基于TB级海量数据的全脑神经环路三维分析与可视化方法研究

Emotion and memory are both key cognitive brain functions, which allow the individuals to adapt to and evolve with a constantly changing environment. Although it is well known that neuronal circuits are the biological basis of emotion and memory, there still has no complete figure of the networks in a whole brain. The advanced micro-optical sectioning tomography has enabled the feasibility of single cell resolution level imaging in a whole mouse brain, however, the critical information of neuronal circuits has been hidden in the TB size image dataset. The ongoing software and hardware of conventional computer cannot handle the TB size big data. This issue is really the bottleneck and challenge for neuronal circuits study. To this end, this project aims to develop a comprehensive solution for whole mouse brain 3D analysis and visualization with TB size image dataset. The tasks include fast preprocessing method for huge micro-imaging dataset, nonlinear 3D registration for whole brain space, efficient segmentation for brain structures, visualization for the mouse brain atlas. This project would firstly construct and visualize a 3D digital high resolution neuronal circuits connectivity atlas for emotion and memory studies. The establishing methods will provide a scientific paradigm and helpful tool for the neuronal circuits studies on the mechanisms and pathogenesis relevant to emotion and memory with big data of neuroimaging.

情感和记忆是大脑认知功能的重要内容，也是个体藉以适应环境和生存发展的基础。神经环路是情感和记忆等功能实现的生物学基础，但目前尚无全脑范围内情感和记忆神经环路的完整描述。先进的显微光学切片断层成像技术提供了小鼠全脑范围单细胞分辨研究的契机；但是也带来TB级大数据的挑战：现有计算机软、硬件无法有效从TB级数据中提取神经环路的关键信息。针对于此，本项目旨在发展面向TB级海量数据的全脑三维分析和可视化方法。主要包括：海量显微图集的快速预处理方法、三维数据集的非线性空间配准方法、脑结构信息的准确分割方法、脑图谱的三维可视化方法。本项目将首次构建和可视化地展示情感和记忆相关的神经元环路。面向神经成像大数据，本项目将示范性地为情感和记忆神经环路研究提供有力工具。

情感和记忆是大脑认知功能的重要内容，也是个体藉以适应环境和生存发展的基础。神经环路是情感和记忆等功能实现的生物学基础，但目前尚无全脑范围内情感和记忆神经环路的完整描述。先进的显微光学切片断层成像技术提供了小鼠全脑范围单细胞分辨研究的契机；但是也带来TB级大数据的挑战：现有计算机软、硬件无法有效从TB级数据中提取神经环路的关键信息。针对于此，本项目发展了面向TB级海量数据的全脑三维分析和可视化方法。主要包括：海量显微图集的快速预处理方法、三维数据集的非线性空间配准方法、脑结构信息的准确分割方法、脑图谱的三维可视化方法等。本项目将首次构建和可视化地展示了全脑范围内的神经元环路，初步绘制了特定类型神经元全脑分布图谱。面向神经成像大数据，本项目将示范性地为情感和记忆神经环路研究提供有力工具。