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[AUDITORY] PhD in Computational Neuroscience at the University of Exeter (fully funded)



PhD in Computational Neuroscience at the University of Exeter (fully funded)

***Closes in 4 days***

3.5 year college funded PhD Studentship in Computational Neuroscience:
Neural dynamics of perceptual competition
Ref: 2589

Open to UK, EU and International students with maintenance (£14,296 per year) and tuition fees fully funded

http://www.exeter.ac.uk/studying/funding/award/?id=2589

This interdisciplinary project will use mathematical modelling, in conjunction with psychophysics (human perception experiments), to better understand the neural competition underpinning the dynamics of perception. Ambiguity in fixed sensory stimuli can lead to spontaneous switches in perception, both in vision, e.g. binocular rivalry, Necker cube, and audition, e.g. auditory streaming (switches between grouped or segregated interpretations of tone sequences). A set of common characteristics (inevitability of perceptual changes, exclusivity between the competing percepts, and randomness in the percept durations), generalise across sensory modalities. The neural competition driving these perceptual switches has been successfully modelled in small networks of Wilson-Cowan (firing rate) units, each associated with the different perceptual interpretations. For certain stimuli, where competition takes place across a continuous feature space (say, visual orientation, motion direction, or auditory pitch), a continuum model, such as the neural field equation can be applied.  This PhD project will involve the derivation of perceptual competition models in a dynamical systems framework, based on plausible neural mechanisms commonly found in sensory cortex. Modelling hypotheses and predictions will be tested against experimental data collected in our lab or from collaborators. On the modelling side, tools from bifurcation analysis including numerical continuation will be applied to investigate dynamics.  The project will be flexible in terms of the balance between modelling and experiments.  Candidates with quantitative backgrounds (mathematics, physics, and engineering) and from neuroscience or psychology programmes are encouraged to apply.  Programming experience and/or knowledge of dynamical systems theory is a plus.

Contact: j.a.rankin@xxxxxxxxxxxx
Informal enquiries welcome.

Application deadline: 10th April 2017

Please forward to interested parties as appropriate

Thanks,
James