An inverse problem in neural processing.
Any neural network aimed at the coding sensory events must contain computational properties which generally allow the organism to reconstruct the input signals with some degree of accuracy--else the association between stimulus and response would, at best, be uncertain. In this paper we investigate the problem of reconstructing external input signals to neural networks when the activity profiles of only some of its member cells are known. The evolution and activities of such cells are defined by an earlier formulation of one of us (Oğuztöreli 1979) and, here, we restrict our application to local circuits within the vertebrate retina. Solutions to this inverse coding problem are presented for specific network equations and exemplified with 1, 3, and 5 neuron cases.
D008433:Mathematics; D008959:Models, Neurological; D009434:Neural Pathways / Q000502:physiology; D009475:Neurons, Afferent / Q000502:physiology*; D012160:Retina / Q000166:cytology / Q000502:physiology*