On Mapping EEG Information into Music - Guide to Brain-Computer Music Interfacing - page 225

Table 10.2 Associations
between musical notes and
the

Electrode number Electrode name Musical note

1 Fp1 A4

electrodes of a given

2 Fp2 A4#

montage

3 F7 B4

4 F5 C5

5 F4 C5#

6 F8 D5

7 T3 D5#

8 T4 E5

9 T5 F5

10 P3 F5#

11 P4 G5

12 T6 G5#

13 O1 A6

14 O2 A6#

Fig. 10.5 Melody generated
from the behaviour of EEG
power shown in Fig. 10.4

the music were explored through experiments with listeners attempting to associate
the resultant music with levels of sleep. They developed mapping strategies in their
investigations into musical representation of mental states. Figure 10.6 shows the
relationships between EEG features and musical parameters. Here, mappings
accumulate in order to build bars of musical phrases. For example, as time-based
features of sleep stages differ, compositions derived from slow wave sleep (where
activity is high in low-frequency delta and theta rhythms; see Chaps. 1 , 2 , 7 and 9
for more on EEG rhythms), are higher in amplitude and lower in pitch than com-
positions generated from rapid eye movement EEG (where alpha activity is more
prominent, albeit with low amplitudes) (Wu et al. 2010 ). This ability to directly map
time-based features, such as the prominent frequency and amplitude, gives way for
direct musical evocations of the mind

s state, allowing a listener to hear, through
music, brain states of arousal and relaxation.

'

10.5 Early Research into Biofeedback and Music

In 1965, Alvin Lucier performed a piece for live percussion and brainwaves titled
Music for Solo Performer. The piece was inspired by Luciers '

experiments, with the
physicist Edmond Dewan, into controlling bursts of alpha activity with meditative
states. Brainwaves mapped to sounds, in real time, created a neurofeedback loop,
allowing Lucier to affect sonic changes based on the feedback of the previous