Structural decomposition of EEG signatures of melodic processing.

In the current study we investigate the EEG response to listening and imagining melodies and explore the possibility of decomposing this response according to musical features, such as rhythm and pitch patterns. A structural model was created based on musical aspects and multiple regression was used to calculate profiles of the contribution of each aspect, in contrast to traditional ERP components. By decomposing the response, we aimed to uncover pronounced ERP contributions for aspects of the encoding of musical structure, assuming a simple additive combination of these. When using a model built up of metric levels and contour direction, 81% of the variance is explained for perceived, and 57% for imagined melodies. The maximum correlation between the parameters found for the same melodic aspect in perception vs. imagery was 0.88, indicating similar processing between tasks. The decomposition method is shown to be a novel analysis method of complex ERP patterns, which allows subcomponents to be investigated within a continuous context.