<p>Music-evoked nostalgia has the potential to assist in recalling autobiographical memories and enhancing well-being. However, nostalgic music preferences vary from person to person, presenting challenges for applying nostalgia-based music interventions in clinical settings, such as a non-pharmacological approach. To address these individual differences, we developed the Nostalgia Brain-Music Interface (N-BMI), a neurofeedback system that recommends nostalgic songs tailored to each individual. This system is based on prediction models of nostalgic feelings, developed by integrating subjective nostalgia ratings, acoustic features and in-ear electroencephalographic (EEG) data during song listening. To test the effects of N-BMI on nostalgic feelings, state-level well-being, and memory recall, seventeen older and sixteen younger participants took part in the study. The N-BMI was personalized for each individual, and songs were recommended under two conditions: the “nostalgic condition“, where songs were selected to enhance nostalgic feelings, and the “non-nostalgic condition“, to reduce nostalgic feelings. We found nostalgic feelings, state-level well-being, and subjective memory vividness were significantly higher after listening to the recommended songs in the nostalgic condition compared to the non-nostalgic condition in both groups. This indicates that the N-BMI enhanced nostalgic feelings, state-level well-being, and memory recall across both groups. The N-BMI paves the way for innovative therapeutic interventions, including non-pharmacological approaches.</p>

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A Nostalgia Brain-Music Interface for enhancing nostalgia, well-being, and memory vividness in younger and older individuals

  • Yuna Sakakibara,
  • Tomohiro Kusutomi,
  • Sotaro Kondoh,
  • Takahide Etani,
  • Saori Shimada,
  • Yasuhiko Imamura,
  • Yasushi Naruse,
  • Shinya Fujii,
  • Takuya Ibaraki

摘要

Music-evoked nostalgia has the potential to assist in recalling autobiographical memories and enhancing well-being. However, nostalgic music preferences vary from person to person, presenting challenges for applying nostalgia-based music interventions in clinical settings, such as a non-pharmacological approach. To address these individual differences, we developed the Nostalgia Brain-Music Interface (N-BMI), a neurofeedback system that recommends nostalgic songs tailored to each individual. This system is based on prediction models of nostalgic feelings, developed by integrating subjective nostalgia ratings, acoustic features and in-ear electroencephalographic (EEG) data during song listening. To test the effects of N-BMI on nostalgic feelings, state-level well-being, and memory recall, seventeen older and sixteen younger participants took part in the study. The N-BMI was personalized for each individual, and songs were recommended under two conditions: the “nostalgic condition“, where songs were selected to enhance nostalgic feelings, and the “non-nostalgic condition“, to reduce nostalgic feelings. We found nostalgic feelings, state-level well-being, and subjective memory vividness were significantly higher after listening to the recommended songs in the nostalgic condition compared to the non-nostalgic condition in both groups. This indicates that the N-BMI enhanced nostalgic feelings, state-level well-being, and memory recall across both groups. The N-BMI paves the way for innovative therapeutic interventions, including non-pharmacological approaches.