Table 1.
Characteristics of the four beamforming toolboxes. The non-default settings of each toolbox are shown in bold. The toolbox version is indicated either by the version number or by the download date (yyyymmdd) from GitHub.
| MNE-Python | FieldTrip | DAiSS (SPM12) | Brainstorm | |
|---|---|---|---|---|
| Version | 0.18 | 20190922 | 20190924 | 20190926 |
| Data import functions | MNE (Python) | MNE (Matlab) | MNE (Matlab) | MNE (Matlab) |
| Internal units of MEG data | T, T/m | T, T/m | fT, fT/mm | T, T/m |
| Band-pass filter type | FIR | IIR | IIR | FIR |
| MRI segmentation | FreeSurfer | SPM8/SPM12 | SPM8/SPM12 | FreeSurfer/SPM8 |
| Head model | Single-shell BEM | Single-shell corrected sphere | Single-shell corrected sphere | Overlapping spheres |
| Source space | Rectangular grid (5 mm), inside of the inner skull | Rectangular grid (5 mm), inside of the inner skull | Rectangular grid (5 mm), inside of the inner skull | Rectangular grid (5 mm), inside of the brain volume |
| MEG–MRI coregistration | Point-cloud co-registration and manual correction | 3-point manual co-registration followed by ICP co-registration | Point-cloud co-registration using ICP | Point-cloud co-registration using ICP |
| Data covariance matrix | Sample data covariance | Sample data covariance | Sample data covariance | Sample data covariance |
| Noise normalization for NAI computation | Sample noise covariance | Sample noise covariance | Sample noise covariance | Sample noise covariance |
| Combining data from multiple sensor types | Prewhitening (full noise covariance) | No scaling or prewhitening | No scaling or prewhitening | Prewhitening (full noise covariance but cross-sensor-type terms zeroed) |
| Beamformer type | Scalar | Scalar | Scalar | Vector |
| Beamformer output | Neural activity index (NAI) | Neural activity index (NAI) | Neural activity index (NAI) | Neural activity index (NAI) |