PhD Study : Automating pre-surgical evaluation of epilepsy patients by applying AI for MEG-based interictal spike detection and epileptogenic source localisation

Summary

Over 50 million people world-wide suffer from epilepsy [1]. Up to 30% people with epilepsy fail to respond  to anti-epileptic drugs and may need to go for resective surgery [2], if Epileptogenic Zone (EZ) could be accurately identified. However, for about 30% of surgical candidates, the routine electro-clinical investigations yield discrepant outcomes and/or MRI is contradictory. In such cases, mainly because of its excellent spatio-temporal resolution, magnetoencephalography (MEG) is increasingly used to determine the Irritative Zone (IZ), i.e. the cortical area where Interictal Epileptiform Discharges (IEDs) originate.

The standard approach to IZ localization involves IEDs identification through careful observation of multi-channel MEG recordings and  source localization at selected time points, using the only clinically approved method Equivalent Current Dipole (ECD) fitting [3]. Current MEG systems have 306 channels (Triux, Elekta Oy) and are sampled at 1k Hz giving inherently noisy and non-stationary signals. The IEDs in MEG are normally detected as ‘possible spikes’, if they satisfy IFCN criteria [4] consisting of (1) sharp peak, (2) duration 20-200 ms, (3) outstanding from ongoing background activity, and (4) involvement of more than two MEG channels. Thus, dipole localization from MEG data is a highly time-consuming and complex procedure involving subjective choices, and therefore reliable only when performed by experienced users. There is therefore urgent need for automating this procedure as much as possible.

To this end, it is proposed to investigate an intelligent assistive system (e.g.[6]) that facilitates a user to identify inter-ictal spikes with minimum effort in an interactive way. Using hybrid computational intelligence techniques, appropriate objective function would need to be devised for optimal feature selection. Important features may be hidden in vast amount of unrelated information. Procedure needs to be devised that can effectively utilise known brainwave dynamics (e.g., EMD [5]) so as to select only related part of the signal, while  ensuring that no relevant information (related to interictal spikes) is missed. Archival MEG-EEG data from ongoing pre-surgical evaluation of epilepsy patients at Ulster’s Northern Ireland Brain Mapping (NIFBM) facility is readily available for investigation purposes.

The successful PhD candidate will gain valuable knowledge in machine learning, high-performance computing, mathematics/statistics and neuroscience. This experience will open wide opportunities for the student in finding skilled work in the field of data science and machine/deep learning.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Research proposal of 1500 words detailing aims, objectives, milestones and methodology of the project
• A demonstrable interest in the research area associated with the studentship

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Masters at 70%
• For VCRS Awards, Masters at 75%
• Publications - peer-reviewed
• Experience of presentation of research findings
• Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

• Full Award: (full-time tuition fees + £19,000 (tbc))
• Part Award: (full-time tuition fees + £9,500)
• Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

• Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
• Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
• Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
• Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living