The bsfit toolbox provides a principled framework for reducing and interpreting high-dimensional cross-bispectral EEG data. By using a low-rank tensor decomposition, the toolbox expresses complex sensor-level interactions as a product of a single spatial mixing matrix and a compact source-interaction tensor.
- Language: MATLAB (100%)
- Dependencies: Requires the METH toolbox for forward/inverse calculations, visualization, and MOCA implementation.
If you use this toolbox, please cite:
Kaziki, D., Engel, A. K., & Nolte, G. (2025). Low-Rank Tensor Decomposition for Cross-Bispectral Analysis of EEG Data. bioRxiv .