The intrinsic cost of cognitive control: Neural foundations and behavioral impact

描述（由申请人提供）：这是一个长期的想法，认知处理是主观代价：所有其他条件相同，人们会选择策略或行动，最大限度地减少认知需求。这一原理被认为可以解释大量的决策现象，但令人惊讶的是，它几乎没有受到直接的实验检验。在最近的工作中，我们已经在纠正这一点上取得了一些进展，为认知需求回避提供了第一个直接证据。我们最初的行为发现将认知成本与执行功能或控制信息处理的需求联系起来。与此相一致的是，我们已经获得了神经成像结果，将认知成本与中枢参与的皮层区域联系起来， 执行控制在本申请中，我们的目标是建立在这个初步的基础上，构建一个更全面的考虑，控制成本在决策中发挥的作用，以及相关的神经过程。拟议的实验采用行为，神经成像和遗传技术，以追求三个具体目标：1）我们的目标是评估更广泛的控制成本的决策后果。使用个体差异的方法，我们建议在两个特别重要的领域测试控制成本的参与：A。跨期选择的研究表明，“自我控制”在抵制即时奖励的诱惑方面发挥了作用。我们的目标是测试的假设，这种宽容进行控制成本，可能解释为什么跨期选择的自我控制是容易偶尔失败。B。启发式决策的使用已被提出产生的努力最小化原则。我们建议评估这一假设，通过测试启发式使用和认知需求回避之间的相关性。2)我们的目标是进一步探索控制成本的神经基础。特别是，我们将调查控制成本和以前工作中的两个关键发现之间的关系：A。先前的研究已经揭示了多巴胺在决定是否愿意付出体力方面的核心作用。使用行为遗传学的方法，我们的目的是调查是否多巴胺能功能在认知努力的情况下起着相关的作用。B。神经影像学研究表明，支持认知控制的皮层区域与"默认模式网络“一起运作。在将控制成本计算与控制相关领域联系起来之后，我们提出了新的神经成像工作，旨在调查默认网络在塑造基于成本的决策中的潜在参与。3)我们的目标是测试一个新的经济模型的成本敏感的决策的基础上经济劳动力供给理论，一个正式的框架，最初开发的努力分配劳动力市场。初步实验表明，劳动供给理论可能提供一个强大的工具，了解控制成本的作用，奖励为基础的决策。我们建议扩展这一初步工作，以解决两个悬而未决的问题：A。认知需求回避是源于纯粹的反应机制，还是决策主动地预期控制需求？B。劳动力供给模型能否解释控制权分配随时间的变化，包括所谓的“自我损耗”效应？

DESCRIPTION (provided by applicant): It is a longstanding idea that cognitive processing is subjectively costly: All else being equal, people will choose strategies or actions that minimize cognitive demands. This principle has been presumed to explain a wide array of decision-making phenomena, but has been subjected to surprisingly little direct experimental scrutiny. In recent work, we have gone some distance toward rectifying this, providing the first direct evidence for cognitive demand avoidance. Our initial behavioral findings link cognitive costs to demands on executive function or controlled information processing. Consistent with this, we have obtained neuroimaging results that tie cognitive costs to cortical areas centrally involved in executive control. In the present application, our objective is to build on this initial foundation constructing a fuller account of the role that control costs play in decision making, and of the relevant neural processes. The proposed experiments employ behavioral, neuroimaging and genetic techniques to pursue three specific aims: 1) We aim to evaluate the broader decision-making ramifications of control costs. Using an individual-differences approach, we propose to test for the involvement of control costs in two particularly important areas: A. Research on intertemporal choice has suggested a role for 'self-control' in resisting the temptation of immediate rewards. We aim to test the hypothesis that such forbearance carries control costs, potentially explaining why self-control in intertemporal choice is prone to occasional failure. B. Heuristic use in decision making has been proposed to arise from an effort-minimization principle. We propose to evaluate this hypothesis, by testing for a correlation between heuristic use and cognitive demand avoidance. 2) We aim to further probe the neural foundations of control costs. In particular, we will investigate the relationship between control costs and two key findings from previous work: A. Previous research has revealed a central role for dopamine in determining willingness to exert physical effort. Using a behavioral-genetic approach, we aim to investigate whether dopaminergic function plays a related role in the case of cognitive effort. B. Neuroimaging research has revealed that cortical areas supporting cognitive control operate alongside a 'default mode network.' Having linked control-cost computations with the control-related areas, we propose new neuroimaging work aimed at investigating the potential involvement of the default network in shaping cost-based decision making. 3) We aim to test a novel economic model of cost-sensitive decision making based on economic labor supply theory, a formal framework originally developed to account for effort allocation in labor markets. Initial experiments suggest that labor supply theory may provide a powerful tool for understanding the role of control costs in reward-based decision making. We propose to extend this initial work to address two outstanding questions: A. Does cognitive demand avoidance arise from a purely reactive mechanism, or does decision making actively anticipate demands for control? B. Can the labor-supply model account for shifts in control allocation over time, including so-called 'ego-depletion' effects?