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Altered motor coordination is common in autistic individuals affecting a range of movements such as manual dexterity, eye-hand coordination, balance and gait. However, motor coordination is not routinely assessed leading to undiagnosed and untreated motor coordination difficulties, particularly in adults. Few studies have investigated motor coordination difficulties and their impact from the viewpoint of autistic people. Therefore, the current study used FGs and thematic analysis to document the experience of motor coordination difficulties from the viewpoint of 17 autistic adults. Four main themes were identified. First, motor coordination difficulties were pervasive and variable, being present life-long and within multiple movements and affecting many aspects of life. Furthermore, the nature of the difficulties was variable within and between participants along with differing awareness of coordination ability. Second, participants described motor coordination as an active process, requiring concentration for most actions and at a level seemingly greater than other people. Third, motor coordination difficulties impacted upon social and emotional wellbeing by placing strain on relationships, prompting bullying and exclusion, putting safety at risk and causing a range of negative emotions. Fourth, in the absence of any support, participants described multiple learning and coping strategies. Findings highlight how it is essential to address the current lack of support for motor coordination considering the significant social and emotional consequences described by our participants. Further investigation of motor learning and interactions between sensory and motor performance in autistic adults is also warranted.

BackgroundDance provides a range of beneficial effects for older adults including individuals with age-related neurological conditions such as Parkinson's disease (PD). The COVID-19 pandemic accelerated the development of at-home dance programs delivered digitally through live and pre-recorded media, but little is known about how participants may engage with and benefit from these resources.ObjectiveThis study explored experiences and potential benefits of digital dance participation among healthy older adults and people with PD.MethodsAn online survey consisting of fixed-choice and open questions was designed in collaboration with dance program providers and distributed between June and November 2020.ResultsHealthy older adults (N = 149) and people with PD (N = 178) participating in at-home dance programs reported frequent engagement and a range of benefits. People with PD reported greater levels of motor (e.g., ease of movement, balance) than non-motor (e.g., energy, confidence) outcomes, while healthy older adults reported similar numbers of motor and non-motor outcomes. Positive outcomes were associated with the use of movement imagery during dance in both groups, while singing was associated with benefits in people with PD and vocalising was associated with benefits in older adults. At-home dance resources were found to offer convenience and flexibility, but participants missed the interaction, support, and routine provided by in-person classes. The majority expressed a preference to continue with both digital and in-person participation in the future. Qualitative analysis of participants' comments further revealed that digital participation could help to maintain connection and well-being, as well as identifying further considerations for improving accessibility and facilitating digital engagement.ConclusionsAt-home dance appears to be accessible, engaging, and potentially beneficial for older adults and people with PD, although barriers to participation should be addressed. Digital resources will be increasingly important to enable cost-effective, large-scale provision of home-based therapeutic activities.

Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other technology-based data collection methods have led to a torrent of high dimensional datasets, which commonly have a small number of samples because of the intrinsic high cost of data collection involving human participants. High dimensional data with a small number of samples is of critical importance for identifying biomarkers and conducting feasibility and pilot work, however it can lead to biased machine learning (ML) performance estimates. Our review of studies which have applied ML to predict autistic from non-autistic individuals showed that small sample size is associated with higher reported classification accuracy. Thus, we have investigated whether this bias could be caused by the use of validation methods which do not sufficiently control overfitting. Our simulations show that K-fold Cross-Validation (CV) produces strongly biased performance estimates with small sample sizes, and the bias is still evident with sample size of 1000. Nested CV and train/test split approaches produce robust and unbiased performance estimates regardless of sample size. We also show that feature selection if performed on pooled training and testing data is contributing to bias considerably more than parameter tuning. In addition, the contribution to bias by data dimensionality, hyper-parameter space and number of CV folds was explored, and validation methods were compared with discriminable data. The results suggest how to design robust testing methodologies when working with small datasets and how to interpret the results of other studies based on what validation method was used.

Some people perceive themselves to look more, or less attractive than they are in reality. We investigated the role of emotions in enhancement and derogation effects; specifically, whether the propensity to experience positive and negative emotions affects how healthy we perceive our own face to look and how we judge ourselves against others. A psychophysical method was used to measure healthiness of self-image and social comparisons of healthiness. Participants who self-reported high positive (N = 20) or negative affectivity (N = 20) judged themselves against healthy (red-tinged) and unhealthy looking (green-tinged) versions of their own and stranger's faces. An adaptive staircase procedure was used to measure perceptual thresholds. Participants high in positive affectivity were un-biased in their face health judgement. Participants high in negative affectivity on the other hand, judged themselves as equivalent to less healthy looking versions of their own face and a stranger's face. Affective traits modulated self-image and social comparisons of healthiness. Face health judgement was also related to physical symptom perception and self-esteem; high physical symptom reports were associated a less healthy self-image and high self-reported (but not implicit) self-esteem was associated with more favourable social comparisons of healthiness. Subject to further validation, our novel face health judgement task could have utility as a perceptual measure of well-being. We are currently investigating whether face health judgement is sensitive to laboratory manipulations of mood.

Attention can be directed to particular spatial locations, or to objects that appear at anticipated points in time. While most work has focused on spatial or temporal attention in isolation, we investigated covert tracking of smoothly moving objects, which requires continuous coordination of both. We tested two propositions about the neural and cognitive basis of this operation: first that covert tracking is a right hemisphere function, and second that pre-motor components of the oculomotor system are responsible for driving covert spatial attention during tracking. We simultaneously recorded event related potentials (ERPs) and eye position while participants covertly tracked dots that moved leftward or rightward at 12 or 20°/s. ERPs were sensitive to the direction of target motion. Topographic development in the leftward motion was a mirror image of the rightward motion, suggesting that both hemispheres contribute equally to covert tracking. Small shifts in eye position were also lateralized according to the direction of target motion, implying covert activation of the oculomotor system. The data addresses two outstanding questions about the nature of visuospatial tracking. First, covert tracking is reliant upon a symmetrical frontoparietal attentional system, rather than being right lateralized. Second, this same system controls both pursuit eye movements and covert tracking.