A sensor sensitivity and correlation analysis through polynomial chaos in the EEG problem

We study the effect of uncertain conductivity on the electroencephalography (EEG) forward problem. A three-layer spherical head model with different and random-layer conductivities is considered. The randomness is modelled by Legendre polynomial chaos. We perform a sensitivity and correlation analysis of EEG sensors influenced by uncertain conductivity. We addressed the sensitivity analysis at three stages: dipole location and moment averaged out, only the dipole moment averaged out and both fixed. Also two subregions of the brain (cerebrum and cerebellum) are compared. On an average, we observe the least influenced electrodes along the great longitudinal fissure. Also, sensors located closer to a dipole source, are of greater influence to a change in conductivity. The highly influenced sensors were on average located temporal. This was also the case in the correlation analysis. Sensors in the temporal parts of the brain are highly correlated. Whereas the sensors in the occipital and lower frontal regions, though they are close together, are not so highly correlated as in the temporal regions.