Development of the Experimental Design for the Validation of EEG Source Localization with fMRI

Application of a Haptic Robot to Identify Active Neuronal Ensembles

Master Thesis (2023)
Author(s)

T.J. van Rooijen (TU Delft - Mechanical Engineering)

Contributor(s)

FCT Van Der Helm – Mentor (TU Delft - Biomechatronics & Human-Machine Control)

Kianoush Rassels – Graduation committee member (TU Delft - Biomechatronics & Human-Machine Control)

J. van der Cruijssen – Coach

A.F. van Rootselaar – Mentor (Amsterdam UMC)

Faculty
Mechanical Engineering
Copyright
© 2023 Thom van Rooijen
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Thom van Rooijen
Graduation Date
08-11-2023
Awarding Institution
Delft University of Technology
Project
['4D EEG']
Programme
['Biomedical Engineering']
Faculty
Mechanical Engineering
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Abstract

Various source localization algorithms exist to perform localization with High Density (HD)-ElectroEncephaloGraphy (EEG). However, validation of these EEG source localization algorithms is lacking. The current gold standard for source localization in the brain is functional Magnetic Resonance Imaging (fMRI) by calculating the difference in hemodynamic response to different stimuli. This study aims to validate HD-EEG source localization with fMRI using an MR compatible haptic robot. Participants performed several tasks with the robot to activate cortex patches and allow localization of source activity under various circumstances. These hypothesized patches are the somatosensory, motor and visual cortex. No comparison is made with fMRI due to time constraints. As no comparison could be made, we aim to validate the experimental methodology.
Activation of the somatosensory cortex is clearly visible. The visual cortex is often localized, but lacks power in some settings. Activity during the torque task can be localized, but not conclusively to the motor cortex. In all, the experiment was a success, as it was able to induce verifiable different brain states. Hypothesized task contrasts contained different activity distributions. Improvements can be made by generating a more detailed leadfield and by applying a linear manipulator

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