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

描述（由申请人提供）：认知处理的主观成本是一个长期存在的观点：在其他条件相同的情况下，人们会选择最小化认知需求的策略或行动。这一原理被认为可以解释各种各样的决策现象，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，我们在纠正这一问题上取得了一定的进展，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受控信息处理的需求联系起来。与此一致的是，我们获得了神经影像学结果，将认知成本与主要参与的皮质区域联系起来。 执行控制。在本应用中，我们的目标是在此初始基础上构建对控制成本在决策中所起的作用以及相关神经过程的更全面的解释。拟议的实验采用行为、神经影像和遗传技术来实现三个具体目标：1）我们的目标是评估控制成本的更广泛的决策影响。我们建议使用个体差异方法来测试控制成本在两个特别重要的领域中的参与情况： A. 关于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着作用。我们的目的是检验这样的假设：这种忍耐会带来控制成本，这可能解释为什么跨期选择中的自我控制容易偶尔失败。 B. 决策中的启发式使用被提议源于努力最小化原则。我们建议通过测试启发式使用和认知需求回避之间的相关性来评估这一假设。 2）我们的目标是进一步探讨控制成本的神经基础。特别是，我们将研究控制成本与之前工作的两个关键发现之间的关系： A. 之前的研究揭示了多巴胺在决定体力活动意愿方面的核心作用。使用行为遗传学方法，我们的目的是研究多巴胺能功能是否在认知努力的情况下发挥相关作用。 B. 神经影像学研究表明，支持认知控制的皮质区域与“默认模式网络”一起运作。将控制成本计算与控制相关领域联系起来后，我们提出了新的神经影像学工作，旨在研究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种基于经济劳动力供给理论的成本敏感决策的新型经济模型，该理论是最初为解释劳动力市场的努力分配而开发的正式框架。初步实验表明，劳动力供给理论可能为理解控制成本在基于奖励的决策中的作用提供了一个强有力的工具。我们建议扩展这项初步工作，以解决两个悬而未决的问题：A.认知需求回避是否源于纯粹的反应机制，或者决策是否主动预测控制需求？ 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?