Department of Psychology, University of Chicago, Chicago, 60637, USA.
Sci Rep. 2023 Sep 1;13(1):14340. doi: 10.1038/s41598-023-41613-4.
A central assumption in the behavioral sciences is that choice behavior generalizes enough across individuals that measurements from a sampled group can predict the behavior of the population. Following from this assumption, the unit of behavioral sampling or measurement for most neuroimaging studies is the individual; however, cognitive neuroscience is increasingly acknowledging a dissociation between neural activity that predicts individual behavior and that which predicts the average or aggregate behavior of the population suggesting a greater importance of individual differences than is typically acknowledged. For instance, past work has demonstrated that some, but not all, of the neural activity observed during value-based decision-making is able to predict not just individual subjects' choices but also the success of products on large, online marketplaces-even when those two behavioral outcomes deviate from one another-suggesting that some neural component processes of decision-making generalize to aggregate market responses more readily across individuals than others do. While the bulk of such research has highlighted affect-related neural responses (i.e. in the nucleus accumbens) as a better predictor of group-level behavior than frontal cortical activity associated with the integration of more idiosyncratic choice components, more recent evidence has implicated responses in visual cortical regions as strong predictors of group preference. Taken together, these findings suggest a role of neural responses during early perception in reinforcing choice consistency across individuals and raise fundamental scientific questions about the role sensory systems in value-based decision-making processes. We use a multivariate pattern analysis approach to show that single-trial visually evoked electroencephalographic (EEG) activity can predict individual choice throughout the post-stimulus epoch; however, a nominally sparser set of activity predicts the aggregate behavior of the population. These findings support an account in which a subset of the neural activity underlying individual choice processes can scale to predict behavioral consistency across people, even when the choice behavior of the sample does not match the aggregate behavior of the population.
行为科学的一个基本假设是，个体之间的选择行为具有足够的通用性，以至于从抽样群体中获得的测量结果可以预测总体行为。基于这一假设，大多数神经影像学研究的行为抽样或测量单位是个体；然而，认知神经科学越来越认识到，预测个体行为的神经活动与预测群体平均或总行为的神经活动之间存在分离，这表明个体差异比通常所承认的更为重要。例如，过去的工作已经表明，在基于价值的决策过程中观察到的一些但不是所有的神经活动不仅能够预测个体受试者的选择，还能够预测大型在线市场上产品的成功，即使这两种行为结果彼此偏离——这表明决策过程中的一些神经成分过程比其他过程更容易在个体之间推广到总体市场反应。虽然这类研究的大部分内容都强调了与情感相关的神经反应（例如，在伏隔核）作为群体行为的更好预测指标，而不是与更特殊的选择成分整合相关的额皮质活动，但最近的证据表明，视觉皮层区域的反应是群体偏好的强有力预测指标。这些发现表明，在个体之间强化选择一致性方面，早期感知过程中的神经反应起到了作用，并提出了关于感觉系统在基于价值的决策过程中的作用的基本科学问题。我们使用多元模式分析方法来表明，单次视觉诱发脑电图 (EEG) 活动可以在刺激后时期预测个体选择；然而，一组名义上稀疏的活动可以预测总体行为。这些发现支持了这样一种观点，即个体选择过程的神经活动子集可以扩展到预测人们之间的行为一致性，即使样本的选择行为与总体行为不匹配。
