Massachusetts Institute of Technology
Sign in | Create Account
Default-xlarge-collection

9.29 Introduction to Computational Neuroscience (2004)


Collection videos

Introduction

Introduction

Added 4 years ago | 01:18:00 | 6039 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

Correlation and Convolution

Added 4 years ago | 01:21:00 | 4561 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 Regression

MATLAB, Statistics, and Linear Regr...

Added 4 years ago | 01:06:00 | 5265 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 and correlation in continuous time

Wiener-Hopf equations & Convolution...

Added 4 years ago | 01:18:00 | 3555 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 the Visual System

Spike Train Averaging & Basics of t...

Added 4 years ago | 01:18:00 | 3344 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.

See all 26 videos

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.