Spikefinder results released!

This week, we have finally released the results of the spikefinder challenge to infer action potentials from calcium recordings. We had more than 50 submissions, many of them in the last few days of the challenge. Obviously, deep learning frameworks were hugely popular, but also “classical” generative modeling approaches (“MLspike”) did remarkably well. Here are the top 10:

top10 submissions.png

We declared Patrick Mineault (Google), Nikolay Chenkov (BCCN Berlin), Peter Rupprecht and Stephan Gerhard (FMI Basel) joint winners, as there submissions were extremely close to each other. A lively debate emerged on twitter about what it all means:

Our preliminary analysis can be found on github. A more complete paper with thorough discussion and analysis will follow.


Leave a Reply

Please log in using one of these methods to post your comment:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s