Editing Cognitive model (section)

====Associative memory====
Early work in the application of dynamical systems to cognition can be found in the model of [[Hopfield network]]s.<ref>Hopfield, J. J. (1982). [http://www.pnas.org/content/pnas/79/8/2554.full.pdf Neural networks and physical systems with emergent collective computational abilities]. PNAS, 79, 2554-2558.</ref><ref>Hopfield, J. J. (1984). [http://www.pnas.org/content/pnas/81/10/3088.full.pdf Neurons with graded response have collective computational properties like those of two-state neurons]. PNAS, 81, 3088-3092.</ref> These networks were proposed as a model for [[associative memory (psychology)|associative memory]]. They represent the neural level of [[memory]], modeling systems of around 30 neurons which can be in either an on or off state.  By letting the [[Neural network|network]] learn on its own, structure and computational properties naturally arise. Unlike previous models, “memories” can be formed and recalled by inputting a small portion of the entire memory. Time ordering of memories can also be encoded. The behavior of the system is modeled with [[Euclidean vector|vectors]] which can change values, representing different states of the system. This early model was a major step toward a dynamical systems view of human cognition, though many details had yet to be added and more phenomena accounted for.