Callum Mole

Optic flow asymmetries bias high-speed steering along roads.

How do animals and insects use visual information to move through the world successfully? Optic flow, the pattern of motion at the eye, is a powerful source of information about self-motion. Insects and humans are sensitive to the global pattern of optic flow and try to maintain flow symmetry when flying or walking. The environments humans encounter, however, often contain demarcated paths that constrain future trajectories (e.g., roads), and steering has been successfully modeled using only road edge information. Here we examine whether flow asymmetries from a textured ground plane influences humans steering along demarcated paths. Using a virtual reality simulator we observed that different textures on either side of the path caused predictable biases to steering trajectories, consistent with participants reducing flow asymmetries. We also generated conditions where one textured region had no flow (either the texture was removed or the textured region was static). Despite the presence of visible path information, participants were biased toward the no-flow region consistent with reducing flow asymmetries. We conclude that optic flow asymmetries can lead to biased locomotor steering even when traveling along demarcated paths.

The need for speed: global optic flow speed influences steering

How do animals follow demarcated paths? Different species are sensitive to optic flow and one control solution is to maintain the balance of flow symmetry across visual fields; however, it is unclear whether animals are sensitive to changes in asymmetries when steering along curved paths. Flow asymmetries can alter the global properties of flow (i.e. flow speed) which may also influence steering control. We tested humans steering curved paths in a virtual environment. The scene was manipulated so that the ground plane to either side of the demarcated path produced larger or smaller asymmetries in optic flow. Independent of asymmetries and the locomotor speed, the scene properties were altered to produce either faster or slower globally averaged flow speeds. Results showed that rather than being influenced by changes in flow asymmetry, steering responded to global flow speed. We conclude that the human brain performs global averaging of flow speed from across the scene and uses this signal as an input for steering control. This finding is surprising since the demarcated path provided sufficient information to steer, whereas global flow speed (by itself) did not. To explain these findings, existing models of steering must be modified to include a new perceptual variable: namely global optic flow speed.

Driving with homonymous visual field loss: Does visual search performance predict hazard detection?

Introduction Stroke often causes homonymous visual field loss, which can lead to exclusion from driving. Retention of a driving licence is sometimes possible by completing an on-road assessment, but this is not practical for all. It is important to find simple tests that can inform the assessment and rehabilitation of driving-related visual-motor function. Method We developed novel computerised assessments: visual search; simple reaction and decision reaction to appearing pedestrians; and pedestrian detection during simulated driving. We tested 12 patients with stroke (seven left, five right field loss) and 12 controls. Results The homonymous visual field defect group was split into adequately compensated or inadequately compensated groups based on visual search performance. The inadequately compensated group had problems with stimuli in their affected field: they tended to react more slowly than controls and in the driving task they failed to detect a number of pedestrians. In contrast, the adequately compensated group were better at detecting pedestrians, though reaction times were slightly slower than controls. Conclusion We suggest that our search task can predict, to a limited extent, whether a person with stroke compensates for visual field loss, and may potentially identify suitability for specific rehabilitation to promote return to driving.

Visuomotor control, eye movements, and steering: A unified approach for incorporating feedback, feedforward, and internal models.

The authors present an approach to the coordination of eye movements and locomotion in naturalistic steering tasks. It is based on recent empirical research, in particular, on driver eye movements, that poses challenges for existing accounts of how we visually steer a course. They first analyze how the ideas of feedback and feedforward processes and internal models are treated in control theoretical steering models within vision science and engineering, which share an underlying architecture but have historically developed in very separate ways. The authors then show how these traditions can be naturally (re)integrated with each other and with contemporary neuroscience, to better understand the skill and gaze strategies involved. They then propose a conceptual model that (a) gives a unified account to the coordination of gaze and steering control, (b) incorporates higher-level path planning, and (c) draws on the literature on paired forward and inverse models in predictive control. Although each of these (a–c) has been considered before (also in the context of driving), integrating them into a single framework and the authors’ multiple waypoint identification hypothesis within that framework are novel. The proposed hypothesis is relevant to all forms of visually guided locomotion.

Metacognitive judgements of perceptual-motor steering performance

Control of skilled actions requires rapid information sampling and processing, which may largely be carried out subconsciously. However, individuals often need to make conscious strategic decisions that ideally would be based upon accurate knowledge of performance. Here, we determined the extent to which individuals have explicit awareness of their steering performance (conceptualised as “metacognition”). Participants steered in a virtual environment along a bending road while attempting to keep within a central demarcated target zone. Task demands were altered by manipulating locomotor speed (fast/slow) and the target zone (narrow/wide). All participants received continuous visual feedback about position in zone, and one sub-group was given additional auditory warnings when exiting/entering the zone. At the end of each trial, participants made a metacognitive evaluation: the proportion of the trial they believed was spent in the zone. Overall, although evaluations broadly shifted in line with task demands, participants showed limited calibration to performance. Regression analysis showed that evaluations were influenced by two components: (a) direct monitoring of performance and (b) indirect task heuristics estimating performance based on salient cues (e.g., speed). Evaluations often weighted indirect task heuristics inappropriately, but the additional auditory feedback improved evaluations seemingly by reducing this weighting. These results have important implications for all motor tasks where conscious cognitive control can be used to influence action selection.

Steering along curved paths is influenced by global flow speed not speed asymmetry

Retinal flow, the pattern of motion caused by self-motion through a textured world, is used to control steering. Our previous work has shown that flow asymmetries influence humans steering along demarcated paths, with different textures on either side of the path causing biases consistent with participants reducing flow asymmetries (Kountouriotis et al., 2013). To test whether asymmetries in speed also bias locomotor control, participants were asked to steer a series of curved trajectories in a virtual reality simulated environment. Regions of the ground plane either side of a visible bounded path were rotated at different speeds to create flow asymmetries. The manipulation varied (i) Asymmetry Direction: whether the ground to the inside of the bend moved slower or faster than the outside of the bend, (ii) Asymmetry Size: whether the difference in speeds of the two regions was a small gap or a large gap, and (iii) Global Flow Speed: whether the average speed across both regions was slower than, the same as, or faster than the actual locomotor travel speed. The results suggest that participants did not simply equalise the flow vectors (i.e. steer towards the slower-moving region) since asymmetry size and direction did not systematically alter steering. Instead, participants were influenced by the global flow speed, whereby faster global flow led to greater oversteer (towards the inside of the bend) and vice versa. Importantly, steering biases occurred despite the visible path providing splay angle information across all conditions. We conclude that global flow speed is used to control locomotor steering even when travelling along visible paths that provide alternative useful sources of information Meeting abstract presented at VSS 2015.