TMS-EEG Step, Drift, and Filtering Artifacts in MATLAB Format

MATLAB files characterize step, drift, and filtering-related artifacts in Transcranial Magnetic Stimulation combined with Electroencephalography recordings. The 294.1 MB dataset includes ground-truth examples of step and decay artifacts and processed data from filtering pipeline comparisons. Author Marissa Holden last updated the dataset in May 2026.

Use Cases

• Benchmarking artifact detection algorithms based on provided ground-truth examples.
• Comparing the performance of different signal filtering pipelines using the included processed data.
• Training machine learning models to identify step and decay artifacts in electrophysiological data.
• Validating artifact removal methods in TMS-EEG research workflows.

Strengths

• Dataset size is 294.1 MB, indicating substantial content.
• Includes ground-truth examples of specific artifacts, which can serve as a validation benchmark.
• Contains processed data from multiple filtering pipelines for direct comparison.

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 training.

Provenance

Source

Marissa Holden via figshare

Collection Method

Files used to characterize artifacts as described in an associated manuscript.

Freshness

Last updated 2026-05-13 06:11:28