Category Archives: Data analysis

Matlab magic spells

Most neuroscientists who analyze their data themselves use either Matlab or Python or both – the use of R is much less common than in other fields of biology. I’ve been working with Matlab on a daily basis for >10 … Continue reading

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Annual report of my intuition about the brain (2019)

How does the brain work and how can we understand it? I want to make it a habit to report some of the thoughts about the brain that marked me most during the past twelve month at the end of … Continue reading

Posted in Calcium Imaging, Data analysis, electrophysiology, machine learning, Network analysis, Neuronal activity, Review | Tagged , , , , , , , | 7 Comments

Review: An artificial ground truth for calcium imaging

Selected paper: Charles, Song, Tank et al., Neural Anatomy and Optical Microscopy Simulation (NAOMi) for evaluating calcium imaging methods, bioRxiv (2019). What is the paper about? Calcium imaging is a central method to observe neuronal activity in the brain of … Continue reading

Posted in Calcium Imaging, Data analysis, Imaging, Microscopy, Neuronal activity, Reviews | Tagged , , , , | 2 Comments

The power of correlation functions

During my physics studies, I got to know several mathematical tools that turned out to be extremely useful to describe the world and to analyze data, for example vector calculus, fourier analysis or differential equations. Another tool that I find … Continue reading

Posted in Calcium Imaging, Data analysis, electrophysiology | Tagged , , , , | 4 Comments

Precise synaptic balance of excitation and inhibition

The main paper of my PhD just got published: Rupprecht and Friedrich, Precise Synaptic Balance in the Zebrafish Homolog of Olfactory Cortex, Neuron (2018). (PDF) You might like it if you are also interested in Classical balanced networks Things you … Continue reading

Posted in Calcium Imaging, Data analysis, electrophysiology, Network analysis, Neuronal activity, zebrafish | Tagged , , , , | 1 Comment

Entanglement of temporal and spatial scales in the brain, but not in the mind

In physics, many problems can be solved by a separation of scales and thereby become tractable. For example, let’s have a look at surface waves on water: they are rather easy to understand when the water wave-length is much larger … Continue reading

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Blue light-induced artifacts in glass pipette-based recording electrodes

Recently, I was carrying out whole-cell voltage-clamp and LFP recordings with simultaneous optogenetic activation of a channelrhodopsin using blue light. Whole-cell voltage clamp techniques can record the input currents seen by a neuron (previously on this blog [1], [2]); an … Continue reading

Posted in Data analysis, electrophysiology, Neuronal activity | Tagged , | 2 Comments

Open access 3D electron microscopy datasets of brains

One of the coolest technical developments in neuroscience during the last decade has been driven by 3D electron microscopy (3D EM). This allowed to cut large junks of small brains (or small junks of big brains) into 8-50 nm thick … Continue reading

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How well do CNNs for spike detection generalize to unseen datasets?

Some time ago, Stephan Gerhard and I have used a convolutional neural network (CNN) to detect neuronal spikes from calcium imaging data. (I have mentioned this before, here, here, and on Github.) This method is covered by the spikefinder paper … Continue reading

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A list of cognitive biases

There are a handful of cognitive biases that are well-known to most scientists: confirmation bias, the Dunning-Kruger effect, the hindsight bias, the recency effect, the planning fallacy,┬áloss aversion, etc.. Although they should not be taken as universal laws (for example, … Continue reading

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