Resting state networks and memory consolidation

静息态网络和记忆巩固

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Abstract

Despite their name, resting state networks (RSNs) provide a clear indication that the human brain may be hard-working. Unlike the cardiac and respiratory systems, which greatly reduce their rate of function during periods of inactivity, the human brain may have additional responsibilities during rest. One particularly intriguing function performed by the resting brain is the consolidation of recent learned information, which is known to take place over a period of several hours after learning. We recently reported that resting state brain activity is modulated by recent learning. We measured the brain activity using functional MRI during periods of rest that preceded and followed learning of a sensorimotor task, and found a network of brain areas that changed their resting activity. These areas are known to be involved in the acquisition and memory of such sensorimotor tasks. Furthermore, the changes were specific to a task that required learning, and were not found after motor performance without learning. Here we discuss the implications and possible extensions of this work and its relevance to the study of memory consolidation.

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