increase of autistic traits, males’ social attention is gradually impaired. In the general population, males may use other strategies to compensate for their differences with females. However, in individuals with autism, the presence of autism symptoms may exacerbate this difference, resulting in autism males tend to exhibit more pronounced and severe symptoms than females.

Although we did not find a correlation between autistic traits and visual attention in females in the current study, our results do not completely negate the effect of autistic traits on females. Even in the clinic, females may be underdiagnosed with autism because they have less externalizing behavioral problems [35]. Studies have shown autism females performed similarly to TD males in social attention, but their social attention was still reduced compared with TD females [36]. Given that females had comparable levels of autistic traits to males in our study, we speculate that TD females may require a higher level of autistic traits in order to achieve the similar association observed in males, at least in the current emotion recognition task.

In this study, we utilized the general population to quantify their autistic traits using the AQ scale, providing a complementary perspective on understanding gender differences in autism. In the present study population, we are able to overcome the issue of having more male samples in clinical research and reduce gender bias. Additionally, studies have pointed out that males are more likely to be diagnosed with autism compared to females, and females require more behavioral/cognitive issues to receive a clinical diagnosis of autism [1]. This disparity in diagnostic symptoms may translate into differences in scale scores between autistic males and females. In the current population, we can control for confounding factors such as the quantified symptomatic scores, comorbidities, and IQ scores [37]. Nonetheless, this study still has some limitations. Specifically, due to the limited number of participants, all of whom were college students and similar in age and intelligence. In light of this, it is need to verify in larger and more diverse male and female samples in future studies to ensure greater precision. Moreover, our results can only complement, not substitute for, research on gender differences in individuals with autism. Therefore, future validation will be conducted in individuals with autism.

Increased discussion of the gender factor in individuals with autistic traits is essential to understanding the differences the behavioral and cognitive differences between autistic males and females and contributes to the clinical diagnosis and treatment of autism. Our results suggest that gender-related differences in visual attention to emotional faces: When viewing emotional faces, females pay more attention to the eyes than males, which is the critical region that contains more emotional information. Moreover, we further analyzed the correlation between autistic traits and visual attention in the two gender groups and found that autistic traits had a more significant negative effect on males' social attention, but not females. Our findings support that the existence of gender differences in social visual attention among individuals with autistic traits, with females potentially exhibiting stronger social attention than males, and males being more affected by the level of autistic traits. In future studies, it is necessary to explore the role of gender in individuals with autism for a deeper understanding.

Human Ethics and Consent to Participate declarations

This study was approved by the Ethics Committee of Tianjin Children's Hospital (NO. 2021-KY-01). This study was performed in accordance with the Ethical Guidelines for Biomedical Research involving Humans and the Declaration of Helsinki. The participants provided their written informed consent to participate in this study.

Consent for publication

To the publisher:

Researchers may always include sample images from KDEF or AKDEF in his/her manuscript when said manuscript is a doctoral thesis OR is a manuscript submitted to a scientific journal. A publisher may regard this mail as a written consent for such publication, or contact me directly if needed.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Competing interests

The authors declare no competing interests.

Funding

This research was funded by the National Natural Science Foundation of China (Grant Nos. 81925020), Tianjin Key Technology R&D 21JCYBJC00360, and the Natural Science Foundation of Tianjin (Key Program, Grant Nos. 23JCZDJC01030).

Authors' Contributions

SL conceived of the study, contributed to the overall design, management and interpretation of results, and had a major role in interpreting the data and drafting the manuscript. LZ contributed to the design of the study, collected the data, performed the data analysis, and interpreted the data and drafting the manuscript. XG collected the data, performed the data analysis, participated in the design of the study and interpretation of results. HX participated in collected the data and the data analysis. XL and BZ contributed to the interpretation of data and in revising the manuscript. DM contributed to the overall design, management and interpretation of results. All authors approved the final version of the manuscript.

Acknowledgements

Thank you to all participants for their involvement in this study.

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No competing interests reported.

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Editorial decision: Revision requested
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Gender-Specific Patterns in Social Visual Attention Among Individuals with Autistic Traits

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Abstract

Background

Methods

Results

Conclusions

Figures

Introduction

Method

Participants

The measure of Autistic Traits

Stimuli

Procedure

Data Analysis

Results

Participants’ Essential Information

Gender Differences in Gaze Pattern

Gender Difference in Relationship between Proportional Fixation Duration to Eye Region and Autistic Traits

Discussion

Conclusion

Declarations

References

Additional Declarations

Status:

Version 1