Computational Neuroscience

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  • Week 1 - Introduction & Basic Neurobiology (Rajesh Rao)
    This module includes an Introduction to Computational Neuroscience, along with a primer on Basic Neurobiology.
  • Week 2 - What do Neurons Encode? Neural Encoding Models (Adrienne Fairhall)
    This module introduces you to the captivating world of neural information coding. You will learn about the technologies that are used to record brain activity. We will then develop some mathematical formulations that allow us to characterize spikes from neuron...
  • Week 3 - Extracting Information from Neurons: Neural Decoding (Adrienne Fairhall)
    In this module, we turn the question of neural encoding around and ask: can we estimate what the brain is seeing, intending, or experiencing just from its neural activity? This is the problem of neural decoding and it is playing an increasingly important role ...
  • Week 4 - Information Theory & Neural Coding (Adrienne Fairhall)
    This module will unravel the intimate connections between the venerable field of information theory and that equally venerable object called our brain.
  • Week 5 - Computing in Carbon (Adrienne Fairhall)
    This module takes you into the world of biophysics of neurons, where you will meet one of the most famous mathematical models in neuroscience, the Hodgkin-Huxley model of action potential (spike) generation. We will also delve into other models of neurons and ...
  • Week 6 - Computing with Networks (Rajesh Rao)
    This module explores how models of neurons can be connected to create network models. The first lecture shows you how to model those remarkable connections between neurons called synapses. This lecture will leave you in the company of a simple network of integ...
  • Week 7 - Networks that Learn: Plasticity in the Brain & Learning (Rajesh Rao)
    This module investigates models of synaptic plasticity and learning in the brain, including a Canadian psychologist's prescient prescription for how neurons ought to learn (Hebbian learning) and the revelation that brains can do statistics (even if we ourselve...
  • Week 8 - Learning from Supervision and Rewards (Rajesh Rao)
    In this last module, we explore supervised learning and reinforcement learning. The first lecture introduces you to supervised learning with the help of famous faces from politics and Bollywood, casts neurons as classifiers, and gives you a taste of that bedro...




Rajesh P. N. Rao
Computer Science & Engineering

Adrienne Fairhall
Associate Professor
Physiology and Biophysics


华盛顿大学是位于华盛顿州西雅图市的一所公立研究型大学。华盛顿大学成立于 1861 年 11 月 4 日,原名领土大学,是西海岸历史最悠久的大学之一,在西雅图建市约十年后落户西雅图。

该大学的主校区位于该市的大学区,占地 703 英亩,在塔科马和博特尔也有校区。总的来说,华盛顿大学由 500 多座建筑和 2000 多万平方英尺的总面积组成,其中包括世界上最大的图书馆系统之一,拥有 26 个学术图书馆、艺术中心、博物馆、实验室、演讲厅和体育馆。



Coursera是一家数字公司,提供由位于加利福尼亚州山景城的计算机教师Andrew Ng和达芙妮科勒斯坦福大学创建的大型开放式在线课程。

Coursera与顶尖大学和组织合作,在线提供一些课程,并提供许多科目的课程,包括:物理,工程,人文,医学,生物学,社会科学,数学,商业,计算机科学,数字营销,数据科学 和其他科目。

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