Head reconstruction and localization of brain activity using Bayesian evidence

This study is devoted to a detection of evoked potentials in a brain activity with aim to map these potentials onto a scalp. In this case, there is necessary to focus recorded scalp potentials, which are blurred due to scalp attenuation and, moreover masked by a brain activity. The aim is to estimate the foci of active regions of the brain during evoked potentials. Our suggested approach is based on the use of Bayesian evidence to detect potentials in background noise (brain activity). New formula evaluating the Bayesian evidence suitable for this purpose is derived, tested and verified on artificially generated and real data. This method can be used to detect evoked potentials in a brain activity up to signal to noise ratio approximately - 25 dB. This value corresponds to a real situation when potentials are measured on the surface of scalp. The main advantage of the method is the ability to detect evoked potential without any averaging. On the other hand this method cannot reconstruct the shape of evoked potential. Computational costs are very low and enabling the real-time implementation.