Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Blog
Articles about computational science and data science, neuroscience, and open source solutions. Along with other personal stories, I also love exploring historical and cultural narratives from local and global perspectives.
Atom Feeds
Atom/RSS-links to follow my blog
CC BY-NC-SA 4.0 License
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License (CC BY-NC-SA 4.0)
Research
My work focuses on the analysis of neurological data to better understand the neuronal processes related to the Hippocampus, especially memory and learning and neurodegenerative diseases. This covers the analysis of multi-fluorescence ex- and in-vivo imag...
Teachings
Teaching material, mostly on computational neuroscience, bioimage analysis, and machine learning. Feel free to use and share it.
Weekend Stories
Weekend Stories is a visual diary of everyday stories, (mostly) captured on weekends.
Weekend Stories: Seen
Weekend Stories is a visual diary of everyday stories, (mostly) captured on weekends. This subcategory contains pure photo series only. Accompanying stories can be found in the subcategory ‘told’.
Weekend Stories: Told
Weekend Stories is a visual diary of everyday stories, (mostly) captured on weekends. This subcategory is a collection of personal stories, that usually accompany the photo series listed in the subcategory ‘seen’.
Posts
FitzHugh-Nagumo model
In the previous post, we analyzed the dynamics of Van der Pol oscillator by using phase plane analysis. In this post, we will see, that this oscillator can be considered as a special case of another dynamical system, the FitzHugh-Nagumo model. The FitzHugh...
Van der Pol oscillator
In this post, we will apply phase plane analysis to the Van der Pol oscillator. The Van der Pol oscillator is a non-conservative oscillator with nonlinear damping, which was first described by the Dutch electrical engineer Balthasar van der Pol in 1920. We ...
Nullclines and fixed points of the Rössler attractor
After introducing phase plane analysis in the previous post, we will now apply this method to the Rössler attractor presented earlier. We will investigate the system’s nullclines and fixed points, and analyze the attractor’s dynamics in the phase space.
Using phase plane analysis to understand dynamical systems
When it comes to understanding the behavior of dynamical systems, it can quickly become too complex to analyze the system’s behavior directly from its differential equations. In such cases, phase plane analysis can be a powerful tool to gain insights into ...
PyTorch on Apple Silicon
Already some time ago, PyTorch became fully available for Apple Silicon. It’s no longer necessary to install the nightly builds to run PyTorch on the GPU of your Apple Silicon machine as I described in one of my earlier posts.
Rössler attractor
Unlike the Lorenz attractor which emerges from the dynamics of convection rolls, the Rössler attractor does not describe a physical system found in nature. Instead, it is a mathematical construction designed to illustrate and study the behavior of chaotic s...
Understanding Hebbian learning in Hopfield networks
Hopfield networks, a form of recurrent neural network (RNN), serve as a fundamental model for understanding associative memory and pattern recognition in computational neuroscience. Central to the operation of Hopfield networks is the Hebbian learning rule,...
Building a neural network from scratch using NumPy
Ever thought about building you own neural network from scratch by simply using NumPy? In this post, we will do exactly that. We will build, from scratch, a simple feedforward neural network and train it on the MNIST dataset.
Python’s version logos
Have you ever noticed that Python has introduced individual version logos starting with version 3.10? I couldn’t find any official announcement, but luckily, the Python community on Mastodon was able to help out.
Switching to a Mastodon-powered comment system
I’m switching to a new Mastodon-powered comment system for my blog.
Conditional GANs
I was wondering whether it would be possible to let GANs generate samples conditioned on a specific input type. I wanted the GAN to generate samples of a specific digit, resembling a personal poor man’s mini DALL•E. And indeed, I found a GAN architecture, t...
Eliminating the middleman: Direct Wasserstein distance computation in WGANs without discriminator
We explore an alternative approach to implementing WGANs. Contrasting from the standard implementation that requires both a generator and discriminator, the method discussed here employs the optimal transport to compute the Wasserstein distance directly be...
Wasserstein GANs
We apply the Wasserstein distance to Generative Adversarial Networks (GANs) to train them more effectively. We compare a default GAN with a Wasserstein GAN (WGAN) trained on the MNIST dataset and discuss the advantages and disadvantages of both approaches.
Probability distance metrics in machine learning
Probabilistic distance metrics play a crucial role in a broad range of machine learning tasks, including clustering, classification, and information retrieval. The choice of metric is often determined by the specific requirements of the task at hand, with e...
Comparing Wasserstein distance, sliced Wasserstein distance, and L2 norm
In machine learning, especially when dealing with probability distributions or deep generative models, different metrics are used to quantify the ‘distance’ between two distributions. Among these, the Wasserstein distance (EMD), sliced Wasserstein distance ...
Approximating the Wasserstein distance with cumulative distribution functions
In the previous two posts, we’ve discussed the mathematical details of the Wasserstein distance, exploring its formal definition, its computation through linear programming and the Sinkhorn algorithm. In this post, we take a different approach by approximat...
Wasserstein distance via entropy regularization (Sinkhorn algorithm)
Calculating the Wasserstein distance can be computational costly when using linear programming. The Sinkhorn algorithm provides a computationally efficient method for approximating the Wasserstein distance, making it a practical choice for many applications...
Wasserstein distance and optimal transport
The Wasserstein distance, also known as the Earth Mover’s Distance (EMD), provides a robust and insightful approach for comparing probability distributions and finds application in various fields such as machine learning, data science, image processing, and...
Visualizing Occam’s Razor through machine learning
Here, we illustrate the concept of Occam’s Razor, a principle advocating for simplicity, by examining its manifestation in the domain of machine learning using Python.
Mamba vs. Conda: Unleashing lightning-fast Python package installations
If you’ve ever experienced the frustration of waiting for ages while installing Python packages with conda, there’s a game-changer I wish I’d heard about earlier: Mamba. This lightning-fast package manager surprised me with its incredible speed, making pack...
Integrate and Fire Model: A simple neuronal model
In this post we explore the Integrate-and-Fire model, a simplified representation of a neuron. We also run some simulations in Python to understand the model dynamics.
Assessing animal behavior with machine learning
High-throughput and multi-modal behavior experiments, coupled with machine learning analysis, unlock valuable insights into complex systems by capturing diverse behavioral responses and deciphering hidden structures within high-dimensional datasets. I just ...
Bioimage analysis with Napari
I’ve added new teaching material on using the free and open-source software (FOSS) Napari for bioimage analysis. Feel free to use and share it.
Using random forests for pixel classification
Beyond traditional classification problems, random forests have proven their effectiveness in pixel classification. In this post, we will delve into this domain and explore how random forests can be effectively utilized to tackle the task of pixel classific...
Decision Trees vs. Random Forests for classification and regression: A comparison
Decision trees and random forests are popular machine learning algorithms that are widely used for both classification and regression tasks. In this blog post, we elucidate their theoretical foundations and discuss the differences as well as their advantage...
Image denoising techniques: A comparison of PCA, kernel PCA, autoencoder, and CNN
In this post, we explore the performance of PCA, Kernel PCA, denoising autoencoder, and CNN for image denoising.
Using Autoencoders to reveal hidden structures in high-dimensional data
In this Python tutorial, we explore the application of Autoencoders for dimensionality reduction, demonstrating how this powerful technique can help us uncover and interpret hidden patterns within our data.
Unlocking hidden patterns with Factor Analysis
In this Python tutorial, we dive into Factor Analysis, a powerful statistical method used to uncover hidden, or ‘latent,’ variables within high-dimensional datasets. Like PCA, grasping this technique will allow us to simplify complex data structures, thereb...
Untangling complexity: harnessing PCA for data dimensionality reduction
This tutorial explores the use of Principal Component Analysis (PCA), a powerful tool for reducing the complexity of high-dimensional data. By delving into both the theoretical underpinnings and practical Python applications, we illuminate how PCA can revea...
t-SNE and PCA: Two powerful tools for data exploration
Dimensionality reduction techniques play a vital role in both data exploration and visualization. Among these techniques, t-SNE and PCA are widely used and offer valuable insights into complex datasets. In this blog post, we explore te mathematical backgrou...
Bridging ideas on the go: WikiLinks come to DEVONthink To Go
The WikiLinks feature has finally arrived on DEVONthink to go, DEVONthink’s mobile app, which unleashes new possibilities to work with your Personal Knowledge Management (PKM) system on the go.
New publication on Tauopathy
A new study on Tauopathy in which our lab was involved has just been published.
Understanding L1 and L2 regularization in machine learning
Regularization techniques play a vital role in preventing overfitting and enhancing the generalization capability of machine learning models. Among these techniques, L1 and L2 regularization are widely employed for their effectiveness in controlling model c...
Understanding gradient descent in machine learning
Gradient descent is a fundamental optimization algorithm widely used in machine learning for finding the optimal parameters of a model. It is a powerful technique that enables models to learn from data by iteratively adjusting their parameters to minimize a...
Loading and saving files in Google Colab
Enable I/O support in your notebooks running in Google Colab with just a few additional commands.
Mutual information and its relationship to information entropy
Mutual information is an essential measure in information theory that quantifies the statistical dependence between two random variables. Given its broad applicability, it has become an invaluable tool in diverse fields like machine learning, neuroscience, ...
Information entropy
A fundamental concept that plays a pivotal role in quantifying the uncertainty or randomness of a set of data is the information entropy. Information entropy provides a measure of the average amount of information or surprise contained in a random variable....
Understanding entropy
In physics, entropy is a fundamental concept that plays a crucial role in understanding the behavior of physical systems. It provides a measure of the disorder or randomness within a system, and its study has far-reaching applications across various branche...
Zen and natural sciences
In this post, I broaden the scope and explore the intersections of Zen and natural sciences more generally.
The Zen of Python
The connection between Zen and programming is not a subjective one at all. For instance, Python has built it directly into its core programming, known as The Zen of Python.
The Zen of programming
Some thoughts about the connections between Zen and programming.
How to get an RSS feed of your Mastodon bookmarks
The third-party service Mastodon Bookmark RSS allows you to subscribe to your Mastodon bookmarks via RSS, so you don’t forget to make use out of them. You can even integrate the feed into your favorite Zettelkasten apps such as DEVONthink and Obsidian.
Track the growth of your Zettelkasten with DEVONthink
You can easily track the growth of your Zettelkasten using DEVONthink’s smart groups.
Problems with large vaults in Obsidian
In the past few days I played a bit with Obsidian. Turns out that its iOS app has some serious problems with large vaults.
DEVONthink and privacy
One thing I really love about DEVONthink, is its high security and privacy measures regarding the synchronization of my notes across different devices. No other app that I have so far used offered such high standards.
Bio-image registration with Python
Which method works best for which registration problem? In this tutorial we compare different methods for the registration of bio-images using Python.
Using VS Code as LaTeX editor
It doesn’t take much to convert Visual Studio Code into a powerful LaTeX editor. Here are the necessary steps that enable full LaTeX support.
Moving a Mastodon account to another server
I recently moved my Mastodon account to a new server, including all my followers. I was surprised, how easy and seamless it worked. Here is a how-to, summarizing the migration steps.
Some useful Mastodon links
This is a curated list of useful Mastodon links.
I’m on Mastodon
Mastodon is not just a Twitter alternative. It’s a free and open-source social media platform of its own kind. Here is my story how I got there.
Embedding flickr photos on your Jekyll website
Easily integrate entire flickr photosets on your Jekyll website via a ruby plugin.
How to run PyTorch on the M1 Mac GPU
As for TensorFlow, it takes only a few steps to enable a Mac with M1 chip (Apple silicon) for machine learning tasks in Python with PyTorch.
How to run TensorFlow on the M1 Mac GPU
In just a few steps you can enable a Mac with M1 chip (Apple silicon) for machine learning tasks in Python with TensorFlow.
Is there a difference between miniconda and miniforge?
Simply said: not really. Miniconda is the company driven minimal conda installer, while miniforge is its community driven variant. In the end, you’ll get the same minimal conda installation on your machine – with a minor difference.
Hacks and extensions to improve your coding with Visual Studio Code
This curated list contains useful hacks and extensions to improve the overall coding performance with Visual Studio Code (VS Code).
Setting up Visual Studio Code for Python
In just a few steps you can turn Visual Studio Code (VS Code) into a powerful Python editor for both pure Python code and Jupyter Notebooks.
Laying off thousands of employees: Not okay! How to delete a Twitter account
Putting thousands of people on the street is anything else than cool. Here is how to fix it.
Enable interactive plots and other plot modes in Jupyter notebooks
Learn how to enable interactive, static and stand-alone window plots in Jupyter notebooks with the magic command %matplotlib.
Enable code folding in JupyterLab
Learn how to enable code folding in JupyterLab for both, Jupyter Notebooks and pure Python scripts.
How to create and apply a requirements.txt file in Python
Learn how to install Python packages with a requirements.txt file and how to create one yourself.
Virtual environments with venv
In addition to conda’s create command, Python’s built-in venv command offers another way for creating virtual environments.
Using pip to install Python packages
pip is another package installer for Python. Learn how to use it for installing and managing Python packages in your projects.
How to install and run Python code from GitHub
Learn how to install code from GitHub, that is, e.g., not (yet) available via conda or pip.
A minimal Python installation with miniconda
Learn how to install miniconda to have a quick and minimal Python installation on any operating system. Also learn how to use conda to create and manage virtual environments, install packages, run Python scripts and run Jupyter Notebooks and JupyterLab.
Stable installation of Napari on a M1 Mac
In case you’re having problems installing Napari on your M1 Mac, try to install it from conda instead of pip.
Open Zarr files in Fiji
Both Zarr and OME-ZARR files are supported in Fiji. Here’s how to get it working.
Using Zarr for images – The OME-ZARR standard
As for any other NumPy array, we can use the Zarr file format to store image files. In this post we additionally explore the NGFF (next-generation file format) OME-ZARR standard.
Zarr – or: How to save NumPy arrays
What is Zarr and why is it probably the most suitable file format for saving NumPy arrays?
How to read patch clamp recordings in WaveMetrics IGOR binary files (ibw) in Python
This is a mini tutorial on how to read patch clamp recordings in WaveMetrics IGOR binary files (*.ibw) in Python using the neo and igor packages.
How to add statistical annotations to matplotlib plots
This mini tutorial shows, how to add statistical annotations to matplotlib plots with just a few commands.
Make matplotlib plots look more appealing with just a few extra commands
Learn how to enhance matplotlib plots with just a few hacks.
Putting text sources into the Zettelkasten?
Should text sources (ebooks, PDF, website snapshots) be saved in a Zettelkasten?
On project notes in the Zettelkasten
Should project notes be a type of notes of their own in our Zettelkasten?
The Feynman problem-solving algorithm
Yet another problem-solving approach by Richard Feynman.
The Feynman method as an effective learning tool
The Feynman method can help you not only to remember new knowledge, but also to really and deeply understand it.
Variable Explorer in Jupyter Notebooks
Extend your Jupyter environment with Notebook Extensions and enable, e.g., the option to explore your currently defined variables in a running Jupyter session.
How DEVONthink’s auto-WikiLink feature changed my Zettelkasten workflow
DEVONthink’s automatic WikiLinks function is a powerful tool, both for discovering connections between notes – expected and unexpected ones – and for the automatized linking of these notes. In this post I briefly explain, how this feature has impacted my Z...
DEVONthink Markdown Table-of-Contents generator
I wrote a custom AppleScript for DEVONthink Markdown files, that bypasses the problem of broken links in the auto-generated Table-of-Contents (TOC) of MultiMarkdown (MMD).
DEVONthink Image Toolbox
I just shared a collection of AppleScripts on GitHub for handling images in DEVONthink.
Floating Back-to-top button for Markdown documents
You can quickly add a floating Back-to-top button to your Markdown documents in just two steps.
Using Obsidian as a Zettelkasten
In this post I show how you can quickly set up a Zettelkasten in Obsidian.
Using DEVONthink as a Zettelkasten
In this post I show how you can quickly set up a Zettelkasten in DEVONthink.
Use your Zettelkasten as a research, thinking and learning tool – Personal knowledge management as a system
In the last part of the series about personal knowledge management, we dive deeper into the Zettelkasten method and demonstrate, how to integrate all parts as an overall system into our research workflow.
Take smart notes with the Zettelkasten method
With the Zettelkasten method by Niklas Luhmann, we give the previously presented personal knowledge network a concrete shape and practical implementation. This is the second of three parts of the series about personal knowledge management.
Don’t take isolated notes, connect them! Vannevar Bush on building a self-organizing network of knowledge
In 1945, Vannevar Bush presented his concept of a self-organizing personal knowledge network by linking informational units with each other. This concept, that would later be known as the Hypertext concept or Hypertext theory, provides the theoretical base ...
Boost your research with a smart personal knowledge management system
My next posts will be a short series about personal knowledge management and how it can be integrated as a holistic system into our overall research workflow. The system is based on the Hypertext Theory and the Zettelkasten method, and its core element is t...
Clean Thesis: A simple and elegant LaTeX thesis template
If you’re looking for some inspiration for your thesis, I just came across Clean Thesis by Ricardo Langner, a simple and elegant LaTeX template for thesis documents.
Using Markdown for note-taking
It might be a bit difficult to learn at the beginning, but there are several benefits of taking personal notes in Markdown. Here is why I switched.
Opening a Jupyter notebook from GitHub in Binder: A step-by-step guide
Opening a Jupyter notebook from GitHub in Binder simplifies access to shared code and facilitates seamless collaboration. With just a few steps, you can launch and interact with Jupyter notebooks directly in your browser, without the need for complex setup ...
The quickest way to find help for Python commands: The help() command
Python’s built-in help system is probably the fastest way, to quickly look up Python commands and their syntax. It works without leaving your Python environment and is fully offline available.
On teaching
I strongly believe that teaching is not a unidirectional thing, but both sides, the participants and the teacher benefit from it. This is a personal comment on teaching.
My website is now completely cookie-free
I made several changes to my website to further increase the privacy protection. As a result, it runs now completely without cookies.
New Teaching Material: Python Cheat Sheets
I’ve started a collection of various Python cheat sheets that contain some useful and commonly used commands and usage examples.
New Teaching Material: Statistical data analysis and basic time series analysis with Python
I’ve added two new tutorials in the teaching section on statistical data analysis and basic time series analysis with Python.
New Teaching Material: Analyzing IGOR binary files of patch clamp recordings
I’ve added a new tutorial in the teaching section on how to read and process IGOR binary files (ibw) of patch clamp recordings.
Create fancy text styles with Unicode
I found an online font generator to create fancy text styles, simply by using Unicode letters.
New Teaching Material: Fiji short course
There is a new tutorial in the Teaching Material. It’s a short Fiji tutorial on analyzing biomedical image data.
On website subscriptions via RSS and Atom feeds
Personal opinion on how to create and maintain personal news feeds beyond the dependence on big social media and tech companies.
Free LaTeX editors
A list of currently freely available LaTeX editors (constantly updated).
Markdown vs. LaTeX for Scientific Writing
A comparison of Markdown and LaTeX in regard of scientific writing.
Free Markdown editors
A list of currently freely available Markdown editors (constantly updated).
Dealing with future posts in Jekyll
While drafting blog posts in Jekyll, you may want to keep some posts hidden from the public eye until they’re ready to be published. In the world of blogging with Jekyll, there are several effective methods to draft such posts without immediately publishing...
Running and testing your Jekyll site locally with custom options
Developing with Jekyll often requires running your site locally to test changes before deploying them live. Here is a handy yet useful one-line command that I usually use to run my Jekyll site locally with custom options.
Emojis for Jekyll via Jemoji
A how-to and a list of all currently working Emojis on Jekyll built websites.
strftime Cheat Sheet
Cheat Sheet on formatted date and time strings used, e.g., in Python, C/C++ or even on Jekyll websites by using Liquid tags.
Liquid Cheat Sheet
This Cheat Sheet gives an overview of Liquid syntax commands one might encounter while developing a Jekyll website.
Minimal Mistakes Cheat Sheet
A quick overview of available commands for creating content with the Minimal Mistakes Jekyll theme.
Supported syntax highlighting in Jekyll
A list of supported programming languages for Jekyll’s syntax highlighting.
How to use LaTeX in Markdown
A quick guide on how to enable MathJax support in your Markdown documents.
New Teaching Material: LaTeX Guide
I’ve added a LaTeX guide to the General Teaching Materials in the teaching section. It serves as a Getting started with LaTeX guide and as a LaTeX glossary.
New Teaching Material: Markdown Guide
I’ve composed a Markdown Guide for my teaching courses.
The Weierstrass function and the beauty of fractals
Fractals are captivating mathematical objects that exhibit intricate patterns and self-similarity at various scales. In this post, we explore the elegance and significance of the Weierstrass function, its relation to fractals and fractal geometry, and disc...
Feed subscriptions to this website
In order to follow updates of my website, I provide RSS/Atom feeds you can subscribe to.
Running a personal website with Jekyll
I have redesigned my website and moved it to a new host as well: I’m running it as personal Jekyll website hosted on GitHub now.
The Lotka-Volterra equations: Modeling predator-prey dynamics
The Lotka-Volterra system, also known as the predator-prey equations, is a mathematical model that describes the interaction between two species: predators and their prey. The system captures the dynamic relationship between the population sizes of predator...
Interactive COVID-19 data exploration with Jupyter notebooks
Amidst the ongoing challenges of the COVID-19 pandemic, I have written a Jupyter notebook that facilitates interactive exploration of COVID-19 data. You can select specific countries and visualize key aspects such as confirmed cases, deaths, and vaccination...
The SIR model: A mathematical approach to epidemic dynamics
In the wake of the COVID-19 pandemic, epidemiological models have garnered significant attention for their ability to provide insights into the spread and control of infectious diseases. One such model is the SIR model, forming the foundation for studying t...
The two-body problem
The two-body system is a classical problem in physics. It describes the motion of two massive objects that are influenced by their mutual gravitational attraction. The two-body problem is a special case of the n-body problem, which describes the motion of t...
Solving the Lorenz system using Runge-Kutta methods
In my previous post, I introduced the Runge-Kutta methods for numerically solving ordinary differential equations (ODEs), that are challenging to solve analytically. In this post, we apply the Runge-Kutta methods to solve the Lorenz system. The Lorenz syst...
Runge-Kutta methods for solving ODEs
In physics and computational mathematics, numerical methods for solving ordinary differential equations (ODEs) are of central importance. Among these, the family of Runge-Kutta methods stands out due to its versatility and robustness. In this post we compar...
Earth’s dipolar magnetic field
In physics and computational mathematics, numerical methods for solving ordinary differential equations (ODEs) are of central importance. Among these, the family of Runge-Kutta methods stands out due to its versatility and robustness. In this post we compar...
Restarting my website
In the wake of the COVID-19 pandemic, I have made the decision to relaunch my website. While I have previously utilized my website for smaller personal projects and showcasing my photographs, I now intend to broaden its scope. I will be posting on a range o...
German Angst
Co-effects of the Corona lockdown: people buy like crazy toilet paper, until nothing is left anymore. This is a copycat work, the original work from David Hugendick can be found on twitter ꜛ.
Posts from 2013 to 2020 moved to the archive
I just cleaned up my website and put a lot of old stuff from 2013 to 2020 into the archive.
Archive
Hello world
It is done! Welcome to my new website.
Study with Colored Pencils
Searching for a new desktop wallpaper, I took some photographs with colored pencils. For the first time, I worked with my little improvised studio. You can download all images as desktop-wallpapers (16:9, mid-res: ~3MB, hi-res: ~70 MB) for your personal use...
Rheinkirmes in Düsseldorf 2015
This weekend we visited the Rheinkirmes in Düsseldorf
Material Design
In 2014, Google introduced its new design language Material Design ꜛ. I was fascinated by its design concept:
IDAHOT (International Day Against Homophobia, Transphobia and Biphobia, May 17)
Today is the International Day Against Homophobia, Transphobia and Biphobia ꜛ. As a small contribution to the fight for equal rights, I’ve redesigned my “heart” graphic and I will share it on my social media accounts. Feel free to re-share it anytime.
Kiosk Gadget Gangster Shit
Things you do on a rainy Friday night
#fckafd
Demonstration against the far-right party AfD in Cologne.
#fckafdp
Spontaneous demonstration against the liberal party FDP in Cologne after Prime Minister election in Thuringia with support by the far-right party AfD.
ok cool
wuhaa! Thanks a lot to ok cool ꜛ for featuring my work! Please check out their websiteꜛ (or flickr or instagram) to see many more cool 😎 photographers 📸
About Weekend Stories
Weekend Stories is my on-going photographic diary project, where I collect everyday stories (mostly) occurring on the weekends.
Building New Universes
Lost&found: In the wake of the redesign of my website, I’ve rediscovered an old project from 2016, where I created imaginative sceneries by using water, oil, transparency film and a camera.
Publications
The search for a subsurface ocean in Ganymede with Hubble Space Telescope observations of its auroral ovals
Abstract We present a new approach to search for a subsurface ocean within Ganymede through observations and modeling of the dynamics of its auroral ovals. The locations of the auroral ovals oscillate due to Jupiter’s time-varying magnetospheric field seen ...
The far ultraviolet aurora of Ganymede
Abstract The far ultraviolet (FUV) aurora on Jupiter’s largest moon, Ganymede, is characterized by two distinct ovals in the northern and southern hemisphere, which have been investigated by several campaigns of the Hubble Space Telescope (HST) in the past ...
Morphology of Ganymede’s FUV auroral ovals
Abstract We study the morphology of Ganymede’s FUV aurora by analyzing spectral images obtained over the past two decades by the Space Telescope Imaging Spectrograph on board the Hubble Space Telescope. The observations cover the eastern and western elongat...
Memory trace interference impairs recall in a mouse model of Alzheimer’s disease
Abstract In Alzheimer’s disease (AD), hippocampus-dependent memories underlie an extensive decline. The neuronal ensemble encoding a memory, termed engram, is partially recapitulated during memory recall. Artificial activation of an engram can restore memor...
The diagonal band of broca regulates olfactory-mediated behaviors by modulating odor-evoked responses within the olfactory bulb
Abstract Sensory perception is modulated in a top-down fashion by higher brain regions to regulate the strength of its own input resulting in the adaptation of behavioral responses. In olfactory perception, the horizontal diagonal band of broca (HDB), embed...
Active Debris Removal
Abstract Eine wesentliche Kernkompetenz des Fraunhofer-Instituts für Naturwissenschaftlich-Technische Trendanalysen (INT) ist die flächendeckende, systematische und kontinuierliche Technologiefrühaufklärung, um technologische Entwicklungen frühzeitig zu ide...
Dual truncation of tau by caspase-2 accelerates its CHIP-mediated degradation
Abstract Intraneuronal aggregates of the microtubule binding protein Tau are a hallmark of different neurodegenerative diseases including Alzheimer’s disease (AD). In these aggregates, Tau is modified by posttranslational modifications such as phosphorylati...
Talks
HST/STIS observation of Ganymede’s aurora: Investigating the variability of the auroral ovals
Abstract We examine Space Telescope Imaging Spectrograph (STIS) observations of Ganymede’s auroral emissions acquired during two visits in 2010 and 2011 with the Hubble Space Telescope (HST) when Ganymede was at eastern elongation (ID 12244). The observatio...
Observations of Ganymede’s variable auroral ovals on leading side derived from HST/STIS
Abstract We investigate properties of Ganymede’s FUV auroral ovals using spectral images acquired during two visits in 2010 and 2011 with Hubble’s Space Telescope Imaging Spectrograph (HST/STIS campaign 12244) when Ganymede was at eastern elongation. We ana...
HST/STIS observation of Ganymede’s aurora: Investigating the variability of the auroral ovals
Abstract We analyze the variability of Ganymede’s FUV auroral ovals using spectral images acquired during two visits in 2010 and 2011 with Hubble’s Space Telescope Imaging Spectrograph (HST/STIS) when Ganymede was at eastern elongation. The observed electro...
The spatial structure and temporal variability of Ganymede’s auroral ovals from Hubble Space Telescope observations
Abstract We investigate properties of Ganymede’s FUV auroral ovals using spectral images acquired during the past two decades with Hubble’s Space Telescope Imaging Spectrograph (HST/STIS). The observations cover Ganymede at eastern and western elongation. W...
The spatial structure and temporal variability of Ganymede’s auroral ovals from Hubble Space Telescope observations
Abstract We analyze spectrally and spatially resolved images of Ganymede’s FUV-auroral ovals obtained during the past two decades by Hubble’s Space Telescope Imaging Spectrograph (HST/STIS). We find both, spatial inhomogeneities of the brightness-distribut...
The spatial structure and temporal variability of Ganymede’s auroral ovals from Hubble Space Telescope observations
Abstract We investigate properties of Ganymede’s OI 1356 Å and OI 1304 Å auroral ovals using spectral images acquired during the past two decades with Hubble’s Space Telescope Imaging Spectrograph (HST/STIS). The observations cover the leading and trailing ...
The applicability of spatial memory tests in the IntelliCage
Abstract We evaluate the automatic behavioral assessment system IntelliCage® for investigating cognitive functions of mice. Here, we apply a spatial memory test paradigm to a mouse model of two different tau-pathologies, which demonstrates the feasibility o...
MotilA – An open-source tool for automatized and standardized microglia process motility analysis
Abstract Fluorescence microscopy in combination with implanting a chronic window enables the consecutive in-vivo monitoring of cellular activity in the brain over long time periods. To handle both, the standardized and reproducible analysis of microglia pro...
Nature Conferences: AI, Neuroscience and Hardware: From Neural to Artificial Systems and Back Again
Abstract We developed a pipeline for automatic dendritic spine segmentation in volumetric in-vivo multi-photon images. Based on a FCN with U-Net as underlying network architecture, only few labeled training images are required. Our pipeline enables the furt...
Bernstein Conference
Abstract The automatic detection of dendritic spines is still a challenging and yet not fully resolved problem with regard to multi-photon microscopy. The emergence of convolutional neural networks (CNN) like U-Nets enabled the development of deep learning ...
Deep learning based 3D-segmentation of dendritic spines recorded with two-photon in vivo imaging
Abstract The automatic detection of dendritic spines in 3D is still a challenging and yet not fully resolved problem with regard to two-photon in-vivo imaging. The emergence of convolutional neural networks (CNN) like U-Nets1 enabled the development of deep...
Deep learning based 3D-segmentation of dendritic spines recorded with two-photon in vivo imaging
Abstract Bookꜛ
Remission after stress via enriched environment increases hippocampal dendritic spine density independent of microglia
Abstract Major depressive disorder (MDD) is a common disease of the central nervous system that leads to high socio-economic and clinical challenges. Chronic stress is suggested to be a major risk factor for the disease, but little is known about the underl...
Remission after stress via enriched environment increases hippocampal dendritic spine density independent of microglia
Abstract Major depressive disorder (MDD) is a common disease of the central nervous system that leads to high socio-economic and clinical challenges. Chronic stress is suggested to be a major risk factor for the disease, but little is known about the underl...
Deep learning based 3D-segmentation of dendritic spines recorded with two-photon in vivo imaging
Abstract The automatic detection of dendritic spines in 3D is still a challenging and yet not fully resolved problem with regard to two-photon in-vivo imaging. The emergence of convolutional neural networks (CNN) like U-Nets1 enabled the development of deep...
Teaching
Past courses
A summary of courses and lectures I was involved in during my studies and Ph. D.
MATLAB Workshop: A beginner’s guide into scientific programming and data analysis
Introductory workshop into scientific programming and data analysis with MATLAB. The workshop was held in the 4th DZNE Doctoral Retreat in Dresden, Germany (23 to 25 October 2019).
Python: Basics for Data Scientists
Introductory course into the Python programming language. The course is condensed to the minimum requirements for the use of Python in numerical data analysis. This is the preliminary course to the Python Neuro-Practical course.
Python: Neuro-Practical
The course is a collection of short tutorials tailored to practical Data Science problems in Neuroscience. The aim of these short tutorials is to demonstrate, how to think about problem solution in Python and how to find strategies and individual solutions ...
Fiji Short Course
A short introductory course on using Fiji for Ca2+ images.
Bioimage analysis with Napari
In this course, we will learn how to use the free open-source software (FOSS) Napari for bioimage analysis. Napari is a fast, interactive, multi-dimensional image viewer for Python. It’s designed for browsing, annotating, and analyzing large multi-dimension...
Assessing animal behavior
A short introduction into cutting-edge methods for assessing animal behavior in a multi-modal and high-throughput fashion and deciphering animal behavior and neuronal activity in latent space.
Teaching assessing animal behavior
Teaching bioimage analysis
Teaching fiji short course
Teaching material
Markdown Guide
Markdown guide with a broad overview of Markdown syntax and ready to use examples for direct application in your Markdown documents and Jupyter notebooks.
LaTeX Guide
A getting started with LaTeX guide.
Python Cheet Sheets
A collection of useful Python commands and application examples.
Minimal Python installation with miniconda
With miniconda, we can have minimal Python installation on any OS. Learn how to install it and how to use conda to create and manage virtual environments, install packages, run Python scripts and run Jupyter Notebooks and JupyterLab.
Teaching python cheat sheets
Python data I/O Cheat Sheet
This Cheat Sheet is a collection of common Python data I/O functions for Data Science applications.
Teaching python course
Teaching python course neuropractical
Analyzing patch clamp recordings
How to read IGOR binary ibw-files of patch clamp recordings and how to read and process a batch of files.
Using Fourier transform for time series decomposition
How to read IGOR binary ibw-files of patch clamp recordings and how to read and process a batch of files.
Improving matplotlib plots
How to read IGOR binary ibw-files of patch clamp recordings and how to read and process a batch of files.