学術雑誌論文

学術雑誌論文

Scientific Reports. 2024, 14, p. 11164

Decoding predicted musical notes from omitted stimulus potentials

Nature Research

英語

2024-05-15

https://doi.org/10.1038/s41598-024-61989-1

Ishida K., Ishida T., Nittono H.. Decoding predicted musical notes from omitted stimulus potentials. Scientific Reports 14, 11164 (2024); https://doi.org/10.1038/s41598-024-61989-1.

Electrophysiological studies have investigated predictive processing in music by examining event-related potentials (ERPs) elicited by the violation of musical expectations. While several studies have reported that the predictability of stimuli can modulate the amplitude of ERPs, it is unclear how specific the representation of the expected note is. The present study addressed this issue by recording the omitted stimulus potentials (OSPs) to avoid contamination of bottom-up sensory processing with top-down predictive processing. Decoding of the omitted content was attempted using a support vector machine, which is a type of machine learning. ERP responses to the omission of four target notes (E, F, A, and C) at the same position in familiar and unfamiliar melodies were recorded from 25 participants. The results showed that the omission N1 were larger in the familiar melody condition than in the unfamiliar melody condition. The decoding accuracy of the four omitted notes was significantly higher in the familiar melody condition than in the unfamiliar melody condition. These results suggest that the OSPs contain discriminable predictive information, and the higher the predictability, the more the specific representation of the expected note is generated.

This article is licensed under a Creative Commons Attribution 4.0 International License.

97221

Decoding predicted musical notes from omitted stimulus potentials

Nature Research

英語

2024-05-15

Scientific Reports

14

11164

https://doi.org/10.1038/s41598-024-61989-1

https://hdl.handle.net/11094/97221