EEG/ MEG network measures as a biomarker in pre-surgical planning for epilepsy patients

Summary In both neuroscience and neurology, there is a plethora of data that has not been quantitatively analysed.  One interesting way of analysing this `big data’ is to convert it into a functional network that is spatially sampled at different points.  This not only reduces the order of the data, but also provides a way of examining the internal structure of the data.  Using various network measures, this project aims to find a functional biomarker that indicates cortical hyper-excitability.  We can then use this to systematically analyse brain networks for pre-surgical planning for resective surgery in epilepsy patients.

Project Details

In both neuroscience and neurology, there is a plethora of data that has not been quantitatively analysed.  One interesting way of analysing this `big data’ is to convert it into a functional network that is spatially sampled at different points.  This not only reduces the order of the data, but also provides a way of examining the internal structure of the data.  Using various network measures, this project aims to find a functional biomarker that indicates cortical hyper-excitability.  We can then use this to systematically analyse brain networks for pre-surgical planning for resective surgery in epilepsy patients.

The aim of this project will be to increase the success rate of surgeries, optimise the amount of cortical tissue resected from patients, and be able to successfully evaluate more complex cases that normally would not be eligible for surgery.

This project involves multiple fields such as epileptology, neuroimaging, neuroscience, network science and data analysis.  Candidates from neuroscience, computer science, maths/physics/engineering are all suitable.