title: [Predicting suicide or predicting the unpredictable in an uncertain world: Reinforcement Learning Model-Based analysis].
abstract: In general, it appears that the suicidal act is highly unpredictable with the current scientific means available. In this article, the author submits the hypothesis that predicting suicide is complex because it results in predicting a choice, in itself unpredictable. The article proposes a Reinforcement learning model-based analysis. In this model, we integrate on the one hand, four ascending modulatory neurotransmitter systems (acetylcholine, noradrenalin, serotonin, and dopamine) with their regions of respective projections and afferences, and on the other hand, various observations of brain imaging identified until now in the suicidal process.
authors.affiliation: Faculté de Médecine de l'Université de Namur; Clinique Psychiatrique des Frères Alexiens, Château de Ruyff, Henri-Chapelle, Belgique. martin.desseilles@fundp.ac.be
authors.forename: Martin
authors.initials: M
authors.lastname: Desseilles
mesh_terms: D002755:Choice Behavior; D005544:Forecasting; D006801:Humans; D008960:Models, Psychological; D009638:Norepinephrine / Q000502:physiology; D012054:Reinforcement, Psychology; D013405:Suicide / Q000523:psychology*; D035501:Uncertainty
chemical_list: D009638:Norepinephrine