High Throughput Imaging Characterization of Brain Cell Types and Connectivity
Date
Location
Overview
The advent of high throughput single-cell sequencing and imaging methods has enabled comprehensive molecular profiling of mammalian brain cell diversity and construction of foundational reference brain cell atlases for the study of brain function and disorders.
The purpose of this NIH BRAIN Initiative workshop was to discuss unmet needs and emerging imaging approaches to characterizing brain cell types and their connectivity in human and other mammalian brains, in parallel with the BRAIN Initiative funding opportunity announcements (RFA-MH-22-290 , RFA-MH-22-291 , RFA-MH-22-292 ).
The workshop:
- Benchmarked existing technologies, identified critical gaps and barriers of imaging pipelines, and discussed potential solutions through innovation and collaboration
- Streamlined individual steps and processes from tissue acquisition and processing through tissue labeling, imaging, data analysis, visualization, and integration
- Established expectations for data sharing, scalable computing, and reuse by the broad research and education communities
Recordings
Watch the full playlist of videos from NIH BRAIN workshop.
2022 High Throughput Imaging Characterization of Brain Cell Types and Connectivity-Day 1, Part 1
2022 High Throughput Imaging Characterization of Brain Cell Types and Connectivity-Day 1, Part 2
2022 High Throughput Imaging Characterization of Brain Cell Types and Connectivity-Day 2, Part 1
2022 High Throughput Imaging Characterization of Brain Cell Types and Connectivity-Day 2, Part 2
2022 High Throughput Imaging Characterization of Brain Cell Types and Connectivity-Day 2, Part 3
2022 High Throughput Imaging Characterization of Brain Cell Types and Connectivity-Day 2, Part 4
2022 High Throughput Imaging Characterization of Brain Cell Types and Connectivity-Day 2, Part 5
2022 High Throughput Imaging Characterization of Brain Cell Types and Connectivity-Day 2, Part 6
Sponsored by
Division of Neuroscience and Basic Behavioral Science