Adaptation in decision circuits: temporal history and the efficiency of choice

决策回路的适应：时间历史和选择效率

• 批准号: 8887904
• 负责人: KENWAY LOUIE
• 金额: $ 39.02万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-22 至 2020-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8887904
• 关键词: Address; Algorithms; Animal Model; Animals; Area; Behavior; Behavioral; Benchmarking; Biological; Bipolar Disorder; Brain; Characteristics; Choice Behavior; Code; Communities; Complex; Computational algorithm; Computer Simulation; Decision Making; Dependence; Disease; Ecology; Economics; Environment; Epilepsy; Equilibrium; Face; Future; Human; Link; Literature; Major Depressive Disorder; Mediating; Mental Depression; Modeling; Monkeys; Mood Disorders; Nature; Neurobiology; Neurons; Organism; Outcome; Parietal; Performance; Process; Psychology; Recording of previous events; Rewards; Role; Schizophrenia; Sensory; Stimulus; Structure; Substance abuse problem; System; Testing; Visual Cortex; Work; base; behavioral economics; comparative; experience; high reward; human subject; improved; information processing; insight; lateral intraparietal area; neural circuit; neurophysiology; neuropsychiatry; novel strategies; public health relevance; relating to nervous system; research study; response; reward processing; sensory neuroscience; simulation; theories; tool

 DESCRIPTION (provided by applicant): The ability to make efficient decisions is critical in a dynamic and changing environment, governing behavior ranging from the simple to the complex. Furthermore, altered decision-making is a hallmark of a number of diseases, such as epilepsy, major depression, and schizophrenia. In particular, value-guided decisions can be altered by aberrant processing of the history of recent rewards and the ability to use past experience to guide future decisions. While emerging work has outlined many brain areas involved in decision-making, how neural circuits decide is unknown. Theorists in psychology, economics, and ecology have outlined standard models of rational choice behavior, defining how optimal choosers should behave to maximize outcomes. In contrast to these theoretical predictions, empirical choice behavior in animals and humans often deviates markedly from optimality. Such inefficiencies likely reflect the constraints of a biological decision system, and studying rationality violations offers potential insight into the neurobiological basis of decision making. In this application, we examine the effect of previous history on the decision process and its underlying circuits. We hypothesize that temporal context-dependence in both value-coding neural activity and choice behavior arises from the way neural circuits represent value. Specifically, we hypothesize that adaptive value- coding is implemented using a standard computation widely found in sensory cortical circuits, divisive normalization, and that adaptation in perceptual processing provides a framework for understanding adaptation in valuation and decision-making. To test this hypothesis, we propose to undertake three aims addressing adaptation in value coding at the neural, computational, and behavioral levels. In Aim 1, we propose electrophysiological recording experiments to test whether the neural representation of value adapts to prior reward history, and whether this computation matches the divisive normalization algorithm. In Aim 2, we propose computational modeling experiments which will test the generality of the normalization model in explaining various, different value adaptation effects, and make specific predictions about the effect of adaptive value coding on choice behavior. In Aim 3, we propose choice behavior experiments, in both an animal model and human subjects, to test the prediction that adaptive value coding can selectively enhance the efficiency of choice. Understanding adaptation in value coding is crucial for understanding both standard and pathological choice behavior. Temporal history effects in decision-making are suboptimal in terms of rational theories of choice, but may reflect a more global optimality that balances choice efficiency and the constraints of operating a biological decision process. Such temporal-dependence may be particularly important for understanding affective disorders, such as depression and bipolar disorder, where prolonged periods of low or high reward states may significantly impede the decision process.

 描述（由申请人提供）：在动态和不断变化的环境中做出有效决策的能力至关重要，管理从简单到复杂的行为。此外，改变的决策是许多疾病的标志，如癫痫，重度抑郁症和精神分裂症。特别是，价值导向的决策可以通过对最近奖励历史的异常处理以及使用过去经验指导未来决策的能力来改变。虽然新兴的工作已经概述了许多参与决策的大脑区域，但神经回路如何决定尚不清楚。心理学、经济学和生态学的理论家已经概述了理性选择行为的标准模型，定义了最佳选择者应该如何行为以最大化结果。与这些理论预测相反，动物和人类的经验选择行为往往明显偏离最优性。这种低效率可能反映了生物决策系统的限制， 研究违反理性的行为，可以深入了解决策的神经生物学基础。 制作。 在这个应用程序中，我们研究了以前的历史对决策过程及其底层电路的影响。我们假设，时间上下文依赖的价值编码神经活动和选择行为产生的方式神经回路表示的价值。具体来说，我们假设，自适应值编码是使用一个标准的计算广泛发现的感觉皮层电路，分裂的正常化，并在感知处理的适应提供了一个框架，理解适应的评价和决策。为了验证这一假设，我们提出了三个目标，解决适应价值编码在神经，计算和行为水平。在目标1中，我们提出了电生理记录实验来测试价值的神经表征是否适应先前的奖励历史，以及这种计算是否与分裂归一化算法相匹配。在目标2中，我们提出了计算建模实验，将测试归一化模型在解释各种不同的价值适应效应方面的通用性，并对自适应价值编码对选择行为的影响做出具体预测。在目标3中，我们提出了选择行为实验，在动物模型和人类受试者，以测试预测，自适应值编码可以选择性地提高选择的效率。 理解价值编码中的适应对于理解标准和病理选择行为至关重要。决策中的时间历史效应在理性选择理论中是次优的，但可能反映了一种更全局的最优性，这种最优性平衡了选择效率和操作生物决策过程的约束。这种时间依赖性对于理解情感障碍（如抑郁症和双相情感障碍）可能特别重要，在这些情感障碍中，长时间的低或高奖励状态可能会显著阻碍决策过程。