This model focuses on the analyst's personal involvement, which is seen as having a continuous effect on what both the patient and analyst understand about the patient and their interaction. Therefore, the analyst's actual behavior is a strong influence on the patient's transference perceptions. Neural network models have provided a bridge from psychoanalytic concepts of transference to cognitive neuroscience. Inherent in this model is the property of one-way transmission between neurons. The strength of a synaptic connection is referred to as the weight of the synapse.
Connections are modifiable through changes in the weight.
Neural networks are trained during a process in which the weights of the synaptic connections are altered through rules of learning. This learning is of a type known as error correction, in which the output neuron is given feedback about whether it has fired correctly or not. In neural network models, representations, like memories, do not exist in a specific anatomical site. They exist as potentials that are distributed throughout a network of neural units that are simultaneously activated to produce the representation. There are multiple transferences, each of which reflects different representations and different activations of neural networks.