A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals
Mohit Rana1, Nalin Gupta, Josue L Dalboni Da Rocha
1Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen Tübingen, Germany ; Graduate School of Neural & Behavioural Sciences International Max Planck Research School, University of Tübingen Tübingen, Germany ; Department of Biomedical Engineering, University of Florida Gainesville, FL, USA.
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.
