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Tag Archives: machine learning
Annual report of my intuition about the brain (2022)
How does the brain work and how can we understand it? To view this big question from a broad perspective at the end of each year, I’m reporting some of the thoughts about the brain that marked me most during … Continue reading
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
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
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
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
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
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
Layer-wise decorrelation in deep-layered artificial neuronal networks
The most commonly used deep networks are purely feed-forward nets. The input is passed to layers 1, 2, 3, then at some point to the final layer (which can be 10, 100 or even 1000 layers away from the input). … Continue reading
Posted in Data analysis, machine learning, Neuronal activity
Tagged CNN, Data analysis, deep learning, machine learning, Network analysis, Python
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A blog about neurophysiology 