[CuttingGardens2026:Frankfurt] Workshop—Building a 1,000-Song Naturalistic EEG Dataset: Practical Lessons from ManyMusic

This workshop shares the experience of building a deep phenotyping dataset of music-evoked emotions, namely "ManyMusic🎶" (). This ongoing project involves 17 EEG sessions and 17 fMRI sessions per participant, measuring neural and behavioural responses during intense affective experiences evoked by complete musical works spanning a wide range of genres, including Western classical, jazz, rock, pop, hip-hop, and more. Across six participants, the project will collect data from more than 1,000 full-length musical pieces.In this workshop, we will discuss the challenges of building a deep phenotyping dataset such as stimulus selection, participant screening, data quality monitoring, and on-the-fly troubleshooting. Participants will also have the opportunity to examine a subset of the collected EEG data first-hand. We will conclude by discussing the future prospects of developing foundation models from deeply sampled multimodal datasets.

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Publication Details

Journal
Figshare
Published
2026-11-02
DOI
https://doi.org/10.6084/m9.figshare.34886340
Primary Topic
Neuroscience and Music Perception
Type
article
Field-Weighted Citation Impact
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article

[CuttingGardens2026:Frankfurt] Workshop—Building a 1,000-Song Naturalistic EEG Dataset: Practical Lessons from ManyMusic

Seung-Goo Kim
Figshare
Neuroscience and Music Perception
article

[CuttingGardens2026:Frankfurt] Workshop—Building a 1,000-Song Naturalistic EEG Dataset: Practical Lessons from ManyMusic

Seung-Goo Kim
article en

Abstract

This workshop shares the experience of building a deep phenotyping dataset of music-evoked emotions, namely "ManyMusic🎶" (). This ongoing project involves 17 EEG sessions and 17 fMRI sessions per participant, measuring neural and behavioural responses during intense affective experiences evoked by complete musical works spanning a wide range of genres, including Western classical, jazz, rock, pop, hip-hop, and more. Across six participants, the project will collect data from more than 1,000 full-length musical pieces.In this workshop, we will discuss the challenges of building a deep phenotyping dataset such as stimulus selection, participant screening, data quality monitoring, and on-the-fly troubleshooting. Participants will also have the opportunity to examine a subset of the collected EEG data first-hand. We will conclude by discussing the future prospects of developing foundation models from deeply sampled multimodal datasets.

Figshare
Openalex Percentile: Top 17%
Neuroscience and Music Perception
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