Sonifikation in der Musik

Thomas Hermann, Gerold Baier, Markus Müller

Polyrhythm in the Human Brain

2004 / Bielefeld, Morelos/ Mexiko / Parameter Mapping / EEG-Data

"Three complementary methods are used to analyze the

dynamics of multivariate EEG data obtained from a human

listening to a piece of music. The analysis yields parameters for

a data sonification that conserves temporal and frequency

relationships as well as wave intensities of the data. Multiple

events taking place on different time scales are combined to a

polyrhythmic display in real time.

EEG time series with their broadband Fourier spectra are

known to be polyrhythmic, i.e. they result from the

superposition of many individual rhythms. In general, these

individual rhythms are irregular but can be identified by their

dominant frequencies. Examples are the alpha rhythm (between

8 and 13 Hz in adults) which reflects resting activity of the

visual cortex; and the theta rhythm (between 4 and 8 Hz)

connected with rhythmic activity of the hippocampus and

probably also of the thalamus. As far as higher brain functions

(like cognitive processes) are concerned, there is accumulating

evidence that they can be related to changes of the degree of

firing synchronization of collaborating populations of neurons,

the so-called neural assemblies [1]. In the scalp EEG the degree

of synchronization of cortical activity is reflected in the

intensity of a given rhythm and consequently cognitive

processing should be reflected in temporal dynamics of the

respective cortical rhythms. Therefore we decided to sonify the

dynamics of multiple EEG rhythms such that their interactions

can be perceived.

Our sonification is an attempt to represent the polyrhythmic

texture of human cortical activity. Among the many hypothesis

available about the connection between mental activity and

certain EEG rhythms, we focus on recent evidence for thalamo-

cortical interaction. In particular, during semantic memory

recall significant power changes were observed in the theta and

beta band of human scalp EEG [2]. We therefore decided to

sonify the temporal evolution of multiple rhythms in these

frequency bands for various EEG channels.

All parameters for frequency, rhythmic patterns and loudness of

sound events were extracted from the time series. No musical

material was introduced for aesthetic purposes. Thus, rhythmic,

harmonic and even melodic patterns that the listener detects canbe

traced back to the cerebral activity of the listening subject

from which the data were recorded."



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