Peter Rupprecht

I’m a neuroscientist interested in understanding the principles that underlie the organization of neurons in the brain.

The main purpose of this blog is to share knowledge about technology and scientific ideas with other researchers. You can find me also on Twitter, on Github, Google scholar or on OrcID, and you can find my email address on my lab’s website.

I’m currently working as a postdoctoral researcher in the lab of Fritjof Helmchen at the Brain Research Institute in Zürich/Switzerland.

Before I became a neuroscientists, I studied physics with a major in biophysics at the university of Bayreuth/Germany. From the beginning on, it was clear to me that I would switch to neuroscience after my studies, but learning quantum mechanics, mathematics, statistics and programming as a physicist turned out to be very useful for neuroscience research lateron. – During a year abroad at the ENS Lyon in 2011, I took the chance to do a research internship in the biophysics lab of Prof. Jean-Paul Rieu, where I worked with cancer cells and explored how they behave under mechanical stress. When I first saw a (breast cancer) cell moving its filopodia under the microscope, I was determined to spend some time on that topic, fascinated by the rich behavior of a single cell. In the end, I used this internship to get known to Matlab, as I developed a tracking program, and I wrote a technical paper about a microfluidic device that I had designed and used.

Then I went on to finish my diploma (Dipl.-Phys.) in Bayreuth. For my diploma thesis in 2012/2013, I joined the lab of  Prof. Matthias Weiss, a biophysicist with a strong theoretical background. I worked with C. elegans, investigating the dynamics of cytosceletal proteins and of the endoplasmic reticulum during the early phase of embryogenesis using confocal microscopy of the whole embryo. In plain words, I watched many times how a little one-cell thing developed into something much more complex in the course of some dozen minutes. On the technique side, I spent quite some time using FRAP, PIV, and developing mathematical models for diffusion in inhomogeneous media.

As my focus had always been on neuroscience, I then looked for interesting research groups in this field after finishing my studies. I struggled for quite some time to find research groups where I could find a methodological rigor that was comparable to what I had previously encountered during my physics studies. Finally, I decided to stay at the FMI in Basel in the group of Rainer Friedrich for some months, where I worked on computational models of a brain area in fish linked to the perception of odors.

Determined to stay in this particular research group for a PhD, I wanted to gather some more technical experience before and decided to work as a research assistant in the lab of Alipasha Vaziri at the IMP in Vienna for five months. In close collaboration with then-postdoc Robert Prevedel, I re-designed an already existing temporal focusing microscope for the use with small model organisms like C. elegans and the zebrafish larva, which resulted in a methods paper (in the paper, we used mouse brain slices instead of worms and fish). Besides from designing and building the microscope, I also collected some experience with calcium imaging in these organisms.

After that, I felt ready to work rather independently, and I joined Rainer Friedrich’s lab at the FMI for my PhD. To begin with, I constructed a resonant scanning 2P microscope for calcium imaging and wrote the control software; for fast z-scanning, I developed a remote scanning technique based on a voice coil motor, described on this blog, and published in Biomedical Optics Express in 2016. After a while, I decided to learn whole-cell patch-clamp, which became the second main method during my PhD, resulting in an exploratory and, in my opinion, technically very creative paper that describes the precise structure of the synaptic input of the olfactory cortex homolog in zebrafish. In parallel, I also worked on projects that used machine learning to infer spiking probabilities from calcium imaging data, and I also got involved in a dense connectomics project based on serial block scanning electron microscopy (you will hear about this project in 3-8 years, because this is how long these projects take …).

After completing the PhD, I started a postdoctoral position in the lab of Fritjof Helmchen in Zürich/Switzerland. The lab is renowned for the development of leading-edge methods and their application to neuroscience, and I think it will be the perfect platform for me to work on biological questions. In continuation of my PhD work, I have developed the algorithm CASCADE together with a ground truth database to enable reliable spike inference from unseen calcium imaging data, and I am currently involved in a number of interesting project, not only but also focused on the hippocampus.

A few years ago, I wrote that “my general approach to neuroscience is curiosity”. Now, I feel that a more systematic and thought-out approach might be helpful as well, because the brain is full of curious phenomena, and if I get caught by every strange thing, I will never go into depth for one single aspect. However, once I’ve understood a particular aspect, I want to know if this changes the way I think about my own brain. On the one hand, modern neuroscience convinces me more and more that a brain can in principle be explained in mechanistic terms. For example, nobody will deny the changes in behavior, development or even memory due to knock-out or optogenetic manipulation in smaller animals; or the effects of lesions, drugs or techniques like ECT or DBS on human beings – evidence that information processing can be influenced, guided or disturbed by mechanistic processes. On the other hand, almost nothing is known about how this information and information processing could look like. The fact that we can interfere with the information processing (which is more interesting for the biomedical side) does not mean that we know what is happening (which is more interesting for those who want to understand). I think that right now with the current knowledge and techniques, it is the best decision to look at in vivo systems with single-neuron precision or even below that, and to find a balanced mixture of focused technical development, repetitive experiments and data analysis guided by human intelligence.

At this point, I’d like to point out that the opinions presented in this blog do not necessarily reflect the opinions of my host laboratory and my host research institute. This is a private web blog.

(Written in 2014, slightly updated in 2019 and 2021.)

1 Response to Peter Rupprecht

  1. Paul O. says:

    Awesome! Very Helpful!

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