Project Description:

There exists a demand to provide the neuroscience and connectomics communities with an atlas of available datasets by model organism. Current data exists in isolation with little information about relative spatial location, which makes comparison difficult. The scale and implications of dense neural reconstructions present a significant challenge in exploratory data analysis and hypothesis-generation. We present Connectomics Multimodal Atlas Project (C-MAP) as a tool to address this. C-MAP is a web-based visualization platform that maps datasets from BossDB, a volumetric database for 3- and 4-D data, to locations in the Allen Institute Brain Atlas. This facilitates analysis of the distribution of areas imaged, suggests candidate regions for multi-study review, and illustrates greater precision of sample acquisition location. In this paper, we describe the development and implementation of C-MAP and share milestones for future development. We also present a use-case demonstrating how C-MAP enables comparison between datasets in the mouse cerebellum.

Project Photo:

Connectomics Multi-modal Atlas Project (C-MAP) is a web-based visualization platform that maps datasets from BossDB, a database for 3- and 4-D data, to locations in the Allen Institute Brain Atlas. It enables comparative analysis of dense neural reconstructions by placing them in relative contexts, facilitating advances in health and computation.

Student Team Members

• Lavanya Gupta
• Giancarlo Zambrano

Course Faculty

• William Gray-Roncal

Project Mentors, Sponsors, and Partners

• Daniel Xenes
• Hannah Martinez
• Nicole Stock
• Brock Wester