Decoding Individual Musical Pitches in Perception and Imagery using Evoked Theta and Beta Power in EEG

Abstract

Imagery evokes perceptual-like experiences and recruits similar neural activity to perception. In music, this shared activity has already been established in secondary auditory cortex, yet the nature of the representation is not fully understood; specifically, it is not clear whether the identity of individual imagined pitches can be decoded from brain activity. Using temporal lobe EEG channels, we examined the shared evoked patterns of musical pitch perception and imagery, and decoded individual imagined pitches from evoked oscillatory power across three conditions (Perception, Imagery, Random Pitch). Twenty-two participants heard the opening tones of a familiar melody, imagined its continuation, and judged whether a final probe tone matched the original note; a random-pitch condition served as a control. Replicating previous findings, the evoked perceptual pattern was reinstated during imagery, particularly in the right temporal channels, which showed stronger event-related potential correlations and a larger mismatch negativity to the probe tone than the left. A multiclass support vector machine decoded individual pitch identity from evoked oscillatory power (phase-locked activity time-locked to each tone onset) exceeding chance in all conditions, with accuracy higher for Perception and Imagery than Random Pitch. The optimal oscillatory bands differed across conditions: theta-beta gave the highest accuracy for Perception and Imagery, theta-alpha for the Random Pitch. These results demonstrate that individual pitch information is present during both perception and imagery, and that the theta–beta signature shared by the predictive contexts, distinct from the control, suggests a contribution of predictive processing. Significance Statement Musical imagery — the experience of “hearing” music in the mind’s ear — recruits brain activity resembling perception, yet whether the pitch specific information during imagery can be read out from this activity has remained unknown. Using EEG, we show for the first time that individual imagined pitches can be decoded from evoked oscillatory power, and that perception and imagery share a spectral signature (theta–beta) absent from a non-predictive random-pitch control. This dissociation indicates that imagined pitch reflects top-down predictions reactivating sensory representations, consistent with a predictive-coding view of imagery. These findings clarify the oscillatory basis of musical imagery and establish that its specific content is recoverable from non-invasive signals, informing future imagery-based brain–computer interfaces.