MNE Scan
MNE Scan is MNE-CPP's real-time data acquisition and processing application. It uses a modular plugin pipeline where data flows from acquisition plugins through processing stages to output plugins. Users wire plugins together in a visual GUI, enabling flexible experiment setups without writing code.
Key Features
- Real-time acquisition from MEG and EEG hardware (BabyMEG, Neuromag/Elekta/MEGIN, BrainAmp, gUSBamp, EEGoSports, TMSI, Natus) or via generic protocols (FieldTrip Buffer, Lab Streaming Layer)
- Signal processing including real-time filtering, noise reduction (SSP/compensators), signal-space separation, and artifact rejection
- Real-time averaging with configurable baseline correction and artifact thresholds
- Forward modeling with on-the-fly BEM-based computation and optional HPI-driven head-position updates
- Source localization using minimum-norm estimates (MNE), including real-time cortical source mapping with 3D visualization
- Head position monitoring with continuous HPI coil fitting for MEG systems
- Neuronal connectivity estimation in real time
- File recording in FIFF format for offline analysis
- Pre-recorded data playback via the FiffSimulator plugin for testing and development
Plugin Architecture
MNE Scan plugins fall into three categories:
| Category | Role | Examples |
|---|---|---|
| Sensor | Acquire data from hardware or network streams | FiffSimulator, BabyMEG, BrainAmp, LSL, FieldTrip Buffer |
| Algorithm | Process data in the pipeline | Averaging, Covariance, Noise Reduction, Forward Solution, MNE, HPI |
| IO | Output or store results | Write-to-File |
Plugins are loaded as shared libraries at runtime and communicate through typed input/output connectors linked by lock-free ring buffers.
Guides
Below are guides to get you started with MNE Scan.