Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose a schematic self-organizing neural network model, to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network model, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The model is illustrated through computer simulations. We relate sensitivity to temperature and adaptive capabilities of our model, with the sensitivity of cortical map modulation to the catecholamines (norepinephrine and dopamine). The signal-to-noise ratio regulated by these substances influence thought associativity, suggesting a continuous potentiality for the creation of different mental structures, from psychotic through to normal and neurotic behavior, and creativity.
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