A Computational Model of Cortico-Striato-Thalamic Circuits in Goal-Directed Behaviour
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
From occasional choices to inevitable musts: a computational model of nicotine addiction
Computational Intelligence and Neuroscience
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Continuous exposure to nicotine causes behavioral choice to be modified by dopamine to become rigid, resulting in addiction. In this work, a computational model for nicotine addiction is proposed and the proposed model captures the effect of continuous nicotine exposure in becoming addict through reinforcement learning. The computational model is composed of three subsystems each corresponding to neural substrates taking part in nicotine addiction and these subsystems are realized by nonlinear dynamical systems. Even though the model is sufficient in acquiring addiction, it needs to be further developed to give a better explanation for the process responsible in turning a random choice into a compulsive behavior.