It has been proposed that visual learning is accomplished not only by neural plasticity in the visual cortex, but also by complex interactions between bottom-up and top-down processes that may induce global network reorganization. Here, we applied a multivariate analysis to functional connectivity (FC) patterns across the brain to investigate how visual association learning was achieved through large-scale network reorganization. Participants were trained to associate a set of artificial line-drawing objects with English letters. After three consecutive days of training, participants underwent a functional magnetic resonance imaging scan in which they were presented with the trained stimuli, untrained stimuli, and English words. By calculating pairwise FC between 189 nodes of 10 well-established networks across the brain, we found that the visual association learning induced changes in the global FC pattern when viewing the trained stimuli, rendering it more similar to the FC pattern when viewing English words. Critically, the learning-induced global FC pattern differences were mainly driven by the FC related to the high-level networks involved in attention and cognitive control, suggesting the modification of top-down processes during learning. In sum, our study provides one of the first evidence revealing global network reorganization induced by visual learning and sheds new light on the network mechanisms of top-down influences in learning.

已经提出视觉学习不仅通过视觉皮层中的神经可塑性来实现，而且还通过自下而上和自上而下的过程之间的复杂相互作用来实现，这可能引起全局网络重组。在这里，我们对大脑的功能连接（FC）模式进行了多元分析，以研究如何通过大规模网络重组实现视觉联想学习。培训了参与者以使一组人工画线对象与英文字母相关联。经过连续三天的训练，参与者进行了功能磁共振成像扫描，并向他们展示了经过训练的刺激，未经训练的刺激和英语单词。通过计算整个大脑10个完善网络的189个节点之间的成对FC，我们发现，视觉联想学习在查看训练后的刺激时会导致整体FC模式发生变化，从而使其与查看英语单词时的FC模式更加相似。至关重要的是，学习引起的全球FC模式差异主要是由与注意力和认知控制所涉及的高级网络相关的FC驱动的，这表明学习过程中自上而下的过程发生了变化。总之，我们的研究提供了第一个证据，揭示了视觉学习引起的全球网络重组，并为自上而下的学习影响网络机制提供了新的思路。学习引起的全球FC模式差异主要由与注意力和认知控制所涉及的高级网络相关的FC驱动，表明学习过程中自顶向下过程的修改。总之，我们的研究提供了第一个证据，揭示了视觉学习引起的全球网络重组，并为自上而下的学习影响网络机制提供了新的思路。学习引起的全球FC模式差异主要由与注意力和认知控制所涉及的高级网络相关的FC驱动，表明学习过程中自顶向下过程的修改。总之，我们的研究提供了第一个证据，揭示了视觉学习引起的全球网络重组，并为自上而下的学习影响网络机制提供了新的思路。