ï~~COMPOSING WITH BRAINWAVES: MINIMAL TRIAL P300
RECOGNITION AS AN INDICATION OF SUBJECTIVE
PREFERENCE FOR THE CONTROL OF A MUSICAL
INSTRUMENT
Dr M Grierson
Goldsmiths Electronic
Music Studios
Dept. of Music
Goldsmiths College
ABSTRACT
This paper presents a method for the stimulation and
detection of P300 event related potentials in a real-time
environment, and the application of this method for the
sending of control signals to a computer music device. In
the case of this study, an argument is advanced that the
P300 can be triggered by certain types of visual stimuli,
and that the following responses can be interpreted as an
indication of subjective preference. Through this
technique, a subject connected to an EEG can control a
synthesiser or sequencer remotely without moving, by
making a subjective decision to focus on a particular
choice offered to them on a display. It is noted that this
technique could be extended to a variety of contexts, not
least the provision of a musical interface for the physically
disabled. In addition, the implications of this study are
discussed with respect to other work being carried out as
part of the AHRC funded Cultural Processing project
(Formerly C.A.V.E.).
1.INTRODUCTION
"Perhaps within the next hundred years, science will
perfect a process of thought transference from composer to
listener. The composer will sit alone on the concert stage
and merely think his idealized conception of his music.
Instead of recordings of actual music sound, recordings
will carry the brainwaves of the composer directly to the
mind of the listener."
Raymond Scott, 1949 [1]
This quote is emblematic of many a composer's
desire - to successfully communicate music directly from
the mind to the minds of others, without need for the
manual translation of musical ideas. Raymond Scott hoped
that this would one day be possible with the aid of
computers. There is as yet no method for translating music
directly from mind to mind. However, there has been
significant progress in the field of Brain Computer
Interface (BCI) development that is beginning to make
possible the translation of subjective states, however
crudely interpreted, to information that can be employed
in the real-time control of musical devices. This study
presents one such method which has been demonstrated to
work with a small group of subjects, and is being
developed in the short term to allow for a usable level of
musical interaction and analysis.
2.THEORY
Event Related Potentials (ERPs) are brain signals that
occur in response to external stimuli. They can be detected
through the processing of an Electroencephalograph
(EEG) signal. This method of brain signal measurement is
effective for the identification of ERPs due to its relatively
high temporal resolution when compared to other methods
such as fMRI (functional Magnetic Resonance Imaging).
As ERPs mainly occur in direct response to external
stimuli, their identification is time sensitive to the onset of
the stimuli. It seems logical to hypothesise that the relative
temporality of ERPs can be seen as indicative of a
particular type of neural processing, or - to be more
specific, as the brain is a distributed processing network of
circuit elements [2], the type of process occurring in
response to stimuli can be said to be related to the amount
of time taken for a neural signal to be processed by the
network. Signals take time to be transferred from one part
of the network to another, and the amount of time taken by
extension may reveal the process taking place [3]. ERPs
are at present seen as classifiable by these means, as they
appear predictably across subjects given similar sensory
stimulation within reasonable limits. Importantly, EEG has
a relatively low spatial resolution, and although methods
do exist for using EEG data to analyse the locations of
specific brain activity, it is not the most effective method
of doing so.
ERPs are difficult to detect in real-time. They are
normally revealed through the non-real-time analysis of a
high number of EEG trials (20 or more). Commonly, a
stimulus will be presented to a series of subjects, with each
trial being defined by the time tagged onset of a stimulus.
If an ERP is to be detected from the recorded signal, the
EEG data must be heavily processed. ERPs manifest
themselves as small variations in the signal occurring at a
regular interval after the onset of the each stimulus. As the
amplitude of an ERP is relatively low compared to the rest
of the EEG signal, the signal needs to be averaged so that
the non-random, time-dependent, event related signal can
