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Mengxia Yu, Yiying Song, Jia Liu; Global network reorganization induced by short-term visual association learning. Journal of Vision 2018;18(10):758. doi: 10.1167/18.10.758.
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It has been proposed that visual learning is reflected not only by a change of neural activity in visual cortex, but also by a global reorganization of distributed brain networks involving both high- and low-level regions. Here, we used connectivity pattern similarity approach to assess global network reorganization across the whole brain induced by short-term visual association learning. Subjects were trained to associate a set of artificial line-drawing objects with English letters. After 3 days of association training, subjects went through functional magnetic resonance imaging scanning in which they performed a one-back task on trained stimuli, untrained stimuli, English words, and Chinese characters. We calculated pairwise functional connectivity (FC) between 189 nodes belonging to ten networks across the brain for each condition. We found that training modulated global FC pattern when viewing the trained objects, rendering it more similar to the FC pattern when viewing English words compared with untrained objects. Notably, the FC between low-level visual and sensory networks and high-level attention and cognitive control networks showed higher similarity between English words and trained stimuli than untrained stimuli, implicating interaction between bottom-up and top-down processes during learning. Furthermore, the global FC pattern when viewing the trained objects also became more similar to that when viewing Chinese characters after learning, suggesting a language-general effect. In sum, our study revealed global brain network reorganization induced by short-term visual learning and suggested interaction between low-level and high-level networks during learning.
Meeting abstract presented at VSS 2018
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