Seminar Report on Real-Time Neuroscience using Open-VIBE for Computer Science Students

Introduction to Real-Time Neuroscience using Open-VIBE Seminar Topic:

This paper discussed about a 3D platform for Real-Time Neuroscience, Open-VIBE and also discussed about Neurofeedback and Brain-computer interfaces.

In real-time if brain’s physiological activity monitored in real-time then the feedback can be returned which in turn helps him or her to exercise some control over it. This is the basic idea for the evolution of Neurofeedback and Brain-Computer Interfaces.  These methods are getting improved with many advanced technologies including improving speed of microprocessors,    graphics    cards and    digital   signal    processing algorithms.    More meaningful features can be extracted from the continuous flow of brain activation can and in turn its feedback becomes more informative. Open-VIBE is a platform which based on publicly available frameworks such as OpenMASK and OpenSG and it is also an open source.

Conclusions:

This paper reviewed about recent NF and BCI research, which focused on similarities, mostly the interaction between the user and the system. Open-ViBE is a general       platform designed to build brain virtual environments based upon real-time neuro-imaging data.  The most appreciable qualities of neurofeedback are that it     requires    an active role the patient and it is non-invasive.  Neurofeedback training became a preferred choice in the case   of children and adolescents for whom the balance of neurotransmitters and the brain anatomy are still in its formation stage.

 For a human, the maximum reported number of binary commands per minute is 20. But this transfer rate is low for non-clinical application even though this rate is a great achievement for locked-in syndrome patients. The common characteristics of all systems are interactive analysis and visualization of brain data.  Computation efficiency occurs due to the notion of interactivity. In parallel computation field, Open-VIBE platform takes advantage of OpenMASK and enables the use of multiprocessor machines along with computer PC clusters.  In OpenMASK, every module takes responsibility of a specific computation which can be used in turn by several other modules. 

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