EEG: ERPs & Time–Frequency (EEGLAB/FieldTrip, Sternberg)
Goal: Preprocess EEG, compute ERPs and time–frequency (TF), and test condition differences with cluster-based permutation.
Snapshot
- Dataset: EEGLAB Sternberg (multi-subject tutorial)
- Local subset: · **Disk:** ~0.4–1 GB depending on subset
- Tools: EEGLAB (preproc/ERPs), FieldTrip (TF + cluster stats)
- Status: <planned / in progress / complete>
- Last updated:
Data
- Source: EEGLAB tutorial dataset.
- What I downloaded: list subjects/sessions.
- Layout: subject folders; note montage/reference.
Pipeline (high-level)
1) Filter, bad channel handling, ICA artifact removal
2) Epoching by condition → ERPs
3) TF (wavelets or multitaper)
4) Cluster-based permutation for condition effects
Results (to be filled)
- Figure: ERP grand-average + topomaps
- Figure: TF difference map with significant clusters
Reproducibility
- Versions in
env/TOOL_VERSIONS.md.
- Steps: “EEGLAB preproc → ERPs → TF → FieldTrip stats → export figures.”
- Limitations: small sample; montage differences.
Author: Rene Andrade Rey · 🧪 ORCID: https://orcid.org/0000-0001-5627-579X · 🌐 Scholar: https://scholar.google.es/citations?hl=es&user=Nl3ApFEAAAAJ