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Generating a computational model of dopaminergic networks and exploring the selective vulnerability of different neurons within this circuit to protein aggregates

Primary Supervisor: Dr Mark Wall, School of Life Sciences

Secondary supervisors: Dr Emily Hill and Professor Magnus Richardson

PhD project title: Generating a computational model of dopaminergic networks and exploring the selective vulnerability of different neurons within this circuit to protein aggregates

University of Registration: University of Warwick

Project outline:

This project will bridge the fields of experimental neuroscience and theoretical computational mathematical modelling. Patch Clamping will be used to explore the way in which dopamine neurons are connected and how they respond to protein aggregation. The project will also expand on previous neuronal microcircuit network work, both in the hippocampus and also of dopaminergic neurons in the substantia nigra and ventral tegmental area. Acquisition of such network information will be greatly assisted by the production of simplified computational models, which allow the production of large networks without requiring large amount of computational power. In order to translate this initial electrophysiology data into a network model, MATLAB will be used to generate dynamic IV curves. These can then be compared across different cell types and conditions. We propose to modify the rEIF model, which is already published for pyramidal neurons in the hippocampus but does not accurately describe the electrophysiological properties of dopaminergic neurons. It will need to be altered using the electrophysiology data to give accurate spike prediction and hence a reliable model. This model can then be used to compliment the experimental work.

The aggregation and accumulation of protein species is commonly found in ageing. Determining what makes different cell types more susceptible to changes induced by these aggregates is vital to understand what happens during the ageing process. We have previously shown that by introducing alpha synuclein aggregates (oligomers) into single neurons (Kaufman et al 2016, Hill et al 2020), we can evaluate changes to neuronal function in a controlled manner and assess time- and concentration- dependent effects. We have established that the profile of KATP channels and the expression of endogenous alpha synuclein within neurons are factors that could influence vulnerability in response to oligomer introduction. The experimental side of this project will therefore focus on understanding this selective vulnerability between different cell types, leading to better mechanistic understanding.

By combining both experimental neuroscience and theoretical computational mathematical modelling, the project will offer training in a wide range of different techniques and will offer a fantastic opportunity for development.


  1. Hill, E, Gowers, R, Richardson, M.J., Wall. M. J, (2020) Alpha-synuclein aggregates increase the conductance of substantia nigra dopamine neurons, an effect partly reversed by the KATP channel inhibitor glibenclamide. eNeuro.0330-20.2020
  2. Kaufmann, T.J., Harrison, P.M., Richardson, M.J.E., Pinheiro, T.J.T., Wall, M.J., (2016). Intracellular soluble ╬▒Synuclein oligomers reduce pyramidal cell excitability. Journal of Physiology 594, 2751–2772.

BBSRC Strategic Research Priority: Understanding the Rules of Life: Neuroscience and behaviour & Integrated Understanding of Health:Ageing

      Techniques that will be undertaken during the project:

      • Whole cell patch clamp electrophysiology
      • Immunohistochemistry
      • Cell Culture
      • Molecular Biology
      • Computational Modelling

      Contact: Dr Mark Wall, University of Warwick