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Electrical Impedance Tomography (EIT) is a medical imaging technique that reconstructs impedance distribution inside a target object by injecting electrical currents into pairs of electrodes and measuring induced voltages on the remaining electrodes. Since neural signals result from the activity of ion channels causing impedance changes in the cell membrane, EIT can image these neural activities for understanding brain function and medical purposes. In our research, our self-developed electronic prototype board was used to generate high-quality electrical current and collect the data on electrodes with a high sampling rate and bit-resolution. In image reconstruction, a preprocessing data analysis algorithm was newly developed and applied to improve the accuracy of our EIT imaging. The human head has complex anatomical geometry and non-uniform resistivity distribution along with the highly resistive skull, which makes brain-EIT remains challenging inaccurate image reconstruction. To mimic the human head, a multi-layered human head phantom was designed and tested to investigate the effect of the skull structure on imaging. In this presentation, comparison studies for measurements and simulation results will be introduced to discuss the source of errors and improve the accuracy and efficiency of our brain-EIT system.