A Simple Model of Optimal Population Coding for Sensory Systems
Figure 3
(a) Network diagram. Nodes represent individual elements of the indicated variables (noise variables indicated by small gray nodes); lines represent dependencies between them. Bold lines highlight, respectively, a point spread function of the blur from a point in the original signal to the observed signal, an encoding filter (or receptive field) that transforms the observed signal into the neural representation in a single neuron (encoding unit), and a decoding filter (or projective field) which represents the patten of that neuron's contribution in the reconstructed signal (its amplitude is given by the neural representation). In this diagram, the number of coding units at the neural representation is smaller than that of sensory units at the observed signal, which is called an undercomplete representation. Note that the proposed model is general and could form an optimal code with an arbitrary number of neurons, including complete and overcomplete cases. (b) The block flow diagram of the same model using the model variables defined in Methods. Each stage of sensory representation is depicted by a circle; each transformation by a square; each noise by a gray circle.