The brain circuit is an intricately interconnected network of a vast number of neurons with diverse molecular, anatomical and physiological properties. Neuronal cell types are fundamental building blocks of neural circuits. To understand the principles of information processing in the brain circuit, it is essential to have a systematic understanding of the common and unique properties for each of its components - the cell types, how they are connected to each other, and what are their functions in the circuit. From the study of numerous circuits, many types of mechanisms have been proposed regarding the roles of different cell types in signal processing. However, despite of the importance, we are far from a comprehensive understanding of the number and kinds of cell types in the brain or a given circuit. We do have a wealth of knowledge on the major cell types in each region, and many examples of specific types. But for the most part, due to the lack of systematic efforts, we don't know the complete cell type composition of most circuits, and we have very little idea about the degree of variation and heterogeneity among single cells, both within a given type and between different types. To address this issue, we propose to establish a comprehensive and standardized cell type characterization platform that can be scaled up to systematically examine the properties and function of cell type components in any neural circuits throughout the brain. To implement this, we propose a model for collaboration between academic labs/centers and Allen Institute for characterizing cell types in specific brain circuits, with all the QC-passed daa going into the Allen Institute Cell Types Database and becoming publicly available. We will test a range of experimental approaches, encompassing molecular, anatomical and physiological measurements and their integration at the single cell level. Our proof of principle studies are based on comparison of three major brain neural circuits in the mouse brain: two closely related cortical circuits - primary visual cortex (V1) and primary somatosensory cortex (S1), and a more distinct circuit - the hypothalamus/amygdala emotional pathway. These two axes of comparison should be very informative in assessing the reliability and generality of the cell type characterization approaches we will be testing. We thereby hope to determine the critical parameters and metrics necessary to classify neurons into discrete cell types, guided by their functions. Thus, we anticipate that this project and the resources it produces will have a broad impact and catalytic effect on the scientific community studying brain circuitry function and dysfunction.
The brain circuit is an intricately interconnected network of a vast number of neurons with diverse molecular, anatomical and physiological properties, and many mental health disorders can be attributed to malfunction of brain circuitry. To understand the principles of information processing in the brain circuit, we propose to establish a comprehensive and standardized cell type characterization platform that can be scaled up to systematically examine the common and unique properties and function of cell type components in any neural circuit throughout the brain. Creating a publicly accessible cell types database will have broad impact on the study of brain circuitry as a foundation to further our understanding of brain function and brain diseases.
|Seeman, Stephanie C; Campagnola, Luke; Davoudian, Pasha A et al. (2018) Sparse recurrent excitatory connectivity in the microcircuit of the adult mouse and human cortex. Elife 7:|
|Daigle, Tanya L; Madisen, Linda; Hage, Travis A et al. (2018) A Suite of Transgenic Driver and Reporter Mouse Lines with Enhanced Brain-Cell-Type Targeting and Functionality. Cell 174:465-480.e22|
|Tasic, Bosiljka; Yao, Zizhen; Graybuck, Lucas T et al. (2018) Shared and distinct transcriptomic cell types across neocortical areas. Nature 563:72-78|
|Economo, Michael N; Viswanathan, Sarada; Tasic, Bosiljka et al. (2018) Distinct descending motor cortex pathways and their roles in movement. Nature 563:79-84|
|Zeng, Hongkui (2018) Mesoscale connectomics. Curr Opin Neurobiol 50:154-162|
|Zeng, Hongkui; Sanes, Joshua R (2017) Neuronal cell-type classification: challenges, opportunities and the path forward. Nat Rev Neurosci 18:530-546|
|Ecker, Joseph R; Geschwind, Daniel H; Kriegstein, Arnold R et al. (2017) The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas. Neuron 96:542-557|
|Tasic, Bosiljka; Menon, Vilas; Nguyen, Thuc Nghi et al. (2016) Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat Neurosci 19:335-46|