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原文連結
論文資訊
- 類型：已發表論文
- 日期：2020-05-22
摘要
A diverse set of white matter connections supports seamless transitions between 認知 states. However, it remains unclear how these connections guide the temporal progression of large-scale 大腦 activity patterns in different 認知 states. Here, we analyze the 大腦’s trajectories across a set of single time point activity patterns from functional magnetic resonance imaging data acquired during the resting state and an n-back working memory task. We find that specific temporal sequences of 大腦 activity are modulated by 認知 load, associated with age, and related to task performance. Using 擴散-weighted imaging acquired from the same subjects, we apply tools from 網絡 control theory to show that linear spread of activity along white matter connections constrains the probabilities of these sequences at rest,
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