title: From occasional choices to inevitable musts: a computational model of nicotine addiction.
abstract: Although, there are considerable works on the neural mechanisms of reward-based learning and decision making, and most of them mention that addiction can be explained by malfunctioning in these cognitive processes, there are very few computational models. This paper focuses on nicotine addiction, and a computational model for nicotine addiction is proposed based on the neurophysiological basis of addiction. The model compromises different levels ranging from molecular basis to systems level, and it demonstrates three different possible behavioral patterns which are addict, nonaddict, and indecisive. The dynamical behavior of the proposed model is investigated with tools used in analyzing nonlinear dynamical systems, and the relation between the behavioral patterns and the dynamics of the system is discussed.
authors.affiliation: Electrical and Electronic Engineering Faculty, Istanbul Technical University, Maslak, Istanbul 34469, Turkey. selinmetin@gmail.com
authors.forename: Selin
authors.initials: S
authors.lastname: Metin
authors.forename: N Serap
authors.initials: NS
authors.lastname: Sengor
mesh_terms: D016739:Behavior, Addictive; D001921:Brain / Q000187:drug effects / Q000502:physiology; D002755:Choice Behavior / Q000502:physiology*; D003198:Computer Simulation; D003657:Decision Making / Q000187:drug effects*; D007858:Learning / Q000502:physiology; D008959:Models, Neurological; D008960:Models, Psychological; D009474:Neurons / Q000187:drug effects / Q000502:physiology; D009538:Nicotine / Q000494:pharmacology*; D012201:Reward
chemical_list: D009538:Nicotine