控制调整成本限制目标灵活性:经验证据和理论解释。

Ivan Grahek, Xiamin Leng, Sebastian Musslick, Amitai Shenhav
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引用次数: 0

摘要

在目标之间切换的能力是人类认知和行为的基石。认知控制允许根据新目标快速调整认知,但控制调整是有代价的。传统上,这种成本是在需要改变任务的情况下进行研究的,而不需要对控制状态进行其他改变。然而,目标灵活性通常需要维持相同的任务,同时调整分配给该任务的控制量和类型。例如,给定任务的不同阶段可能需要我们或多或少地高效地处理信息(例如,通过改变注意力水平)和/或或多或少地谨慎地做出反应(例如,改变反应阈值)。在四个实验中,我们表明这种任务内控制调整会产生性能成本,并且动态系统模型可以解释这些成本的来源。参与者在不同的表现目标下(例如,快速或准确)执行一项认知要求较高的任务(颜色词Stroop)。我们对控制分配进行了建模,以包括从当前控制状态调整到给定性能目标的目标状态的动态过程。通过将惯性纳入这一调整过程,我们的模型预测和实证结果证实,当(a)目标在一个区块内转换而不是保持固定时,人们会更多地低估目标控制状态(即表现出更大的调整成本)(研究1);(b) 目标控制状态彼此相距更远(研究2);(c) 给予较少的时间来适应新的目标(研究3);以及(d)当预期必须更频繁地切换目标时(研究4)。我们的研究结果表明,即使在没有任务变化的情况下,调整控制以实现目标也是有成本的,并表明这种成本可以直接来自控制调整的动态。通过这样做,他们为人类目标导向行为的灵活性的来源和限制提供了新的线索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Control adjustment costs limit goal flexibility: Empirical evidence and a computational account.

Control adjustment costs limit goal flexibility: Empirical evidence and a computational account.

Control adjustment costs limit goal flexibility: Empirical evidence and a computational account.

Control adjustment costs limit goal flexibility: Empirical evidence and a computational account.

A cornerstone of human intelligence is the ability to flexibly adjust our cognition and behavior as our goals change. For instance, achieving some goals requires efficiency, while others require caution. Different goals require us to engage different control processes, such as adjusting how attentive and cautious we are. Here, we show that performance incurs control adjustment costs when people adjust control to meet changing goals. Across four experiments, we provide evidence of these costs, and validate a dynamical systems model explaining the source of these costs. Participants performed a single cognitively demanding task under varying performance goals (e.g., being fast or accurate). We modeled control allocation to include a dynamic process of adjusting from one's current control state to a target state for a given performance goal. By incorporating inertia into this adjustment process, our model accounts for our empirical finding that people under-shoot their target control state more (i.e., exhibit larger adjustment costs) when goals switch rather than remain fixed (Study 1). Further validating our model, we show that the magnitude of this cost is increased when: distances between target states are larger (Study 2), there is less time to adjust to the new goal (Study 3), and goal switches are more frequent (Study 4). Our findings characterize the costs of adjusting control to meet changing goals, and show that these costs emerge directly from cognitive control dynamics. In so doing, they shed new light on the sources of and constraints on flexibility of goal-directed behavior.

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