Abstract
Accuracy in localizing the brain areas that generate neuromagnetic activity in magnetoencephalography (MEG) is dependent on properly co-registering MEG data to the participant's structural magnetic resonance image (MRI). Effective MEG-MRI co-registration is, in turn, dependent on how accurately we can digitize anatomical landmarks on the surface of the head. In this study, we compared the performance of three devices—Polhemus electromagnetic system, NextEngine laser scanner and Microsoft Kinect for Windows—for source localization accuracy and MEG-MRI co-registration. A calibrated phantom was used for verifying the source localization accuracy. The Kinect improved source localization accuracy over the Polhemus and the laser scanner by 2.23 mm (137%) and 0.81 mm (50%), respectively. MEG-MRI co-registration accuracy was verified on data from five healthy human participants, who received the digitization process using all three devices. The Kinect device captured approximately 2000 times more surface points than the Polhemus in one third of the time (1 min compared to 3 min) and thrice as many points as the NextEngine laser scanner. Following automated surface matching, the calculated mean MEG-MRI co-registration error for the Kinect was improved by 2.85 mm with respect to the Polhemus device, and equivalent to the laser scanner. Importantly, the Kinect device automatically aligns 20–30 images per second in real-time, reducing the limitations on participant head movement during digitization that are implicit in the NextEngine laser scan (~1 min). We conclude that the Kinect scanner is an effective device for head digitization in MEG, providing the necessary accuracy in source localization and MEG-MRI co-registration, while reducing digitization time.
Highlights
Magnetoencephalography (MEG) is a non-invasive functional neuroimaging technology that maps brain activity by measuring magnetic fields generated from the electrical currents in the neurons of the brain (Cohen, 1968; Hämäläinen et al, 1993; Baillet et al, 2001)
PHANTOM STUDY Figure 2 shows the mean displacement between the known and estimated location of each current source in the calibrated phantom across all three digitization systems. This provides the profile of source localization accuracy for each device across a number of locations in the calibrated phantom
The Kinect improved the source localization accuracy over the Polhemus and laser scanner by 2.23 mm and 0.81 mm, respectively. Investigating these results in the cardinal planes showed that the source localization error for laser and Polhemus was dominant in the z-direction
Summary
Magnetoencephalography (MEG) is a non-invasive functional neuroimaging technology that maps brain activity by measuring magnetic fields generated from the electrical currents in the neurons of the brain (Cohen, 1968; Hämäläinen et al, 1993; Baillet et al, 2001). The accuracy of MEG for localizing brain activity is valuable when MEG functional data are combined with anatomical data generated from magnetic resonance imaging (MRI). In this case, state of the art methods can localize the current source that is generating neuromagnetic activity with an accuracy of approximately 1 mm (Bardouille et al, 2012). The accuracy with which MEG functional and MRI anatomical data can be combined is dependent on how accurately the coordinate systems can be co-registered
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