School of Psychology, Cognition Institute, University of Plymouth.
Psychol Bull. 2015 Jan;141(1):213-35. doi: 10.1037/bul0000006. Epub 2014 Dec 15.
Economic approaches to decision making assume that people attach values to prospective goods and act to maximize their obtained value. Neuroeconomics strives to observe these values directly in the brain. A widely used valuation term in formal learning and decision-making models is the reward prediction error: the value of an outcome relative to its expected value. An influential theory (Holroyd & Coles, 2002) claims that an electrophysiological component, feedback related negativity (FRN), codes a reward prediction error in the human brain. Such a component should be sensitive to both the prior likelihood of reward and its magnitude on receipt. A number of studies have found the FRN to be insensitive to reward magnitude, thus questioning the Holroyd and Coles account. However, because of marked inconsistencies in how the FRN is measured, a meaningful synthesis of this evidence is highly problematic. We conducted a meta-analysis of the FRN's response to both reward magnitude and likelihood using a novel method in which published effect sizes were disregarded in favor of direct measurement of the published waveforms themselves, with these waveforms then averaged to produce "great grand averages." Under this standardized measure, the meta-analysis revealed strong effects of magnitude and likelihood on the FRN, consistent with it encoding a reward prediction error. In addition, it revealed strong main effects of reward magnitude and likelihood across much of the waveform, indicating sensitivity to unsigned prediction errors or "salience." The great grand average technique is proposed as a general method for meta-analysis of event-related potential (ERP).
经济决策方法假设人们对预期的商品赋予价值，并采取行动以最大化他们获得的价值。神经经济学努力直接在大脑中观察这些价值。在正式学习和决策模型中，一个广泛使用的评估术语是奖励预测误差：结果的价值相对于其预期价值。一个有影响力的理论（Holroyd 和 Coles，2002）声称，一个电生理成分，反馈相关负性（FRN），在人类大脑中编码奖励预测误差。这样的成分应该对奖励的先验可能性及其收到时的大小敏感。许多研究发现 FRN 对奖励大小不敏感，因此对 Holroyd 和 Coles 的说法提出了质疑。然而，由于 FRN 的测量方式存在明显的不一致，因此对这些证据进行有意义的综合是非常困难的。我们使用一种新的方法对 FRN 对奖励大小和可能性的反应进行了荟萃分析，在这种方法中，我们忽略了已发表的效应量，而是直接测量已发表的波型本身，然后对这些波型进行平均，以产生“大平均波型”。在这个标准化的测量下，荟萃分析显示 FRN 对大小和可能性有强烈的影响，与它编码奖励预测误差一致。此外，它还在整个波型中显示出奖励大小和可能性的强烈主效应，表明对无符号预测误差或“显着性”敏感。大平均波型技术被提议作为事件相关电位（ERP）荟萃分析的一般方法。
