Executive Function Index (EFI) performance in nonclinical individuals with high levels of autistic traits

Autistic traits are associated with enhanced working memory capacity for abstract visual stimuli

We tested whether the association between autistic traits and enhanced performance in visual-perceptual tasks extends to visual working memory capacity. We predicted that any positive effect of autistic traits on visual working memory performance would be greatest during domain-specific tasks, in which visual resources must be relied upon. We used a visual 'matrix' task, involving recall of black-and-white chequered patterns which increased in size, to establish participants' capacity (span). We assessed 144 young adults' (M = 22.0 years, SD = 2.5) performance on abstract, 'low semantic' versus 'high semantic' task versions. The latter offered multimodal coding due to the availability of long-term memory resources that could supplement visual working memory. Participants also completed measures of autistic traits and trait anxiety. Autistic traits, especially Attention to Detail, Attention Switching, and Communication, positively predicted visual working memory capacity, specifically in the low semantic task, which relies on visual working memory resources. Autistic traits are therefore associated with enhanced processing and recall of visual information. The benefit is removed, however, when multimodal coding may be incorporated, emphasising the visual nature of the benefit. Strengths in focused attention to detail therefore appear to benefit domain-specific visual working memory task performance.

To What Extent is the Contribution of Language to Learning via Instructions Modulated by the Expression of Autism Traits?

Language plays a fundamental role in enabling flexible, goal-directed behaviour. This study investigated whether the contribution of language to instruction encoding is modulated by the expression of autism traits, as measured by the Autism Spectrum Quotient (ASQ) questionnaire. Participants (N = 108) completed six choice reaction time tasks, with each task consisting of six stimulus-response mappings. During an instruction phase preceding each task, participants performed either a verbal, non-verbal or no distractor task. Participants made more errors in the verbal distractor task condition, but this detrimental effect did not differ significantly between the high (top 33%) and low (bottom 33%) ASQ groups. Hence, the contribution of language to instruction encoding does not appear to be modulated by the expression of autism traits.

Towards Robot-Assisted Therapy for Children With Autism—The Ontological Knowledge Models and Reinforcement Learning-Based Algorithms

Robots are more and more present in our lives, particularly in the health sector. In therapeutic centers, some therapists are beginning to explore various tools like video games, Internet exchanges, and robot-assisted therapy. These tools will be at the disposal of these professionals as additional resources that can support them to assist their patients intuitively and remotely. The humanoid robot can capture young children’s attention and then attract the attention of researchers. It can be considered as a play partner and can directly interact with children or without a third party’s presence. It can equally perform repetitive tasks that humans cannot achieve in the same way. Moreover, humanoid robots can assist a therapist by allowing him to teleoperated and interact from a distance. In this context, our research focuses on robot-assisted therapy and introduces a humanoid social robot in a pediatric hospital care unit. That will be performed by analyzing many aspects of the child’s behavior, such as verbal interactions, gestures and facial expressions, etc. Consequently, the robot can reproduce consistent experiences and actions for children with communication capacity restrictions. This work is done by applying a novel approach based on deep learning and reinforcement learning algorithms supported by an ontological knowledge base that contains relevant information and knowledge about patients, screening tests, and therapies. In this study, we realized a humanoid robot that will assist a therapist by equipping the robot NAO: 1) to detect whether a child is autistic or not using a convolutional neural network, 2) to recommend a set of therapies based on a selection algorithm using a correspondence matrix between screening test and therapies, and 2) to assist and monitor autistic children by executing tasks that require those therapies.

The use of a tablet-based app for investigating the influence of autistic and ADHD traits on performance in a complex drawing task

This paper describes a smart tablet-based drawing app to digitally record participants’ engagement with the Rey-Osterrieth complex figure (ROCF) task, a well-characterised perceptual memory task that assesses local and global memory. Digitisation of the tasks allows for improved ecological validity, especially in children attracted to tablet devices. Further, digital translation of the tasks affords new measures, including accuracy and computation of the fine motor control kinematics employed to carry out the drawing Here, we report a feasibility study to test the relationship between two neurodevelopmental conditions: autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). The smart tablet app was employed with 39 adult participants (18-35) characterised for autistic and ADHD traits, and scored using the ROCF perceptual and organisational scoring systems. Trait scores and conditions were predictor variables in linear regression models. Positive correlations were found between the attention-to-detail, attention-switching and communication subscales of the autistic trait questionnaire and organisational scores on the ROCF task. These findings suggest that autistic traits might be linked to differential performance on the ROCF task. Novelty and future applications of the app are discussed.

Error monitoring and daily life executive functioning

Error monitoring during task execution is reflected in post-error slowing (PES), which refers to the tendency to slow down performance after making an error in order to prevent future mistakes. The key question of the present study is whether poor error monitoring (reduced magnitude of PES) has negative consequences for daily life executive function skills, as well as functioning in different life settings such as work, family, social, and academic settings. Eighty-five university students performed a lexical decision task and completed The Executive Function Index Scale (EFI), and the Weiss Functional Impairments Rating Scale (WFIRS). Individual academic achievement was measured using the Grade Point Average. Statistical analysis revealed that a decreased magnitude of PES was weakly associated with less efficient planning (one of the executive functions). Results suggest that error monitoring, as measured by PES, was not associated with functioning in a naturalistic environment, but could be interpreted to some extent as an experimental marker of planning in daily life executive functioning.

Gender Difference in the Association Between Executive Function and Autistic Traits in Typically Developing Children

Autistic traits and executive function (EF) were assessed in 413 typically developing children aged 6-9 years. The children were divided into the high- autistic-trait (HAT) and low-autistic-trait (LAT) groups based on their total autistic traits. Results suggested that there were gender differences in specific autistic traits in children with LAT. There were gender-specific associations between EF and autistic traits in children with HAT: the set shifting of EF predicted difficulties in social awareness in boys; whereas all the EF components predicted difficulties in social communication and social cognition in girls. These findings may have implications for developing customized interventions that are targeted at specific autistic deficits in males and females.