The US BRAIN Initiative archive for publishing and sharing neurophysiology data including electrophysiology, optophysiology, and behavioral time-series, and images from immunostaining experiments.
DANDI: Distributed Archives for Neurophysiology Data Integration is a Web platform for scientists to share, collaborate, and process data from cellular neurophysiology experiments.
A whole-cortex macaque structural connectome constructed from a combination of axonal tract-tracing and diffusion-weighted imaging data. Created for modeling brain dynamics using TheVirtualBrain (thevirtualbrain.org) platform. A detailed description and example usage can be found in the paper here: https://www.
The large diversity of cell-types of the brain, provides the means by which circuits perform complex operations. Understanding such diversity is one of the key challenges of modern neuroscience. Neurons have many unique electrophysiological and behavioral features from which parallel cell-type classification can be inferred.
World Wide Series Seminar AAV are versatile tools used by neuroscientists for expression and manipulation of neurons. Many scientists have benefited from the high-quality, ready-to-use AAV prep service from Addgene, a nonprofit plasmid repository.
COINSTAC provides a platform to analyze data stored locally across multiple organizations without the need for pooling the data at any point during the analysis. It is intended to be an ultimate one-stop shop by which researchers can build any statistical or machine learning model collaboratively in a decentralized fashion.
KnowledgeSpace aims to be a globally-used, community-based, data-driven encyclopedia for neuroscience that links brain research concepts to data, models, and the literature that support them. Further it aims to serve as a framework where large-scale neuroscience projects can expose their data to the neuroscience community-at-large.
NeuroImaging Tools & Resources Collaboratory is an award-winning free web-based resource that offers comprehensive information on an ever expanding scope of neuroinformatics software and data. Since debuting in 2007, NITRC has helped the neuroscience community make further discoveries using software and data produced from research that used to end up lost or disregarded.
ReproNim’s goal is to improve the reproducibility of neuroimaging science and extend the value of our national investment in neuroimaging research, while making the process easier and more efficient for investigators.
Several excellent computational frameworks exist that enable high-throughput and consistent tracking of freely moving unmarked animals. SimBA introduce and distribute a plug-and play pipeline that enables users to use these pose-estimation approaches in combination with behavioral annotation for the generation of supervised machine-learning behavioral predictive classifiers.