Mesoscale Mapping of Mouse Cortex Reveals Frequency-Dependent Cycling between Distinct Macroscale Functional Modules
Mesoscale Mapping of Mouse Cortex Reveals Frequency-Dependent Cycling between Distinct Macroscale Functional Modules
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DOI：
10.1523/jneurosci.3560-16.2017
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发表时间：
2017-08
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影响因子：
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通讯作者：
M. Vanni;Allen W. Chan;M. Balbi;G. Silasi;T. Murphy
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作者：
M. Vanni;Allen W. Chan;M. Balbi;G. Silasi;T. Murphy
基于小鼠静息状态活动的连接性映射揭示了相关活动的功能基序。然而，模体组织成更大的功能模块，导致半球广泛的时空活动序列的规则是不清楚的。我们探索大脑皮层活动parcellation头部固定，安静清醒的GCaMP6小鼠从两种性别使用介观钙成像。自发皮层活动的频谱分解显示存在两个主导频率模式（1 Hz产生两个较大的共激活区域簇，具有扩大的默认模式网络样后部区域）。我们认为，区域内皮质活动流的明显约束结构可以在未来的努力中被利用，以使神经系统疾病的活动正常化。意义陈述越来越多地，自发活动的功能连接映射被用来揭示大脑的组织。然而，由于大脑在多个空间和时间域中运行，因此有必要对该组织进行更详细的了解。我们在头部固定的清醒小鼠中使用指示剂GCaMP6的体内宽场钙成像来表征不同时空尺度下自发皮质活动的组织。相关性分析定义了存在两到三个超集群的活动，跨越传统定义的功能领域和频率依赖。这项工作有助于确定不同皮层区域在时间和空间上如何相互作用的规则。我们提供了一个必要的框架，为未来的研究，探索疾病模型中的脑回路的功能重组。
Connectivity mapping based on resting-state activity in mice has revealed functional motifs of correlated activity. However, the rules by which motifs organize into larger functional modules that lead to hemisphere wide spatial-temporal activity sequences is not clear. We explore cortical activity parcellation in head-fixed, quiet awake GCaMP6 mice from both sexes by using mesoscopic calcium imaging. Spectral decomposition of spontaneous cortical activity revealed the presence of two dominant frequency modes (1 Hz yielded two larger clusters of coactivated areas with an enlarged default mode network-like posterior region. We suggest that the apparent constrained structure for intra-areal cortical activity flow could be exploited in future efforts to normalize activity in diseases of the nervous system. SIGNIFICANCE STATEMENT Increasingly, functional connectivity mapping of spontaneous activity is being used to reveal the organization of the brain. However, because the brain operates across multiple space and time domains a more detailed understanding of this organization is necessary. We used in vivo wide-field calcium imaging of the indicator GCaMP6 in head-fixed, awake mice to characterize the organization of spontaneous cortical activity at different spatiotemporal scales. Correlation analysis defines the presence of two to three superclusters of activity that span traditionally defined functional territories and were frequency dependent. This work helps define the rules for how different cortical areas interact in time and space. We provide a framework necessary for future studies that explore functional reorganization of brain circuits in disease models.