Oscillatory Episodes of Brain Activity from 128 Healthy Participants

Source-reconstructed magnetoencephalography (MEG) brain activity from 128 healthy participants from The Open MEG Archive (OMEGA). Oscillatory episodes were identified using the sBOSC algorithm, which detects events exceeding power and duration thresholds while incorporating spatial information. The dataset was authored by Enrique Stern and last updated in May 2026.

Use Cases

• Analyzing the spatial distribution of oscillatory brain activity based on the source-reconstructed MEG data.
• Investigating the duration and power characteristics of oscillatory episodes detected by the sBOSC algorithm.
• Developing or validating new methods for detecting oscillatory events in neuroimaging time-series data.
• Studying individual differences in brain oscillatory patterns across a healthy participant cohort.

Strengths

• Contains data from 128 healthy participants, providing a moderate sample size for group-level analysis.
• Uses a defined algorithm (sBOSC) for detecting oscillatory episodes, which incorporates spatial information and spectral peaks.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale modeling tasks.

Provenance

Source

The Open MEG Archive (OMEGA, version 2.0)

Collection Method

Oscillatory episodes were identified using the sBOSC algorithm applied to source-reconstructed MEG data.

Freshness

Last updated 2026-05-24 04:30:15