Building a large population of neurons requires a lot of programming and great sensitivity of picking network parameters. You need to specify all the parameters all well to be able to record from your network. — If you are studying computational neuroscience, chances are you came from different backgrounds such as mathematics, physics, computer science or simply physiology. I myself have a background of physics.

In the brain, the neuron only activates in a fraction of time. we call this activation, spiking of a neuron. These spiking neurons are the building blocks of future deep learning. — Introduction: As we go further into developing new neural network architectures, it seems that we’re going to reach some point where there’s no more progressing involves. Scientists come with the idea of getting inspiration from mother nature and use biological neuron models to boost up the speed of DNNs (Deep Neural…

Create stunning plots is not that hard you think. You just need to do some tricks that I didn’t see people use them that much. — Believe it or not, visualization is important. Whether it’s a simple report for your 101 class of something! or it’s a paper you’re trying to publish in a scientific journal, you have to put times on your plots. You can use professional visualizations in your presentation to report how efficient…

The focus of this post is on filtering frequencies and why we need it. And I’m sure you can find dozens of good tutorials on how to take Fourier transform of your data/signals — Introduction: As a person who studies computational neuroscience, there’s a great deal of my time spending on brain signals and then processing those signals. If we can assume that signals are the sum of some pure sin waves with different frequencies (which in the majority of topics we can) then we…