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Maximum Likelihood Multisensory Integration Toolbox

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Maximum Likelihood Multisensory Integration Toolbox

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15 Apr 2015 (Updated )

This toolbox tests multisensory psychophysical data for statistically optimal perception.

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Description

Humans combine redundant multisensory estimates into a coherent multimodal percept. Experiments in cue integration have shown for many modality pairs and perceptual tasks that multisensory information is fused in a statistically optimal manner: Perceptual judgments take the unimodal sensory reliability into consideration and combine the senses according to the rules of Maximum Likelihood Estimation to maximize overall perceptual precision.
This toolbox, created by Loes van Dam and Marieke Rohde, serves as a tool for analysing psychophysical data in terms of whether or not such statistically optimal integration of the senses occurs. The toolbox expects both unimodal (single cue) as bimodal (multiple cue) psychophysical data to perform this analysis. Further information on how to use the toolbox can be found in the file "toolbox_documentation.pdf" located inside the toolbox folder.
The principles behind optimal multisensory integration and how to measure it are explained in the following paper:
Statistically Optimal Multisensory Cue Integration: A Practical Tutorial
by Rohde, M., van Dam, L.C.J. & Ernst, M.O.
in Multisensory Research 2015
doi:10.1163/22134808-­‐00002510
Please cite this paper if you use the toolbox.

Required Products Statistics and Machine Learning Toolbox
MATLAB
MATLAB release MATLAB 7.10 (R2010a)
MATLAB Search Path
/
/MLEtoolbox
Other requirements This version has been tested in both MATLAB R2010a and MATLAB R2014b. Note that the code may not be functional for MATLAB versions older than R2010a.
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Updates
15 Apr 2015 1.1

corrected copyright.

15 Apr 2015 1.2

Corrected copyright.

05 Oct 2015 1.3

The following updates were performed:
- Updated data-set for the example experiment
- Updated documentation
- Bug-fix: corrected error bars for population results.

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