Brains at rest generate dynamical activity that is highly structured in space and time. We suggest that spontaneous activity, as in rest or dreaming, underlies top-down dynamics of generative models. During active tasks, generative models provide top-down predictive signals for perception, cognition, and action. When the brain is at rest and stimuli are weak or absent, top-down dynamics optimize the generative models for future interactions by maximizing the entropy of explanations and minimizing model complexity. Spontaneous fluctuations of correlated activity within and across brain regions may reflect transitions between ‘generic priors’ of the generative model: low dimensional latent variables and connectivity patterns of the most common perceptual, motor, cognitive, and interoceptive states. Even at rest, brains are proactive and predictive.

休息时的大脑会产生在空间和时间上高度结构化的动态活动。我们认为，自发活动，如休息或做梦，是生成模型自上而下动态的基础。在主动任务期间，生成模型为感知、认知和行动提供自上而下的预测信号。当大脑处于休息状态且刺激较弱或不存在时，自上而下的动力学通过最大化解释熵和最小化模型复杂性来优化未来交互的生成模型。大脑区域内和大脑区域之间相关活动的自发波动可能反映了生成模型的“一般先验”之间的转变：低维潜在变量和最常见的知觉、运动、认知和内感受状态的连接模式。即使在休息时，大脑也具有主动性和预测性。