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The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas

Authors :
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Media Laboratory
McGovern Institute for Brain Research at MIT
Regev, Aviv
Wickersham, Ian R.
Ecker, Joseph R.
Geschwind, Daniel H.
Kriegstein, Arnold R.
Ngai, John
Osten, Pavel
Polioudakis, Damon
Sestan, Nenad
Zeng, Hongkui
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Media Laboratory
McGovern Institute for Brain Research at MIT
Regev, Aviv
Wickersham, Ian R.
Ecker, Joseph R.
Geschwind, Daniel H.
Kriegstein, Arnold R.
Ngai, John
Osten, Pavel
Polioudakis, Damon
Sestan, Nenad
Zeng, Hongkui
Source :
PMC
Publication Year :
2018

Abstract

A comprehensive characterization of neuronal cell types, their distributions, and patterns of connectivity is critical for understanding the properties of neural circuits and how they generate behaviors. Here we review the experiences of the BRAIN Initiative Cell Census Consortium, ten pilot projects funded by the U.S. BRAIN Initiative, in developing, validating, and scaling up emerging genomic and anatomical mapping technologies for creating a complete inventory of neuronal cell types and their connections in multiple species and during development. These projects lay the foundation for a larger and longer-term effort to generate whole-brain cell atlases in species including mice and humans. In this Perspective, Ecker et al. discuss the efforts of the BRAIN Initiative Cell Census Consortium, ten pilot projects whose collective goal was to develop and validate methods for generating comprehensive atlases of neuronal cell types in the mammalian brain.<br />BRAIN Initiative

Details

Database :
OAIster
Journal :
PMC
Notes :
application/pdf
Publication Type :
Electronic Resource
Accession number :
edsoai.on1076281915
Document Type :
Electronic Resource