Brain development is characterized by a diverse set of cell types that are born and connected into rapidly growing complex 3D structures across time. Quantitative understanding of cell type composition and distribution in different brain regions provides fundamental knowledge about the building blocks of the brain and serves as an essential baseline with which to assess changes that may occur in brain disorders. The importance of this information is reflected by the significant effort among the neuroscience community, including the creation of the BRAIN Initiative Cell Census Network, to improve our understanding of cell type compositions across different brain regions in the adult mouse brain. These efforts have been made possible and accelerated by technological advances in high-resolution 3D imaging coupled with computational analysis methods that can reveal cell type arrangement in the brain with unprecedented detail. For example, we developed a quantitative brain mapping method to uncover the spatial arrangement of GABAergic neuron subtypes in the adult mouse brain. For the adult mouse brain, the Allen Common Coordinate Framework (CCF) currently serves as the standard atlas resource with which to map and integrate results from different studies. The neuroscience community, on the other hand, does not have similar CCFs for the developing mouse brain. The lack of developmental CCFs significantly hinders progress on cell type mapping of the developing mouse brain by limiting the reproducibility and integration of data from different studies. To address this deficiency, we have assembled a highly synergistic, multi-institutional team with complementary skill sets to create developmental CCFs with associated ontology and true 3D anatomical labels while also demonstrating the application of our CCFs by generating quantitative mappings of GABAergic neurons in the developing mouse brain. Toward this end, we will first utilize MRI and light sheet fluorescent microscopy (LSFM) to develop high-resolution developmental CCFs at seven different developmental time points (E11.5, E13.5, E15.5, E18.5, P4, P14, and P56) with different cellular features, including total cell density, myelination, and neurovasculature. Second, we will create true 3D anatomical labels for the CCFs based on cellular and gene expression information, and build a comprehensive ontology that will allow anatomical region changes to be linked across development and maturation. Lastly, we will generate a cellular-resolution quantitative map of GABAergic neuronal subtypes using tissue clearing and LSFM imaging in developing mouse brains, which will serve as a substantial data resource to accelerate developmental neuroscience discovery. The successful completion of this project will enable a broad field of scientists to leverage modern brain mapping technologies more effectively in studying the developing mouse brain.

Public Health Relevance

Common coordinate frameworks (CCF) provide an essential spatial context to understand cell type composition and 3D arrangement in the mouse brain. Unlike for the adult mouse, the lack of CCFs in developing mouse brains significantly impedes progress on quantitative spatiotemporal understanding of cell types during neurodevelopment. Thus, we propose to create mouse brain developmental CCFs with true 3D anatomical labels and associated ontology, and apply the CCFs to comprehensively map the developmental trajectory of GABAergic neurons in the developing mouse brain.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Multi-Year Funded Research Project Grant (RF1)
Project #
1RF1MH124605-01
Application #
10088508
Study Section
Special Emphasis Panel (ZMH1)
Program Officer
Yao, Yong
Project Start
2020-09-15
Project End
2023-09-14
Budget Start
2020-09-15
Budget End
2023-09-14
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Pennsylvania State University
Department
Neurosciences
Type
Schools of Medicine
DUNS #
129348186
City
Hershey
State
PA
Country
United States
Zip Code
17033