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.
Starting July 1st, we are part of the Institute of Ophthalmic Research at the University of Tübingen. The institute aims at uncovering the causes of diseases of the eye and develop treatments based on these discoveries. To our basic science research, we will therefore add a clinical component, which I am very excited about. The IOR wrote a short news report about our start, which you can read here. My group will be mainly funded by the Bernstein Award of the German Ministry of Science and Education. We will remain affiliated with the Center for Integrative Neuroscience and the Bernstein Center for Computational Neuroscience in Tübingen.
Our new phone number is: +49-7071-2988833
Finally, our paper on “Benchmarking Spike Rate Inference in Population Calcium Imaging” has been published – as a NeuroResource in Neuron. In the paper, we evaluate a range of algorithms for spike rate inference from calcium imaging data on a large ground-truth dataset. What’s important is that the recordings were all performed under realistic conditions for population imaging, that is without zooming in on individual cells. This makes the task much more difficult – the best algorithms achieve correlations of 0.5-0.6 when evaluated in time bins of 40 ms. It will be interesting to find out whether this can be improved upon by better algorithms or whether new indicators and imaging systems are needed for that. We provide our method, which performs very well under a wide range of recording conditions, for ready reuse.
Together with Ralf Haefner and Eckart Arnold I headed a one week spring school on the role of simulations in neuroscience with undergraduate students supported by the German National Academic Foundation. The goal was to discuss (1) what simulations can contribute to generating knowledge and (2) if there is such a thing as a right level of abstraction, both from a scientific and philosophical point of view. The school was located in beautiul Annency in the French Alps, close to Geneva. Therefore, we spent a day on a field trip, visiting Felix Schürrmann of the Human Brain Project in the morning and Alex Pouget of University of Geneva in the afternoon. The students spent also time performing simulations themselves, diving into the details of Integrate&Fire and Hodgkin-Huxley neurons. A great in week in a spectacular setting!
Our patch-seq paper has now officially been published in the February issue of Nature Biotechnology, back to back with another article describing a very similar method. Both methods allow combining electrophysiological characterization of neurons with single-cell transcriptomics. The journal chose to advertise both papers on the cover, yielding a fancy 3D rendering of the process.
Our paper “The functional diversity of retinal ganglion cells in the mouse” has just been published in Nature. As a data scientist, it is a unique chance to work with two-photon recordings from more than 11,000 ganglion cells. The paper complements recent attempts providing anatomical or genetic definitions of neural cell types by teasing apart the functional signatures of ganglion cell types – we thus termed our approach “retinal functomics“.
While we don’t offer any fancy online visualizations to play with, all the data is available online.
Today, our paper “Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq” has been published as a Letter in Nature Biotechnology. My experimental co-authors developed a technique to perform patch-clamp recordings in cortical neurons followed by single-cell RNA sequencing. As a proof of principle, we show that physiological and anatomical cell types as well as physiological properties can be recovered based on the transcriptomes of individual neurons. Interestingly, a very related technique was independently developed by another lab – their paper is published alongside with ours. These techniques allow studying cell types from the genetic to the functional level, opening exciting avenues for future work!
The paper’s altmetric score can be found here.
Alex Ecker and I received a teaching award from the senior students of the Master program in Neural Information Processing for our lecture Neural Data Analysis from summer term 2015.
There has been some media coverage of the Bernstein Award including a articles in the Stuttgarter Zeitung (de/en by Google Translate, more or less readable), the Schwäbische Tagblatt (de) and the Healthcare Industry BW portal (de/en) as well as radio coverage on SWR4 (de). Thanks for the interest in our work!
Our new paper has been published today in Science! In this work lead by Xiaolong Jiang in Andreas Tolias’ lab at Baylor College of Medicine in Houston, we classified cortical interneurons in adult mice and mapped their connectivity diagram. Interestingly, three simple rules go a long way in explaining the structure of the connectivity matrix. For me, this is a nice piece of heroic wet-lab work combined with the right level of machine learning based analysis.