We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network. Memory was initially modelled by a Boltzmann machine (BM). We simulated known microscopic mechanisms that control synaptic properties and showed that the network self-organizes to a hierarchical, clustered structure. Some properties of the complex networks which result from this self-organization indicate that a generalization of the BM may be necessary to model memory. We have thus generalized the memory model, using Generalized Simulated Annealing, derived from the nonextensive formalism, and show some properties of the resulting memory access mechanism.
Consciousness-unconsciousness; Neuroses; Self-organized neural networks; Boltzmann machine; Generalized simulated annealing; Hierarchical memory model
