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通过分析伽马波估计大脑区域之间的功能连接。

Functional connectivity between brain areas estimated by analysis of gamma waves.

机构信息

Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

出版信息

J Neurosci Methods. 2013 Apr 15;214(2):184-91. doi: 10.1016/j.jneumeth.2013.01.007. Epub 2013 Jan 31.

Abstract

The goal of this study is to investigate functional connectivity between different brain regions by analyzing the temporal relationship of the maxima of gamma waves recorded in multiple brain areas. Local field potentials were recorded from motor cortex, hippocampus, entorhinal cortex and piriform cortex of rats. Gamma activity was filtered and separated into two bands; high (65-90Hz) and low (30-55Hz) gamma. Maxima for gamma activity waves were detected and functional connectivity between different brain regions was determined using Shannon entropy for perievent histograms for each pair channels. Significant Shannon entropy values were reported as connectivity factors. We defined a connectivity matrix based the connectivity factors between different regions. We found that maxima of low and high frequency gamma occur in strong temporal relationship between some brain areas, indicating the existence of functional connections between these areas. The spatial pattern of functional connections between brain areas was different for slow wave sleep and waking states. However for each behavioral state in the same animal the pattern of functional connections was stable over time within 30min of continuous analysis and over a 5 day period. With the same electrode montage the pattern of functional connectivity varied from one subject to another. Analysis of the temporal relationship of maxima of gamma waves between various brain areas could be a useful tool for investigation of functional connections between these brain areas. This approach could be applied for analysis of functional alterations occurring in these connections during different behavioral tasks and during processes related to learning and memory. The specificity in the connectivity pattern from one subject to another can be explained by the existence of unique functional networks for each subject.

摘要

本研究旨在通过分析记录于多个脑区的伽马波最大值之间的时间关系,研究不同脑区之间的功能连接。研究记录了大鼠运动皮层、海马体、内嗅皮层和梨状皮层的局部场电位。伽马活动被滤波并分为两个频段;高(65-90Hz)和低(30-55Hz)伽马。检测伽马活动波的最大值,并使用每个通道对的事件直方图的香农熵来确定不同脑区之间的功能连接。报告显著的香农熵值作为连接因子。我们根据不同区域之间的连接因子定义了一个连接矩阵。我们发现,低频和高频伽马的最大值在一些脑区之间存在强烈的时间关系,表明这些区域之间存在功能连接。在慢波睡眠和清醒状态下,脑区之间的功能连接的空间模式不同。然而,对于同一动物的每种行为状态,在连续 30 分钟的分析和 5 天的时间内,功能连接的模式是稳定的。在相同的电极布局下,功能连接的模式因个体而异。分析不同脑区之间伽马波最大值之间的时间关系可能是研究这些脑区之间功能连接的有用工具。这种方法可以应用于分析在不同行为任务和与学习记忆相关的过程中这些连接中发生的功能改变。来自不同个体的连接模式的特异性可以通过为每个个体存在独特的功能网络来解释。

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