ToFFi -- Toolbox for Frequency-based Fingerprinting of Brain Signals
This provides a versatile tool for researchers in neuroscience to analyze brain signals, but it is incremental as it fills a gap in existing software without introducing new scientific methods.
The authors tackled the lack of open-source tools for calculating spectral fingerprints in brain signals by creating ToFFi, a MATLAB toolbox that transforms MEG/EEG signals into unique spectral representations using various brain parcellations, resulting in a modular and configurable tool that supports reproducibility and parallel computations.
Spectral fingerprints (SFs) are unique power spectra signatures of human brain regions of interest (ROIs, Keitel & Gross, 2016). SFs allow for accurate ROI identification and can serve as biomarkers of differences exhibited by non-neurotypical groups. At present, there are no open-source, versatile tools to calculate spectral fingerprints. We have filled this gap by creating a modular, highly-configurable MATLAB Toolbox for Frequency-based Fingerprinting (ToFFi). It can transform MEG/EEG signals into unique spectral representations using ROIs provided by anatomical (AAL, Desikan-Killiany), functional (Schaefer), or other custom volumetric brain parcellations. Toolbox design supports reproducibility and parallel computations.