In this paper we report a new rat head phantom developed for testing electroencephalogram source localization techniques. The phantom is composed of an agar based mixture mimicking the rat brain, six dipoles and fourteen electrodes for modeling and monitoring of neural activity of the brain, respectively, and a 3D printed skull based on a computed tomography scan of a rat skull. In order to fabricate the phantom with currently available conventional techniques, the phantom is 1.8 times enlarged. To allow scaling, we performed an extensive study of electric properties of the agar based mixture, including electric conductivity, permittivity, and applied voltage, to ensure a linear operating regime. The new phantom facilitates testing of existing and the development of new cortical electrode implants as well as studying the quality of various source localization techniques.

This work presents and evaluates a 12-electrode intracranial electroencephalography system developed at the National Institute of Mental Health (Klecany, Czech Republic) in terms of an electrical source imaging (ESI) technique in rats. The electrode system was originally designed for translational research purposes. This study demonstrates that it is also possible to use this well-established system for ESI, and estimates its precision, accuracy, and limitations. Furthermore, this paper sets a methodological basis for future implants. Source localization quality is evaluated using three approaches based on surrogate data, physical phantom measurements, and in vivo experiments. The forward model for source localization is obtained from the FieldTrip-SimBio pipeline using the finite-element method. Rat brain tissue extracted from a magnetic resonance imaging template is approximated by a single-compartment homogeneous tetrahedral head model. Four inverse solvers were tested: standardized low-resolution brain electromagnetic tomography, exact low-resolution brain electromagnetic tomography (eLORETA), linear constrained minimum variance (LCMV), and dynamic imaging of coherent sources. Based on surrogate data, this paper evaluates the accuracy and precision of all solvers within the brain volume using error distance and reliability maps. The mean error distance over the whole brain was found to be the lowest in the eLORETA solution through signal to noise ratios (SNRs) (0.2 mm for 25 dB SNR). The LCMV outperformed eLORETA under higher SNR conditions, and exhibiting higher spatial precision. Both of these inverse solvers provided accurate results in a phantom experiment (1.6 mm mean error distance across shallow and 2.6 mm across subcortical testing dipoles). Utilizing the developed technique in freely moving rats, an auditory steady-state response experiment provided results in line with previously reported findings. The obtained results support the idea of utilizing a 12-electrode system for ESI and using it as a solid basis for the development of future ESI dedicated implants.

In the paper, we propose a procedure to be used for the validation of software for forward modeling of rat electroencephalogram with scalp potentials measured on rat head phantoms. Measurements are performed on a cuboidal phantom, a simplified shape of a rat brain, and an anatomically realistic, computed tomography (CT)-based phantom considering the brain and the skull. The physical phantoms are composed of an agar mixture to mimic the rat brain, excitation dipoles for modeling the neural activity of the brain, electrodes for monitoring the surface electric potential and a 3D printed skull. To ensure correct positions of dipoles and electrodes for numerical simulations, the phantoms are scanned by a computed tomography. After that, reconstructed 3D models are simulated in three EM solvers and results are compared with EEG measurements. Differences between simulations and measurements are further analyzed by parametric simulations and discussed. Obtained results provide the software validation method for rat brain forward modeling. Properly validated computation of electric potentials is essential for development of electrical brain stimulation protocols as well as in optimization of electrode placement.INDEX TERMS Forward model, CT-based rat head phantom, numerical simulation, validation studies.

In this paper we deal with a simplified anisotropic rat head phantom development and the investigation of the influence of the anisotropic white matter on electroencephalogram source localization. The proposed phantom is based on the cubic cross cell composition combined with agar mixture to set desired electrical conductivity anisotropic ratio. For the fabrication of the phantom, the 3D printed technology is exploited. Starting from a real rat brain, we proposed a simplified brain model incorporating the actual dimensions, shape and conductivity parameters of both grey and white matter containing simultaneously relevant deep-brain electrical signal sources. Five testing dipoles were located in the areas corresponding to the active brain regions. A single dipole localization error was calculated by comparing an inverse solution with a dipole position obtained from a computer tomography image. Neglecting anisotropy had a rather weak effect on localization error of a single testing dipole in our model. The reliability map was computed and interpreted in terms of spatial similarity between distributed inverse solutions involving isotropic and anisotropic forward models. We found spatially specific error increases located close to the electrodes and in the vicinity of anisotropic compartment. Hence, areas to be most sensitive to neglecting anisotropy in our model were identified.

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