The human brain is a complex container of interconnected networks. Network neuroscience is a recent venture aiming to explore the connection matrix built from the human brain or human “Connectome.” Network-based algorithms provide parameters that define global organization of the brain; when they are applied to electroencephalographic (EEG) signals network, configuration and excitability can be monitored in millisecond time frames, providing remarkable information on their instantaneous efficacy also for a given task’s performance via online evaluation of the underlying instantaneous networks before, during, and after the task. Here we provide an updated summary on the connectome analysis for the prediction of performance via the study of task-related dynamics of brain network organization from EEG signals.

人脑是互连网络的复杂容器。网络神经科学是一项最近的冒险活动，旨在探索从人脑或人“ Connectome”建立的连接矩阵。基于网络的算法提供了定义大脑全局组织的参数。当将它们应用于脑电图（EEG）信号网络时，可以在毫秒时间范围内监视配置和兴奋性，并通过在线评估基础瞬时网络之前，之中和之后，针对给定任务的性能提供了有关其瞬时功效的重要信息。任务。在这里，我们通过研究脑电信号与大脑网络组织的任务相关动力学，提供了有关连接组分析的最新摘要，用于预测性能。