Strains of mice, through breeding or the disruption of normal genetic pathways, are widely used to model human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison. We have developed a digital atlas of the adult C57BL/6J mouse brain as a comprehensive framework for storing and accessing the myriad types of information about the mouse brain. Our implementation was constructed using several different imaging techniques: magnetic resonance microscopy, blockface imaging, classical histology and immunohistochemistry. Along with raw and annotated images, it contains database management systems and a set of tools for comparing information from different techniques. The framework allows facile correlation of results from different animals, investigators or laboratories by establishing a canonical representation of the mouse brain and providing the tools for the insertion of independent data into the same space as the atlas. This tool will aid in managing the increasingly complex and voluminous amounts of information about the mammalian brain. It provides a framework that encompasses genetic information in the context of anatomical imaging and holds tremendous promise for producing new insights into the relationship between genotype and phenotype. We describe a suite of tools that enables the independent entry of other types of data, facile retrieval of information and straightforward display of images. Thus, the atlas becomes a framework for managing complex genetic and epigenetic information about the mouse brain. The atlas and associated tools may be accessed at

A standard atlas space with stereotaxic co-ordinates for the postnatal day 0 (P0) C57BL/6J mouse brain was constructed from the average of eight individual co-registered MR image volumes. Accuracy of registration and morphometric variations in structures between subjects were analyzed statistically. We also applied this atlas coordinate system to data acquired using different imaging protocols as well as to a high-resolution histological atlas obtained from separate animals. Mapping accuracy in the atlas space was examined to determine the applicability of this atlas framework. The results show that the atlas space defined here provides a stable framework for image registration for P0 normal mouse brains. With an appropriate feature-based co-registration strategy, the probability atlas can also provide an accurate anatomical map for images acquired using invasive imaging methods. The atlas templates and the probability map of the anatomical labels are available at http://www.loni.ucla.edu/MAP/ .

Digital brain atlases are useful as references, analytical tools, and as a data integration framework. As a result, they and their supporting tools are being recognized as potentially useful resources in the movement toward data sharing. Several projects are connecting infrastructure to these tools which facilitate sharing, managing, and retrieving data of different types, scale, and even location. With these in place, we have the ability to combine, analyze, and interpret these data in a manner not previously possible, opening the door to examine issues in new and exciting ways, and potentially leading to speedier discovery of answers as well as new questions about the brain. Here we discuss recent efforts in the use of digital mouse atlases for data sharing.

Summary: Naturally occurring mutants and genetically manipulated strains of mice are widely used to model a variety of human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison and to facilitate the integration of anatomic, genetic, and physiologic observations from multiple subjects and experiments. We have developed digital atlases of the C57BL/6J mouse brain (adult and neonate) as comprehensive frameworks for storing and accessing the myriad types of information about the mouse brain. Along with raw and annotated images, these contain database management systems and a set of tools for comparing information from different techniques and different animals. Each atlas establishes a canonical representation of the mouse brain and provides the tools for the manipulation and analysis of new data. We describe both these atlases and discuss how they may be put to use in organizing and analyzing data from mouse models of epilepsy.

Over the past decade, the use of informatics to solve complex neuroscientific problems has increased dramatically. Many of these research endeavors involve examining large amounts of imaging, behavioral, genetic, neurobiological, and neuropsychiatric data. Superimposing, processing, visualizing, or interpreting such a complex cohort of datasets frequently becomes a challenge. We developed a new software environment that allows investigators to integrate multimodal imaging data, hierarchical brain ontology systems, on-line genetic and phylogenic databases, and 3D virtual data reconstruction models. The Laboratory of Neuro Imaging visualization environment (LONI Viz) consists of the following components: a sectional viewer for imaging data, an interactive 3D display for surface and volume rendering of imaging data, a brain ontology viewer, and an external database query system. The synchronization of all components according to stereotaxic coordinates, region name, hierarchical ontology, and genetic labels is achieved via a comprehensive BrainMapper functionality, which directly maps between position, structure name, database, and functional connectivity information. This environment is freely available, portable, and extensible, and may prove very useful for neurobiologists, neurogenetisists, brain mappers, and for other clinical, pedagogical, and research endeavors.