Emergence of persistent networks in long-term intracranial EEG recordings.
Emergence of persistent networks in long-term intracranial EEG recordings.
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DOI：
10.1523/jneurosci.2287-11.2011
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发表时间：
2011-11-02
期刊：
影响因子：
--
通讯作者：
Cash SS
中科院分区：
文献类型：
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作者：
Kramer MA;Eden UT;Lepage KQ;Kolaczyk ED;Bianchi MT;Cash SS
在过去的二十年里，分析神经结构之间的网络关系的能力的增强为我们提供了对大脑功能的新见解。然而，大多数网络方法侧重于大脑物理或统计连接的静态表示。很少有研究研究大脑功能网络是如何在漫长的连续时间内自发进化的。为了解决这个问题，我们研究了从连续的长期皮层脑电(ECoG)记录中推导出的功能连接网络。对于6个人类患者群体，我们识别形成频带依赖网络模板的连接的持久模式，以及频繁且一起出现的一组核心连接。这些结构是健壮的，出现在短暂的时间间隔(~100秒)中，与认知状态无关。这些结果表明，存在一个亚稳态的、依赖于频带的大脑连接支架，从这个支架上，瞬时活动出现和消退。
Over the past two decades, the increased ability to analyze network relationships among neural structures has provided novel insights into brain function. Most network approaches, however, focus on static representations of the brain's physical or statistical connectivity. Few studies have examined how brain functional networks evolve spontaneously over long epochs of continuous time. To address this we examine functional connectivity networks deduced from continuous long-term electrocorticogram (ECoG) recordings. For a population of 6 human patients, we identify a persistent pattern of connections that form a frequency-band dependent network template, and a set of core connections that appear frequently and together. These structures are robust, emerging from brief time intervals (~100s) regardless of cognitive state. These results suggest that a metastable, frequency-band dependent scaffold of brain connectivity exists from which transient activity emerges and recedes.