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活跃的CA3神经网络的亚稳定性。

Metastability of active CA3 networks.

作者信息

Sasaki Takuya, Matsuki Norio, Ikegaya Yuji

机构信息

Laboratory of Chemical Pharmacology, Graduate School of Pharmaceutical Sciences, University of Tokyo, Tokyo 113-0033, Japan.

出版信息

J Neurosci. 2007 Jan 17;27(3):517-28. doi: 10.1523/JNEUROSCI.4514-06.2007.

Abstract

The brain is spontaneously active even in the absence of external input. This ongoing background activity impacts neural information processing. We used functional multineuron calcium imaging (fMCI) to analyze the net structure of spontaneous CA3 network activity in hippocampal slice cultures loaded with Oregon Green 488 BAPTA-1 using a spinning disk confocal microscope (10-30 frames/s). Principal component analysis revealed that network states, defined by active cell ensembles, were stable but heterogenous and discrete. These states were stabilized through synaptic activity and maintained against external perturbations. A few discrete states emerged during our observation period of up to 30 min. Networks tended to stay in a single state for tens of seconds and then suddenly jump to a new state. After a state transition, the old state was rarely, if ever, revisited by the network during our observation period. This temporal profile of state transitions could not be simulated by a hidden Markov model, indicating that the state dynamics is nonrandomly organized. Within each state, the pattern of network activity tended to stabilize in a specific configuration. Neither maintenance nor transition of the network states required NMDA receptor activity. These findings suggest that the network states are metastable, rather than multistable, and might be governed by local attractor-like dynamics. The fMCI data analyzed here are available at http://hippocampus.jp/data/

摘要

即使在没有外部输入的情况下,大脑也会自发活动。这种持续的背景活动会影响神经信息处理。我们使用功能性多神经元钙成像(fMCI),通过旋转盘共聚焦显微镜(10 - 30帧/秒)分析加载了 Oregon Green 488 BAPTA - 1的海马切片培养物中自发CA3网络活动的网络结构。主成分分析表明,由活跃细胞群定义的网络状态是稳定的,但具有异质性和离散性。这些状态通过突触活动得以稳定,并能抵御外部干扰。在长达30分钟的观察期内出现了一些离散状态。网络倾向于在单一状态下保持数十秒,然后突然跃迁至新状态。在状态转换后,在我们的观察期内,网络很少(如果有的话)会重新回到旧状态。这种状态转换的时间特征无法用隐马尔可夫模型模拟,这表明状态动态是由非随机组织的。在每个状态内,网络活动模式倾向于稳定在特定配置。网络状态的维持和转换都不需要NMDA受体活动。这些发现表明,网络状态是亚稳态而非多稳态,并且可能受局部吸引子样动力学支配。此处分析的fMCI数据可在http://hippocampus.jp/data/获取

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