Overt Naming Task EEG Data from 40 Participants

Adrian Gilmore published minimally processed scalp EEG data from an overt naming experiment. The data includes recordings from 40 participants, with gradient artifacts and ballistocardiogram effects removed. The dataset was last updated on April 25, 2026.

Use Cases

• Analyze neural correlates of language production based on EEG recordings during an overt naming task.
• Study repetition-related reductions in neural activity as referenced in the associated research.
• Investigate the relationship between oscillatory power and behavioral performance in naming tasks.
• Validate artifact removal techniques for EEG data based on the described MR gradient and ballistocardiogram correction.

Strengths

• Data is from 40 participants, providing a moderate sample size for analysis.
• Includes both raw and minimally processed EEG data, allowing for methodological comparisons.
• Specific artifacts (MR gradient and ballistocardiogram effects) have been removed, which may reduce preprocessing burden.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Data and code from: Repetition-related reductions in neural activity support improved behavior through increases in oscillatory power

Collection Method

Collected from an overt naming experiment with participants.

Freshness

Last updated 2026-04-25 00:08:16; freshness should be verified.