SMART: An Open-Source Extension of WholeBrain for Intact Mouse Brain Registration and Segmentation

Mapping immediate early gene (IEG) expression across intact mouse brains allows for unbiased identification of brain-wide activity patterns underlying complex behaviors. Accurate registration of sample brains to a common anatomic reference is critical for precise assignment of IEG-positive (active) neurons to known brain regions of interest (ROIs). While existing automated voxel-based registration methods provide a high-throughput solution, they require substantial computing power, can be difficult to implement and fail when brains are damaged or only partially imaged. Additionally, it is challenging to cross-validate these approaches or compare them to any preexisting literature based on serial coronal sectioning. Here, we present the open-source R package SMART (Semi-Manual Alignment to Reference Templates) that extends the WholeBrain R package framework to automated segmentation and semi-automated registration of intact mouse brain light-sheet fluorescence microscopy (LSFM) datasets. The SMART package was created for novice programmers and introduces a streamlined pipeline for aligning, registering, and segmenting LSFM volumetric datasets across the anterior-posterior (AP) axis, using a simple choice game and interactive menus. SMART provides the flexibility to register whole brains, partial brains or discrete user-chosen images, and is fully compatible with traditional sectioned coronal slice-based analyses. We demonstrate SMART's core functions using example datasets and provide step-by-step video tutorials for installation and implementation of the package. We also present a modified iDISCO1 tissue clearing procedure for uniform immunohistochemical labeling of the activity marker Fos across intact mouse brains. The SMART pipeline, in conjunction with the modified iDISCO1 Fos procedure, is ideally suited for examination and orthogonal cross-validation of brain-wide neuronal activation datasets. Significance Statement Immediate early genes (IEG) are invaluable for revealing the structure-activity-function relationships of different brain regions. By leveraging the activity-dependent expression of IEGs (e.g., Fos), brain activity in mice can be associated with recent experiences. The combination of advances in tissue clearing, immunolabelling, and volumetric fluorescent imaging provide the methodology to extract brain-wide imaging datasets of IEG expression. Automated pipelines can analyze these datasets, but often exclude accessible validation checkpoints. There is a need for computational tools that streamline analysis of such datasets and include human checkpoints for orthogonal cross-validation of automated approaches. Addressing this gap, we introduce SMART, an open-source user-friendly R package, which builds on existing registration and automated cell counting methods, to facilitate whole-brain IEG mapping in mice.

Automated summary

This study introduces a user-friendly R package called SMART for automated segmentation and semi-automated registration of LSFM datasets in intact mouse brains. SMART is designed for novice programmers and offers flexible registration and segmentation capabilities that are compatible with traditional sectioned coronal slice-based analyses. The study also presents a modified iDISCO1 tissue clearing procedure for immunohistochemical labeling in intact mouse brains.