Previous neuroimaging studies have offered unique insights about the spatial organization of activations and deactivations across the brain; however, these were not powered to explore the exact timing of events at the subsecond scale combined with a precise anatomical source of information at the level of individual brains. As a result, we know little about the order of engagement across different brain regions during a given cognitive task. Using experimental arithmetic tasks as a prototype for human-unique symbolic processing, we recorded directly across 10,076 brain sites in 85 human subjects (52% female) using the intracranial electroencephalography. Our data revealed a remarkably distributed change of activity in almost half of the sampled sites. In each activated brain region, we found juxtaposed neuronal populations preferentially responsive to either the target or control conditions, arranged in an anatomically orderly manner. Notably, an orderly successive activation of a set of brain regions—anatomically consistent across subjects—was observed in individual brains. The temporal order of activations across these sites was replicable across subjects and trials. Moreover, the degree of functional connectivity between the sites decreased as a function of temporal distance between regions, suggesting that the information is partially leaked or transformed along the processing chain. Our study complements prior imaging studies by providing hitherto unknown information about the timing of events in the brain during arithmetic processing. Such findings can be a basis for developing mechanistic computational models of human-specific cognitive symbolic systems.

之前的神经影像学研究对大脑激活和失活的空间组织提供了独特的见解。然而，这些技术无法结合个体大脑层面的精确解剖信息源来探索亚秒级事件的确切时间。因此，我们对特定认知任务期间不同大脑区域的参与顺序知之甚少。使用实验算术任务作为人类独特的符号处理的原型，我们使用颅内脑电图直接记录了 85 名人类受试者（52% 女性）的 10,076 个大脑部位。我们的数据显示，几乎一半的采样点的活动发生了显着分布的变化。在每个激活的大脑区域中，我们发现并置的神经元群优先响应目标条件或控制条件，并以解剖学顺序排列。值得注意的是，在个体大脑中观察到一组大脑区域的有序连续激活（在解剖学上在受试者之间是一致的）。这些位点激活的时间顺序可以在受试者和试验中复制。此外，站点之间的功能连接程度随着区域之间时间距离的变化而降低，这表明信息在处理链上部分泄漏或转换。我们的研究通过提供迄今为止未知的关于算术处理过程中大脑事件发生时间的信息来补充之前的成像研究。这些发现可以成为开发人类特定认知符号系统的机械计算模型的基础。