SAS
HRS4R
Our colleague Zuzana Rošťáková has successfully completed the research project EDABSS – EEG data analysis by blind source separation methods (09I03-03-V04-00205), implemented within the Recovery and Resilience Plan of the Slovak Republic (Plán obnovy a odolnosti SR).
The project focused on enhancing EEG analysis through the application of tensor decomposition methods, with the aim of improving the understanding and interpretation of complex EEG signals.
Her research addressed three main areas:
📍 EEG preprocessing – development and refinement of SPECTER, a novel tensor-based algorithm designed to effectively detect and remove eye-blink artifacts from EEG signals.
📍 Resting-state EEG analysis – investigation of the relationship between resting-state EEG microstates and latent components identified through tensor decomposition, with the aim of uncovering new insights into patterns of brain activity.
📍Block-oriented tensor decomposition – application of the PARALIND (parallel profiles with linear dependencies) model. In the analysis, subject-specific oscillatory rhythms were successfully identified in EEG data from a patient following an ischemic stroke, demonstrating the potential of tensor-based methods to reveal individual patterns in complex brain signals.
The project resulted in four scientific journal papers, four conference papers and one diploma thesis, covering the SPECTER algorithm, its deflation properties, SPECTER 2.0 and PARALIND analysis of human EEG.
The successful completion of EDABSS highlights the potential of tensor decomposition methods for advanced EEG signal processing and for revealing meaningful patterns in brain activity, including subject-specific characteristics that may be relevant when analysing neurological conditions.
Read the papers here:
Rošťáková, Z. – Rosipal, R. Equivalence of modified k-means and tensor decomposition in EEG microstates: Implications for analysis and interpretation. In NeuroImage, 2026, vol. 334, art. no. 121962. ISSN 1053-8119.
https://doi.org/10.1016/j.neuroimage.2026.121962
Evetović, N. – Rosipal, R. – Polyanskaya, A. – Rošťáková, Z. – Dvornák, K. – Vankó, M. – Korečko, Š. – Trejo, L.J. EEG-based monitoring of mental fatigue during virtual-reality motor imagery tasks. In Frontiers in Behavioral Neuroscience, 2026, vol. 20, art. no. 1810723. ISSN 1662-5153.
https://doi.org/10.3389/fnbeh.2026.1810723
Rošťáková, Z. – Rosipal, R. – Trejo, L.J. SPECTER – The Signal sPECtrum Tensor decomposition and Eye blink Removal algorithm. In Biomedical Signal Processing and Control, 2025, vol. 99, art. no. 106889. ISSN 1746-8094.
https://doi.org/10.1016/j.bspc.2024.106889
Rošťáková, Z. – Rosipal, R. Deflation properties in tensor-based eye blink removal algorithm. In Statistical Papers, 2025, vol. 66, art. no. 91. ISSN 0932-5026.