A dataset listing regions of interest and their associated EEG channels for research on predicting neurophysiological responses to intermittent theta-burst stimulation. The dataset was created by Matthew Herbert Ning and last updated on April 30, 2026. It is a small 8.4 KB XLSX file containing information used in supervised machine learning models integrating baseline EEG and TMS-evoked measures.
Use Cases
- Training machine learning models to predict cortical excitability changes based on baseline resting-state EEG features.
- Analyzing the relationship between EEG complexity measures and responses to single-session iTBS.
- Conducting reliability analysis on neurophysiological predictors across test-retest studies.
Strengths
- Data is openly licensed under CC-BY-4.0, permitting reuse and modification.
- File size is 8.4 KB, indicating a lightweight and easily accessible dataset.
- The research context is described in detail, including model performance metrics (81% internal, 69% external accuracy).
Limitations
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
- The dataset is very small (8.4 KB), indicating limited scope and likely a simple reference list.
Provenance
- Source
- figshare
- Collection Method
- Likely compiled from experimental studies using EEG and TMS on healthy adults.
- Time Range
- null
- Freshness
- Last updated 2026-04-30 17:31:39; freshness should be verified.
- Geography
- null