Although the volume conductor is an inhomogeneous and anatomically complex structure, it is still a linear model ( Nunez and Srinivasan, 2006). As the different tissue types are associated with different electrical conductivity, the volume conductor is an inhomogeneous structure. The geometric description of the head anatomy is referred to as the head model. The volume conductor is described by the anatomy of the head, and is typically modeled as four segments of different tissue types: the brain, the cerebrospinal fluid (CSF), the skull, and the scalp. The electrical field in the brain and on the surface of the scalp are related to electrical current from cortical sources through volume conduction. The main advantage of ear-EEG is that it enables discreet and unobtrusive long-term monitoring of EEG in real-life environments ( Fiedler et al., 2016 Goverdovsky et al., 2016 Kappel, 2016 Kappel and Kidmose, 2018).

Ear-EEG is a method in which EEG is measured from electrodes placed in the ear ( Kidmose et al., 2013 Bleichner et al., 2015 Mikkelsen et al., 2015). We consider the proposed method to be an important step forward in the characterization and utilization of ear-EEG.Įlectroencephalography (EEG) is a non-invasive method for recording signals from the brain. In addition, we demonstrated that the developed forward models can be used to explore the sensitivity to brain sources for different ear-EEG electrode configurations. Generally, the correlation was high in the ear closest to the dipole location, showing that the ear-EEG forward models provided a good model to predict ear potentials. The correlation between the topographic IC map and the topographic map predicted by the forward model, was computed for each IC. A subset of ICs were selected, based on how well they were modeled by a single dipole in the brain volume. The EEG recordings were analyzed with independent component analysis (ICA) and using the individualized ear-EEG forward models, single dipole fitting was performed for each independent component (IC). To validate the method, individualized ear-EEG forward models were computed for four subjects, and ear-EEG and scalp EEG were recorded concurrently from the subjects in a study comprising both auditory and visual stimuli. The result is a method to compute an ear-EEG forward model, which enables mapping of sources in the brain to potentials in the ear. Here we present an extension to existing computational models, by incorporating an improved description of the external ear anatomy based on 3D scanned impressions of the ears. However, current models do not describe the external ear anatomy well, and is therefore not suitable for ear-EEG recordings. 3Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California, San Diego, La Jolla, CA, United StatesĬomputational models for mapping electrical sources in the brain to potentials on the scalp have been widely explored.2Department of Electronic and Telecommunication Engineering, University of Moratuwa, Katubedda, Sri Lanka.1Neurotechnology Lab, Department of Engineering, Aarhus University, Aarhus, Denmark.Kappel 1,2 *, Scott Makeig 3 and Preben Kidmose 2

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