EEG Alpha-Band Long-Range Correlations from Two Music Listening Studies

Electroencephalogram (EEG) data from two music listening experiments, preprocessed to analyze long-range temporal correlations in the alpha frequency band. The data includes recordings from 24 subjects across two datasets, one featuring live Indian classical music and the other featuring Jazz and Synth-pop clips. The dataset was created by Dasari Shivakumar and shared on figshare under a CC-BY-4.0 license.

Use Cases

• Developing methods for quantifying long-range temporal correlations based on alpha-band power features.
• Comparing nonlinear manifold learning (Isomap) and PCA dimensionality reduction techniques for EEG analysis.
• Investigating brain activity synchronization in response to different musical genres like Indian classical, Jazz, and Synth-pop.

Strengths

• Includes data from two distinct music EEG datasets with 13 and 11 subjects respectively.
• Preprocessing details are specified, including band-limiting to 8–13 Hz and segmentation into 2-second windows.
• Analysis results, such as scaling exponents (α) in the range of 0.62–0.70, are provided, demonstrating the applied methodology.

Limitations

• The primary file is a DOCX document (161.3 KB), which likely contains analysis descriptions rather than raw or processed time-series data files.
• Row count and column-level documentation are unknown, limiting suitability assessment for direct machine learning use.
• Description metadata is limited; actual data quality and accessibility require manual inspection after download.

Provenance

Source

figshare, author Dasari Shivakumar.

Collection Method

EEG recorded from healthy volunteers during music listening sessions.

Freshness

Last updated 2026-05-20 05:44:16; freshness should be verified.