Mesina Lilia, Wilber Aaron A, Clark Benjamin J, Dube Sutherland, Demecha Alexis J, Stark Craig E L, McNaughton Bruce L
Canadian Centre for Behavioural Neuroscience, The University of Lethbridge, Lethbridge, AB, Canada.
Canadian Centre for Behavioural Neuroscience, The University of Lethbridge, Lethbridge, AB, Canada; Department of Neurobiology and Behavior, University of California, Irvine, CA, USA.
J Neurosci Methods. 2016 Jun 15;266:151-60. doi: 10.1016/j.jneumeth.2016.03.021. Epub 2016 Mar 31.
Understanding the neurobiological basis of cognition and behavior, and disruptions to these processes following injury and disease, requires a large-scale assessment of neural populations, and knowledge of their patterns of connectivity.
We present an analysis platform for large-scale investigation of functional and neuroanatomical connectivity in rodents. Retrograde tracers were injected and in a subset of animals behavioral tests to drive immediate-early gene expression were administered. This approach allows users to perform whole-brain assessment of function and connection in a semi-automated quantitative manner. Brains were cut in the coronal plane, and an image of the block face was acquired. Wide-field fluorescent scans of whole sections were acquired and analyzed using Matlab software.
The toolkit utilized open-source and custom platforms to accommodate a largely automated analysis pipeline in which neuronal boundaries are automatically segmented, the position of segmented neurons are co-registered with a corresponding image acquired during sectioning, and a 3-D representation of neural tracer (and other products) throughout the entire brain is generated.
Current whole brain connectivity measures primarily target mice and use anterograde tracers. Our focus on segmented units of interest (e.g., NeuN labeled neurons) and restricting measures to these units produces a flexible platform for a variety of whole brain analyses (measuring activation, connectivity, markers of disease, etc.).
This open-source toolkit allows an investigator to visualize and quantify whole brain data in 3-D, and additionally provides a framework that can be rapidly integrated with user-specific analyses and methodologies.
了解认知和行为的神经生物学基础，以及损伤和疾病后这些过程的破坏情况，需要对神经群体进行大规模评估，并了解它们的连接模式。
我们提出了一个用于大规模研究啮齿动物功能和神经解剖连接性的分析平台。注射逆行示踪剂，并对一部分动物进行行为测试以驱动即刻早期基因表达。这种方法允许用户以半自动定量方式对全脑功能和连接进行评估。将大脑切成冠状平面，并获取块面图像。使用Matlab软件获取并分析整个切片的宽场荧光扫描图像。
该工具包利用开源和自定义平台来适应一个高度自动化的分析流程，在这个流程中，神经元边界会自动分割，分割后的神经元位置会与切片过程中获取的相应图像进行配准，并生成整个大脑中神经示踪剂（及其他产物）的三维表示。
目前的全脑连接性测量主要针对小鼠并使用顺行示踪剂。我们专注于感兴趣的分割单元（例如NeuN标记的神经元）并将测量限制在这些单元上，从而为各种全脑分析（测量激活、连接性、疾病标志物等）提供了一个灵活的平台。
这个开源工具包允许研究人员以三维方式可视化和量化全脑数据，此外还提供了一个可以快速与用户特定分析和方法集成的框架。
