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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2013-10-01
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| Series: | Frontiers in Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00170/full |
| _version_ | 1818523804480045056 |
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| author | Mohit eRana Mohit eRana Mohit eRana Nalin eGupta Josue Luiz eDalboni da rocha Sangkyun eLee Ranganatha esitaram Ranganatha esitaram Ranganatha esitaram |
| author_facet | Mohit eRana Mohit eRana Mohit eRana Nalin eGupta Josue Luiz eDalboni da rocha Sangkyun eLee Ranganatha esitaram Ranganatha esitaram Ranganatha esitaram |
| author_sort | Mohit eRana |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-11T05:49:17Z |
| format | Article |
| id | doaj.art-b3ef9758452244baa8fc84c51ac19cad |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-12-11T05:49:17Z |
| publishDate | 2013-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-b3ef9758452244baa8fc84c51ac19cad2022-12-22T01:18:52ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2013-10-01710.3389/fnins.2013.0017057290A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals.Mohit eRana0Mohit eRana1Mohit eRana2Nalin eGupta3Josue Luiz eDalboni da rocha4Sangkyun eLee5Ranganatha esitaram6Ranganatha esitaram7Ranganatha esitaram8Institute of medical psychology and behavioral neurobiologyGraduate School of Neural & Behavioural Sciences | International Max Planck Research SchoolUniversity of FloridaIndian Institute of Technology KharagpurUniversity of FloridaMax plank institute for biological cyberneticsInstitute of medical psychology and behavioral neurobiologyUniversity of FloridaSree Chitra Tirunal Institute for Medical Sciences & TechnologyThere 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.http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00170/fullClassificationNeurofeedbackSVMmultivariate analysispattern recognitionfMRI BOLD |
| spellingShingle | Mohit eRana Mohit eRana Mohit eRana Nalin eGupta Josue Luiz eDalboni da rocha Sangkyun eLee Ranganatha esitaram Ranganatha esitaram Ranganatha esitaram A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals. Frontiers in Neuroscience Classification Neurofeedback SVM multivariate analysis pattern recognition fMRI BOLD |
| title | A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals. |
| title_full | A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals. |
| title_fullStr | A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals. |
| title_full_unstemmed | A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals. |
| title_short | A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals. |
| title_sort | toolbox for real time subject independent and subject dependent classification of brain states from fmri signals |
| topic | Classification Neurofeedback SVM multivariate analysis pattern recognition fMRI BOLD |
| url | http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00170/full |
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