9.29 Introduction to Computational Neuroscience (2004)
Collection videos
Introduction
Added over 2 years ago | 01:18:00 | 4836 views
In this first lecture of the class, an overview of the course structure is provided, followed by the dual definition of Computational Neuroscience as A) using a computer to study the brain, and B) studying the brain as a computer, then a...
Correlation and Convolution
Added over 2 years ago | 01:21:00 | 3772 views
In this lecture, we'll learn about two mathematical operations that are commonly used in signal processing, convolution and correlation. The convolution is used to linearly filter a signal, for example to smooth a spike train to estimate...
MATLAB, Statistics, and Linear Regr...
Added over 2 years ago | 01:06:00 | 4779 views
MATLAB is a powerful software package for matrix manipulation. It’s a very useful language not only for this class, but for a variety of scientific applications, and is used widely thoughout industry. Just as when you have a hammer, ever...
Wiener-Hopf equations & Convolution...
Added over 2 years ago | 01:18:00 | 3034 views
In this lecture the famous Wiener-Hopf equations are introduced, and it is shown how they can be used to calculate the filter in a model of the neuron, where the output is a linear filtration of the stimulus. In addition, convolution an...
Spike Train Averaging & Basics of t...
Added over 2 years ago | 01:18:00 | 2857 views
In this lecture, the discussion of the Weiner Hopf equations is continued, applying this to white noise analysis, and spike train averaging. An introduction to the basics of the visual system, and visual receptive fields is given.
Collection details
- Category
- Education
- Language
- English
- Website
- 9.29 Introduction to Computational Neuroscience (2004) (hebb.mit.edu/courses/9.29/2004/lectures/index.html)
Subscribe
You can have new episodes delivered directly to your computer as soon as they’re available.