Abstract
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 magnetoencephalographic and electroencephalographic 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.
| Original language | English |
|---|---|
| Article number | 126236 |
| Journal | Neurocomputing |
| Volume | 544 |
| DOIs | |
| State | Published - Aug 1 2023 |
| Externally published | Yes |
Funding
Funding: This work has been supported by the National Science Centre, Poland, grant UMO-2016/20/W/NZ4/00354. Data were provided [in part] by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. Calculations were carried out at the Tricity Academic Supercomputer & Network Center in Gdańsk. We thank professor Joachim Gross for his generous technical support, Ewa Ratajczak, and Bartosz Kochański for helping out with testing and debugging the software.
Keywords
- Biomarkers
- Brain fingerprinting
- Computational neuroscience
- Source localization
- Spectral fingerprints