optophysiology
We have developed a family of tools for the purposes of inferring precise spike trains from noisy calcium imaging data, and then using these spike times to infer connectivity. These tools have been tested both in vivo and in vitro, using organic dyes and genetic sensors, with various preps, cell types, imaging rates, and labs around the world. Collectively, these tools comprise the Optimal OPtical Spike Inference (oopsi) family. Please contact me with any difficulties or exciting results!
fast-oopsi
fast-oopsi our relatively simple theory and algorithm for inferring spike trains from calcium imaging. We recommend starting here. The manuscript, code, and repository (containing an archive of all work on this project) are all freely available for download.
smc-oopsi
smc-oopsi our relatively sophisticated theory and algorithm for inferring spike trains from calcium imaging. If fast-oopsi doesn't do it for you, perhaps this stuff will. The manuscript, code, and repository (containing an archive of all work on this project) are all freely available for download.
pop-oopsi
given that you have already inferred the approximately most likely spikes from a population of neurons, you might want to relax that assumption, to use neighboring neurons to help with the inference, or estimate connectivity between those neurons. pop-oopsi comes to the rescue. The manuscript, code, and repository (containing an archive of all work on this project) are all freely available for download.