4.3 Article

MANIA-A Pattern Classification Toolbox for Neuroimaging Data

Journal

NEUROINFORMATICS
Volume 12, Issue 3, Pages 471-486

Publisher

HUMANA PRESS INC
DOI: 10.1007/s12021-014-9223-8

Keywords

Pattern classification; Neuroimaging software; Machine learning; fMRI; MVPA

Ask authors/readers for more resources

Conventional univariate statistics are common and widespread in neuroimaging research. However, functional and structural MRI data reveal a multivariate nature, since neighboring voxels are highly correlated and different localized brain regions activate interdependently. Multivariate pattern classification techniques are capable of overcoming shortcomings of univariate statistics. A rising interest in such approaches on neuroimaging data leads to an increasing demand of appropriate software and tools in this field. Here, we introduce and release MANIA-Machine learning Application for NeuroImaging Analyses. MANIA is a Matlab based software toolbox enabling easy pattern classification of neuroimaging data and offering a broad assortment of machine learning algorithms and feature selection methods. Between groups classifications are the main scope of this software, for instance the differentiation between patients and controls. A special emphasis was placed on an intuitive and easy to use graphical user interface allowing quick implementation and guidance also for clinically oriented researchers. MANIA is free and open source, published under GPL3 license. This work will give an overview regarding the functionality and the modular software architecture as well as a comparison between other software packages.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available