Music for psilocybin therapy and the temporal arc of psychedelic experience

Music playlists used in psilocybin therapy rarely reflect the theoretically proposed arc of the psychedelic experience.

Gómez-Cañón et al. (2026) analysed 45.1 hours of music across eight playlists used in psilocybin therapy, comprising 369 tracks, to investigate whether the music followed the commonly proposed onset–peak–return arc of the psychedelic experience.

Using supervised and unsupervised machine-learning methods to assess acoustic features, estimated emotional qualities and musical characteristics, the researchers found little consistent differentiation between the three phases. Some playlists showed weak phase-related differences in basic acoustic features, but overall the tracks lacked a clear, reproducible structure aligned with the model.

The findings suggest that current playlist-curation practices do not consistently reflect the theory that music should evolve alongside the drug’s effects. However, the study analysed musical characteristics rather than participants’ responses or clinical outcomes, so it does not establish that phase-based sequencing is ineffective or that music lacks therapeutic value; personal emotional resonance, cultural familiarity and individual context may also influence its role in therapy

Abstract

Music plays a central role in psilocybin therapy (PT), where playlists are designed to be supportive and stimulating over a 4–6-hour psychedelic experience. The primary design principle underlying PT music programming is that music should be affectively aligned with the onset–peak–return model of pharmacodynamic action. However, in the absence of clear acoustic criteria, this framework has been implemented largely through individual or team-based curatorial judgment, making it unclear whether contemporary research PT playlists consistently realize the proposed onset–peak–return progression. Here, we test this question by analyzing 45.1 hours of audio from eight PT music playlists (369 tracks) for systematic acoustic and affective organization across onset, peak, and return phases. To this end, we applied supervised and unsupervised machine learning approaches to a comprehensive set of audio features extracted from PT music playlist tracks, evaluating phase differentiation across the full dataset as well as within individual playlists.

The results demonstrate that although weak phase-based differentiation is apparent for low-level audio features, especially within some playlists, the overall set lacks consistent phase-based structure. This implies that current curatorial practices are not aligned with their theoretical basis, raising questions about how such practices can evolve to better support emerging psychedelic treatments.

Gómez-Cañón, J.S., Leininger, C., Mayall, D. et al. Music for psilocybin therapy and the temporal arc of psychedelic experience. Sci Rep (2026). Read Paper

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