BIFROST: A method for registering diverse imaging datasets

The heterogeneity of brain imaging methods in neuroscience provides rich data that cannot be captured by a single technique, and our interpretations benefit from approaches that enable easy comparison both within and across different data types. For example, comparing brain-wide neural dynamics across experiments and aligning such data to anatomical resources, such as gene expression patterns or connectomes, requires precise alignment to a common set of anatomical coordinates. However, this is challenging because registering in vivo functional imaging data to ex vivo reference atlases requires accommodating differences in imaging modality, microscope specification, and sample preparation. We overcome these challenges in Drosophila by building an in vivo reference atlas from multiphoton-imaged brains, called the Functional Drosophila Atlas (FDA). We then develop a two-step pipeline, BrIdge For Registering Over Statistical Templates (BIFROST), for transforming neural imaging data into thi..., , , # BIFROST: A method for registering diverse imaging datasets

[https://doi.org/10.5061/dryad.8pk0p2nx1](https://doi.org/10.5061/dryad.8pk0p2nx1)

This repository provides four things:

* the Functional Drosophila Atlas (FDA)
* bridging transformations between the FDA and JRC 2018
* the code that was used to generate the FDA and recapitulated ANTs format transformations
* a replication dataset

## Description of the data and file structure

### FDA

Three closely related but distinct FDA images are provided, a thresholded version, an unthresholded version and an (unthresholded) version that complies strictly with the NIfTI-1 specification. A bridging transformation is available only for the thresholded version. The NIfTI-1 compliant and unthresholded versions share the same raster data. The thresholded and unthresholded versions share the same metadata but have slightly different raster data. The NIfTI compliant image follows the NIfTI convention for the spatial coordinates of +x...

神经科学领域中脑成像技术的异质性带来了单一技术无法囊括的丰富数据，而我们的数据分析与解读可得益于能够轻松实现不同数据类型内部及跨类型比较的方法。例如，在不同实验间对比全脑神经动态，并将此类数据对齐至基因表达模式、连接组（connectome）等解剖学资源时，需要将数据精确匹配至一套通用解剖坐标。然而，这一过程颇具挑战：将活体功能成像数据配准至离体参考图谱时，需要适配成像模态、显微镜规格与样本制备方式之间的差异。我们以果蝇为研究对象，通过构建基于多光子成像大脑的活体参考图谱——功能果蝇图谱（Functional Drosophila Atlas, FDA），攻克了上述挑战。随后，我们开发了两步式流程——统计模板配准桥接流程（BrIdge For Registering Over Statistical Templates, BIFROST），可将神经成像数据转换为……
# BIFROST：多样化成像数据集配准方法

[https://doi.org/10.5061/dryad.8pk0p2nx1](https://doi.org/10.5061/dryad.8pk0p2nx1)

本仓库提供四项核心内容：
* 功能果蝇图谱（FDA）
* FDA与JRC 2018之间的桥接变换
* 用于生成FDA并复现ANTs格式变换的代码
* 复现数据集

## 数据与文件结构说明
### 功能果蝇图谱（FDA）
本次提供了三组紧密相关但各具差异的FDA图像：阈值化版本、非阈值化版本，以及严格符合NIfTI-1规范的非阈值化版本。仅阈值化版本提供桥接变换。符合NIfTI-1规范的版本与非阈值化版本拥有相同的光栅数据；阈值化版本与非阈值化版本共享相同的元数据，但光栅数据存在细微差异。符合NIfTI规范的图像遵循NIfTI关于+x轴空间坐标的约定……