Filtering – A practical guide

Finding good information on how filters work, what the different types of filters mean, and how you should filter your data is hard. Lots of explanations only make sense if you have a year or two of electrical engineering education, and most of the rest are just a list of rules of thumb. I want to try to get you to a place where you can test your own filter settings, and show you the importance of the rules of thumb without going into the relatively complex math that is often used to explain filters. Warning: a lot of the code I’m going to use requires the Matlab Signal Processing Toolbox. If you don’t have it, you wont be able to execute the code yourself, but hopefully you’ll still be able to follow along with the logic.
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Neuronal Modelling – The very basics. Part 2: Hodgkin and Huxley.

In part 1 of this post, I discussed the very basics of neuronal modelling. We discussed the fundamental equations that explain how ion channels create current and how current changes the membrane potential. With that knowledge, we created a simple one-compartment model that had capacitance, and a leak ion channel. But we didn’t have any action potentials. In order to model action potentials, we need to insert some mechanism to generate them. There are several ways of doing this, but the most common is the Hodgkin and Huxley (HH) model. I’m going to dive straight in to understanding the HH model, and as usual, I’m going to start from the ground floor.

\mathbf{\overset{n}{Open}} \overset{\beta}{\rightarrow} \mathbf{\overset{1-n}{Closed}}

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