Research Group Leader

Prof. Dr. Matthias Bethge
Prof. Dr. Matthias Bethge
Phone: +49 7071 29-89017
Fax: +49 7071 29-25015


Secretary: Heike König
Phone: +49 7071 29-89018
Fax: +49 7071 29-25015


GPmaps: Estimating orientation preference maps from optical imaging data using Gaussian Process methods

Matlab-code implementing the Gaussian Process based methods for estimating orientation preference maps described in Macke et al, NIPS 2009 and Macke at al, 2010, under revision. The package contains code for

(1) Generating synthetic orientation preference maps and noisy imaging measurements
(2) Estimating orientation preference maps using Gaussian process methods or vector averaging
(3) Sampling from the posterior distribution over maps

While the current implementation is useful for orientation preference maps only, it should be straightforward to adapt it for the estimation of other cortical maps as well.


To install the code, just unzip the file and add all the folders originating from it to your matlab path. Then, run the script DemoScript.m, which contains a brief tutorial on how to use the methods.

The code is published under the GNU Gneral Public License
The code is provided "as is" and has no warranty whatsoever.


CODE (294 KB)

This file contains all the functions necessary to run the Gaussian Process methods, as well as the demo-file DemoScript.m, which contains a brief tutorial on how to use the methods.

imagingdata.mat(90 MB)

Imaging data (optical imaging of intrinsic signals) used in the paper. The data is already normalized, and consists of one four-dimensional array of dimensions 126 by 252 by 8 by 100. The first two dimensions are pixels, the third dimension stimulus conditions, and the fourth dimension trials.
Last updated: Mittwoch, 27.02.2013