Dr. Sitaram’s lab publishes software for rapid decoding and feedback of brain states from FMRI signals

Dr. Sitaram and his co-workers reported the release of an open toolbox for rapid, online decoding of brain’s functional states from functional magnetic resonance imaging signals.  The technical article was published recently in the Journal of Frontiers in Neuroscience: http://www.frontiersin.org/Journal/10.3389/fnins.2013.00170/abstract. The co-authors of his group are post-doctoral researcher Mohit Rana and PhD student Josue Dalboni Rocha.

There is enormous interest 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. Dr. Sitaram’s lab developed 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. The toolbox provides two different approaches for real-time classification: subject dependent and subject independent classification. The journal article presents the methodology of real-time subject dependent and subject independent pattern classification of fMRI signals; the MANAS software architecture and subsystems; and finally demonstrates the use of the system with experimental results. The figure below shows the MANAS graphical toolbox.


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