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首页> 外文期刊>Behavioural Brain Research: An International Journal >Canonical correlation between LFP network and spike network during working memory task in rat
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Canonical correlation between LFP network and spike network during working memory task in rat

机译:大鼠工作记忆任务中LFP网络与峰值网络之间的典范相关性

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Working memory refers to a system to temporary holding and manipulation of information. Previous studies suggested that local field potentials (LFPs) and spikes as well as their coordination provide potential mechanism of working memory. Popular methods for LFP-spike coordination only focus on the two modality signals, isolating each channel from multi-channel data, ignoring the entirety of the networked brain. Therefore, we investigated the coordination between the LFP network and spike network to achieve a better understanding of working memory. Multi-channel LFPs and spikes were simultaneously recorded in rat prefrontal cortex via microelectrode array during a Y-maze working memory task. Functional connectivity in the LFP network and spike network was respectively estimated by the directed transfer function (DTF) and maximum likelihood estimation (MLE). Then the coordination between the two networks was quantified via canonical correlation analysis (CCA). The results show that the canonical correlation (CC) varied during the working memory task. The CC-curve peaked before the choice point, describing the coordination between LFP network and spike network enhanced greatly. The CC value in working memory showed a significant higher level than inter-trial interval. Our results indicate that the enhanced canonical correlation between the LFP network and spike network may provide a potential network integration mechanism for working memory. (C) 2015 Elsevier B.V. All rights reserved.
机译:工作存储器是指暂时保存和操纵信息的系统。先前的研究表明,局部场电势(LFP)和峰值及其协调提供了工作记忆的潜在机制。 LFP峰值协调的流行方法仅关注两种模式信号,将每个通道与多通道数据隔离开来,而忽略了整个网络大脑。因此,我们调查了LFP网络和峰值网络之间的协调,以更好地了解工作内存。在Y迷宫工作记忆任务期间,通过微电极阵列在大鼠前额叶皮层中同时记录了多通道LFP和峰值。 LFP网络和峰值网络中的功能连通性分别通过定向传递函数(DTF)和最大似然估计(MLE)进行估计。然后,通过规范相关分析(CCA)量化两个网络之间的协调。结果表明,在工作记忆任务期间规范相关性(CC)发生了变化。 CC曲线在选择点之前达到峰值,说明LFP网络和峰值网络之间的协调性大大增强。工作记忆中的CC值显着高于审判间隔。我们的结果表明,LFP网络和峰值网络之间增强的规范相关性可能为工作内存提供潜在的网络集成机制。 (C)2015 Elsevier B.V.保留所有权利。

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