Yi Hu, Zhang Xiaofan, Bai Wenwen, Liu Tiaotiao, Tian Xin
School of Biomedical Engineering, Tianjin Medical University, Tianjin, 300070, China.
School of Biomedical Engineering, Tianjin Medical University, Tianjin, 300070, China.
Behav Brain Res. 2015 Aug 1;289:84-91. doi: 10.1016/j.bbr.2015.04.042. Epub 2015 Apr 28.
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.
工作记忆是指一个用于临时存储和处理信息的系统。先前的研究表明，局部场电位（LFP）、尖峰信号及其协同作用为工作记忆提供了潜在机制。常用的LFP-尖峰信号协同分析方法仅关注这两种模态信号，从多通道数据中分离每个通道，忽略了大脑网络的整体性。因此，我们研究了LFP网络和尖峰网络之间的协同作用，以更好地理解工作记忆。在Y迷宫工作记忆任务中，通过微电极阵列同时记录大鼠前额叶皮层的多通道LFP和尖峰信号。分别采用定向传递函数（DTF）和最大似然估计（MLE）来估计LFP网络和尖峰网络中的功能连接。然后通过典型相关分析（CCA）对两个网络之间的协同作用进行量化。结果表明，在工作记忆任务期间，典型相关（CC）发生变化。CC曲线在选择点之前达到峰值，表明LFP网络和尖峰网络之间的协同作用大大增强。工作记忆中的CC值显著高于试验间隔期。我们的结果表明，LFP网络和尖峰网络之间增强的典型相关性可能为工作记忆提供一种潜在的网络整合机制。
