Distinguishing Social From Private Intentions Through the Passive Observation of Gaze Cues

Impaired recognition of interactive intentions in adults with autism spectrum disorder not attributable to differences in visual attention or coordination via eye contact and joint attention

Altered nonverbal communication patterns especially with regard to gaze interactions are commonly reported for persons with autism spectrum disorder (ASD). In this study we investigate and differentiate for the first time the interplay of attention allocation, the establishment of shared focus (eye contact and joint attention) and the recognition of intentions in gaze interactions in adults with ASD compared to control persons. Participants interacted via gaze with a virtual character (VC), who they believed was controlled by another person. Participants were instructed to ascertain whether their partner was trying to interact with them. In fact, the VC was fully algorithm-controlled and showed either interactive or non-interactive gaze behavior. Participants with ASD were specifically impaired in ascertaining whether their partner was trying to interact with them or not as compared to participants without ASD whereas neither the allocation of attention nor the ability to establish a shared focus were affected. Thus, perception and production of gaze cues seem preserved while the evaluation of gaze cues appeared to be impaired. An additional exploratory analysis suggests that especially the interpretation of contingencies between the interactants' actions are altered in ASD and should be investigated more closely.

Differentiated, rather than shared, strategies for time-coordinated action in social and non-social domains in autistic individuals

Autism spectrum disorder (ASD) is a neurodevelopmental condition with a highly heterogeneous adult phenotype that includes social and non-social behavioral characteristics. The link between the characteristics assignable to the different domains remains unresolved. One possibility is that social and non-social behaviors in autism are modulated by a common underlying deficit. However, here we report evidence supporting an alternative concept that is individual-centered rather than deficit-centered. Individuals are assumed to have a distinctive style in the strategies they adopt to perform social and non-social tasks with these styles presumably being structured differently between autistic individuals and typically-developed (TD) individuals. We tested this hypothesis for the execution of time-coordinated (synchronized) actions. Participants performed (i) a social task that required synchronized gaze and pointing actions to interact with another person, and (ii) a non-social task that required finger-tapping actions synchronized to periodic stimuli at different time-scales and sensory modalities. In both tasks, synchronization behavior differed between ASD and TD groups. However, a principal component analysis of individual behaviors across tasks revealed associations between social and non-social features for the TD persons but such cross-domain associations were strikingly absent for autistic individuals. The highly differentiated strategies between domains in ASD are inconsistent with a general synchronization deficit and instead highlight the individualized developmental heterogeneity in the acquisition of domain-specific behaviors. We propose a cognitive model to help disentangle individual-centered from deficit-centered effects in other domains. Our findings reinforce the importance to identify individually differentiated phenotypes to personalize autism therapies.

Intrapersonal synchrony analysis reveals a weaker temporal coherence between gaze and gestures in adults with autism spectrum disorder

The temporal encoding of nonverbal signals within individuals, referred to as intrapersonal synchrony (IaPS), is an implicit process and essential feature of human communication. Based on existing evidence, IaPS is thought to be a marker of nonverbal behavior characteristics in autism spectrum disorders (ASD), but there is a lack of empirical evidence. The aim of this study was to quantify IaPS in adults during an experimentally controlled real-life interaction task. A sample of adults with a confirmed ASD diagnosis and a matched sample of typically-developed adults were tested (N = 48). Participants were required to indicate the appearance of a target invisible to their interaction partner nonverbally through gaze and pointing gestures. Special eye-tracking software allowed automated extraction of temporal delays between nonverbal signals and their intrapersonal variability with millisecond temporal resolution as indices for IaPS. Likelihood ratio tests of multilevel models showed enlarged delays between nonverbal signals in ASD. Larger delays were associated with greater intrapersonal variability in delays. The results provide a quantitative constraint on nonverbal temporality in typically-developed adults and suggest weaker temporal coherence between nonverbal signals in adults with ASD. The results provide a potential diagnostic marker and inspire predictive coding theories about the role of IaPS in interpersonal synchronization processes.

Crossing the street in front of an autonomous vehicle: An investigation of eye contact between drivengers and vulnerable road users

Communication between road users is a major key to coordinate movement and increase roadway safety. The aim of this work was to grasp how pedestrians (Experiment A), cyclists (Experiment B), and kick scooter users (Experiment C) sought to visually communicate with drivengers when they would face autonomous vehicles (AVs). In each experiment, participants (n = 462, n = 279, and n = 202, respectively) were asked to imagine themselves in described situations of encounters between a specific type of vulnerable road user (e.g., pedestrian) and a human driver in an approaching car. The human driver state and the communicative means of the approaching car through an external Human-Machine Interface (eHMI) were manipulated between the scenarios. The participants were prompted to rate from “never” to “always” (6-point Likert scale) the frequency with which they would seek eye contact with the human driver either in order to express their willingness to cross or to make their effective decision to cross. Our findings revealed that a passive human driver in an AV with no visual checking on the road triggered a decline in vulnerable road users’ desire to communicate by eye contact (Experiments A–C). Moreover, the results of Experiment C demonstrated that the speed screen, the text message screen, and the vibrating mobile app eHMI signals diminished kick scooter users’ desire to communicate visually with the human driver, with some age-based differences. This suggested a better comprehension of the approaching car’s intentions by the kick scooter users, driven by the features of the eHMI.

Lane-change intention prediction using eye-tracking technology: A systematic review

The aim of this study is to identify the best practices and future research directions for driver lane-change intention (DLCI) prediction using eye-tracking technologies based on a systematic literature review. We searched five academic literature databases and then conducted an in-depth review, structured coding, and analysis of 40 relevant articles. The literature on DLCI prediction is summarized in terms of input features, feature extraction and prediction time windows, labeling methods, and machine learning algorithms. The results show that eye tracking data features along with other data sources can be useful inputs for the prediction of DLCI. Major challenges in this line of research include determining the optimal time window for feature extraction and developing and evaluating the appropriate machine learning algorithm. Suggestions for future research and practice for DLCI prediction in intelligent vehicles are discussed.

Atypical processing pattern of gaze cues in dynamic situations in autism spectrum disorders

Psychological studies have generally shown that individuals with Autism Spectrum Disorder (ASD) have particularity in the processing of social information by using static or abstract images. Yet, a recent study showed that there was no difference in their use of social or non-social cues in dynamic interactive situations. To establish the cause of the inconsistent results, we added gaze cues in different directions to the chase detection paradigm to explore whether they would affect the performance of participants with ASD. Meanwhile, eye-tracking methodology was used to investigate whether the processing patterns of gaze cues were different between individuals with ASD and TD. In this study, unlike typical controls, participants with ASD showed no detection advantage when the direction of gaze was consistent with the direction of movement (oriented condition). The results suggested that individuals with ASD may utilize an atypical processing pattern, which makes it difficult for them to use social information contained in oriented gaze cues in dynamic interactive situations.

Gazing at Social Interactions Between Foraging and Decision Theory

Finding the underlying principles of social attention in humans seems to be essential for the design of the interaction between natural and artificial agents. Here, we focus on the computational modeling of gaze dynamics as exhibited by humans when perceiving socially relevant multimodal information. The audio-visual landscape of social interactions is distilled into a number of multimodal patches that convey different social value, and we work under the general frame of foraging as a tradeoff between local patch exploitation and landscape exploration. We show that the spatio-temporal dynamics of gaze shifts can be parsimoniously described by Langevin-type stochastic differential equations triggering a decision equation over time. In particular, value-based patch choice and handling is reduced to a simple multi-alternative perceptual decision making that relies on a race-to-threshold between independent continuous-time perceptual evidence integrators, each integrator being associated with a patch.

The Effect of Feedback on Attention Allocation in Category Learning: An Eye Tracking Study

It has been suggested that category learning involves changes in attention allocation based on the relevance of input to the classification. Using eye-gaze measures, Rehder and Hoffman studied changes in attention allocation during category learning in a 5–4 category structure paradigm with four features of varying diagnosticity levels. In this paradigm, participants are tasked with classifying creatures into two groups through trial and error guided by feedback. While learners’ eye-gaze patterns have been studied as a function of feature diagnosticity levels throughout the learning process, they have not been evaluated in relation to performance and feedback. The present study borrowed and modified Rehder and Hoffman’s category paradigm and evaluated eye-gaze behavior as a function of the diagnosticity level of features, and the valence (positive vs. negative) of the preceding feedback during learning. Our results support Rehder and Hoffman’s observations that gaze on the low diagnosticity feature decreased from the beginning to the end of the task. When change in eye gaze behavior was evaluated in relation to feedback, change in fixation probability was found to be greater following negative feedback. The results indicate that in a category task that includes performance feedback, learning strategies as indicated by changes in selective attention to features are affected to some degree by the valence of the feedback on a preceding trial.