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Organised Sound, Mental Imageries and the Future of Music Technology: a neuroscience outlook*

Published online by Cambridge University Press:  11 March 2010

Eduardo Reck Miranda
Eduardo Reck Miranda*
Affiliation:
Interdisciplinary Centre for Computer Music Research (ICCMR), Faculty of Arts, University of Plymouth, Plymouth PL4 8AA, UK
*
E-mail: eduardo.miranda@plymouth.ac.uk
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Abstract

The prospect of being able to gain a better understanding of how the brain processes music is very exciting for musicians and developers of music technology. Composers would certainly welcome the possibility of being able to predict more objectively the effect of particular musical configurations on their audiences. Furthermore, new music technologies are bound to emerge from such understanding. Despite an impressive amount of ongoing research into the neuroscience of music, progress in this field still remains largely uncharted for musicians and unexplored by developers of technology: the literature is complex and difficult to disentangle. This paper is an attempt to chart the field for the readership of this journal. It articulates a working hypothesis for the neural basis of mental imageries elicited by music, based on the notion that such imageries are by-products of the inherent abstracting and predicting properties of the brain. It is argued that such mental imageries are scaffolds for music perception. The paper also speculates on the impact that a better understanding of the musical brain may have on the development of future technology for electroacoustic music, which may include the development of new analysis tools such as the olivogram and the thalamogram.

Type
Articles
Information
Organised Sound , Volume 15 , Issue 1: Sonic imagery , April 2010 , pp. 13 - 25
Copyright
Copyright © Cambridge University Press 2010

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Footnotes

*

The author is thankful to Dr Simon Durrant for the fMRI images used in figure 1 and for his insights into the auditory pathways, which contributed to the difficult task of summarising their functioning in this paper. The author acknowledges the funding support of EPSRC for the project ‘Learning the Structure of Music’, grant EP/D0629341. The author thanks Elsevier for granting permission to reproduce the image of the brain in figure 2.

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