Welcome
The Neurology area of Gradient Biotech is a web workspace for brain connectivity, functional imaging, and electrophysiology research. Upload connectivity matrices, EEG, or fMRI data; compute graph-theoretic network metrics; explore interactive brain visualizations; compare cohorts with Network-Based Statistics (NBS); and generate AI-assisted interpretations grounded in computed outputs.
What you can do today
| Capability | Status |
|---|---|
| Connectivity matrix upload | CSV, NPZ, NumPy, or MATLAB .mat square matrices |
| BCT graph metrics | Clustering, modularity, efficiency, small-worldness, centrality |
| Network visualization | Heatmap, graph layout, and 3D brain views when atlas coordinates exist |
| EEG preprocessing | Bandpass, notch, re-reference, bad-channel handling, optional ICA |
| EEG features | Band power, spectral entropy, PLV/coherence/wPLI connectivity |
| fMRI functional connectivity | Atlas parcellation, confound regression, Pearson + Fisher z |
| Dynamic FC | Sliding-window correlation and k-means state identification |
| Cohort analysis | Group assignment, batch graph metrics, NBS, group metric comparison |
| Advanced EEG | Microstates, time-frequency analysis, source localization |
| AI interpretation | Graph metrics, NBS, cohort, prediction, and microstate summaries with metric citations |
| Predictive biomarkers | NBS-Predict-style cross-validated classification/regression on connectivity edges, with permutation testing and edge-stability maps |
| Reporting | Study run history table; pull neurology plots into the shared cross-area report composer |
How the product is organized
Every analysis lives inside a study — your neuroscience project container. From the neurology dashboard you create or open a study, then work through:
- Study home — upload datasets, review subjects, launch cohort or run-history views
- Dataset workspace — run modality-specific pipelines and explore results
- Cohort analysis — assign groups, run NBS or prediction, compare graph metrics across conditions
- Runs — review run history for the study; add plots to the shared cross-area report composer
Pipeline jobs run asynchronously. Poll status from dataset and cohort pages until jobs complete.
Who this is for
- Neuroscience researchers running connectivity and network analysis without maintaining local MATLAB toolchains
- Cognitive and systems neuroscience labs comparing resting-state or task-based connectivity across groups
- Psychiatry and neurology research groups exploring group-level brain network differences
- Neurotech teams preprocessing EEG and extracting connectivity features at scale
What this is not
- Not a regulated clinical diagnostic or neurological assessment tool
- Not a passive brain viewer — visualizations support QC and hypothesis testing
- Not automatic diagnosis — outputs are research metrics for exploratory analysis
Next steps
- Use cases — scenario guides for connectome analysis, fMRI, EEG, and cohort comparison
- Quick start — run your first connectivity matrix analysis in minutes
- Key concepts — studies, datasets, runs, and subjects
- Study workflow — how the main sections fit together