A Community-Developed Open-Source Computational Ecosystem for Big Neuro Data
Randal Burns, Eric Perlman, Alex Baden, William Gray Roncal, Ben Falk,, Vikram Chandrashekhar, Forrest Collman, Sharmishtaa Seshamani, Jesse, Patsolic, Kunal Lillaney, Michael Kazhdan, Robert Hider Jr., Derek Pryor,, Jordan Matelsky, Timothy Gion, Priya Manavalan, Brock Wester
TL;DR
This paper introduces a comprehensive cloud-based computational ecosystem that facilitates storage, visualization, and analysis of large-scale neuroimaging data, supporting extensive research and data sharing in brain sciences.
Contribution
It presents a community-developed open-source platform that manages diverse large neuroimaging datasets, enabling advanced analysis and visualization in a scalable cloud environment.
Findings
Supports over 20 publications and 100+ terabytes of data
Enables visualization and analysis of nanoscale to mesoscale brain data
Establishes NeuroData as the largest open brain data repository
Abstract
Big imaging data is becoming more prominent in brain sciences across spatiotemporal scales and phylogenies. We have developed a computational ecosystem that enables storage, visualization, and analysis of these data in the cloud, thusfar spanning 20+ publications and 100+ terabytes including nanoscale ultrastructure, microscale synaptogenetic diversity, and mesoscale whole brain connectivity, making NeuroData the largest and most diverse open repository of brain data.
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Taxonomy
TopicsCell Image Analysis Techniques · Advanced Fluorescence Microscopy Techniques · Functional Brain Connectivity Studies