Tuning the Senses:How the Pupil Shapes Vision at the Earliest Stage

The pupil responds reflexively to changes in brightness and focal distance to maintain the smallest pupil (and thus the highest visual acuity) that still allows sufficient light to reach the retina. The pupil also responds to a wide variety of cognitive processes, but the functions of these cognitive responses are still poorly understood. In this review, I propose that cognitive pupil responses, like their reflexive counterparts, serve to optimize vision. Specifically, an emphasis on central vision over peripheral vision results in pupil constriction, and this likely reflects the fact that central vision benefits most from the increased visual acuity provided by small pupils. Furthermore, an intention to act with a bright stimulus results in preparatory pupil constriction, which allows the pupil to respond quickly when that bright stimulus is subsequently brought into view. More generally, cognitively driven pupil responses are likely a form of sensory tuning: a subtle adjustment of the eyes to optimize their properties for the current situation and the immediate future

DeepMetricEye: Metric Depth Estimation in Periocular VR Imagery

Despite the enhanced realism and immersion provided by VR headsets, users frequently encounter adverse effects such as digital eye strain (DES), dry eye, and potential long-term visual impairment due to excessive eye stimulation from VR displays and pressure from the mask. Recent VR headsets are increasingly equipped with eye-oriented monocular cameras to segment ocular feature maps. Yet, to compute the incident light stimulus and observe periocular condition alterations, it is imperative to transform these relative measurements into metric dimensions. To bridge this gap, we propose a lightweight framework derived from the U-Net 3+ deep learning backbone that we re-optimised, to estimate measurable periocular depth maps. Compatible with any VR headset equipped with an eye-oriented monocular camera, our method reconstructs three-dimensional periocular regions, providing a metric basis for related light stimulus calculation protocols and medical guidelines. Navigating the complexities of data collection, we introduce a Dynamic Periocular Data Generation (DPDG) environment based on UE MetaHuman, which synthesises thousands of training images from a small quantity of human facial scan data. Evaluated on a sample of 36 participants, our method exhibited notable efficacy in the periocular global precision evaluation experiment, and the pupil diameter measurement

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Neural Prosthetic Advancement: identification of circuitry in the Posterior Parietal Cortex

There are limited options for rehabilitation following an established Spinal Cord Injury (SCI) resulting in paralysis. For most of the individuals affected, SCI means a lifetime of confinement to a wheelchair and overall reduced independence. Brain-Computer and Brain-Machine Interface (BCI and BMI) techniques may be of aid when used for assistive purposes. However, these techniques are still far from being implemented in daily rehabilitative practice. Existing literature on the use of BCI and BMI techniques in SCI is limited and focuses on the extraction of motor control signals from the primary motor cortex (M1). However, evidence suggests that in long-term established SCI the functional activation of motor and premotor areas tends to decrease over time. In the present project, we explore the possibility of successful implementation of assistive BCI and BMI systems using posterior parietal areas as extraction sites of motor control activity. Firstly, we will investigate the representation of space in the posterior parietal cortex (PPC) and whether evidence of body-centered reference frames can be found in healthy individuals. We will then proceed to extract information regarding the residual level of motor imagery activity in individuals suffering from long-term and high-level SCI. Our aim is to ascertain whether functional activation of motor and posterior areas is comparable to that of matched controls. Finally, we will present work that was done in collaboration with the Netherlands Organisation for Applied Scientific Research that can offer an example of successful application of a BCI technique for rehabilitation purposes

The assessment of visual behaviour and depth perception in surgery

Imperial Users onl

Investigating the effects of controlled language on the reading and comprehension of machine translated texts: A mixed-methods approach

This study investigates whether the use of controlled language (CL) improves the readability and comprehension of technical support documentation produced by a statistical machine translation system. Readability is operationalised here as the extent to which a text can be easily read in terms of formal linguistic elements; while comprehensibility is defined as how easily a text’s content can be understood by the reader. A biphasic mixed-methods triangulation approach is taken, in which a number of quantitative and qualitative evaluation methods are combined. These include: eye tracking, automatic evaluation metrics (AEMs), retrospective interviews, human evaluations, memory recall testing, and readability indices. A further aim of the research is to investigate what, if any, correlations exist between the various metrics used, and to explore the cognitive framework of the evaluation process. The research finds that the use of CL input results in significantly higher scores for items recalled by participants, and for several of the eye tracking metrics: fixation count, fixation length, and regressions. However, the findings show slight insignificant increases for readability indices and human evaluations, and slight insignificant decreases for AEMs. Several significant correlations between the above metrics are identified as well as predictors of readability and comprehensibility