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Abstract
This chapter discusses a software lens for image reconstitution of the electroencephalography (EEG). The electrical fields of current of active neurons in the cerebral cortex spread through the tissue to the surface of the cortex, where they can be observed as EEG waves. The potential fields of adjacent cell groups overlap and sum in the volume conductor. If there is a degree of uniformity in cell types and in the spread of their field currents with location within a sheet of cortex, the summation can be described by the mathematical operation of convolution. The standard pattern of spreading is known as the kernel. A neural activity pattern within the cortex can be said to be convolved with the kernel to give the surface EEG pattern. If the kernel is known, its inverse may be computed. Then convolution of a surface EEG pattern with the inverse kernel should restore the original neural activity pattern. The procedure is called spatial deconvolution of the EEG.
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