Neural/Iconic Understanding of the Visual World

The key element presented in this paper is an adaptive state machine in which neurons form the state variables and these are sufficient in number for the state to be “iconic”. That is, the state reflects events in the world in a many-to-some manner. Early processing forms part of this model. The model is a variant of the previously defined Neural State Machine Model (NSMM). The variant presented in this paper has the ability of functioning in the vision domain both in a rule-based way and an adaptive, neural way. Examples are given of integrated models of concept binding, learning concepts from widely different objects and the memory of scenarios. This is a brief summary of a wide-ranging group of research topics in visual understanding that are enabled by the NSMM technique.