Functional structures of the primary visual cortex, particularly clearly apparent structures such as orientation columns, are studied by recording the brain's intrinsic optical signals. These reflect changes in local neuron metabolism and cerebral blood flow induced by functional loading. Despite the advantages of this method, mapping of neurons with weak signals can be hindered by noise generated by the global and local components of optical signals associated with physiological processes occurring in the body as well as equipment factors. This generates the need to correct functional optical maps to eliminate noise effects. The present report describes a new method of processing functional maps using approximations to identify and remove the global components of the optical signal and other interference from maps. The results are compared with data obtained by traditional map processing methods.