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One potentially powerful application of Electrical Impedance Tomography (EIT) lies in the detection of the source of epileptic seizures in the brain (Holder, 2005). Many patients with epilepsy can be treated with drugs, but surgical resection of the abnormal region which produces seizures may be the only option in severe cases (Engel, Jr., 1993; Rosenow and Luders, 2001). For these, EIT could be used to provide continuous imaging over days while the subject is observed on a ward and so could, uniquely, provide images of conductivity changes related to increased blood volume or cell swelling in the onset zone of the brain where the seizure starts. If successful, this would provide imaging evidence not possible with any other method and would obviate the need in some difficult cases for invasive investigation with intracranial electrodes (Fabrizi et al., 2006). It has already been shown that impedance increases locally in the brain by 3-12% at 1kHz up to 22% at 50 Hz during induced epileptic seizures (Elazar et al., 1966; Fox et al., 2004; VAN HARREVELD and Shade, 1962). Resistance changes of 5.5-7.1% associated with focal and generalized seizures have been imaged with EIT using a ring of electrodes placed on the exposed cortex of rabbits at 51 kHz (Rao, 2000). It therefore seems plausible that these changes are large enough to enable EIT to produce images of conductivity variations of clinical interest. Nevertheless, in a first pilot study in humans, it was not possible to measure reproducible boundary voltage changes during seizures as they were reaching 1-54% (Fabrizi et al., 2006). The most probable explanation was that true scalp voltage changes due to cerebral seizure were obscured by movement artefacts. However it was not clear whether even in ideal conditions it would have been possible to obtain informative tomographic images. Therefore it is important to understand what are the EIT hardware and recording system requirements that would maximise the chance of detecting reliable changes associated with

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Determination of Optimal Parameters and Feasibility for Imaging of Epileptic Seizures by Electrical Impedance Tomography: A Modelling Study Using a Realistic Finite Element Model of the Head