My group is using machine learning and data analytics for large-scale neuroscience, working on identifing cell types, circuits and computations in the healthy and diseased visual system. We are part of the Institute of Ophthalmic Research at the University of Tübingen and affiliated with the Center for Integrative Neuroscience and the Bernstein Center for Computational Neuroscience in Tübingen. Our official lab website can be found here.
Joint lab retreat with Euler/Franke labs
We spent two intense days at Kloster Obermarchtal on a joint lab retreat with the labs of Thomas Euler and Katrin Franke to discuss where we are currently at with our projects, were we want to go and what we want to achieve. Tom Baden, Günther Zeck and Matthias Bethge came as guests to provide feedback and input and discuss collaborations. Also, Tom gave an entertaining talk about the latest on fish vision.
Thanks everyone for the commitment and the discussions!
Lab team in 100k relay race
Together with some people from the Euler lab we participated in the 100k relay race of the University of Tübingen. The race is special because you run in pairs and 1k at a time, ten times each. Effectively, that makes it ten 1k-sprints. We made a very good 11th place out of 37 teams!
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:
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:
#spikefinder results are out! https://t.co/nLx62nATuA @patrickmineault @DarioRingach @thefreemanlab
— Philipp Berens (@CellTypist) 13. Mai 2017
Our preliminary analysis can be found on github. A more complete paper with thorough discussion and analysis will follow.
FEI Technology Award 2017
On occasion of the Meeting of the German Neuroscience Society, I received the FEI Technology Award 2017 for my work on using machine learning to define cell types in the nervous system.
Bipolar cell paper published in Nature
Our paper on the functional diversity of bipolar cells and its origin in the inner retina has just been published online by Nature. We show that spatially extended stimulation induces a decorrelation between bipolar cell feature channels and that this effect is mediated by GABAergic amacrine cells. Richard Masland wrote a nice feature piece “Systems neuroscience: Diversity in sight“. The data will be available shortly.
Paper of the year award
Representing all authors, Katrin and I received the paper of the year award for a paper in the basic sciences from the medical faculty of the University of Tübingen 2016 for our paper “The functional diversity of mouse retinal ganglion cells“, awarded by Thomas Gasser, the vice-dean of the medical faculty.
Postdoc position in Medical Data Science
My lab is offering a position as
Postdoctoral Researcher (TV-L E13 100%)
in
Medical Data Science for Ophthalmology
to be filled as soon as possible, with funding for up to 4 years.
Moving beyond Frontiers
I have been considering this for a while, here is one new year’s resolutions for 2017: Moving beyond Frontiers. There’s lots of evidence that we should not take Frontiers seriously (anymore?) as a scientific publisher.
The spikefinder challenge
Calcium imaging is one of the most widely used techniques to acquire data from large populations of neurons. Unfortunately, inferring action potentials from the measured calcium traces is not straightforward and algorithmically far from solved.
To make progress in this direction, we opened the spikefinder challenge at http://spikefinder.codeneuro.org/!
We collected a large dataset of simultaneous two-photon imaging and electrophysiologically records and made it available separated into training and test sets. We ask you to design your favorite algorithm and submit your results on the website!
What is your benefit?
- You get to advance the community
- All algorithms that beat state of the art will be included in an overview paper and you will be coauthor
- The top three teams will win a 1200/500/300 EUR award sponsored by our partner ZEISS AG.
We look forward from receiving your submissions. The deadline is the 31st of March 2017.
You might also be interested in the neurofinder challenge at http://neurofinder.codeneuro.org/ – a challenge to find the best ROI detection algorithm.
Best
Philipp, Jeremy, Matthias, Andreas, Josh, Lucas
