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Functional neuroimaging analysis to identify brain abnormality in epilepsy

Combined functional magnetic resonance imaging (fMRI) and electro-encephalography (EEG) approaches can be used to define the brain networks in patients with epilepsy. 

Aims

The aim of this project is to further develop and apply algorithms that can best identify the components of the network that are responsible for the generation of the hyper-synchronisation that is characteristic of the epileptic seizure.  

This project uses advanced neuroimaging methods in functional imaging including functional connectivity, signal processing and data-driven analysis methods. The project may suit a candidate with a background or strong interest in physics, engineering, computer science, mathematics or statistics.  Figure caption: Example demonstrating how methodological improvement can yield additional information from functional imaging data. Here the same brain imaging data are analysed in two ways. The analysis on the right included a novel de-noising algorithm (SOCK, developed by Florey PhD student Kaushik Bhaganagarapu) and yielded additional information regarding the spatio-temporal pattern of brain activity compared to the conventional analysis without SOCK.

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