The dynamical balance of the brain at rest.

The dynamical balance of the brain at rest.
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DOI:
10.1177/1073858409354384
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发表时间:
2011-02
期刊:
The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry
影响因子:
--
通讯作者:
Corbetta M
Corbetta M
中科院分区:
其他
文献类型:
--
作者:
Deco G;Corbetta M

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我们回顾相关证据表明,大脑中自发的(即非刺激驱动或任务驱动的)活动并非噪声,而是在大规模系统层面有序地组织在一系列功能网络中,这些网络始终保持高度的一致性。这些自发活动相关性网络或静息态网络(RSN)与潜在的解剖连接密切相关,但其拓扑结构也受到先前任务激活历史的调控。网络一致性并不依赖于隐蔽的认知活动,但其强度和完整性与行为表现相关。一些静息态网络在休息和任务期间在功能上被组织为动态竞争的系统。计算研究表明,其中一种动态,即网络之间的反相关性,取决于不同多稳态簇同步状态之间由噪声驱动的转换。这些多稳态是由于被建模为耦合振子系统的区域之间的传输延迟而出现的。大规模系统动力学有助于使不同的功能子网络处于高度竞争状态,这种竞争状态可以通过感觉或内部信号的微小调节而稳定和激发。
We review evidence that spontaneous, i.e. not stimulus- or task-driven, activity in the brain is not noise, but orderly organized at the level of large scale systems in a series of functional networks that maintain at all times a high level of coherence. These networks of spontaneous activity correlation or resting state networks (RSN) are closely related to the underlying anatomical connectivity, but their topography is also gated by the history of prior task activation. Network coherence does not depend on covert cognitive activity, but its strength and integrity relates to behavioral performance. Some RSN are functionally organized as dynamically competing systems both at rest and during tasks. Computational studies show that one of such dynamics, the anti-correlation between networks, depends on noise driven transitions between different multi-stable cluster synchronization states. These multi-stable states emerge because of transmission delays between regions that are modeled as coupled oscillators systems. Large-scale systems dynamics are useful for keeping different functional sub-networks in a state of heightened competition, which can be stabilized and fired by even small modulations of either sensory or internal signals.
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