Photo of Dr James Rankin

Dr James Rankin

Maths Lecturer


Telephone: 01392 724673 or 01392 725359

Extension: (Streatham) 4673 or (Streatham) 5359

Office: Harrison 276

I am a Lecturer in Mathematical Biology at the University of Exeter doing research in mathematical and computational neuroscience. My research interests include dynamical systems, bifurcation theory, modelling of sensory cortex (auditory and visual), perceptual bistability and experiments in auditory perception (psychoacoustics).

Andrea Ferrario working on EPSRC-funded project "Neural oscillator network modelling of auditory stream segregation"

PGR students
Vicky Clark, EPSRC-funded PhD student working on "Cortical network models to understand differential input response properties during active and silent states" co-supervised with Mick Craig
Farzaneh Darki, PhD student working on "Neural dynamics of perceptual competition" co-supervised with Pete Ashwin
Curtis Alcock, Masters by Research student working on "Can Shannon Entropy be used to measure mishearing and isolate the impact of reduced audibility from the underlying hearing loss?" co-supervised with Marc Goodfellow

Clinical secondee
Yusur Al-Nuaimi  working on "Connectivity within human skin: predictive modelling of hair loss patterns in Primary Cicatricial Alopecia"

Project students
Andrew Cox working on "Computational modelling of neural populations encoding visual motion"
Jo Fisher working on "Dynamical systems modelling of hair growth in health and disease" co-supervised with Marc Goodfellow and Yusur Al-Nuaimi

Current opening: PhD in Computational and Mathematical Neuroscience (EPSRC funded, 3.5 yrs, Sept 2019 start)

General information & apply:

Project description:

This interdisciplinary project will develop computational and mathematical models of the auditory system to understand how complex stimuli like speech are encoded by spiking neurons in the midbrain.

The auditory midbrain is a key hub in the auditory processing pathway, functioning as an important junction that relays and shapes neural signals as they ascend towards auditory cortex.  Knowledge of the way in which complex sounds, e.g. speech, are encoded in the midbrain is crucial for understanding how dysfunction in the earlier auditory processing pathway (cochlea, auditory nerve, cochlear nucleus) leads to different types of hearing loss (a problem affecting 1 in 6 people in the UK). Working with neural recordings from the auditory midbrain in gerbils, a commonly-used animal for the study of low-frequency hearing, this project will develop mathematical and computational models of the auditory processing pathway. The aim is to understand the different roles of the patterns of inputs to midbrain neurons and their intrinsic response properties (e.g. their spiking rate) in shaping their responses to complex sounds.

The project will use a dynamical systems approach to model the intrinsic properties of individual neurons in the midbrain in a biologically plausible way (working with, e.g. adaptive exponential integrate-and-fire neurons or the Hodgkin-Huxley equations). Inputs to these neurons will be based on established cochlear models and the biological details of the auditory nerve and cochlear nucleus. The resulting model will produce firing patterns directly comparable with neural recordings provided by the experimental supervisor. This data will be used to train and parameter fit the model using e.g. Bayesian optimisation or genetic algorithms. The resultant model will have explanatory power for the extent to which midbrain responses are shaped by its inputs from cochlear nucleus. Further, it will make predictions, testable in new experiments, of how midbrain responses will be affected by different dysfunctions of the early auditory system relating to hearing loss.

The successful candidate will receive training dynamical systems theory and in the development and analysis of individual neuron and neural network models. An interdisciplinary approach, incorporating known biological details of the auditory processing pathway, will require the candidate to learn the relevant biology and neuroscience along with mathematical and computational techniques. The project will involve working closely with experimental neuroscientists and experimental data. This project provides a unique opportunity to receive training in mathematical modelling in close collaboration with experimentalists using cutting-edge methods recording spikes simultaneously from hundreds of neurons. Experience working on such interdisciplinary projects is highly sought after.

Candidates with quantitative backgrounds (mathematics, physics, engineering) and from neuroscience programmes are encouraged to apply. Programming experience, knowledge of dynamical systems theory and experience in biological modelling are a plus.

For further information, please contact me at the email address above. Closing date Jan 7th