2014年1月7日火曜日

Decision making: from neuroscience to psychiatry.

Lee D.
Neuron. 2013 Apr 24;78(2):233-48. doi: 10.1016/j.neuron.2013.04.008.

意思決定について、経済学や機械学習のモデルと、それらの枠組みを援用した神経科学の最新の知見を紹介した総説。
パーキンソン病、統合失調症、自閉症などとの関連、精神医学への応用についても議論している。

Adaptive behaviors increase the likelihood of survival and reproduction and improve the quality of life. However, it is often difficult to identify optimal behaviors in real life due to the complexity of the decision maker's environment and social dynamics. As a result, although many different brain areas and circuits are involved in decision making, evolutionary and learning solutions adopted by individual decision makers sometimes produce suboptimal outcomes. Although these problems are exacerbated in numerous neurological and psychiatric disorders, their underlying neurobiological causes remain incompletely understood. In this review, theoretical frameworks in economics and machine learning and their applications in recent behavioral and neurobiological studies are summarized. Examples of such applications in clinical domains are also discussed for substance abuse, Parkinson's disease, attention-deficit/hyperactivity disorder, schizophrenia, mood disorders, and autism. Findings from these studies have begun to lay the foundations necessary to improve diagnostics and treatment for various neurological and psychiatric disorders.

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