Claremont McKenna College, Claremont, California, USA.
University of Toronto Scarborough, Toronto, Ontario, Canada.
Wiley Interdiscip Rev Cogn Sci. 2022 May;13(3):e1586. doi: 10.1002/wcs.1586. Epub 2021 Dec 2.
As interest in the temporal dynamics of decision-making has grown, researchers have increasingly turned to computational approaches such as the drift diffusion model (DDM) to identify how cognitive processes unfold during choice. At the same time, technological advances in noninvasive neurophysiological methods such as electroencephalography and magnetoencephalography now allow researchers to map the neural time course of decision making with millisecond precision. Combining these approaches can potentially yield important new insights into how choices emerge over time. Here we review recent research on the computational and neurophysiological correlates of perceptual and value-based decision making, from DDM parameters to scalp potentials and oscillatory neural activity. Starting with motor response preparation, the most well-understood aspect of the decision process, we discuss evidence that urgency signals and shifts in baseline activation, rather than shifts in the physiological value of the choice-triggering response threshold, are responsible for adjusting response times under speeded choice scenarios. Research on the neural correlates of starting point bias suggests that prestimulus activity can predict biases in motor choice behavior. Finally, studies examining the time dynamics of evidence construction and evidence accumulation have identified signals at frontocentral and centroparietal electrodes associated respectively with these processes, emerging 300-500 ms after stimulus onset. These findings can inform psychological theories of decision-making, providing empirical support for attribute weighting in value-based choice while suggesting theoretical alternatives to dual-process accounts. Further research combining computational and neurophysiological approaches holds promise for providing greater insight into the moment-by-moment evolution of the decision process. This article is categorized under: Psychology > Reasoning and Decision Making Neuroscience > Cognition Economics > Individual Decision-Making.
随着人们对决策的时间动态的兴趣不断增加，研究人员越来越多地采用计算方法，如漂移扩散模型 (DDM)，以确定认知过程在选择过程中是如何展开的。与此同时，脑电图和脑磁图等非侵入性神经生理学方法的技术进步现在使研究人员能够以毫秒级的精度绘制决策的神经时间过程。将这些方法结合起来，有可能为我们如何随着时间的推移做出选择提供重要的新见解。在这里，我们回顾了最近关于感知和基于价值的决策的计算和神经生理学相关性的研究，从 DDM 参数到头皮电位和振荡神经活动。从决策过程中最容易理解的方面——运动反应准备开始，我们讨论了证据表明紧急信号和基线激活的转变，而不是选择触发反应阈值的生理价值的转变，是负责调整快速选择场景下的反应时间。关于起始点偏差的神经相关性的研究表明，刺激前活动可以预测运动选择行为的偏差。最后，研究检查了证据构建和证据积累的时间动态，在刺激开始后 300-500 毫秒识别出与这些过程分别相关的额中和中央顶电极的信号。这些发现可以为决策的心理理论提供信息，为基于价值的选择中的属性加权提供经验支持，同时为双过程解释提供理论替代方案。结合计算和神经生理学方法的进一步研究有望更深入地了解决策过程的瞬间演变。本文属于以下类别：心理学 > 推理和决策 神经科学 > 认知 经济学 > 个人决策。
