An adaptive temporal-causal network model for decision making under acute stress

In recent literature from Neuroscience the adaptive role of the effects of stress on decision making is highlighted. The problem addressed in this paper is how that can be modelled computationally. The presented adaptive temporal-causal network model addresses the suppression of the existing network connections in a first phase as a result of the acute stress, and then as a second phase relaxing the suppression after some time and give room to start new learning of the decision making in the context of the stress again