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Dynamic scientific visualizations in the browser for Python users
As a scientist, interacting with data allows you to gain new insight into the phenomena you’re studying. If you read the New York Times, the D3 docs or you browse distill, you’ll see impressive browser-based visualizations – interactive storytelling that not only accurately represent data but bring your attention to surprising aspects of it. Making…
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Accelerating progress in brain recording tech
In Stevenson and Kording (2011), the authors estimated that every 7.4 years, the number of neurons we can record with doubles. Think of it as Moore’s law for brain recordings. Since then, Stevenson has updated the estimate, which now stands at 6 years. Could it be that progress itself is accelerating? Matteo Carandini raised a…
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Is early vision like a convolutional neural net?
Early convolutional neural net (CNNs) architectures like the Neocognitron, LeNet and HMAX were inspired by the brain. But how much like the brain are modern CNNs? I made a pretty strong claim on Twitter that the early visual processing is nothing like a CNN: In typical Twitter fashion, my statement was a little over-the-top, and…
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Building Neuromatch Academy
Neuromatch Academy 2020 is a three-week online summer school in computational neuroscience that took place in July of 2020. We created interactive notebooks covering all aspects of computational neuroscience – from signals and models of spikes to machine learning and behaviour. We hired close to 200 TAs to teach this material to 1,700 students from…
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Scraping webpages with developer tools and Selenium
There’s a lot of interesting statistics you can do by scraping websites, whether it’s reading tables from Wikipedia, grabbing and aggregating climate change tables from government websites, or quantifying the exponential growth of covid-19 articles on Medium. Many of these pages will have easy-to-use methods to download the data in a develop-friendly format, for example…
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Reverse correlation: linearizing black-box functions
Reverse correlation is a tried-and-tested nonlinear systems identification method to understand biological neurons. The idea is to open the black box that is a biological neuron by using random stimuli to probe how the neuron responds. We present a series of random stimuli to a sensory neuron. By averaging those that generated a response, we…
xcorr: AI & neuro 