EEG Alpha-Band Activity During Music Listening from Two Datasets

Two EEG datasets from 24 subjects were analyzed to study long-range temporal correlations in alpha-band activity during music listening. The data includes recordings from 13 volunteers listening to Indian classical ragas and 11 subjects listening to Jazz and Synth-pop clips. The dataset, authored by Dasari Shivakumar and last updated in May 2026, presents results from applying a novel nonlinear manifold learning and detrended fluctuation analysis framework.

Use Cases

• Benchmarking nonlinear dimensionality reduction techniques for EEG based on the described Isomap and PCA pipelines.
• Investigating music-evoked brain synchronization patterns based on alpha-band power features extracted from the two music datasets.
• Developing models for characterizing scale-free temporal structure in neural time-series data based on the detrended fluctuation analysis approach.

Strengths

• The dataset description provides specific methodological details, including the use of 24 and 64 EEG channels sampled at 500 Hz and downsampled to 200 Hz.
• Analysis results are quantified with concrete metrics, such as scaling exponents (α) in the range of 0.62–0.70 and statistical significance values (e.g., p = 0.008).

Limitations

• The primary file is a 836 KB PDF, which likely contains analysis results and methodology rather than the raw or processed EEG data files.
• Row count and column-level documentation for the underlying data are unknown, limiting suitability assessment for direct machine learning applications.
• Description metadata is limited; actual data quality and accessibility require manual inspection after download.

Provenance

Source

figshare

Collection Method

EEG was recorded from healthy volunteers during music listening sessions. Data was preprocessed, band-limited to 8–13 Hz, and segmented.

Freshness

Last updated 2026-05-20 05:44:18; freshness should be verified.