Total ROI counts of FAA can vary from 1 to more than 1000. This report presents a pipeline to construct a flexible annotation atlas (FAA) for the mouse brain, for which brain structures can be combined or divided objectively using resources by AIBS on gene expression and fiber projection. Indeed, the original AV by AIBS per se is not perfectly suited for MRI analysis because (1) a considerable number of brain structures defined in it are too small or large for MRI analysis, (2) the original AV is single-sided Corresponding brain structures in the right and left brain hemisphere are treated as a single structure, and (3) there is inconsistency between an annotation ontology file and AVs provided by AIBS, leading to destructive nodes (defined in the first section of “ Results” section). Still, reconstruction of ROIs used in these studies is difficult because the original AVs by AIBS are often modified according to each researcher’s necessity without instruction for ROI reconstruction. An increasing number of studies have used the Allen mouse brain atlas for analyzing MRI data 17, 18, 19, 20. Spatial coordinates of three-dimensional volume data at AIBS adopt CCFv3, enabling integration of multimodal resources by AIBS on (1) an anatomical template of the mouse brain (AT), (2) annotation volume (AV), (3) gene expression, and (4) axonal fiber projection. 3 (CCFv3) for the mouse brain in 2015 15, 16. After two earlier editions in 20, AIBS provided a complete version for a common coordinate framework ver. The Allen Institute for Brain Science (AIBS) provides resources related to the brain of C57BL/6J mouse 14. combinations and divisions of ROIs for brain structures were not implemented, leading to inconsistent ROIs among laboratories for MRI in the mouse brain. Such a situation might result from the fact that earlier AVs were fixed, i.e. For instance, a spherical ROI was used for the hippocampus and the cortex, which nevertheless did not reflect the anatomy of the structure 12, 13. Despite these excellent annotation atlases, it is still common in MRI studies of the mouse brain that ROIs for brain structures are prepared with arbitrary boundaries and locations according to each researcher’s necessities. Various three-dimensional annotation volumes (AVs) for the mouse brain have been proposed with various spatial resolution (32–156 μm), numbers of animals for averaging (4–27 animals), and numbers of segmented structures (5–70, and 707 regions-of-interest, ROIs) 4, 5, 6, 7, 8, 9, 10, 11. FAA can improve the consistency of whole brain ROI definition among laboratories by fulfilling various requests from researchers with its flexibility and reproducibility.Ī standard brain atlas plays a key role in magnetic resonance imaging (MRI) for investigating anatomical and functional architecture of the brain 1, 2, 3. Unique characteristics of FAA realized analysis of resting-state functional connectivity (FC) across the anatomical hierarchy and among cortical layers, which were thin but large brain structures. ![]() Four FAAs with total node count of 4, 101, 866, and 1381 were demonstrated. A mere two-step procedure with user-specified, text-based information and Python codes constructs FAA with nodes which can be combined or divided objectively while maintaining anatomical hierarchy of brain structures. This report presents a pipeline for constructing a flexible annotation atlas (FAA) of the mouse brain by leveraging public resources of the Allen Institute for Brain Science on brain structure, gene expression, and axonal projection. ![]() combination and division of nodes were not implemented. One reason for such a situation is the fact that earlier AVs were fixed, i.e. Although various annotation volumes (AVs) for the mouse brain have been proposed, it is common in magnetic resonance imaging (MRI) of the mouse brain that regions-of-interest (ROIs) for brain structures (nodes) are created arbitrarily according to each researcher’s necessity, leading to inconsistent ROIs among studies. A brain atlas is necessary for analyzing structure and function in neuroimaging research.
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