Complexities of emotional responses to social and non-social affective stimuli in schizophrenia.

BACKGROUND: Adaptive emotional responses are important in interpersonal relationships. We investigated self-reported emotional experience, physiological reactivity, and micro-facial expressivity in relation to the social nature of stimuli in individuals with schizophrenia (SZ). METHOD: Galvanic skin response (GSR) and facial electromyography (fEMG) were recorded in medicated outpatients with SZ and demographically matched healthy controls (CO) while they viewed social and non-social images from the International Affective Pictures System. Participants rated the valence and arousal, and selected a label for experienced emotions. Symptom severity in the SZ and psychometric schizotypy in CO were assessed. RESULTS: The two groups did not differ in their labeling of the emotions evoked by the stimuli, but individuals with SZ were more positive in their valence ratings. Although self-reported arousal was similar in both groups, mean GSR was greater in SZ, suggesting differential awareness, or calibration of internal states. Both groups reported social images to be more arousing than non-social images but their physiological responses to non-social vs. social images were different. Self-reported arousal to neutral social images was correlated with positive symptoms in SZ. Negative symptoms in SZ and disorganized schizotypy in CO were associated with reduced mean fEMG. Greater corrugator mean fEMG activity for positive images in SZ indicates valence-incongruent facial expressions. CONCLUSION: The patterns of emotional responses differed between the two groups. While both groups were in broad agreement in self-reported arousal and emotion labels, their mean GSR, and fEMG correlates of emotion diverged in relation to the social nature of the stimuli and clinical measures. Importantly, these results suggest disrupted self awareness of internal states in SZ and underscore the complexities of emotion processing in health and disease.

A physiologically informed virtual reality based social communication system for individuals with autism.

Clinical applications of advanced technology may hold promise for addressing impairments associated with autism spectrum disorders (ASD). This project evaluated the application of a novel physiologically responsive virtual reality based technological system for conversation skills in a group of adolescents with ASD. The system altered components of conversation based on (1) performance alone or (2) the composite effect of performance and physiological metrics of predicted engagement (e.g., gaze pattern, pupil dilation, blink rate). Participants showed improved performance and looking pattern within the physiologically sensitive system as compared to the performance based system. This suggests that physiologically informed technologies may have the potential of being an effective tool in the hands of interventionists.

Can Robotic Interaction Improve Joint Attention Skills?

Although it has often been argued that clinical applications of advanced technology may hold promise for addressing impairments associated with autism spectrum disorder (ASD), relatively few investigations have indexed the impact of intervention and feedback approaches. This pilot study investigated the application of a novel robotic interaction system capable of administering and adjusting joint attention prompts to a small group (n = 6) of children with ASD. Across a series of four sessions, children improved in their ability to orient to prompts administered by the robotic system and continued to display strong attention toward the humanoid robot over time. The results highlight both potential benefits of robotic systems for directed intervention approaches as well as potent limitations of existing humanoid robotic platforms.

Assessing the utility of a virtual environment for enhancing facial affect recognition in adolescents with autism.

Teenagers with autism spectrum disorder (ASD) and age-matched controls participated in a dynamic facial affect recognition task within a virtual reality (VR) environment. Participants identified the emotion of a facial expression displayed at varied levels of intensity by a computer generated avatar. The system assessed performance (i.e., accuracy, confidence ratings, response latency, and stimulus discrimination) as well as how participants used their gaze to process facial information using an eye tracker. Participants in both groups were similarly accurate at basic facial affect recognition at varied levels of intensity. Despite similar performance characteristics, ASD participants endorsed lower confidence in their responses and substantial variation in gaze patterns in absence of perceptual discrimination deficits. These results add support to the hypothesis that deficits in emotion and face recognition for individuals with ASD are related to fundamental differences in information processing. We discuss implications of this finding in a VR environment with regards to potential future applications and paradigms targeting not just enhanced performance, but enhanced social information processing within intelligent systems capable of adaptation to individual processing differences.

Pilot clinical application of an adaptive robotic system for young children with autism.

It has been argued that clinical applications of advanced technology may hold promise for addressing impairments associated with autism spectrum disorders. This pilot feasibility study evaluated the application of a novel adaptive robot-mediated system capable of both administering and automatically adjusting joint attention prompts to a small group of preschool children with autism spectrum disorders (n = 6) and a control group (n = 6). Children in both groups spent more time looking at the humanoid robot and were able to achieve a high level of accuracy across trials. However, across groups, children required higher levels of prompting to successfully orient within robot-administered trials. The results highlight both the potential benefits of closed-loop adaptive robotic systems as well as current limitations of existing humanoid-robotic platforms.

Design of a virtual reality based adaptive response technology for children with autism.

Children with autism spectrum disorder (ASD) demonstrate potent impairments in social communication skills including atypical viewing patterns during social interactions. Recently, several assistive technologies, particularly virtual reality (VR), have been investigated to address specific social deficits in this population. Some studies have coupled eye-gaze monitoring mechanisms to design intervention strategies. However, presently available systems are designed to primarily chain learning via aspects of one's performance only which affords restricted range of individualization. The presented work seeks to bridge this gap by developing a novel VR-based interactive system with Gaze-sensitive adaptive response technology that can seamlessly integrate VR-based tasks with eye-tracking techniques to intelligently facilitate engagement in tasks relevant to advancing social communication skills. Specifically, such a system is capable of objectively identifying and quantifying one's engagement level by measuring real-time viewing patterns, subtle changes in eye physiological responses, as well as performance metrics in order to adaptively respond in an individualized manner to foster improved social communication skills among the participants. The developed system was tested through a usability study with eight adolescents with ASD. The results indicate the potential of the system to promote improved social task performance along with socially-appropriate mechanisms during VR-based social conversation tasks.

Understanding how adolescents with autism respond to facial expressions in virtual reality environments.

Autism Spectrum Disorders (ASD) are characterized by atypical patterns of behaviors and impairments in social communication. Among the fundamental social impairments in the ASD population are challenges in appropriately recognizing and responding to facial expressions. Traditional intervention approaches often require intensive support and well-trained therapists to address core deficits, with many with ASD having tremendous difficulty accessing such care due to lack of available trained therapists as well as intervention costs. As a result, emerging technology such as virtual reality (VR) has the potential to offer useful technology-enabled intervention systems. In this paper, an innovative VR-based facial emotional expression presentation system was developed that allows monitoring of eye gaze and physiological signals related to emotion identification to explore new efficient therapeutic paradigms. A usability study of this new system involving ten adolescents with ASD and ten typically developing adolescents as a control group was performed. The eye tracking and physiological data were analyzed to determine intragroup and intergroup variations of gaze and physiological patterns. Performance data, eye tracking indices and physiological features indicated that there were differences in the way adolescents with ASD process and recognize emotional faces compared to their typically developing peers. These results will be used in the future for an online adaptive VR-based multimodal social interaction system to improve emotion recognition abilities of individuals with ASD.

Impact of robot-mediated interaction system on joint attention skills for children with autism.

With Centers for Disease Control and Prevention prevalence estimates for children with autism spectrum disorder 1 in 88, identification and effective treatment of autism spectrum disorder (ASD) is often characterized as a public health emergency. There is an urgent need for more efficacious treatments whose realistic application will yield more substantial impact on the neurodevelopmental trajectories of young children with ASD. Robotic technology appears particularly promising for potential application to ASD intervention. Initial results applying robotic technology to ASD intervention have consistently demonstrated a unique potential to elicit interest and attention in young children with ASD. As such, technologies capable of intelligently harnessing this potential, along with capabilities for detecting and meaningfully responding to young children's attention and behavior, may represent intervention platforms with substantial promise for impacting early symptoms of ASD. Our current work describes development and application of a novel adaptive robot-mediated interaction technology for facilitating early joint attention skills for children with ASD. The system is composed of a humanoid robot endowed with a prompt decision hierarchy to alter behavior in concert with reinforcing stimuli within an intervention environment to promote joint attention skills. Results of implementation of this system over time, including specific analyses of attentional bias and performance enhancement, with 6 young children with ASD are presented.

A step towards developing adaptive robot-mediated intervention architecture (ARIA) for children with autism.

Emerging technology, especially robotic technology, has been shown to be appealing to children with autism spectrum disorders (ASD). Such interest may be leveraged to provide repeatable, accurate and individualized intervention services to young children with ASD based on quantitative metrics. However, existing robot-mediated systems tend to have limited adaptive capability that may impact individualization. Our current work seeks to bridge this gap by developing an adaptive and individualized robot-mediated technology for children with ASD. The system is composed of a humanoid robot with its vision augmented by a network of cameras for real-time head tracking using a distributed architecture. Based on the cues from the child's head movement, the robot intelligently adapts itself in an individualized manner to generate prompts and reinforcements with potential to promote skills in the ASD core deficit area of early social orienting. The system was validated for feasibility, accuracy, and performance. Results from a pilot usability study involving six children with ASD and a control group of six typically developing (TD) children are presented.