Autistic differences in the temporal dynamics of social attention

Temporal progression of pupil dilation and gaze behavior to emotion expressions in preschoolers with autism spectrum disorder

Previous work has shown divergent pupil dilation (PD) and gaze behavior in individuals with autism spectrum disorder (ASD), which may relate to the development of social difficulties in early life. Here, we investigated temporal dynamics of both phenotypes during naturalistic videos of a person displaying facial emotion expressions in 61 autistic and 61 non-autistic preschoolers. PD was segmented into three serial time components derived from a principal component analysis. Growth curve analysis was applied to analyze changes in looking time on eye and mouth regions over time. Groups did not differ in PD time components. Growth curve analysis revealed initially shorter looking times on the eyes and longer looking times on the mouth in autistic versus non-autistic preschoolers. However, a reversion of this pattern was observed over time, suggesting a delayed compensatory increase in eye attention during prolonged viewing periods in autistic children. Positive and negative associations of PD components and gaze behavior over time indicated a dynamic temporal relationship during emotion viewing. Our findings emphasize the need to apply time-sensitive measures in ecologically valid research, which may index etiological mechanisms of social difficulties in ASD.

Nonlinear features of gaze behavior during joint attention in children with autism spectrum disorder

Since children with autism spectrum disorder (ASD) might exhibit a variety of aberrant response to joint attention (RJA) behaviors, there is growing interest in identifying robust, reliable and valid eye-tracking metrics for determining differences in RJA behaviors between typically developing (TD) children and those with ASD. Previous eye-tracking studies have not been deeply investigated nonlinear features of gaze time-series during RJA. As a main motivation, this study aimed to extract three nonlinear features (i.e., complexity, long-range correlation, and local instability) of gaze time-series during RJA in children with ASD, which can be measured by fractal dimension (FD), Hurst exponent (H), and largest Lyapunov exponent (LLE), respectively. To illustrate our idea, this study adopted a publicly accessible database, including eye-tracking data collected during RJA from 19 children with ASD (7.74 ± 2.73) and 30 TD children (8.02 ± 2.89), and conducted a battery of nonparametric analysis of covariance (ANCOVA), where gender was used as covariable. Findings showed that gaze time-series during RJA in autistic children may generally have greater FD but lower H than that in TD controls. This implies that children with ASD possess more complex and unpredictable gaze behaviors during RJA than TD children. Furthermore, nonlinear metrics outperformed traditional eye-tracking metrics in obtaining higher identification performance with an accuracy of 82% and an AUC value of 0.81, distinguishing the differences between successful and failed RJA trails, and predicting the severity of ASD symptoms. Findings might bring some new insights into the understanding of the impairments in RJA behaviors for children with ASD.

Complex network of eye movements during rapid automatized naming

Introduction

Although the method of visualizing eye-tracking data as a time-series might enhance performance in the understanding of gaze behavior, it has not yet been thoroughly examined in the context of rapid automated naming (RAN).

Methods

This study attempted, for the first time, to measure gaze behavior during RAN from the perspective of network-domain, which constructed a complex network [referred to as gaze-time-series-based complex network (GCN)] from gaze time-series. Hence, without designating regions of interest, the features of gaze behavior during RAN were extracted by computing topological parameters of GCN. A sample of 98 children (52 males, aged 11.50 ± 0.28 years) was studied. Nine topological parameters (i.e., average degree, network diameter, characteristic path length, clustering coefficient, global efficiency, assortativity coefficient, modularity, community number, and small-worldness) were computed.

Results

Findings showed that GCN in each RAN task was assortative and possessed “small-world” and community architecture. Additionally, observations regarding the influence of RAN task types included that: (i) five topological parameters (i.e., average degree, clustering coefficient, assortativity coefficient, modularity, and community number) could reflect the difference between tasks N-num (i.e., naming of numbers) and N-cha (i.e., naming of Chinese characters); (ii) there was only one topological parameter (i.e., network diameter) which could reflect the difference between tasks N-obj (i.e., naming of objects) and N-col (i.e., naming of colors); and (iii) when compared to GCN in alphanumeric RAN, GCN in non-alphanumeric RAN may have higher average degree, global efficiency, and small-worldness, but lower network diameter, characteristic path length, clustering coefficient, and modularity. Findings also illustrated that most of these topological parameters were largely independent of traditional eye-movement metrics.

Discussion

This article revealed the architecture and topological parameters of GCN as well as the influence of task types on them, and thus brought some new insights into the understanding of RAN from the perspective of complex network.

Activation of the CA2-ventral CA1 pathway reverses social discrimination dysfunction in Shank3B knockout mice

Mutation or deletion of the SHANK3 gene, which encodes a synaptic scaffolding protein, is linked to autism spectrum disorder and Phelan-McDermid syndrome, conditions associated with social memory impairments. Shank3B knockout mice also exhibit social memory deficits. The CA2 region of the hippocampus integrates numerous inputs and sends a major output to the ventral CA1 (vCA1). Despite finding few differences in excitatory afferents to the CA2 in Shank3B knockout mice, we found that activation of CA2 neurons as well as the CA2-vCA1 pathway restored social recognition function to wildtype levels. vCA1 neuronal oscillations have been linked to social memory, but we observed no differences in these measures between wildtype and Shank3B knockout mice. However, activation of the CA2 enhanced vCA1 theta power in Shank3B knockout mice, concurrent with behavioral improvements. These findings suggest that stimulating adult circuitry in a mouse model with neurodevelopmental impairments can invoke latent social memory function.

Unique dynamic profiles of social attention in autistic females

BACKGROUND

Social attention affords learning opportunities across development and may contribute to individual differences in developmental trajectories, such as between male and female individuals, and in neurodevelopmental conditions, such as autism.

METHODS

Using eye-tracking, we measured social attention in a large cohort of autistic (n = 123) and nonautistic females (n = 107), and autistic (n = 330) and nonautistic males (n = 204), aged 6-30 years. Using mixed Growth Curve Analysis, we modelled sex and diagnostic effects on the temporal dynamics of proportional looking time to three types of social stimuli (lean-static, naturalistic-static, and naturalistic-dynamic) and examined the link between individual differences and dimensional social and nonsocial autistic traits in autistic females and males.

RESULTS

In the lean-static stimulus, average face-looking was higher in females than in males of both autistic and nonautistic groups. Differences in the dynamic pattern of face-looking were seen in autistic vs. nonautistic females, but not males, with face-looking peaking later in the trial in autistic females. In the naturalistic-dynamic stimulus, average face-looking was higher in females than in males of both groups; changes in the dynamic pattern of face looking were seen in autistic vs. nonautistic males, but not in females, with a steeper peak in nonautistic males. Lower average face-looking was associated with higher observer-measured autistic characteristics in autistic females, but not in males.

CONCLUSIONS

Overall, we found stronger social attention in females to a similar degree in both autistic and nonautistic groups. Nonetheless, the dynamic profiles of social attention differed in different ways in autistic females and males compared to their nonautistic peers, and autistic traits predicted trends of average face-looking in autistic females. These findings support the role of social attention in the emergence of sex-related differences in autistic characteristics, suggesting an avenue to phenotypic stratification.

The Components of Interpersonal Synchrony in the Typical Population and in Autism: A Conceptual Analysis

Interpersonal synchrony – the tendency for social partners to temporally co-ordinate their behaviour when interacting – is a ubiquitous feature of social interactions. Synchronous interactions play a key role in development, and promote social bonding and a range of pro-social behavioural outcomes across the lifespan. The process of achieving and maintaining interpersonal synchrony is highly complex, with inputs required from across perceptual, temporal, motor, and socio-cognitive domains. In this conceptual analysis, we synthesise evidence from across these domains to establish the key components underpinning successful non-verbal interpersonal synchrony, how such processes interact, and factors that may moderate their operation. We also consider emerging evidence that interpersonal synchrony is reduced in autistic populations. We use our account of the components contributing to interpersonal synchrony in the typical population to identify potential points of divergence in interpersonal synchrony in autism. The relationship between interpersonal synchrony and broader aspects of social communication in autism are also considered, together with implications for future research.

A constellation of eye-tracking measures reveals social attention differences in ASD and the broad autism phenotype

Background

Social attention differences, expressed through gaze patterns, have been documented in autism spectrum disorder (ASD), with subtle differences also reported among first-degree relatives, suggesting a shared genetic link. Findings have mostly been derived from standard eye-tracking methods (total fixation count or total fixation duration). Given the dynamics of visual attention, these standard methods may obscure subtle, yet core, differences in visual attention mechanisms, particularly those presenting sub-clinically. This study applied a constellation of eye-tracking analyses to gaze data from individuals with ASD and their parents.

Methods

This study included n = 156 participants across groups, including ASD (n = 24) and control (n = 32) groups, and parents of individuals with ASD (n = 61) and control parents (n = 39). A complex scene with social/non-social elements was displayed and gaze tracked via an eye tracker. Eleven analytic methods from the following categories were analyzed: (1) standard variables, (2) temporal dynamics (e.g., gaze over time), (3) fixation patterns (e.g., perseverative or regressive fixations), (4) first fixations, and (5) distribution patterns. MANOVAs, growth curve analyses, and Chi-squared tests were applied to examine group differences. Finally, group differences were examined on component scores derived from a principal component analysis (PCA) that reduced variables to distinct dimensions.

Results

No group differences emerged among standard, first fixation, and distribution pattern variables. Both the ASD and ASD parent groups demonstrated on average reduced social attention over time and atypical perseverative fixations. Lower social attention factor scores derived from PCA strongly differentiated the ASD and ASD parent groups from controls, with parent findings driven by the subset of parents demonstrating the broad autism phenotype.

Limitations

To generalize these findings, larger sample sizes, extended viewing contexts (e.g., dynamic stimuli), and even more eye-tracking analytical methods are needed.

Conclusions

Fixations over time and perseverative fixations differentiated ASD and the ASD parent groups from controls, with the PCA most robustly capturing social attention differences. Findings highlight their methodological utility in studies of the (broad) autism spectrum to capture nuanced visual attention differences that may relate to clinical symptoms in ASD, and reflect genetic liability in clinically unaffected relatives. This proof-of-concept study may inform future studies using eye tracking across populations where social attention is impacted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-022-00490-w.

Application of Machine Learning Techniques to Detect the Children with Autism Spectrum Disorder

Early detection of autism spectrum disorder (ASD) is highly beneficial to the health sustainability of children. Existing detection methods depend on the assessment of experts, which are subjective and costly. In this study, we proposed a machine learning approach that fuses physiological data (electroencephalography, EEG) and behavioral data (eye fixation and facial expression) to detect children with ASD. Its implementation can improve detection efficiency and reduce costs. First, we used an innovative approach to extract features of eye fixation, facial expression, and EEG data. Then, a hybrid fusion approach based on a weighted naive Bayes algorithm was presented for multimodal data fusion with a classification accuracy of 87.50%. Results suggest that the machine learning classification approach in this study is effective for the early detection of ASD. Confusion matrices and graphs demonstrate that eye fixation, facial expression, and EEG have different discriminative powers for the detection of ASD and typically developing children, and EEG may be the most discriminative information. The physiological and behavioral data have important complementary characteristics. Thus, the machine learning approach proposed in this study, which combines the complementary information, can significantly improve classification accuracy.

The Bidirectional Social-Cognitive Mechanisms of the Social-Attention Symptoms of Autism

Differences in social attention development begin to be apparent in the 6th to 12th month of development in children with Autism Spectrum Disorder (ASD) and theoretically reflect important elements of its neurodevelopmental endophenotype. This paper examines alternative conceptual views of these early social attention symptoms and hypotheses about the mechanisms involved in their development. One model emphasizes mechanism involved in the spontaneous allocation of attention to faces, or social orienting. Alternatively, another model emphasizes mechanisms involved in the coordination of attention with other people, or joint attention, and the socially bi-directional nature of its development. This model raises the possibility that atypical responses of children to the attention or the gaze of a social partner directed toward themselves may be as important in the development of social attention symptoms as differences in the development of social orienting. Another model holds that symptoms of social attention may be important to early development, but may not impact older individuals with ASD. The alterative model is that the social attention symptoms in infancy (social orienting and joint attention), and social cognitive symptoms in childhood and adulthood share common neurodevelopmental substrates. Therefore, differences in early social attention and later social cognition constitute a developmentally continuous axis of symptom presentation in ASD. However, symptoms in older individuals may be best measured with in vivo measures of efficiency of social attention and social cognition in social interactions rather than the accuracy of response on analog tests used in measures with younger children. Finally, a third model suggests that the social attention symptoms may not truly be a symptom of ASD. Rather, they may be best conceptualized as stemming from differences domain general attention and motivation mechanisms. The alternative argued for here that infant social attention symptoms meet all the criteria of a unique dimension of the phenotype of ASD and the bi-directional phenomena involved in social attention cannot be fully explained in terms of domain general aspects of attention development.

Deceptive behaviour in autism: A scoping review

LAY ABSTRACT

The ability to deceive others is an important skill that usually develops in early childhood. In this review, we give an overview of studies that have examined deceptive behaviour in autistic children, adolescents and adults. We separated the study findings into three main categories and seven sub-categories: (1) Deception ability and prevalence (1a) gameplay deception; (1b) naturalistic deception; (2) Psychological processes in deception (2a) verbal, intellectual and social ability; (2b) ability to understand others' thoughts and beliefs; (2c) cognitive ability; and (3) Social learning (3a) training; (3b) social contexts. Contrary to some stereotypes, we found that autistic people can and do deceive but often find this more difficult than non-autistic people. We also found that autistic people may use different psychological processes than non-autistic people when deceiving and may get better at deception in adulthood.