References
- Llinás R.R., Ustinin M.N. Frequency-pattern functional tomography of magnetoencephalography data allows new approach to the study of human brain organization. Front. Neural Circuits. 2014;8. Article No. 43. doi: 10.3389/fncir.2014.00043
- Ustinin M.N., Boyko A.I., Rykunov S.D. Functional Tomography of Complex Systems Using Spectral Analysis of Multichannel Measurement Data. Pattern Recognit. Image Anal. 2023;33:1344–1374. doi: 10.1134/S1054661823040491
- Ustinin M., Boyko A., Rykunov S. Healthy aging changes in conventional frequency bands of neuroelectric brain activity reconstructed from resting-state MEG. Geroscience. 2025;47:4093–4108. doi: 10.1007/s11357-025-01522-y
- Rykunov S.D., Boyko A.I., Ustinin M.N. Reconstruction of the Electrical Structure of the Human Body Using Spectral Functional Tomography. Pattern Recognit. Image Anal. 2023;33:1315–1343. doi: 10.1134/S1054661823040387
- Llinás R.R., Ustinin M.N., Rykunov S.D., Boyko A.I., Sychev V.V., Walton K.D., Rabello G.M., Garcia J. Reconstruction of human brain spontaneous activity based on frequency-pattern analysis of magnetoencephalography data. Front. Neurosci. 2015;9. Article No. 373. doi: 10.3389/fnins.2015.00373
- Rykunov S.D., Boyko A.I. Estimation of Spatial Distribution of the Main Rhythms of Human Brain Activity Using the Method of Functional Tomography Based on Magnetic Encephalography Data. Ìàthematical Biology and Bioinformatics. 2025;20:287–300. doi: 10.17537/2025.20.287
- Ustinin M.N., Rykunov S.D., Boyko A.I., Maslova O.A. Reconstruction of the Human Brain Functional Structure Based on the Electroencephalography Data. Ìàthematical Biology and Bioinformatics. 2020;15:106–117. doi: 10.17537/2020.15.106
- Shou G.F., Yuan H., Li C., Chen Y.F., Chen Y.X., Ding L. Whole-brain Electrophysiological Functional Connectivity Dynamics in Resting-state EEG. Journal of Neural Engineering. 2020;17. Article No. 026016. doi: 10.1088/1741-2552/ab7ad3
- Computational Neuroimaging and Neuroengineering Lab at the University of Oklahoma. Resting EEG. OpenNeuro: Dataset. 2025. doi: 10.18112/openneuro.ds006525.v1.0.0
- Delorme A., Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods. 2004;134:9–21. doi: 10.1016/j.jneumeth.2003.10.009
- Nolan H., Whelan R., Reilly R.B. FASTER: Fully Automated Statistical Thresholding for EEG artifact Rejection. Journal of Neuroscience Methods. 2010;192:152–162. doi: 10.1016/j.jneumeth.2010.07.015
- Oostenveld R., Fries P., Maris E., Schoffelen J.-M. FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data. Computational Intelligence and Neuroscience. 2011;2011. Article No. 156869. doi: 10.1155/2011/156869
- Mosher J.C., Leahy R.M., Lewis P.S. EEG and MEG: forward solutions for inverse methods. IEEE Transactions on Biomedical Engineering. 1999;46:245–259. doi: 10.1109/10.748978
- Zhang Z. A fast method to compute surface potentials generated by dipoles within multilayer anisotropic spheres. Phys. Med. Biol. 1995;40:335–349. doi: 10.1088/0031-9155/40/3/001
- Berg P., Scherg M. A Fast Method for Forward Computation of Multiple-Shell Spherical Head Models. Electroencephalography and Clinical Neurophysiology. 1994;90:58–64. doi: 10.1016/0013-4694(94)90113-9
- Niso G., Rogers C., Moreau J.T., Chen L.Y., Madjar C., Das S., Bock E., Tadel F., Evans A., Jolicoeur P., Baillet S. OMEGA: The Open MEG Archive. Neuroimage. 2015;124:1182–1187. doi: 10.1016/j.neuroimage.2015.04.028
|
|
|
