Modeling a neuron with python
This course is an introduction to python for neuroscience and it is based on the Neuromatch academy content. You will learn the basics of python. After this, you will know how to study a neuron dataset with python, make raster plots, obtaining the inter-spike interval distribution. We briefly study functions to approximate this distribution. We will use a popular dataset known as Steinmetz, which consists of multi-arrays electrodes of several regions of the mouse brain. As a core part of this course, you will learn how to model the electrical activity of a neuron´s membrane. We apply simple math operations and Ohm´s Law to achieve this goal. Also, several ways of improving the model are shown. Furthermore, we will use an analogy with electronics in order to achieve this goal.
What you’ll learn
- Use Python to understand a multiarray neuronal dataset.
- Use Python to understand the neuronal spiking distribution.
- Take advantage of Python to make graphics.
- Know the principles of Modelling Neurons with Python.
Course Content
- Introduction –> 1 lecture • 9min.
- The first steps to analyze a neuronal dataset –> 5 lectures • 43min.
- Modelling a neuron –> 8 lectures • 1hr 8min.
Requirements
This course is an introduction to python for neuroscience and it is based on the Neuromatch academy content. You will learn the basics of python. After this, you will know how to study a neuron dataset with python, make raster plots, obtaining the inter-spike interval distribution. We briefly study functions to approximate this distribution. We will use a popular dataset known as Steinmetz, which consists of multi-arrays electrodes of several regions of the mouse brain. As a core part of this course, you will learn how to model the electrical activity of a neuron´s membrane. We apply simple math operations and Ohm´s Law to achieve this goal. Also, several ways of improving the model are shown. Furthermore, we will use an analogy with electronics in order to achieve this goal.
Finally, you will learn to perturb the model in order to study the effects of noise and direct current. All the lectures are walked through using google collaboratory, so it is not necessary to install anything. The scripts are shared at the end of each section.
The basics of python are covered in the first lecture. However, it is not intended for beginners. New courses are coming in order to continue the study of neurons with python.