Division of Anaesthesia, Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Hum Brain Mapp. 2020 Jun 1;41(8):2229-2243. doi: 10.1002/hbm.24942. Epub 2020 Feb 6.
The human brain exhibits a rich functional repertoire in terms of complex functional connectivity patterns during rest and tasks. However, how this is developed upon a fixed structural anatomy remains poorly understood. Here we investigated the hypothesis that resting state functional connectivity and the manner in which it changes during tasks related to a set of underlying structural connections that promote optimal communication in the brain. We used a game-theoretic model to identify such optimal connections in the structural connectome of 50 healthy individuals and subsequently used the optimal structural connections to predict resting-state functional connectivity with high accuracy. In contrast, we found that nonoptimal connections accurately predicted functional connectivity during a working memory task. We further found that this balance between optimal and nonoptimal connections between brain regions was associated with a specific gene expression linked to neurotransmission. This multimodal evidence shows for the first time that structure-function relationships in the human brain are related to how brain networks navigate information along different white matter connections as well as the brain's underlying genetic profile.
人类大脑在休息和任务期间表现出丰富的功能组合，具有复杂的功能连接模式。然而，在固定的结构解剖学基础上，这种功能是如何发展的仍知之甚少。在这里，我们研究了这样一个假设，即静息状态功能连接以及在与一组基础结构连接相关的任务中改变的方式，这些连接促进了大脑中的最佳通信。我们使用博弈论模型来识别 50 名健康个体结构连接组中的这种最佳连接，然后使用最佳结构连接来高精度地预测静息状态功能连接。相比之下，我们发现非最佳连接可以准确预测工作记忆任务期间的功能连接。我们进一步发现，大脑区域之间的最佳和非最佳连接之间的这种平衡与特定的基因表达有关，该基因表达与神经传递有关。这种多模态证据首次表明，人类大脑的结构-功能关系与大脑网络如何沿着不同的白质连接以及大脑的潜在遗传特征传输信息有关。
