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Master theses

Current and past ideas and concepts for Master Theses.

Influence of the estimated structural connectivity on whole-brain dynamics

Subject

In this master thesis, the student will simulate EEG/MEG signals captured at the scalp using a model of weakly coupled oscillators (the Kuramoto model) and compare it to real data using a variety of features (e.g. functional connectivity).

The most important input to this model is the structural connectivity matrix. Yet, this structural connectivity – which ideally represents the underlying white matter pathways – can be estimated using a variety of techniques. The student will assess the influence of the choice of structural connectivity matrix on the fit between the simulated and real MEG data.

This project can be extended by optimising another input of the Kuramoto model: the delay parameter. The student will extract an estimate of distance between any two regions-of-interest in the human brain. This will allow to improve the simulated brain activity and to convert the delay (one of the parameters) into a conduction velocity.

Framework of the Thesis

Development of a biomarker for cognitive impairment in multiple sclerosis

Number of Students

2

Expected Student Profile

Preferential prerequisites:
- A strong interest in neuroimaging
- A strong interest in the inner workings of the brain
- Confident in Linux

Promotor

Dr. Ir. Jef Vandemeulebroucke

+32 (0)2 629 1033

jefvdmb@etrovub.be

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