A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals.

There is a recent increase in the use of multivariate analysis and pattern classification in prediction and real-time feedback of brain states from functional imaging signals and mapping of spatio-temporal patterns of brain activity. Here we present MANAS, a generalized software toolbox for performi...

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Bibliographic Details
Main Authors: Mohit eRana, Nalin eGupta, Josue Luiz eDalboni da rocha, Sangkyun eLee, Ranganatha esitaram
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-10-01
Series:Frontiers in Neuroscience
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Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00170/full
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Summary:There is a recent increase in the use of multivariate analysis and pattern classification in prediction and real-time feedback of brain states from functional imaging signals and mapping of spatio-temporal patterns of brain activity. Here we present MANAS, a generalized software toolbox for performing online and offline classification of fMRI signals. MANAS has been developed using MATLAB, LIBSVM and SVMlight packages to achieve a cross-platform environment. MANAS is targeted for neuroscience investigations and brain rehabilitation applications, based on neurofeedback and brain-computer interface (BCI) paradigms. MANAS provides two different approaches for real-time classification: subject dependent and subject independent classification. In this article, we present the methodology of real-time subject dependent and subject independent pattern classification of fMRI signals; the MANAS software architecture and subsystems; and finally demonstrate the use of the system with experimental results.* M. Rana and N. Gupta are equally contributing authors.
ISSN:1662-453X