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A major unresolved question in understanding visually guided locomotion in humans is whether actions are driven solely by the immediately available optical information (model-free online control mechanisms), or whether internal models have a role in anticipating the future path. We designed two experiments to investigate this issue, measuring spontaneous gaze behaviour while steering, and predictive gaze behaviour when future path information was withheld. In Experiment 1 participants (N = 15) steered along a winding path with rich optic flow: gaze patterns were consistent with tracking waypoints on the future path 1–3 s ahead. In Experiment 2, participants (N = 12) followed a path presented only in the form of visual waypoints located on an otherwise featureless ground plane. New waypoints appeared periodically every 0.75 s and predictably 2 s ahead, except in 25% of the cases the waypoint at the expected location was not displayed. In these cases, there were always other visible waypoints for the participant to fixate, yet participants continued to make saccades to the empty, but predictable, waypoint locations (in line with internal models of the future path guiding gaze fixations). This would not be expected based upon existing model-free online steering control models, and strongly points to a need for models of steering control to include mechanisms for predictive gaze control that support anticipatory path following behaviours.

Some activities can be meaningfully dichotomised as 'cognitive' or 'sensorimotor' in nature-but many cannot. This has radical implications for understanding activity limitation in disability. For example, older adults take longer to learn the serial order of a complex sequence but also exhibit slower, more variable and inaccurate motor performance. So is their impaired skill acquisition a cognitive or motor deficit? We modelled sequence learning as a process involving a limited capacity buffer (working memory), where reduced performance restricts the number of elements that can be stored. To test this model, we examined the relationship between motor performance and sequence learning. Experiment 1 established that older adults were worse at learning the serial order of a complex sequence. Experiment 2 found that participants showed impaired sequence learning when the non-preferred hand was used. Experiment 3 confirmed that serial order learning is impaired when motor demands increase (as the model predicted). These results can be captured by reinforcement learning frameworks which suggest sequence learning will be constrained both by an individual's sensorimotor ability and cognitive capacity.

Many people experience unilateral degraded vision, usually owing to a developmental or age-related disorder. There are unresolved questions regarding the extent to which such unilateral visual deficits impact on sensorimotor performance; an important issue as sensorimotor limitations can constrain quality of life by restricting 'activities of daily living'. Examination of the relationship between visual deficit and sensorimotor performance is essential for determining the functional implications of ophthalmic conditions. This study attempts to explore the effect of unilaterally degraded vision on sensorimotor performance. In Experiment 1 we simulated visual deficits in 30 participants using unilateral and bilateral Bangerter filters to explore whether motor performance was affected in water pouring, peg placing, and aiming tasks. Experiment 2 (n = 74) tested the hypothesis that kinematic measures are associated with visuomotor deficits by measuring the impact of small visual sensitivity decrements created by monocular viewing on sensorimotor interactions with targets presented on a planar surface in aiming, tracking and steering tasks. In Experiment 1, the filters caused decreased task performance-confirming that unilateral (and bilateral) visual loss has functional implications. In Experiment 2, kinematic measures were affected by monocular viewing in two of three tasks requiring rapid online visual feedback (aiming and steering). Unilateral visual loss has a measurable impact on sensorimotor performance. The benefits of binocular vision may be particularly important for some groups (e.g. older adults) where an inability to complete sensorimotor tasks may necessitate assisted living. There is an urgent need to develop rigorous kinematic approaches to the quantification of the functional impact of unilaterally degraded vision and of the benefits associated with treatments for unilateral ophthalmic conditions to enable informed decisions around treatment.

Automated vehicles (AVs) will change the role of the driver, from actively controlling the vehicle to primarily monitoring it. Removing the driver from the control loop could fundamentally change the way that drivers sample visual information from the scene, and in particular, alter the gaze patterns generated when under AV control. To better understand how automation affects gaze patterns this experiment used tightly controlled experimental conditions with a series of transitions from ‘Manual’ control to ‘Automated’ vehicle control. Automated trials were produced using either a ‘Replay’ of the driver’s own steering trajectories or standard ‘Stock’ trials that were identical for all participants. Gaze patterns produced during Manual and Automated conditions were recorded and compared. Overall the gaze patterns across conditions were very similar, but detailed analysis shows that drivers looked slightly further ahead (increased gaze time headway) during Automation with only small differences between Stock and Replay trials. A novel mixture modelling method decomposed gaze patterns into two distinct categories and revealed that the gaze time headway increased during Automation. Further analyses revealed that while there was a general shift to look further ahead (and fixate the bend entry earlier) when under automated vehicle control, similar waypoint-tracking gaze patterns were produced during Manual driving and Automation. The consistency of gaze patterns across driving modes suggests that active-gaze models (developed for manual driving) might be useful for monitoring driver engagement during Automated driving, with deviations in gaze behaviour from what would be expected during manual control potentially indicating that a driver is not closely monitoring the automated system.

Disturbance forces facilitate motor learning, but theoretical explanations for this counterintuitive phenomenon are lacking. Smooth arm movements require predictions (inference) about the force-field associated with a workspace. The Free Energy Principle (FEP) suggests that such 'active inference' is driven by 'surprise'. We used these insights to create a formal model that explains why disturbance might help learning. In two experiments, participants undertook a continuous tracking task where they learned how to move their arm in different directions through a novel 3D force field. We compared baseline performance before and after exposure to the novel field to quantify learning. In Experiment 1, the exposure phases (but not the baseline measures) were delivered under three different conditions: (i) robot haptic assistance; (ii) no guidance; (iii) robot haptic disturbance. The disturbance group showed the best learning as our model predicted. Experiment 2 further tested our FEP inspired model. Assistive and/or disturbance forces were applied as a function of performance (low surprise), and compared to a random error manipulation (high surprise). The random group showed the most improvement as predicted by the model. Thus, motor learning can be conceptualised as a process of entropy reduction. Short term motor strategies (e.g. global impedance) can mitigate unexpected perturbations, but continuous movements require active inference about external force-fields in order to create accurate internal models of the external world (motor learning). Our findings reconcile research on the relationship between noise, variability, and motor learning, and show that information is the currency of motor learning.

Detecting a looming object and its imminent collision is imperative to survival. For most humans, it is a fundamental aspect of daily activities such as driving, road crossing and participating in sport, yet little is known about how the brain both detects and responds to such stimuli. Here we use functional magnetic resonance imaging to assess neural response to looming stimuli in comparison with receding stimuli and motion-controlled static stimuli. We demonstrate for the first time that, in the human, the superior colliculus and the pulvinar nucleus of the thalamus respond to looming in addition to cortical regions associated with motor preparation. We also implicate the anterior insula in making timing computations for collision events.

The neural systems responsible for postural control are separate from the neural substrates that underpin control of the hand. Nonetheless, postural control and eye-hand coordination are linked functionally. For example, a stable platform is required for precise manual control tasks (e.g. handwriting) and thus such skills often cannot develop until the child is able to sit or stand upright. This raises the question of the strength of the empirical relationship between measures of postural stability and manual motor control. We recorded objective computerised measures of postural stability in stance and manual control in sitting in a sample of school children ( n  = 278) aged 3–11 years in order to explore the extent to which measures of manual skill could be predicted by measures of postural stability. A strong correlation was found across the whole sample between separate measures of postural stability and manual control taken on different days. Following correction for age, a significant but modest correlation was found. Regression analysis with age correction revealed that postural stability accounted for between 1 and 10 % of the variance in manual performance, dependent on the specific manual task. These data reflect an interdependent functional relationship between manual control and postural stability development. Nevertheless, the relatively small proportion of the explained variance is consistent with the anatomically distinct neural architecture that exists for ‘gross’ and ‘fine’ motor control. These data justify the approach of motor batteries that provide separate assessments of postural stability and manual dexterity and have implications for therapeutic intervention in developmental disorders.

Monocular blur sometimes impairs locomotion; however, it is not always clear when this will happen. Optic flow (the apparent motion of scene texture elements that occurs during self-motion) provides powerful signals about the direction of travel. Here, we test whether monocular blur impairs heading perception from optic flow compared to full vision under various levels of optic flow degradation. Participants (N = 52, mean age = 30 years) completed contrast sensitivity, visual acuity, and heading perception tasks with rich or degraded optic flow, with or without monocular blur (0.4 logMAR Bangerter filter over the non-dominant eye, full vision in the dominant eye). Heading perception was assessed using a browser-based task where the participants viewed a 3-second video consistent with self-motion over a textured ground plane (moving towards the horizon at an offset heading ranging from −20 to +20°) and identified the point on the horizon towards which they were travelling. The measures of each participant's performance were the absolute and directional angular error between the heading offset and their response. Monocular blur and degraded flow were associated with an increase in absolute heading error and a larger underestimation of heading angle, with the worst performance observed when monocular blur and degraded flow were combined. These results suggest that the impact of monocular blur on heading perception becomes apparent only when optic flow signals are weak (e.g., night-time driving). These findings support the theory that monocular blur and the richness of visual information interact to produce deficits in heading perception.

Some studies have shown that manual asymmetries decrease in older age. These results have often been explained with reference to models of reduced hemispheric specialisation. An alternative explanation, however, is that hand differences are subtle, and capturing them requires tasks that yield optimal performance with both hands. Whereas the hemispheric specialisation account implies that reduced manual asymmetries should be reliably observed in older adults, the 'measurement difficulty' account suggests that manual asymmetries will be hard to detect unless a task has just the right level of difficulty--i.e. within the 'Goldilocks Zone', where it is not too easy or too hard, but just right. Experiment One tested this hypothesis and found that manual asymmetries were only detected when participants performed in this zone; specifically, performance on a tracing task was only superior in the preferred hand when task constraints were high (i.e. fast speed tracing). Experiment Two used three different tasks to examine age differences in manual asymmetries; one task produced no asymmetries, whilst two tasks revealed asymmetries in both younger and older groups (with poorer overall performance in the old group across all tasks). Experiment Three revealed task-dependent asymmetries in both age groups, but highlighted further detection difficulties linked with the metric of performance and compensatory strategies used by participants. Results are discussed with reference to structural learning theory, whereby we suggest that the processes of inter-manual transfer lead to relatively small performance differences between the hands (despite a strong phenomenological sense of performance disparities).

Old age is associated with reduced mobility of the hand. To investigate age related decline when reaching-to-lift an object we used sophisticated kinematic apparatus to record reaches carried out by healthy older and younger participants. Three objects of different widths were placed at three different distances, with objects having either a high or low friction surface (i.e. rough or slippery). Older participants showed quantitative differences to their younger counterparts - movements were slower and peak speed did not scale with object distance. There were also qualitative differences with older adults showing a greater propensity to stop the hand and adjust finger position before lifting objects. The older participants particularly struggled to lift wide slippery objects, apparently due to an inability to manipulate their grasp to provide the level of precision necessary to functionally enclose the object. These data shed light on the nature of age related changes in reaching-to-grasp movements and establish a powerful technique for exploring how different product designs will impact on prehensile behavior.