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

Rana, N., Gupta, M., Dalboni Da Rocha, J., Lee, S., & Sitaram, R. (2013). A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals. Frontiers in Neuroscience, 7: 170, pp. 1-11. doi:10.3389/fnins.2013.00170.

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Rana, N, Author
Gupta, M, Author
Dalboni Da Rocha, JL, Author
Lee, Sangkyun1, 2, Author           
Sitaram, Ranganatha, Author           
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: 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.

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 Dates: 2013-10
 Publication Status: Published online
 Pages: -
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 Identifiers: DOI: 10.3389/fnins.2013.00170
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Title: Frontiers in Neuroscience
  Other : Front Neurosci
Source Genre: Journal
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Publ. Info: Lausanne, Switzerland : Frontiers Research Foundation
Pages: - Volume / Issue: 7 Sequence Number: 170 Start / End Page: 1 - 11 Identifier: ISSN: 1662-4548
ISSN: 1662-453X
CoNE: https://pure.mpg.de/cone/journals/resource/1662-4548