Common Components in Perception and Imagery of Music: an EEG study

Background and Aims Mental imagery has been a subject of investigation for a considerable time. Recent investigations suggest that there is overlap in the electrical brain activations for imagination and perception of music (Schaefer et al., 2009, 2011a; Vlek et al., 2011). The current work is a new analysis of four datasets that investigate imagination of music, aiming to clarify the common processes in perception and imagination of music for stimuli of varying complexity. These studies, using electroencephalography (EEG), look at various aspects of music, namely rhythmic accents, monophonic melodies, more complex rhythms or natural music stimuli. By decomposing the event-related EEG data, widely differing datasets may be investigated using the same analysis method. We first used Principal Component Analysis (PCA), and expanded on this method using PARAFAC tensor decomposition, which allows to add the task into the decomposition, but does not make assumptions of independence or orthogonality, and calculate the relative strengths of the identified components for each task.