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colleagues utilised this control to trigger a series of de
ned notes within a scale
(Miranda et al. 2011 ).
The SSVEP-based BCMI by Miranda and colleagues broke new ground in
BCMI research. This is the
first instance of a system whereby a user can precisely
control note-speci
c commands with real-time neurofeedback. It is interesting to
refer back to the BCI de
nition of Wolpaw and Birbaumer ( 2006 ) who may well
de
ne such systems as outside the realm of true BCI as it relies on the EEG
interpretation of eye position and not pure thought processes. That said, in the
pursuit of real-time control of brainwaves so far SSVEP, in comparison with motor
imagery and P300 BCIs, has been found to offer the quickest and most accurate
EEG response and with the least amount of training (Guger et al. 2011 ). Also, the
advantages of these types of systems over previous BCMIs are clear to see. One of
the outcomes of this initial SSVEP research was the use of BCMIs in collaborative
musical applications. In terms of music used as a real-time communicative tool
between people, this system allows a user to play along with a musician, or
potentially, with another BCMI user. This was recognised as an important break-
through for the potential BCMI systems in therapeutic situations and for potentially
launching the BCMI into a wider
field of collaborative musical applications.
In 2012, we reported on further mapping and compositional techniques using
SSVEP within a BCMI (Eaton and Miranda 2012 ) for the composition of The
Warren , a multichannel electronic performance piece designed to explore the
boundaries of mapping strategies in a BCMI system to generate real-time compo-
sitional rules (Eaton 2011 ). Control of EEG performs generative functions that
control macro-level musical commands, such as shifts in arrangement, tempo and
Fig. 10.7 A mapping diagram from a short section of The Warren . Here, each icon (1
4) is
-
assigned to a number of commands based on the requirements of the composition
 
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