OpenScope: A Platform for High-Throughput and Reproducible Neurophysiology Open to External Scientists to Test Impactful Theories of Brain Function - Project summary Over the past five years, the Allen Institute has built two unique in-house pipelines for in vivo electro- and optical-physiology: together they form the Allen Brain Observatory. We used this observatory to freely and openly share calcium imaging data from ~60,000 cells from 221 running mice viewing standard visual stimuli; in October 2019, we will release Neuropixels electrophysiology recordings from ~100,000 cells from 100 mice under the same conditions, all registered to a common anatomical coordinate system (CCFv3). We wish to open the Brain Observatory pipeline to the community, enabling theoretical, computational, and experimental scientists to test sophisticated hypotheses on brain functions in a process analogous to astronomical observatories that survey the night sky. Our observatory, called OpenScope, will accept, once a year, experimental proposals from external scientists, which will be reviewed by a panel of leading experts for their feasibility and scientific merit. The Allen Institute will carry out the selected experiments by following verified, reproducible, and open protocols for in vivo single- and multi-area two photon calcium imaging and Neuropixels electrophysiology, making the data freely available to these scientists. Funding for this proposal will give the entire community access to a modern experimental platform that operates under standardized, reproducible, and high-throughput conditions. This resource will be particularly attractive to the computational and theoretical communities with limited access to experimental facilities. Our project has the potential to transform systems neuroscience by implementing an observatory model that has been tremendously successful in other scientific fields. By reducing variability in training, imaging and quality control across animals and experiments and by lowering the barrier to select, test, and validate the best ideas, we hope to accelerate progress toward an integrated view of neural circuits.
