I am a neuroscientist & statistician and use machine learning and data analytics to identify cell types, circuits and computations in the healthy and diseased visual system. I work in the labs of Matthias Bethge and Thomas Euler at the University of Tübingen and collaborate closely with Andreas Tolias at Baylor College of Medicine. See my Research page for my current projects and interests.
We have been organizing a sattelite symposium on retinal ganglion cell classification a day before the European Retina Meeting. It aims to bring together people with different approaches (anatomy, genetics, physiology, connectomics) to this topic and discuss the latest advances. I think we have an exciting program including talks by Sebastian Seung, EJ Chichilnisky, Joshua Sanes, Andy Huberman and Estuardo Robles. I will present the latests results from our endeavours into functionally classifying retinal ganglion cells. Space is pretty much filled up, but here
is the program.
Together with Lucas Theis, a PhD student in our lab, I developed a new method to infer spike rates from calcium signals using supervised learning in flexible probabilistic models. In addition, together with our experimental collaborators we collected a large dataset of simultaneously recorded electrophysiology and calcium imaging data that allowed us to benchmark our algorithm against many available methods.
We show that our algorithm performs better than previoulsy published methods (preprint) and make the code available on github. The package includes a model trained on all available data, which should also perform well without training data. Let us know when you use the code in your research!
Tom Baden and I are organizing a workshop at the Bernstein Conference 2015 on ‘What the eye tells the brain and why’. It will take place on the 14th of September, between 9 and 12.30 am as part of the Sattelite Workshop day. We will have Martin Greschner, Karl Farrow, Julijana Gjorgjieva, Katrin Franke and Laura Busse presenting the latest on coding in the retina and beyond! We are looking forward to an exciting day, especially since there are two related afternoon workshops on ‘Dynamic retinal coding’ and ‘From retina to robots’.
Christian Behrens, a new PhD student, has joined our lab to work with me on data analysis and modeling in the retina. He studied theoretical physics in Munich and Heidelberg before coming to Tübingen. He will join the team working on the DFG grant we have been recently awarded, collaborating with Tom Baden, Katrin Franke and Thomas Euler.
We have recently started to implement PyCircStat, a python package for statistical analysis of circular or angular data. It builds on the matlab toolbox for circular statistics I have developed a few years ago. The python package is still in the early stages of development, but a number of features are already working:
You are welcome to check out the toolbox and try it – let us know if you find bugs, or have feature requests. Thanks!
On September 2nd, I will give a talk at the workshop “Characterizing Natural Scenes: Retinal Coding and Statistical Theory” organized by Arno Onken and Jian Liu about our recent Nature Neuroscience paper “Population code in mouse V1 facilitates readout of natural scenes through increased sparseness”. I am looking forward to an exciting workshop program and interesting discussions!
My grant application “Emergence of retinal ganglion cell response diversity from synaptic interactions in the inner retina – a combined approach of two-photon population imaging and computational modeling” together with Tom Baden has been funded by the DFG. We are excited to get started with the work!
Two of our papers came out during the last few weeks. In “Population code in mouse V1 facilitates read-out of natural scenes through increased sparseness” (published in Nature Neuroscience), we show that higher order correlations in natural scenes lead to increased population sparseness, improving the representation of natural scenes in the population code. In “State dependence of noise correlations in macaque V1” (published in Neuron), we show that global activity fluctuations in neural activity lead to noise correlations during anesthesia, and that removing these global fluctuations recovers the awake correlation structure.
A new review on population coding by Maoz Shamir is appearing in the April issue of Current Opinion in Neurobiology. Shamir discusses how correlated noise negatively impacts neural coding, when the noise overlaps with the signal, and how this effect can be overcome by introducing heterogeneity into the population model. Importantly, he points out that current population coding models are heavily underconstraint, such that additional assumptions are needed for testing them. The review references much of our work on population coding over the past 5 years or so, which was nice to see. Overall, this very interesting special issue on theoretical and computational neuroscience assembled by Adrienne Fairhall and Haim Sompolinsky is highly recommended