Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Osaka, Japan.
Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan.
Nat Commun. 2020 Mar 2;11(1):1142. doi: 10.1038/s41467-020-14913-w.
Our daily life is realized by the complex orchestrations of diverse brain functions, including perception, decision-making, and action. The essential goal of cognitive neuroscience is to reveal the complete representations underlying these functions. Recent studies have characterised perceptual experiences using encoding models. However, few attempts have been made to build a quantitative model describing the cortical organization of multiple active, cognitive processes. Here, we measure brain activity using fMRI, while subjects perform 103 cognitive tasks, and examine cortical representations with two voxel-wise encoding models. A sparse task-type model reveals a hierarchical organization of cognitive tasks, together with their representation in cognitive space and cortical mapping. A cognitive factor model utilizing continuous, metadata-based intermediate features predicts brain activity and decodes tasks, even under novel conditions. Collectively, our results show the usability of quantitative models of cognitive processes, thus providing a framework for the comprehensive cortical organization of human cognition.
我们的日常生活是由各种大脑功能的复杂协调实现的，包括感知、决策和行动。认知神经科学的基本目标是揭示这些功能背后的完整表示。最近的研究使用编码模型来描述感知体验。然而，很少有尝试构建一个定量模型来描述多个活跃的、认知过程的皮质组织。在这里，我们使用 fMRI 测量大脑活动，同时让受试者执行 103 项认知任务，并使用两种体素编码模型检查皮质表示。稀疏的任务类型模型揭示了认知任务的层次结构，以及它们在认知空间和皮质映射中的表示。利用基于连续、元数据的中间特征的认知因子模型可以预测大脑活动并对任务进行解码，即使在新的条件下也是如此。总的来说，我们的结果表明认知过程的定量模型具有可用性，从而为人类认知的全面皮质组织提供了一个框架。
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