These simple units can represent neuron and the connections can represent synapse in the neural network.
Biological Activism: Neural network of connectionist modeling suggests that the study of mental activity is the study of neural systems. This links connectionism to neuroscience, and models involve varying degrees of biological realism. The biological aspects of natural neural systems are incorporated in connectionist model for better understanding / biological reality.
Learning: Learning is an important aspect of connectionist modelling. Many sophisticated learning procedures for neural networks have evolved, modifying the connection weights. Mathematical formulas are used to determine the change in weights when given sets of data consisting of activation vectors for some subset of the neural units.
Parallel Distributed Processing: It is a neural network approach emphasizing the parallel nature of neural processing and the distributed nature of neural representations. It provides a general mathematical framework for researchers to operate in. The framework involved eight major aspects:
These aspects are now the foundation for almost all connectionist models. It is assumed that all cognitive processes are explained by neural firing and communication. According to this view there is no room for rational thinking or emotion.
Discovery of methods for training multilayer networks is the ...