Optimal performance in time-constrained and dynamically changing environments depends on
making reliable predictions about future outcomes. In sporting tasks, performers have been found
to employ multiple information sources to maximize the accuracy of their predictions, but
questions remain about how different information sources are weighted and integrated to guide
anticipation. In this paper, we outline how predictive processing approaches, and active inference
in particular, provide a unifying account of perception and action which explains many of the
prominent findings in the sports anticipation literature. Active inference proposes that perception
and action are underpinned by the organisms’ need to remain within certain stable states. To this
end, decision making approximates Bayesian inference and actions are used to minimise future
prediction errors during brain-body-environment interactions. Using a series of Bayesian
neurocomputational models based on a partially observable Markov process, we demonstrate that
key findings from the literature can be recreated from the first principles of active inference. In
doing so, we formulate a number of novel and empirically falsifiable hypotheses about human
anticipation capabilities which could guide future investigations in the field

Research suggests that sensorimotor difficulties in autism could be reduced by providing individuals with explicit contextual information. To test this, we examined autistic visuomotor control during a virtual racquetball task, in which participants hit normal and unexpectedly-bouncy balls using a handheld controller. The probability of facing each type of ball was varied unpredictably over time. However, during cued trials, participants received explicit information about the likelihood of facing each uncertain outcome. When compared to neurotypical controls, autistic individuals displayed poorer task performance, atypical gaze profiles, and more restricted swing kinematics. These visuomotor patterns were not significantly affected by contextual cues, indicating that autistic people exhibit underlying differences in how prior information and environmental uncertainty are dynamically modulated during movement tasks.

PurposeRecent work could further improve the use of VR technology by advocating the use of psychological theories in task design and highlighting certain properties of VR configurations and human – VR interactions. The variety of VR technology used in the trials prevents us from establishing a systematic relationship between the technology type and its effectiveness. As such, more research is needed to study this link, and our piece is an attempt to shed a spotlight on the issue.Design/methodology/approachTo explore recent developments in the field, the authors followed the procedures of scoping review by Savickaite et al. (2022) and included publications from 2021 to 2022.FindingsIn this updated analysis, it was clear that the research themes emerging over the last two years were similar to those identified previously. Social training and intervention work still dominates the research area, in spite of recent calls from the autism community to broaden the scientific understanding of neurodivergent experiences and daily living behaviours. Although, autism is often characterised by difficulties with social interactions, it is just one part of the presentation. Sensory differences, motor difficulties and repetitive behaviours are also important facets of the condition, as well as various wider aspects of health, wellbeing and quality of life. However, many of these topics appear to be understudied in research on VR applications for autism.Originality/valueVR stands out from other representational technologies because of its immersion, presence and interactivity and has grown into its own niche. The question of what constitutes a truly immersive experience has resurfaced. We can no longer deny that VR has established itself in autism research. As the number of studies continues to grow, it is a perfect time to reconsider and update our notion of definitions of immersion and its reliance on hardware.

Purpose: This paper aims to raise awareness of and argue for the use of participatory methods for the research and development of Virtual Reality (VR) applications designed for neurodivergent groups. This includes exploring why it is important to meaningfully include neurodivergent groups and the benefits their inclusion provide. Design/methodology/approach: VR is becoming increasingly widespread as a consumer product and interventional tool. It is vital for researchers and developers to embrace best practices in these early stages of using the technology, making certain that neurodivergent people have the best possible outcomes. Findings: the neurodivergent community is dissatisfied with many of the research directions currently being undertaken. This dissatisfaction arises from conflicting priorities between different stakeholders and the lack of input from the community. Participatory research brings neurodivergent people into the research process, whether as members of the research team or as consultants at key steps. Effective participatory research ensures that the priorities of the neurodivergent community are better incorporated in research, as well as enabling the development of more effective applications for VR. Originality/value: Participatory methods are unutilised in the development of applications aimed for neurodivergent people. By describing their use and utility in other areas, this article aims to encourage other VR researchers to take neurodivergent people on board.

AbstractIn this study, we examined the relationship between physiological encoding of surprise and the learning of anticipatory eye movements. Active inference portrays perception and action as interconnected inference processes, driven by the imperative to minimise the surprise of sensory observations. To examine this characterisation of oculomotor learning during a hand–eye coordination task, we tested whether anticipatory eye movements were updated in accordance with Bayesian principles and whether trial-by-trial learning rates tracked pupil dilation as a marker of ‘surprise’. Forty-four participants completed an interception task in immersive virtual reality that required them to hit bouncing balls that had either expected or unexpected bounce profiles. We recorded anticipatory eye movements known to index participants’ beliefs about likely ball bounce trajectories. By fitting a hierarchical Bayesian inference model to the trial-wise trajectories of these predictive eye movements, we were able to estimate each individual’s expectations about bounce trajectories, rates of belief updating, and precision-weighted prediction errors. We found that the task-evoked pupil response tracked prediction errors and learning rates but not beliefs about ball bounciness or environmental volatility. These findings are partially consistent with active inference accounts and shed light on how encoding of surprise may shape the control of action.

Optimal performance in time-constrained and dynamically changing environments depends on making reliable predictions about future outcomes. In sporting tasks, performers have been found to employ multiple information sources to maximize the accuracy of their predictions, but questions remain about how different information sources are weighted and integrated to guide anticipation. In this paper, we outline how active inference, a unifying account of perception and action, explains many of the prominent findings in the sports anticipation literature. Active inference proposes that perception and action are underpinned by the need to minimize prediction errors and optimise a predictive model of the world. To this end, decision making approximates Bayesian inference and actions are used to minimize future prediction errors. Using a series of Bayesian neurocomputational models based on a partially observable Markov process, we demonstrate that key findings from the literature can be recreated from the first principles of active inference. In doing so, we formulate a number of novel, empirically falsifiable hypotheses about human anticipation capabilities which could guide future investigations in the field.

Developmental coordination disorder (DCD) describes a condition of poor motor performance in the absence of intellectual impairment. Despite being one of the most prevalent developmental disorders, little is known about how fundamental visuomotor processes might function in this group. One prevalent idea is children with DCD interact with their environment in a less predictive fashion than typically developing children. A metric of prediction which has not been examined in this group is the degree to which the hands and eyes are coordinated when performing manual tasks. To this end, we examined hand and eye movements during an object lifting task in a group of children with DCD (n=19) and an age-matched group of children without DCD (n=39). We observed no differences between the groups in terms of how well they coordinated their hands and eyes when lifting objects, nor in terms of the degree by which the eye led the hand. We thus find no evidence to support the proposition that children with DCD coordinate their hands and eyes in a non-predictive fashion. In a follow-up exploratory analysis we did, however, note differences in fundamental patterns of eye movements between the groups, with children in the DCD group showing some evidence of atypical visual sampling strategies and gaze anchoring behaviours during the task.

This paper presents the first two studies to explore the effect of challenge and threat states on endurance exercise capabilities. In study one, relationships between cardiovascular markers of challenge and threat states, ratings of perceived exertion (RPE), and exercise tolerance were explored during moderate- and severe-intensity cycling. Cardiovascular reactivity more reflective of a challenge state (i.e. relatively higher cardiac output and/or lower total peripheral resistance reactivity) predicted lower RPE throughout moderate- but not severe-intensity cycling. Building on these findings, study two experimentally manipulated participants into challenge, threat, and neutral groups, and compared 16.1 km time-trial performances, where pacing is self-regulated by RPE. Participants completed familiarisation, control, and experimental visits while physiological (oxygen uptake), perceptual (RPE), and performance-based (time to completion [TTC] and power output [PO]) variables were assessed. When compared to the threat group, the challenge group demonstrated cardiovascular responses more indicative of a challenge state, and delivered faster early-race pacing (PO) at similar RPE. Although there were no significant differences in TTC, results revealed that augmentations in PO for the challenge group were facilitated by tempered perceptions of fatigue. The findings suggest that an individual's pre-exercise psychophysiological state might influence perceived exertion and endurance exercise capabilities.

Recent research proposes that sensorimotor difficulties, such as those experienced by many autistic people, may arise from atypicalities in prediction. Accordingly, we examined the relationship between non-clinical autistic-like traits and sensorimotor prediction in the material-weight illusion, where prior expectations derived from material cues typically bias one's perception and action. Specifically, prediction-related tendencies in perception of weight, gaze patterns, and lifting actions were probed using a combination of self-report, eye-tracking, motion-capture, and force-based measures. No prediction-related associations between autistic-like traits and sensorimotor control emerged for any of these variables. Follow-up analyses, however, revealed that greater autistic-like traits were correlated with reduced adaptation of gaze with changes in environmental uncertainty. These findings challenge proposals of gross predictive atypicalities in autistic people, but suggest that the dynamic integration of prior information and environmental statistics may be related to autistic-like traits. Further research into this relationship is warranted in autistic populations, to assist the development of future movement-based coaching methods.