You will carry out experiments using high fidelity immersive virtual reality to explore the way that people represent 3D space. You will learn psychophysics techniques and will be introduced in analysis techniques for discriminating between computational models of 3D scene representation.
Department: Psychology
Supervised by: Prof Andrew Glennerster
Our lab focuses on theories about how the brain represents 3D scenes as the observer moves around. Currently, there are very different types of models: one type assumes that the brain generates a 3D model of the scene (either centred on the observer or fixed relative to the word, “allocentric”). Another type of model assumes that the brain “knows” about the way that images change as the observer moves and can do this without building a 3D model. Modern neural network approaches are of the second type. The UROP projects would be part of a larger effort to distinguish between these two types of models. Participants will be asked to explore a realistic indoors scene in VR. Specifically, after viewing the scene from one location (‘home’) they will be transported virtually to a different location from where they must return ‘home’. The pattern of errors that observers make will allow us to discriminate between candidate representations. The student will be actively involved in data collection, analysis and interpretation of the results.
The student will be involved in data collection as well as data analysis. The student will be expected to also advance his/her knowledge in the field through reviewing relevant literature. There will also be an opportunity to gain a range of skills (see below).
The student is expected to show enthusiasm for the project and keenness to learn. The student should, preferably, have a good understanding of statistics while experience with MATLAB is desirable but not necessary.
The student will have the opportunity to gain experience with Virtual Reality and develop transferable skills on data analysis and programming (MATLAB, C#). Furthermore, the student will receive training on software such as Unity Game Engine and develop their knowledge on psychophysical experiments. The level of skills developed will be decided in agreement with the student. Finally, if the project leads to data that are included in a publication, the student would be included in the development of the manuscript.
The student will be provided with a desk space and PC access within the School of Psychology and Clinical Language Sciences.
Regular office hours
Monday 15 June 2020 - Monday 27 July 2020
The deadline to apply for this project is Monday 11th May at 5pm. Students should submit their CV and Cover Letter directly to the Project Supervisor (click on supervisor name at the top of the page for email). Interviews will be held by Prof Andrew Glennerster and Dr Maria Elena Stefanou