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Understanding brain dynamics: merging experiments and models

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  • Full or part time
    Dr M Goodfellow
    Prof G Augustine
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

About the Programme:

The University of Exeter (UoE) and Nanyang Technological University (NTU), Singapore are offering six fully funded postgraduate studentships to undertake collaborative research projects at the two institutions, leading to PhD degrees (split-site) to be conferred either by the UoE or NTU.

Students pursuing these postgraduate research projects will benefit from the unique opportunity to conduct their research at both institutions. Students will be registered at one or other institution, where they will be based for the majority of their time, but will spend at least 12 and not more than 18 months at the partner institution over the duration of the programme. The frequency and length of stays at each institution will be agreed with successful candidates prior to offers being made.

Project Description:

Healthy brain function is mediated by the coordination of neuronal activity - both locally and across different brain regions - giving rise to large-scale brain dynamics. These dynamics are measured using a variety of techniques, for example magneto-/electro-encephalography or functional MRI in humans, or by fluorescence-based imaging of voltage- or calcium-sensitive indicators in animal models in vivo. Uncovering the nature and mechanisms of large-scale brain dynamics at rest, or during sensory processing, remains a fundamental challenge in neuroscience. In addition to basic insight, improving our understanding of healthy brain dynamics will help us elucidate reasons why abnormal dynamics occur, for example in neurological or neuropsychiatric disorders.

Since brain dynamics emerge and fluctuate in a complex system comprised of many interacting, dynamic components, it is crucial to use mathematical models to assimilate information and to make sense of experimental data. We have very well developed and experimentally validated models and theories for single neurons, but the same cannot be said for models of brain regions. The latter have arisen either from purely theoretical considerations or from results of decades-old experiments, in which electrical stimulation and electrode recordings were used to probe the behaviour of circumscribed regions of tissue. Thus, despite showing promise in applications in health and disease, our models and understanding of large-scale brain dynamics remain rudimentary. However, the last 2 decades have seen significant advances in techniques to probe and observe brain circuits. For example, we can now manipulate and record from specific neuronal populations in vivo with high temporal and spatial resolution, using optogenetics and fluorescent reporters. Thus we are now in a position to improve our basic understanding of brain function by constructing and validating new large-scale theories and models in combination with cutting-edge experimental measurements to test these models.

This studentship will develop a novel program of interdisciplinary research across in vivo (mouse) experimentation and mathematical modelling. The overall aim is to construct and validate mathematical models of large-scale brain dynamics that are able to explain the spontaneous activity of the rodent brain in vivo. The student will train in optogenetic technologies and in vivo imaging, as well as mathematical model development, multi-variate time series analysis and parameter fitting tools, thus placing them at the forefront of interdisciplinary neuroscience. In a first step, targeted optogenetic stimuli will be combined with voltage sensitive dye imaging in awake mice to probe the response of brain tissue to excitatory and inhibitory afferent stimuli. Neural mass models will be fit to these data, using machine learning approaches (for example random forests). This information will be compiled into a predictive model of cortical dynamics and tested against experimental recordings of spontaneous activity. Importantly, we will test models constructed at different spatial resolutions; uncovering the best fitting model will add novel information regarding the optimal spatial scale at which brain operates. We will extend this analysis to different brain states, including processing of whisker stimuli, so that we can elucidate basic mechanism of information processing at different spatial scales.

Funding Notes

3 year studentship available for August(NTU)/September(UoE) 2019 entry. The studentship will provide funding of fees and a stipend equivalent to UK research council rate, currently £14,777 per annum for 2018-19, on a full time basis.

Related Subjects

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