Handbook of Research Methods in Complexity Science
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Handbook of Research Methods in Complexity Science

Theory and Applications

Edited by Eve Mitleton-Kelly, Alexandros Paraskevas and Christopher Day

This comprehensive Handbook is aimed at both academic researchers and practitioners in the field of complexity science. The book’s 26 chapters, specially written by leading experts, provide in-depth coverage of research methods based on the sciences of complexity. The research methods presented are illustratively applied to practical cases and are readily accessible to researchers and decision makers alike.
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Chapter 3: Information theoretic measures of causality: music performance as a case study

Theory and Applications

Fatimah Abdul Razak, Xiaogeng Wan and Professor Henrik Jeldtoft Jensen

Abstract

It is fair to say that the raison d'être for science is to identify causations. This despite of the serious philosophical difficulties in defining causation and the scientific subtleties encountered when determining specific causal scenarios. Pragmatic information theoretic approaches were pioneered by Granger and have undergone much recent development in relation to studies of time series from complex systems such as the brain or finance. Here we first review the information theoretic and probabilistic approach to causality measures. We explain the difference between direct and indirect measures. Finally, we present an application of some of the measures to a real system. In particular, we discuss the findings on analysis of music performance where causation amongst the musicians and audience was studied by use of EEG time series.

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