When we move, stationary parts of the world around us move on the retina. Of course, usually we correctly interpret this retinal motion as due to our own movement and not movement of the surrounding environment. This ability is based upon complex neural processing that compensates for self-generated retinal motion using information from multiple sources about our own movement (Warren & Rushton, 2009). Without this processing, moving around in the environment would be much more difficult and dangerous, since we would commonly believe that stationary objects were moving.
In this project we will investigate the accuracy and precision of the neural mechanisms that support this ability and the extent to which they depend on the presence of different sources of information about self movement. In addition, it is known that motion processing in general is impaired with age (Snowden & Kavanagh, 2006; Kavcic et al, 2011) and consequently we will measure the extent to which performance changes across the adult lifespan. This is a particularly important question since it is possible that such changes contribute to increased collision and fall risk observed in older people.
To address these questions we will use the state-of-the-art VR lab recently built by the primary supervisor at the University of Manchester. Using VR we can to break the rules that normally link our own movement to the resulting movement of stationary objects on the retina. For example imagine moving towards an object in front of you. Normally the object would expand on your retina as you move towards it. Now imagine that instead we break the natural rules and make the object expand more or less than it should. Would you notice this? How much can we break the rules before you begin to notice the change? Previous research has suggested that this system is actually prone to making quite significant errors (Thchang et al, 2005; Wexler, 2005) and we will build on this research in the present project, considering different combinations of self and object movement.
The outcome will be an understanding of the contribution of different sources of self movement information to the mechanisms of perceptual stability for different movement types. In addition we will be able to track these parameters over the adult lifespan. This research will therefore underpin future work investigating the potential contribution of these changes to fall risk in older people.
Entry Requirements
Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a related area/subject. Candidates with previous laboratory experience, particularly in cell culture and molecular biology, are particularly encouraged to apply.
How To Apply
For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (https://www.bmh.manchester.ac.uk/study/research/apply/). Informal enquiries may be made directly to the primary supervisor. On the online application form select PhD Genetics
For international students, we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences.
Equality, Diversity and Inclusion
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/”
For international students we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit www.internationalphd.manchester.ac.uk
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