A new method of localizing brain activity using the scalp EEG data

Abstract

We propose a spatial localization method for scalp electroencephalography (EEG). The technique allows reliable and unambiguous identification of the activity for any intracerebral source by its spatial coordinates. Our "virtually implanted electrode" is based on the dynamics and correlation analysis of signals in the EEG leads with the addition of artificially generated data. The generated data helps us accurately model the electrical potential distribution between the studied source and the scalp electrodes. Each modeled intracerebral source is analyzed independently, so the proposed method does not require an estimate of the possible number of sources. The method produces output values that can be interpreted as the "local field" elec-trical activity for the implanted electrode in the corresponding brain point. The signal cleaning procedure makes it possible to exclude the influence from neighboring regions and detect a given brain region's isolated electrical activity. For verification, the method was applied in the empathy study on a sample of 16 people. We compared the background EEG of calm wakefulness with the EEG of empathic behavior for the 33 preselected brain regions.