Neurology
The Neurology area 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.
Start from a research scenario
Guided workflows map common questions to data requirements, analysis steps, and documentation — pick the scenario closest to your study.
Connectome analysis
Research question: What is the topology of this brain network? Which nodes are hubs, how segregated and integrated is the network, and does it exhibit small-world properties?
Analyze a precomputed connectivity matrix — compute Brain Connectivity Toolbox graph metrics, explore interactive visualizations, and generate analytical interpretation.
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Resting-state fMRI
Research question: How is functional connectivity organized in this resting-state scan, and how does it differ across patient and control groups?
Build functional connectivity matrices from resting-state fMRI data, compute graph metrics, and compare connectivity patterns across cohorts.
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EEG connectivity
Research question: What frequency-band activity and functional connectivity patterns characterize this EEG recording, and do microstate dynamics reveal altered brain state organization?
Preprocess EEG recordings, extract spectral and connectivity features, and compute graph metrics on derived connectivity matrices.
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Cohort comparison
Research question: Which connectivity edges or graph-theoretic properties differ significantly between patient and control groups, or between treatment conditions?
Compare brain connectivity across participant groups using batch graph metrics, Network-Based Statistics (NBS), and group-level metric comparison.
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Predictive biomarkers
Research question: Can a subnetwork of connectivity edges *predict* an out-of-sample outcome — a diagnostic group or a continuous clinical score — rather than only differ between groups on average?
Train cross-validated models that predict a participant's group or a continuous phenotype from brain connectivity, using NBS-Predict-style network biomarkers with leakage-free feature selection and permutation testing.
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Intracranial EEG (iEEG/ECoG)
Research question: Which intracranial contacts show task- or event-related high-gamma activation, once the data are bipolar-referenced and quality-checked?
Analyze intracranial recordings from depth electrodes and subdural grids with shaft-aware bipolar referencing, high-gamma band power, and event-related high-gamma mapping — the intracranial signal that scalp EEG cannot resolve.
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Platform features
Everything available in the Neurology workspace today — pipelines, explorers, exports, and provenance.
- Study containers for connectivity, EEG, and fMRI projects
- Connectivity matrix upload in CSV, NPZ, NumPy, and MATLAB `.mat` formats
- Brain Connectivity Toolbox graph metrics: clustering, modularity, and efficiency
- Small-worldness, characteristic path length, and centrality measures
- Network heatmap, graph layout, and 3D brain views when atlas coordinates exist
- EEG preprocessing: bandpass, notch, re-reference, and bad-channel handling
- Optional ICA for artifact reduction in EEG recordings
- Interactive EEG artifact review: per-channel QC, ICA component browser with reject/keep, and cleaned-recording apply
- EEG band power, spectral entropy, and PLV/coherence/wPLI connectivity
- Advanced multi-estimator EEG connectivity (imaginary coherence, PLI, debiased wPLI, AEC) with an estimator-agreement comparison
- EEG microstate analysis with coverage, duration, transitions, and GEV
- Time-frequency spectrogram statistics and band-power dynamics
- Simplified EEG source localization summaries
- iEEG/ECoG workflow: shaft-aware bipolar referencing, high-gamma band power, and peri-event high-gamma response
- fMRI BIDS archive validation with missing-field warnings
- fMRI motion QC: framewise displacement, DVARS, outlier scrubbing, tSNR, and subject-exclusion flags
- Functional connectivity with AAL and Schaefer atlas parcellation
- Confound regression and bandpass filtering for FC pipelines
- Dynamic functional connectivity with sliding-window states
- Task fMRI first-level GLM: BIDS events, HRF design matrix, per-condition activation, contrasts, and timing QC
- Batch graph metrics jobs across labeled subject datasets
- Network-Based Statistics (NBS) for group-level edge comparisons
- Graph-threshold sensitivity sweep with a robustness report flagging which metrics survive the density choice
- Predictive connectome modeling (NBS-Predict): cross-validated classification and regression, permutation testing, and edge-stability maps
- Group metric comparison tables with effect sizes
- Cluster-based nonparametric EEG statistics: sensor × band permutation tests with cluster-mass FWE correction
- Multiplex network metrics across connectivity layers: overlapping strength, participation coefficient, and layer similarity
- Cohort analysis workspace with group assignment and batch jobs
- Reusable protocol templates that chain preset pipeline steps in one click
- Organization-level custom atlas and montage registry with validation on upload
- Report export with methods text, annotations, and run manifest
- Grounded analytical interpretation for graph metrics, NBS, prediction models, and microstate outputs
- Async neurology job polling with versioned pipeline runs
- 4D Brain Exploration Workspace: synchronized orthogonal slice viewer (axial, coronal, sagittal) with shared crosshair cursor and MNI/RAS coordinate readout from the NIfTI affine
- NIfTI volume loading with automatic role detection (anatomical, functional, statistical map, label) from header intent codes and dimensionality
- Manual window/level controls for anatomy brightness with auto-windowing default
- Statistical map overlay on anatomical slices with per-colormap rendering (hot, viridis, plasma, autumn, cool, RdBu_r), positive and negative threshold controls, opacity slider, and a colormap legend
- Synchronized atlas region label: Schaefer 100/200/400 parcellation lookup at the cursor MNI coordinate, updating as crosshairs move
- Template cortical surface renderer in the 3D brain view: toggleable pial/white/inflated hemisphere meshes with sulcal-depth shading, aligned to the same MNI space as atlas-centroid connectivity nodes