Special Issue “Music, Brain, & Cognition” of Connection Science Available

Dear Colleagues,

We would like to announce the Connection Science Special Issue “Music, Brain, & Cognition” Vol. 21 (2-3):

This special issue aims to shed light on some of the key issues in current and future music research and technology. In the 90th, cognitive Musicology was envisaged to be composed from diverse disciplines such as brain research and artificial intelligence striving for a more scientific understanding of the phenomenon of music. One and a half decades following the special issue on Music and Creativity in Connection Science, edited by Griffith and Todd (1994), this issue, again, demonstrates how the horizons in the field have continued to expand.

Research activity in auditory neuroscience, applied to music in particular, is catching up with the scientific advances in vision research. The fast advancement of brain imaging methodology such as the electroencephalogram has further encouraged music research. Brain imaging grants access to music-related brain processes directly rather than circuitously via psychological experiments and verbal feedback by the subjects. Adaptability is an important topic on the agenda of roadmaps for the development of music technology. Adaptability helps transferring knowledge to new situations, users, or music styles. In music information retrieval, solutions have been developed to solve specialized tasks. But would such a system be useful to identify new styles or new musical concepts?

How is the perception of a musical event influenced by the context of previous musical development and high-level structure? The general success of Bayesian networks inspired cognitive science as well, developing models of concept learning, inference, and surprise. Bayesian networks have proven to be an approach well suited to address some of the most vital phenomena in music, such as beat, expectation, attention, tension, interestingness, and surprise.

We would like to thank the special editorial board, consisting of Klaus Obermayer, Eduardo Reck Miranda, Xavier Serra, and John Shawe- Taylor. We owe a great thanks to the 48 highly competent reviewers that have provided elaborated reviews often of original scientific value of their own.

David R. Hardoon and Hendrik Purwins

*Editorial: Trends and perspectives in music cognition research and technology
(Hendrik Purwins; David R. Hardoon)

*Information dynamics: patterns of expectation and surprise in the
perception of music
(Samer Abdallah; Mark Plumbley)

*What/when causal expectation modelling applied to audio signals
(Amaury Hazan; Ricard Marxer; Paul Brossier; Hendrik Purwins; Perfecto Herrera; Xavier Serra)

*Genre classification using chords and stochastic language models
(Carlos Pérez-Sancho; David Rizo; José M. Iñesta)

*GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison
(Simon Durrant; David R. Hardoon; André Brechmann; John Shawe- Taylor; Eduardo R. Miranda; Henning Scheich)

*From frequency to pitch, and from pitch class to musical key: shared principles of learning and perception
(Jamshed J. Bharucha)

*Model cortical responses for the detection of perceptual onsets and beat tracking in singing
(Martin Coath; Susan L. Denham; Leigh M. Smith; Henkjan Honing; Amaury Hazan; Piotr Holonowicz; Hendrik Purwins)

*Analysing musical performance through functional data analysis: rhythmic structure in Schumann’s Träumerei (Josué Almansa; Pedro Delicado)

*Exploiting functional relationships in musical composition (Amy K. Hoover; Kenneth O. Stanley)

*Predictive models for music (Jean-François Paiement; Yves Grandvalet; Samy Bengio)