Computation of positional statistics by the human visual system

Although visual acuity is surprisingly good and visual memory is surprisingly capacious, there are limits. Under various constraints, observers must sacrifice acuity for capacity. Of these constraints, one of the best studied is viewing eccentricity. For example, outside the centre of the visual field, the addition of just two vertical lines can cause the just-noticeable tilt of a third line to double. This dramatic loss of acuity (‘crowding’) is thought to reflect an obligatory statistical analysis by the visual system. Instead of reporting the target’s tilt, observers report the mean of all three lines. Previous research suggests that normal observers perform relatively well when detecting irregularities in dot arrays, but we have yet to address the more general question of how (and how well) multiple positions can be encoded within the visual system. This project will adopt the same systematic approach previously used in our laboratory for exploring the encoding multiple orientations. Instead of lines with various orientations, we will use regularly spaced dots extending from fixation to some maximum eccentricity. Discriminations between different mean azimuths and between different variances in azimuth will be analysed in the same way as we have analysed discriminations between different mean orientations and different orientation variances. Of particular interest is whether there is any crowding of position at all. Nearby dots with identical azimuths may have no effect at all on the acuity for a precued target with a slightly different azimuth.

School of Health Sciences
The School of Health Sciences is offering up to five full/part-time Doctoral Studentships to outstanding candidates. We are a leading provider of applied healthcare research and we offer PhD candidates an outstanding research environment: in REF 2014, 100% of our research environment was judged as world leading or internationally excellent and 100% of research impact was judged as world leading or internationally excellent. In the recent Postgraduate Research Experience Survey, 96% of PhD students responding rated the expertise and responsiveness of their supervisors as excellent. Successful applicants would join around 70 current PhD students in the School, providing a supportive environment of peers.

Eligibility
The studentships will be awarded on the basis of outstanding academic achievement and the potential to produce cutting edge-research.
• Applicants must hold at least a 2.1 honours degree or merit level Masters degree in a relevant subject (or international equivalent)
• Applicants whose first language is not English must have achieved at least 7.0 in IELTS or a recognised equivalent
• Applicants must not be currently registered as a doctoral student at City, University of London or any other academic institution

How to Apply
To apply for studentship funding:
• Complete an application form for a place on the PhD programme by clicking here where you will be asked to register before you can complete your application
• Upload your research proposal (four sides of A4 maximum including references) on one of the specific projects listed by supervisors or in any of the areas covered by the research centres following discussion and agreement with a potential supervisor.
Research centres: https://www.city.ac.uk/health/research

• Suggested structure of proposal:
1. Project description; Topic, motivation from the literature, Methods and potential impact
2. How does this fit with the work carried out in the School of Health Sciences?
3. Potential for this research lead to an important question or methodological innovation that might lead to 4* output

• Upload a short cover letter with your application requesting that your application be considered for studentship funding
• Submit your online application form and supporting documents by 30 November 2018. If you have any queries, please the doctoral degrees support officer, Tracy Rowson ([Email Address Removed]).