About this Research Topic
Music perception and production works as a complex, nonlinear physiological network of brain dynamics, human-human interaction, or complex interplay of subjects with musical instruments, acoustic, electronic, or digital. These networks are often self-organizing, synchronizing, multistable, and strongly time-dependent. Musical networks include brain and body dynamics, musical instrument performance as well as larger social, cultural or historical contexts.
Understanding such highly complex musical phenomena needs models and measurements of the dynamics and complexity of all subsystems related to music. Such models go beyond a description of music in context towards an understanding of music perception and production as dynamical models in perceptual, ecological, sociological, ethnological, or historical contexts. The prediction of musical phenomena could be improved by incorporating multiple aspects of a physiological network.
Contributions are encouraged on all kinds of networks of dynamical systems related to music perception and production, neural networks, machine learning, nonlinear dynamic algorithms, as well as measurement techniques like EEG, fMRI, or listening tests to understand music perception and production, composition, improvisation, or analysis of musical pieces or performances. Emotional and semantic content, musical parameters like melodies, timbre, or rhythm, or complex sociological aspects related to media, intercultural, ethnological, or historical developments are subjects of this Research Topic.
Due to the interdisciplinary nature of this topic we expect relevant contributions from a variety of fields, creating a holistic collection that benefits the broader community. When submitting your manuscript, we would like to encourage authors to please select the most suitable journal and section for the review and publication of your work.
Understanding such highly complex musical phenomena needs models and measurements of the dynamics and complexity of all subsystems related to music. Such models go beyond a description of music in context towards an understanding of music perception and production as dynamical models in perceptual, ecological, sociological, ethnological, or historical contexts. The prediction of musical phenomena could be improved by incorporating multiple aspects of a physiological network.
Contributions are encouraged on all kinds of networks of dynamical systems related to music perception and production, neural networks, machine learning, nonlinear dynamic algorithms, as well as measurement techniques like EEG, fMRI, or listening tests to understand music perception and production, composition, improvisation, or analysis of musical pieces or performances. Emotional and semantic content, musical parameters like melodies, timbre, or rhythm, or complex sociological aspects related to media, intercultural, ethnological, or historical developments are subjects of this Research Topic.
Due to the interdisciplinary nature of this topic we expect relevant contributions from a variety of fields, creating a holistic collection that benefits the broader community. When submitting your manuscript, we would like to encourage authors to please select the most suitable journal and section for the review and publication of your work.
Keywords: Music psychology, neural network, nonlinear dynamics, ecological psychoacoustics, network physiology
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
