Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, 93101, USA.
Neuroimage. 2012 Jan 2;59(1):94-108. doi: 10.1016/j.neuroimage.2011.07.009. Epub 2011 Jul 14.
Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally, our methods highlight the potential of multi-brain computing as a technique to rapidly and in parallel gather increased information about the environment as well as to access collective perceptual/cognitive choices and mental states.
群体决策甚至是多个意见的聚合会导致更高的决策准确性，这一现象被称为集体智慧。关于集体智慧的神经基础以及其益处是出现在决策的晚期阶段还是早期的感觉编码阶段，人们知之甚少。在这里，我们使用脑电图和 20 名人类进行感知决策的多脑计算，结果表明，跨大脑组合神经活动可以提高决策准确性，与聚合观察者意见所显示的改进相平行。虽然最大的收益来自于大脑之间的神经决策变量的最优线性组合，但在人类行为中普遍存在的更简单的神经多数决策规则也会带来实质性的好处。相比之下，一种类似于群体追随最极端意见的极端神经反应规则，随着群体规模的增加，改进最小。在控制电极数量和时间点的同时增加大脑数量的分析中，证明了跨不同大脑整合神经活动所产生的独特益处。多脑整合的好处早在刺激呈现后 200 毫秒的外侧枕叶部位的神经活动中显现出来，并且在与决策相关的神经活动中没有额外的好处。与决策成分相关的神经活动一样，与感觉相关的神经活动可以准确地预测通过聚合个体意见、投票结果和决策信心得出的集体选择。通过跨多个大脑组合信息来估计集体快速决策的潜力的方法，这是许多动物中常见的策略，显示出很大的时间节省。总的来说，这些发现表明，对于感知决策，支持集体智慧和决策的神经活动出现在早期的感觉阶段，并且集体认知的许多特性可以通过跨多个大脑的信息神经编码来解释。最后，我们的方法突出了多脑计算作为一种技术的潜力，可以快速并行地收集关于环境的更多信息，以及访问集体感知/认知选择和心理状态。
