On the canonical form of neural dynamics and a dual system model for neural networks
Two sets of variables seem to be essential for well defining the dynamics of a neural network model, i.e., the set of activity variables which defines the configuration of the activities of all neurons in the system, and the set of connection variables which prescribes the interactions among the neurons. It is obvious that these two sets of variables are closely related to each other. In this work we present an investigation to the possible theoretical framework for the unified description for the dynamics in both of the two sets of variables. We choose steady states to carry out this investigation.