In our natural dynamic environment the senses are constantly bombarded with many different signals. How does the human brain integrate information from multiple senses to form a coherent percept and interact effectively with our environment? How is information integration modulated by attention, awareness and vigilance? To which extent can the brain integrate signals unconsicously (e.g. sleep, vegetative state)?
To study the neural mechanisms underlying multisensory integration and learning in humans, we combine psychophysics, functional imaging (fMRI, EEG/MEG & combined TMS-fMRI) and computational modelling. Effective connectivity analyses (e.g. Dynamic Causal Modelling) are used to investigate how information is integrated from the senses through distinct interactions amongst brain regions. To provide a more informed perspective on the computational operations, we combine functional imaging with models of Bayesian inference and learning.
The Computational Cognitive Neuroimaging Group (Prof Uta Noppeney) is seeking an enthusiastic PhD candidate with a strong quantitative background. The applicant should have a background in neuroscience, psychology, computer science, physics or related areas. Prior experience in functional imaging/psychophysics, MatLab, data analysis and/or machine learning (e.g. Bayesian inference) would be an advantage.
The Computational Cognitive Neuroimaging lab is based at the Computational Neuroscience and Cognitive Robotics Centre and the Department of Psychology of the University of Birmingham, UK. The centre provides an excellent multidisciplinary, interactive and collaborative research environment combining expertise in cognitive neuroimaging, psychophysics and computational neuroscience. The psychology department was rated 5th in the UK research assessment exercise.
For further information, please contact [email protected]
For application to the PhD position, please send application including CV, statement of research interests, and the names and full contact details of two referees to: [email protected]
Applications will be considered until 8th January 2017. The starting date is Sept/Oct 2017
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