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Combination of diffuse and local connections in the cortex

We present a simple neural network model that combines local and diffuse connections. It represents the interaction between ascending or monamine systems, and the cortex in the human brain. We show that this simple model allows the use of salience (cognitive significance) as an input and response in the neural network. Results for single and multiple-trial learning show that salience can drive the learning process to a high degree.