Modelling and estimation of physiological and pathological dynamics at the calyx of Held giant synapse

This project is focused on the development of modelling and estimation tools in support of the experimental investigation into the functioning of neural synapses.

The synapse is the connection and interface where information is transmitted between two neurons. Understanding the behaviour of the synapse in physiological and pathological conditions is a fundamental step towards greater understanding of brain function and neurodegenerative disease. The role of the synapse is central to information transmission in the brain and is compromised in diseases such as deafness, tinnitus, epilepsy and Alzheimer's disease. In this context, co-supervisor Prof Ian Forsythe has pioneered the study of synaptic transmission at the calyx of Held giant synapse. This is the largest synapse in the mammalian brain, whose dimensions allow extensive experimental studies using whole-cell patch recording. This includes recordings of the temporal processes that underlie biochemical variables in both pre-synaptic and post-synaptic compartments.

A dynamical model describing the biochemical mechanisms of information transfer at the synapse has been developed over the last few years in support of the experimental investigation (see Figure). The model is used to test postulates, validate observations and to reconstruct unmeasured variables. It comprises continuous, discrete and probabilistic dynamics and is periodically refined as new phenomena are discovered. Following an initial phase devoted to the understanding of the synapse model developed so far, the focus of this PhD project will be to improve the model formulation and to develop methods to estimate the model’s parameters from experimental data. The ability to integrate data obtained from different experiments, and a better characterisation of the random processes involved, both in the functioning of the synapse and in the recording of experimental data, will be central objectives of the project. In this respect, it is expected that a stochastic modelling framework, possibly complemented with a Bayesian approach to the estimation problem, will be adopted to describe internal random processes and the variability among different experiments.

Entry requirements
Applicants are required to hold/or expect to obtain a UK Bachelor Degree 2:1 or better in a relevant subject. The University of Leicester English language requirements apply where applicable.

How to apply
The online application and supporting documents are due by Monday 21st January 2019.

Any applications submitted after the deadline will not be accepted for the studentship scheme.

References should arrive no later than Monday 28th January 2019.

Applicants are advised to apply well in advance of the deadline, so that we can let you know if anything is missing from your application.

Required Materials
1. Online application form
2. Two academic references
3. Transcripts
4. Degree certificate/s (if awarded)
5. Curriculum Vitae
6. EPSRC Studentship Form
7. English language qualification

Applications which are not complete by the deadline will not be considered for the studentship scheme. It is the responsibility of the applicant to ensure the application form and documents are received by the relevant deadlines.

All applications must be submitted online, along with the supporting documents as per the instructions on the website. Please ensure that all email addresses, for yourself and your referees, are correct on the application form.

Project / Funding Enquiries
Application enquiries to [Email Address Removed]
Closing date for applications – 21st January 2019