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{"title":"啮齿动物基于奖惩的决策。","authors":"Caitlin A Orsini, Nicholas W Simon","doi":"10.1002/cpns.100","DOIUrl":null,"url":null,"abstract":"<p><p>Deficits in decision making are at the heart of many psychiatric diseases, such as substance abuse disorders and attention deficit hyperactivity disorder. Consequently, rodent models of decision making are germane to understanding the neural mechanisms underlying adaptive choice behavior and how such mechanisms can become compromised in pathological conditions. A critical factor that must be integrated with reward value to ensure optimal decision making is the occurrence of consequences, which can differ based on probability (risk of punishment) and temporal contiguity (delayed punishment). This article will focus on two models of decision making that involve explicit punishment, both of which recapitulate different aspects of consequences during human decision making. We will discuss each behavioral protocol, the parameters to consider when designing an experiment, and finally how such animal models can be utilized in studies of psychiatric disease. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Behavioral training Support Protocol: Equipment testing Alternate Protocol: Reward discrimination Basic Protocol 2: Risky decision-making task (RDT) Basic Protocol 3: Delayed punishment decision-making task (DPDT).</p>","PeriodicalId":40016,"journal":{"name":"Current Protocols in Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpns.100","citationCount":"6","resultStr":"{\"title\":\"Reward/Punishment-Based Decision Making in Rodents.\",\"authors\":\"Caitlin A Orsini, Nicholas W Simon\",\"doi\":\"10.1002/cpns.100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Deficits in decision making are at the heart of many psychiatric diseases, such as substance abuse disorders and attention deficit hyperactivity disorder. Consequently, rodent models of decision making are germane to understanding the neural mechanisms underlying adaptive choice behavior and how such mechanisms can become compromised in pathological conditions. A critical factor that must be integrated with reward value to ensure optimal decision making is the occurrence of consequences, which can differ based on probability (risk of punishment) and temporal contiguity (delayed punishment). This article will focus on two models of decision making that involve explicit punishment, both of which recapitulate different aspects of consequences during human decision making. We will discuss each behavioral protocol, the parameters to consider when designing an experiment, and finally how such animal models can be utilized in studies of psychiatric disease. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Behavioral training Support Protocol: Equipment testing Alternate Protocol: Reward discrimination Basic Protocol 2: Risky decision-making task (RDT) Basic Protocol 3: Delayed punishment decision-making task (DPDT).</p>\",\"PeriodicalId\":40016,\"journal\":{\"name\":\"Current Protocols in Neuroscience\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/cpns.100\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Protocols in Neuroscience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/cpns.100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Neuroscience\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Protocols in Neuroscience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/cpns.100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Neuroscience","Score":null,"Total":0}
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