The first paper from my lab “Connectivity map of bipolar cells and photoreceptors in the mouse retina” has just been published by eLife. Congratulations to Christian for his first paper as well!
Together with Timm Schubert from Thomas Euler’s lab we reconstructed the photoreceptors in a publicly available EM dataset of retinal tissue. We build on the work of Moritz Helmstaedter and colleagues, who made their entire dataset and code available – to me this is a great example of how open science can fuel discovery. Our code and data can be found here. The project was our first adventure in connectomics, which provided a great learning experience for everybody involved.
Our collaborative research center “Robust Vision – Inference Principles and Neural Mechanisms” got approved by the German Research Foundation on Friday! This is great news – together with a great team of >20 PIs, we will tackle the question why biological visual systems show so remarkable robustness building on our joint expertise in experimental and computational neuroscience, machine learning and computer vision.
Last year, we published our study “Principles of connectivity among morphologically defined cell types in adult neocortex” in Science. The paper generated quite a bit of attention – and now a technical comment, which was recently published in Science. In their comment, Barth et al. criticize our study as (i) overstating the completeness of our study; (ii) reporting a potentially biased connectivity matrix due to technical limitations of our brain-slicing and multipatching methods; and (iii) simply renaming previously identified interneuron types.
Details of our reply to their criticism can be found in the published version. In particular, we addressed their point about potential biases in the connectivity matrix due to slice cutting quantitatively. Assuming that the neuron are approximately rotationally symmetric, we computed the amount of overlap of their dendritic and axonal fields potentially cut away by the slicing (because this is were connections between the two can happen). A similar method had been used before by Levy and Reyes. The analysis clearly shows that the correction factor that needs to be applied does not strongly depend on the cell type pair, suggesting that the connectivity matrix may need to be scaled, but is unlikely to be distorted.
In the course of preparing the reply, we also submitted all fully reconstructed neurons from that study (n=298) to neuromorpho.org, where they will be available shortly.
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.