The present paper discusses the findings of a systematic review of EEG measures in neuromarketing, identifying which EEG measures are the most robust predictor of customer preference in neuromarketing. The review investigated which TF effect (e.g., theta-band power), and ERP component (e.g., N400) was most consistently reflective of self-reported preference. Machine-learning prediction also investigated, along with the use of EEG when combined with physiological measures such as eye-tracking. Search terms ‘neuromarketing’ and ‘consumer neuroscience’ identified papers that used EEG measures. Publications were excluded if they were primarily written in a language other than English or were not published as journal articles (e.g., book chapters). 174 papers were included in the present review. Frontal alpha asymmetry (FAA) was the most reliable TF signal of preference and was able to differentiate positive from negative consumer responses. Similarly, the late positive potential (LPP) was the most reliable ERP component, reflecting conscious emotional evaluation of products and advertising. However, there was limited consistency across papers, with each measure showing mixed results when related to preference and purchase behaviour. FAA and the LPP were the most consistent markers of emotional responses to marketing stimuli, consumer preference and purchase intention. Predictive accuracy of FAA and the LPP was greatly improved through the use of machine-learning prediction, especially when combined with eye-tracking or facial expression analyses.

中文翻译：

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在神经营销研究中使用脑电图测量和机器学习预测消费者偏好的系统回顾

本文讨论了对神经营销中脑电图测量的系统评价的结果，确定哪些脑电图测量是神经营销中客户偏好的最有力预测指标。该审查调查了哪种 TF 效应（例如，theta 波段功率）和 ERP 组件（例如，N400）最能始终如一地反映自我报告的偏好。还研究了机器学习预测，以及脑电图与眼动追踪等生理措施相结合时的使用。搜索词“neuromarketing”和“consumer neuroscience”确定了使用脑电图测量的论文。如果出版物主要是用英语以外的语言编写的或未作为期刊文章（例如书籍章节）发表，则被排除在外。本次审查收录了 174 篇论文。额叶 alpha 不对称性 (FAA) 是最可靠的偏好 TF 信号，能够区分正面和负面的消费者反应。同样，晚期正向电位 (LPP) 是最可靠的 ERP 组件，反映了对产品和广告的有意识的情感评价。然而，论文之间的一致性有限，当与偏好和购买行为相关时，每项措施都显示出不同的结果。FAA 和 LPP 是对营销刺激、消费者偏好和购买意愿的情绪反应最一致的标志。通过使用机器学习预测，特别是与眼动追踪或面部表情分析相结合时，FAA 和 LPP 的预测准确性得到了极大提高。同样，晚期正向电位 (LPP) 是最可靠的 ERP 组件，反映了对产品和广告的有意识的情感评价。然而，论文之间的一致性有限，当与偏好和购买行为相关时，每项措施都显示出不同的结果。FAA 和 LPP 是对营销刺激、消费者偏好和购买意愿的情绪反应最一致的标志。通过使用机器学习预测，特别是与眼动追踪或面部表情分析相结合时，FAA 和 LPP 的预测准确性得到了极大提高。同样，晚期正向电位 (LPP) 是最可靠的 ERP 组件，反映了对产品和广告的有意识的情感评价。然而，论文之间的一致性有限，当与偏好和购买行为相关时，每项措施都显示出不同的结果。FAA 和 LPP 是对营销刺激、消费者偏好和购买意愿的情绪反应最一致的标志。通过使用机器学习预测，特别是与眼动追踪或面部表情分析相结合时，FAA 和 LPP 的预测准确性得到了极大提高。当与偏好和购买行为相关时，每项措施都显示出混合的结果。FAA 和 LPP 是对营销刺激、消费者偏好和购买意愿的情绪反应最一致的标志。通过使用机器学习预测，特别是与眼动追踪或面部表情分析相结合时，FAA 和 LPP 的预测准确性得到了极大提高。当与偏好和购买行为相关时，每项措施都显示出混合的结果。FAA 和 LPP 是对营销刺激、消费者偏好和购买意愿的情绪反应最一致的标志。通过使用机器学习预测，特别是与眼动追踪或面部表情分析相结合时，FAA 和 LPP 的预测准确性得到了极大提高。