Overview
Neurology workflows connect brain connectivity, functional imaging, and electrophysiology data in a single study workspace. Each use case below maps a common research question to platform capabilities, data requirements, and a suggested analysis path.
Use case index
| Use case | Research question | Key capabilities |
|---|---|---|
| Connectome analysis | What is the topology of this brain network? | Graph metrics, heatmap and 3D visualization, AI interpretation |
| Resting-state fMRI | How does functional connectivity differ across a cohort? | BIDS validation, functional connectivity, dynamic FC, atlas parcellation |
| EEG connectivity | What spectral and connectivity features characterize this recording? | EEG preprocessing, band power, PLV/coherence, microstates, graph metrics |
| Cohort comparison | Which edges or graph metrics differ between groups? | Group assignment, batch graph metrics, NBS, cohort metric comparison |
| Predictive biomarkers | Can connectivity edges predict a group or score out-of-sample? | NBS-Predict cross-validated classification and regression, permutation testing, edge-stability maps |
| Intracranial EEG (iEEG/ECoG) | Which intracranial contacts show event-related high-gamma activation? | Shaft-aware bipolar referencing, high-gamma band power, peri-event high-gamma mapping |
Who these use cases serve
| Audience | Typical goals |
|---|---|
| Neuroscience researchers | fMRI/EEG connectivity analysis, graph metrics, reproducible pipelines |
| Psychiatry and neurology research groups | Group-level connectivity differences, biomarker discovery |
| Cognitive neuroscience labs | Resting-state and task-based fMRI without MATLAB/SPM setup |
| Neurotech and digital health teams | EEG feature extraction, microstate analysis, biomarker pipelines |
| Pharma and clinical trial teams | Connectivity endpoints, treatment-response analysis, reproducible imaging workflows |
| Epilepsy, neurosurgery, and BCI research teams | Intracranial (iEEG/ECoG) bipolar referencing, high-gamma functional mapping |
Common data requirements
Most use cases start with a neurology study containing:
- Datasets — connectivity matrices, EEG recordings, or fMRI NIfTI/BIDS archives
- Subjects (optional) — participant metadata with diagnosis, group label, and cognitive scores
- Group labels — assigned per dataset for cohort comparison and NBS
Choosing a starting point
| If your primary data is… | Start with… |
|---|---|
| Precomputed ROI connectivity matrix | Connectome analysis |
| Resting-state fMRI NIfTI or BIDS | Resting-state fMRI |
| EEG or MEG recording | EEG connectivity |
| Multiple subjects with group labels | Cohort comparison |
| Subjects with an outcome to predict (group or score) | Predictive biomarkers |
| Intracranial depth/grid electrode recording | Intracranial EEG (iEEG/ECoG) |
What these use cases are not
These workflows support exploratory neuroscience research. They are not clinical diagnostic or neurological assessment tools. All AI interpretation outputs include research disclaimers and cite computed metrics only.
Next steps
- Quick start — run your first connectivity matrix analysis
- Study workflow — how study pages fit together
- Pipelines reference — API endpoints and parameters