Neural Networks for Modeling Behavior
This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book shows that most modern ideas in network design have much earlier antecedents. Both the earlier connectionist networks and the networks in computational cognitive neuroscience models include nodes, connections, and equations describing the interactions of node activities and connection strengths. The book describes models that make extensive use of dynamical systems, but in some cases the modelers find it a useful simplification to talk about some part of their network being a representation of some concept. It reviews the most important established models of associative learning and competition, respectively and some of the most significant recent findings in cognitive neuroscience. M. Meeter, J. Jehee, and J. Murre observed that fitting both behavioral and neural data is one of the important criteria but not the only one.