The effects of working memory training on functional brain network efficiency

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• 作者：Nicolas Langer ; Claudia C. von Bastian ; Helen Wirz ; Klaus Oberauer ; Lutz J?ncke
• 关键词：EEG ; Functional connectivity ; Resting state ; Small-world networks ; Working memory training study
• 刊名：Cortex
• 出版年：2013
• 出版时间：October, 2013
• 年：2013
• 卷：49
• 期：9
• 页码：2424-2438
• 全文大小：2108 K

文摘

The human brain is a highly interconnected network. Recent studies have shown that the functional and anatomical features of this network are organized in an efficient small-world manner that confers high efficiency of information processing at relatively low connection cost. However, it has been unclear how the architecture of functional brain networks is related to performance in working memory (WM) tasks and if these networks can be modified by WM training. Therefore, we conducted a double-blind training study enrolling 66 young adults. Half of the subjects practiced three WM tasks and were compared to an active control group practicing three tasks with low WM demand. High-density resting-state electroencephalography (EEG) was recorded before and after training to analyze graph-theoretical functional network characteristics at an intracortical level. WM performance was uniquely correlated with power in the theta frequency, and theta power was increased by WM training. Moreover, the better a person's WM performance, the more their network exhibited small-world topology. WM training shifted network characteristics in the direction of high performers, showing increased small-worldness within a distributed fronto-parietal network. Taken together, this is the first longitudinal study that provides evidence for the plasticity of the functional brain network underlying WM.