1. A method for computation using a neural network architecture comprising the steps of: using a plurality of layers, each layer including a plurality of computational nodes, an input processing layer, a central processing layer, and an output processing layer; using at least one feedforward channel for inputs; using full lateral and feedback connections within the processing layers; using an output channel for outputs; using re-entrant feedback from the output channel to at least one of the processing layers; using local update processes to update each of the plurality of computational nodes; and using re-entrant feedback from the output channel to perform minimalization for general computation.