Tutorials

A set of matlab tutorials have been prepared to allow students to explore some areas in more detail. To run the tutorials, fire up matlab and type:
> cd /Groups/csh06/Tutorials
> Startup
Startup sets the paths you will need to execute the code. To run a tutorial, simply open the tutorial in matlab and execute the code piecewise by copying small sections into the command window.

Tutorials


bayesTutorial
Some basic concepts related to Bayesian estimation applied to a well-determined linear problem

chi2TestTutorial
A simple tutorial of the chi-square distribution and chi-square test for whether a sample was drawn from a known distribution.

choiceProbabilityTutorial
Explores the relationship between single neuron activity in area MT and psychophysical motion direction discrimination

colorConstancyTutorial
A simple simulation of a color constancy algorithm

colorRenderingTutorial
Introduces some standard colormetric calculations

colorSpaceTutorial
Introduces some ideas about color space transformations

DiffEqTutorial
Introduction to differential equations, including applications to phototransduction

FourierTutorial
Introduction to Fourier analysis

eye movements
A number of eye movement tutorials can be found in /csh/tutorials/eyemove

imageFormationTutorial
Explores basic concepts of image formation, including degrees of visual angle, point-spread and line-spread functions

imageTutorial
Explores basic image manipulation and image statistics, including two-dimensional filtering and the discrete Fourier transform

intAndFireTutorial
Model of a simple integrate and fire neuron

leastsqTutorial
Introduction to fitting data with least squares

LinearAlgebraTutorial
Review of linear algebra

linSysTutorial
Basics of linear systems analysis

maskingTutorial
Takes you through an example of how to analyze and fit a psychophysics experiment using MATLAB. This example works through a "fake" spatial pattern detection experiment

momentGeneratingFuncTutorial
Introduces the momenet generating function, Wald's identity, and their connections to psychometric functions

motionTutorial
Presents some concepts for representing and analyzing visual motion (the Motion Energy model of Adelson & Bergen)

MTmodel
2-stage model for neurons in area MT (Simoncelli & Heeger, VisRes 1998).

nonlinearPoolingTutorial
Humans can reliably detect a dim light that produces 5-10 photon absorptions spread over 500 rods. This tutorial shows how a nonlinearity in the rods increases detectability of dim light.

PCATutorial
Introduction to princpal components analysis

PhotonDetectionTutorial
The goal of this tutorial is to develop your intuitions regarding Bayesian approaches to decision making. Includes and introduction to princpal components analysis

poissonTutorial
Introduces the Poisson model of stochastic neuronal firing

pyramidTutorial
A brief introduction to multi-scale pyramids for image processing

redundreduct
A demonstration of how center-surround spatial receptive fields decorrelate images in space

samplingTutorial
Explores the errors that can arise through image subsampling and reconstruction

sdtTutorial
Signal detection theory

STCovTutorial
Introduction to spike-triggered covariance and recovery of a linear subspace from white noise experiments (e.g. reverse correlation for complex cells)

stochasticProcessesTutorial
An introduction to stochastic processes and their application to spike trains (including Poisson and gamma distributions)

svdTutorial
Singular value decomposition and pricipal components analysis

whiteNoiseTutorial
Simulates a white noise experiment (“reverse correlation”)