Multimodal 3D Mouse Brain Atlas Framework with the Skull-Derived Coordinate System.

Area of Science:

• Neuroscience
• Biomedical Imaging
• Computational Biology

Background:

• Magnetic resonance imaging (MRI) and light-sheet fluorescence microscopy (LSFM) offer non-disruptive 3D whole mouse brain imaging.
• Combining MRI and LSFM data is valuable for neuroscience, disease progression, and drug efficacy studies.
• Current atlas mapping methods struggle to accurately translate LSFM data to MRI templates due to tissue clearing artifacts and large datasets.

Purpose of the Study:

• To develop a bidirectional multimodal atlas framework for accurate and fast translation of LSFM and MRI mouse brain data.
• To integrate complementary information from both imaging modalities for comprehensive neuroscience analysis.
• To address the unmet need for tools facilitating LSFM data registration to in vivo, non-distorted templates.

Main Methods:

• Developed a bidirectional multimodal atlas framework incorporating MRI and LSFM brain templates.
• Utilized region delineations from the Allen's Common Coordinate Framework.
• Implemented a skull-derived stereotaxic coordinate system for spatial referencing.
• Created algorithms for bidirectional transformation of imaging data between MR and LSFM (iDISCO cleared) modalities.

Main Results:

• Successfully created a multimodal atlas framework with integrated templates and coordinate systems.
• Developed algorithms enabling bidirectional data transformation between MRI and LSFM datasets.
• Facilitated the assignment of in vivo coordinates across different brain templates, improving data comparability.

Conclusions:

• The developed framework enables fast and accurate translation of LSFM cleared brains to in vivo MRI templates.
• This tool enhances quantitative analysis by allowing seamless integration of data from complementary imaging modalities.
• The framework supports advanced neuroscience research by improving cross-modal data interpretation and spatial referencing.