Category Archives: electrophysiology

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

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Annual report of my intuition about the brain

There are not many incentives for young neuroscientists to think aloud about big questions. Due to lack both of knowledge and authority, discussing very broad questions like how the brain works risks to be embarrassing at best. Still, I feel … Continue reading

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Whole-cell patch clamp, part 4: look and feel

In previous blog posts, I have been discussing some aspects of whole-cell patch clamp recordings ([1], [2], [3], [4]). Today, I will show some instructive videos that I recorded during experiments. I’m hoping that they will convey the look and feel … Continue reading

Posted in Calcium Imaging, electrophysiology, Imaging, Microscopy, Neuronal activity, zebrafish | Tagged , , , | 1 Comment

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

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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

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How deconvolution of calcium data degrades with noise

How does the noisiness of the recorded calcium data affect the performance of spiking-inferring deconvolution algorithms? I cannot offer a rigorous treatment of this question, but some intuitive examples. The short answer: If a calcium transient is not visible at … Continue reading

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A convolutional network to deconvolve calcium traces, living in an embedding space of statistical properties

As mentioned before (here and here), the spikefinder competition was set up earlier this year to compare algorithms that infer spiking probabilities from calcium imaging data. Together with Stephan Gerhard, a PostDoc in our lab, I submitted an algorithm based on convolutional networks. Looking … Continue reading

Posted in Calcium Imaging, Data analysis, electrophysiology, Imaging, machine learning, Neuronal activity | Tagged , , , , | 2 Comments