Music is experienced, performed and shared by people in all societies, ages and social groups. Recently, neuroscientific interest in music has increased dramatically as modern brain imaging techniques have provided researchers the means to investigate the living human brain at work.
Center for Music in the Brain (MIB) is a Danish National Research Foundation Center of Excellence founded in 2015. It aims to facilitate contacts between different scientific approaches to studying music and the brain, and to introduce this scientific field to a broader audience within the danish music community.
The MIB research is centered around the Predictive Coding of Music hypothesis (PCM) formulated by Peter Vuust and colleagues in 2009. PCM states that music, based on the concept of anticipation, reflects fundamental survival-related brain mechanisms associated with predicting future events and has been demonstrated in relation to auditory pre-attentive processing and to processing of musical pleasure in the dopaminergic pathways tying musical anticipatory processes to emerging theories that posits predictive coding as the general principle underlying brain function in general. It is our hope that this effort will significantly influence our understanding of brain function and plasticity, with implications for music education and clinical applications of music.
Perception can be described as the process of minimizing prediction errors between higher-level “prediction units” and lower-level “error units” in the hierarchically organized brain. The dynamic interplay between predictable structures in music and predictive brain processing is a key determinant of perception and cognition of music. The Perception group tests hypotheses derived from PCM (predictive coding of music hypothesis) by varying the intramusical features of music (e.g. in rhythm, melody, harmony, form, instrumentation, and acoustics) and the extra-musical factors influencing the brain’s model. In this way, the work in this group bridges the gap between musicology, psychology and neuroscience and lays out the foundation for the work in the other groups.
Research leader: Professor Lauren Stewart
Action is the active engagement of the motor system to resample the environment in order to reduce prediction error. Music action centered around rhythm is a focus of MIB for several reasons. Rhythm provides a powerful tool for investigating the relation between perception and action, since there is a direct link between listening to musical rhythm and motor behavior. Our work will be based on the hypothesis that action aims at minimizing prediction error. Equally important, performance and music listening have social and communicative functions in which rhythm plays a key role. Hence, in a musicological perspective such studies touch upon the crucial question of whether music is an evolutionary adaptation designated for social cohesion.
Research leader: Professor Peter Vuust
Emotion, attention, and motivation act as weights or modulators of the prediction error itself, guiding behaviour, action and learning through neurotransmitters such as dopamine. Emotion is fundamental to human life, survival and well-being, and music is one of the strongest and most universal sources of human emotion and pleasure. Meyer formulated the idea that musical anticipation and incongruity, i.e. elements that do not fit with schematic, veridical or short term memory-based predictions, may be a fundamental source of music emotion and pleasure, an idea that was later pursued and expanded on by Huron. The Emotion group investigates predictive mechanisms related to emotional and pleasure processing in the brain.
Research leader: Professor Morten Kringelbach
Learning is the long-term influence on the prediction units. Playing music is a highly specialized skill that places immense demands on the underlying neural substrates, making music an important model for studying brain plasticity and development. The Learning group investigates the influence of long and short term training on predictive processing and how predictive mechanisms for music are shaped by music training, expertise, and individual cultural factors such as listening history, music-stylistic preferences, or biological factors such as personality and genotype.
Research leader: Professor Elvira Brattico