Python for Neuroscience, level 1

本课程介绍了用于神经科学的 Python，它基于 Neuromatch 学院的内容。您将学习 Python 的基础知识。在此之后，您将知道如何使用 python 研究神经元数据集，制作栅格图，获得脉冲间间隔分布。我们简要研究了近似此分布的函数。我们将使用一个名为 Steinmetz 的流行数据集，它由小鼠大脑多个区域的多阵列电极组成。作为本课程的核心部分，您将学习如何模拟神经元膜的电活动。我们应用简单的数学运算和欧姆定律来实现这一目标。此外，还展示了几种改进模型的方法。此外，我们将使用电子学类比来实现这一目标。

最后，您将学习扰动模型以研究噪声和直流电的影响。所有的讲座都是使用谷歌合作完成的，所以不需要安装任何东西。脚本在每个部分的末尾共享。

第一讲介绍了python的基础知识。但是，它不适合初学者。新课程即将推出，以继续使用 python 研究神经元。

你会学到什么

• 使用 Python 理解多阵列神经元数据集
• 使用 Python 了解神经元尖峰分布
• 利用 Python 制作图形
• 了解使用 Python 建模神经元的原理

要求

了解 Python 的基础知识很重要。这是一个中级课程。此外，您应该至少参加过一门神经科学本科课程。

本课程适用于谁

• 有兴趣在神经科学领域进行研究生学习并需要知道如何处理神经元数据集的人
• 工人正在寻找工具来提高他们的研究技能
• 希望提高神经科学编程技能的人

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 14 lectures (1h 59m) | Size: 839.2 MB

Modeling a neuron with python

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

Requirements

It is important that you know the basics of Python. This is an intermediate course. Also you should have taken at least one undergraduate course in neuroscience.

Description

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.

Who this course is for

• People interested in doing graduated studies in Neuroscience and need to know how to handle neuronal datasets
• Workers looking for tools to improve their research skills
• People looking to improve their programming skills in Neuroscience