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Category Archives: machine learning
Ambizione fellowship and an open PhD position
I’m glad to share that I am going to start my own junior research group at the University of Zurich in March 2023! As an Ambizione fellow, I will receive funding for my own salary, some equipment, consumables and a … Continue reading
Self-supervised denoising of calcium imaging data
This blog post is about algorithms based on deep networks to denoise raw calcium imaging movies. More specifically, I will write about the difficulties to interprete their outputs, and on how to address these limitations in future work. I will … Continue reading
Video introduction to CASCADE
A video with tutorial on CASCADE, a supervised method to infer spike rates from calcium imaging data. Continue reading
Public peer review files
Peer-review is probably the most obscure part of the publication of scientific results. In this blog post, I would like to make the point that the best way to learn about it – except by being directly involved – is … Continue reading
Posted in Calcium Imaging, Imaging, machine learning, Microscopy, Neuronal activity, Review
Tagged deep learning, Microscopy, neuroscience, peer review
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Annual report of my intuition about the brain (2021)
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
5 reasons why to use Cascade for spike inference
Our paper on A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging is out now in Nature Neuroscience. It consists of a large and diverse ground truth database with simultaneous calcium imaging and juxtacellular recordings … Continue reading
Online spike rate inference with Cascade
To infer spike rates from calcium imaging data for a time point t, knowledge about the calcium signal both before and after time t is required. Our algorithm Cascade (Github) uses by default a window that is symmetric in time … Continue reading
Temporal dispersion of spike rates from deconvolved calcium imaging data
On Twitter, Richie Hakim asked whether the toolbox Cascade for spike inference (preprint, Github) induces temporal dispersion of the predicted spiking activity compared to ground truth. This kind of temporal dispersion had been observed in a study from last year … Continue reading
Annual report of my intuition about the brain (2020)
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 Data analysis, machine learning, Network analysis, Neuronal activity, Reviews
Tagged complexity, deep learning, evolution, self-organization
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Simultaneous calcium imaging and extracellular recording from the same neuron
Calcium imaging is a powerful method to record from many neurons simultaneously. But what do the recorded signals really mean? This question can only be properly addressed by experiments which record both calcium signals and action potentials from the same … Continue reading
A blog about neurophysiology 