Abstract
The coupling of EEG/fMRI allows measuring brain activity at high spatio-temporal resolution. The localisation of EEG sources depends on several parameters including the position of the electrodes on the scalp. An accurate knowledge about this information is important for source reconstruction. Currently, when acquiring EEG/fMRI together, the position of the electrodes is generally estimated according to fiducial points by using a template. In the context of simultaneous EEG/fMRI acquisition, a natural idea is to use MR images to localise EEG electrodes. However, MR compatible electrodes are built to be almost invisible on MR Images. Taking advantage of a recently proposed Ultra-Short Echo Time (UTE) sequence, we introduce a fully automatic method to detect and label those electrodes in MR images. Our method was tested on 8 subjects wearing a 64-channel EEG cap. This automated method showed an average detection accuracy of 94% and the average position error was 3.1 mm. These results suggest that the proposed method has potential for determining the position of the electrodes during simultaneous EEG/fMRI acquisition.
Highlights
Electroencephalography (EEG) measures the electrical potential generated by the neuronal activity over the scalp with electrodes placed on the surface of the scalp (Petsche et al, 1984; Murakami and Okada, 2006; Buzsáki et al, 2012)
For seek of genericity, we propose to make use of a MRI sequence with radial kspace sampling named Ultra short Echo Time (UTE) for Ultra-short Echo-Time
The positive predictive value (PPV) is the percentage of electrodes that have been detected
Summary
Electroencephalography (EEG) measures the electrical potential generated by the neuronal activity over the scalp with electrodes placed on the surface of the scalp (Petsche et al, 1984; Murakami and Okada, 2006; Buzsáki et al, 2012). When acquiring EEG and functional magnetic resonance imaging (fMRI) simultaneously, the position of the electrodes is calculated according to fiducial points (anatomical points of the skull) such as inion, nasion and vertex (Strobel et al, 2008). A precise knowledge of these positions is important because inaccurate information on EEG electrodes coordinates may affect EEG inverse solution (Khosla et al, 1999). This knowledge is even more crucial in the case of simultaneous EEG and fMRI study, when the sessions are conducted repeatedly over a long period of time. As a matter of fact, magnetic resonance (MR) images and EEG need to be registered to be able to compare activations
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