EEG connectivity
Preprocess EEG recordings, extract spectral and connectivity features, and compute graph metrics on derived connectivity matrices.
Research question
What frequency-band activity and functional connectivity patterns characterize this EEG recording, and do microstate dynamics reveal altered brain state organization?
Who this is for
- Neurotech and digital health teams processing wearable or clinical EEG
- Cognitive neuroscience labs studying oscillatory dynamics and functional coupling
- Psychiatry research groups exploring EEG biomarkers for mood, attention, and sleep disorders
Data requirements
| Data | Required | Purpose |
|---|---|---|
| EEG recording | Yes | Preprocessing and feature extraction |
| Channel montage metadata | Embedded in file | Re-referencing and bad-channel detection |
| Subject group labels | No (required for cohort) | Group-level feature comparison |
Supported formats: EDF, BrainVision, EEGLab .set, CSV.
Workflow
Create study → Upload EEG → Preprocess → Features / microstates → Graph metrics on connectivity matrix
Step 1 — Upload EEG
Create a neurology study and upload an EEG recording from the study home page. Open the dataset workspace after upload completes.
Step 2 — Preprocess
Click Preprocess EEG. The pipeline applies:
- Bandpass and notch filtering
- Re-referencing (average or custom)
- Bad-channel detection and interpolation
- Optional ICA for artifact reduction
Review filtered recording summary, bad-channel list, and ICA component counts in the QC panel.
Step 3 — Feature extraction
Run EEG features on the completed preprocess run:
- Band power (delta, theta, alpha, beta, gamma)
- Spectral entropy
- Connectivity measures: PLV, coherence, wPLI
Step 4 — Advanced EEG (optional)
Additional pipelines on preprocessed data:
| Pipeline | Output |
|---|---|
| Microstates | State maps, coverage, duration, transitions, GEV |
| Time-frequency | Spectrogram statistics, band-power dynamics |
| Source localize | Simplified source-space summary |
Step 5 — Graph metrics on connectivity
Export or derive a connectivity matrix from PLV/coherence outputs and run Graph metrics to characterize network topology of the EEG-derived connectome.
Step 6 — Interpret (optional)
Use Interpret in microstates mode after microstate segmentation completes, or graph metrics mode after connectivity analysis.
Expected outputs
- Preprocessed recording with QC summary
- Band power and spectral entropy tables
- PLV/coherence/wPLI connectivity matrices
- Microstate maps with coverage, duration, and transition statistics
- Graph metrics on EEG-derived connectivity
- AI narrative citing computed spectral and connectivity values
Typical analyses
| Analysis | Feature | Question |
|---|---|---|
| Alpha suppression | Band power | Is occipital alpha reduced during active attention? |
| Epileptiform coupling | PLV connectivity | Are interictal spike regions hyper-connected? |
| Microstate dysregulation | Microstate coverage | Do patients show altered state B duration and transitions? |
| Wearable biomarker | Theta/beta ratio | Does the ratio differ between clinical subgroups? |