Abstract
Music information retrieval (MIR) methods offer interesting possibilities for automatically identifying time points in music recordings that relate to specific brain responses. However, how the acoustical features and the novelty of the music structure affect the brain response is not yet clear. In the present study, we tested a new method for automatically identifying time points of brain responses based on MIR analysis. We utilized an existing database including brain recordings of 48 healthy listeners measured with electroencephalography (EEG) and magnetoencephalography (MEG). While we succeeded in capturing brain responses related to acoustical changes in the modern tango piece Adios Nonino, we obtained less reliable brain responses with a metal rock piece and a modern symphony orchestra musical composition. However, brain responses might also relate to the novelty of the music structure. Hence, we added a manual musicological analysis of novelty in the musical structure to the computational acoustic analysis, obtaining strong brain responses even to the rock and modern pieces. Although no standardized method yet exists, these preliminary results suggest that analysis of novelty in music is an important aid to MIR analysis for investigating brain responses to realistic music.
Highlights
Measuring brain responses to music provides important insights into the auditory, non-verbal brain functions of functional hearing and hearing disabilities
Since the artificially designed music differs from real music heard outside the laboratory, there is a growing interest in developing music information retrieval (MIR) methods [1,2] to identify the time points for measuring brain responses to real music [3,4,5,6,7]
We investigate whether automatic extraction of acoustical feature increases, based on MIR analysis, can be applied to isolate brain responses to real pieces of different musical genres, such as metal rock music, tango music and modern symphony orchestra music
Summary
Measuring brain responses to music provides important insights into the auditory, non-verbal brain functions of functional hearing and hearing disabilities. The experimenter uses a set of predefined time points and designs artificial music stimuli adapted to the time points. This approach limits the opportunities for measuring brain responses to realistic music and restricts the generalization of the findings to ecological listening conditions. Since the artificially designed music differs from real music heard outside the laboratory, there is a growing interest in developing music information retrieval (MIR) methods [1,2] to identify the time points for measuring brain responses to real music [3,4,5,6,7]. We have tested a new method, which combines acoustical MIR analysis with modeling of brain mechanisms to automatically extract time points when the brain responds to real music pieces [8]
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