Automatic navigation system for the mouse brain.

Area of Science:

• Neuroscience
• Bioinformatics
• Microscopy

Background:

• Accurate identification of brain regions in histologic mouse brain sections is crucial for neurogenomics, transcriptomics, proteomics, and connectomics.
• Current methods are susceptible to observer error and bias, hindering reliable data acquisition.

Purpose of the Study:

• To introduce NeuroInfo, a novel automated brain navigation system designed to accurately delineate brain regions in histologic mouse brain sections.
• To overcome the limitations of manual identification and reduce observer bias in microscopic analysis of mouse brains.

Main Methods:

• NeuroInfo automatically registers digital images of experimental mouse brain sections with a 3D digital mouse brain atlas (based on Allen Mouse Brain Common Coordinate Framework v3).
• It retrieves and superimposes graphical region delineations and annotations onto the digital image for real-time visualization.
• The system utilizes a global positioning system (GPS)-like principle for navigation through complex brain anatomy.

Main Results:

• NeuroInfo demonstrated remarkable accuracy in delineating large and dorsal brain regions.
• The system's performance was consistent across both fluorescence and bright-field microscopy images.
• Registration and delineation of experimental mouse brain sections with the 3D atlas were achieved efficiently, often within a minute.

Conclusions:

• NeuroInfo provides an intuitive and efficient tool for researchers to accurately identify specific brain regions in histologic mouse brain sections.
• This novel technology significantly enhances the reliability and efficiency of neuroscientific studies relying on precise anatomical localization.
• NeuroInfo addresses a long-standing challenge in microscopic analysis, improving the quality of data for various 'omics' research fields.