Using the MoBI motion capture system to rapidly and accurately localize EEG electrodes in anatomic space
Kevin A Mazurek1, Eleni Patelaki2, John J Foxe1
1The Cognitive Neurophysiology Laboratory, The Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Abstract:
During mobile brain/body imaging (MoBI) experiments, electroencephalography and motion capture systems are used in concert to record high temporal resolution neural activity and movement kinematics while participants perform demanding perceptual and cognitive tasks in a naturalistic environment. A typical MoBI setup involves positioning multi-channel electrode caps based on anatomical fiducials as well as experimenter and participant intuition regarding the scalp midpoint location (i.e., Cz). Researchers often use the "template" electrode locations provided by the manufacturer, however, the "actual" electrode locations can vary based on each participant's head morphology. Accounting for differences in head morphologies could provide more accurate clinical diagnostic information when using MoBI to identify neurological deficits in patients with motor, sensory, or cognitive impairments. Here, we asked whether the existing motion capture system used in a MoBI setup could be easily adapted to improve spatial localization of electrodes across participants without requiring additional or specialized equipment that might impede clinical adoption. Using standard electrode configurations, infrared markers were placed on a subset of electrodes and anatomical fiducials, and the remaining electrode locations were estimated using spherical or ellipsoid models. We identified differences in event-related potentials between "template" and "actual" electrode locations during a Go/No-Go task (p < 9.8e-5) and an object-manipulation task (p < 9.8e-5). Thus, the motion capture system already used in MoBI experiments can be effectively deployed to accurately register and quantify the neural activity. Improving the spatial localization without needing specialized hardware or additional setup time to the workflow has important real-world implications for translating MoBI to clinical environments.
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