Abstract
Objective. Accurate knowledge about the positions of electrodes in electroencephalography (EEG) is very important for precise source localizations. Direct detection of electrodes from magnetic resonance (MR) images is particularly interesting, as it is possible to avoid errors of co-registration between electrode and head coordinate systems. In this study, we propose an automated MR-based method for electrode detection and labeling, particularly tailored to high-density montages. Approach. Anatomical MR images were processed to create an electrode-enhanced image in individual space. Image processing included intensity non-uniformity correction, background noise and goggles artifact removal. Next, we defined a search volume around the head where electrode positions were detected. Electrodes were identified as local maxima in the search volume and registered to the Montreal Neurological Institute standard space using an affine transformation. This allowed the matching of the detected points with the specific EEG montage template, as well as their labeling. Matching and labeling were performed by the coherent point drift method. Our method was assessed on 8 MR images collected in subjects wearing a 256-channel EEG net, using the displacement with respect to manually selected electrodes as performance metric. Main results. Average displacement achieved by our method was significantly lower compared to alternative techniques, such as the photogrammetry technique. The maximum displacement was for more than 99% of the electrodes lower than 1 cm, which is typically considered an acceptable upper limit for errors in electrode positioning. Our method showed robustness and reliability, even in suboptimal conditions, such as in the case of net rotation, imprecisely gathered wires, electrode detachment from the head, and MR image ghosting. Significance. We showed that our method provides objective, repeatable and precise estimates of EEG electrode coordinates. We hope our work will contribute to a more widespread use of high-density EEG as a brain-imaging tool.
Highlights
Electroencephalography (EEG) is an electrophysiological technique that permits to record neuronal activity over the scalp
magnetic resonance (MR)-based localization method, among which the method we propose in this paper, have the great advantage of providing electrodes coordinates directly in the MR space, which is the same space to which EEG activity needs to be projected for source localizations (Lagerlund et al 1993, Towle et al 1993, Van Hoey et al 1997, Yoo et al 1997)
We extended our validation to additional MR datasets with EEG montage having 256 channels, and characterized by relatively lower quality, and to verify whether the approach we developed could be applicable to a wide range of situations
Summary
Electroencephalography (EEG) is an electrophysiological technique that permits to record neuronal activity over the scalp. The availability of EEG systems with high electrode density (number of channels >100) has substantially improved the spatial localization of brain activity sources (Lantz et al 2003). This progress has opened new opportunities for achieving substantially higher spatio-temporal accuracy (Dale and Halgren 2001, Lopes da Silva 2004, He et al 2011, Michel and Murray 2012) making EEG an attractive tool for the noninvasive study of brain activity and connectivity in the human brain (Lantz et al 2003, Michel et al 2004, Brodbeck et al 2011, Song et al 2015). A dedicated image-processing step is used to remove goggles (if present) from the MR image
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