Elzbieta Olejarczyk

Dr. Elzbieta Olejarczyk

Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, 02-109 Warsaw, Poland
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Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 November 2017 in PLOS ONE
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Elzbieta OlejarczykElzbieta Olejarczyk
Elzbieta Olejarczyk
WJWojciech Jernajczyk
Wojciech Jernajczyk
The present study evaluated brain connectivity using electroencephalography (EEG) data from 14 patients with schizophrenia and 14 healthy controls. Phase-Locking Value (PLV), Phase-Lag Index (PLI) and Directed Transfer Function (DTF) were calculated for the original EEG data and following current source density (CSD) transformation, re-referencing using the average reference electrode (AVERAGE) and reference electrode standardization techniques (REST). The statistical analysis of adjacency matrices was carried out using indices based on graph theory. Both CSD and REST reduced the influence of volume conducted currents. The largest group differences in connectivity were observed for the alpha band. Schizophrenic patients showed reduced connectivity strength, as well as a lower clustering coefficient and shorter characteristic path length for both measures of phase synchronization following CSD transformation or REST re-referencing. Reduced synchronization was accompanied by increased directional flow from the occipital region for the alpha band. Following the REST re-referencing, the sources of alpha activity were located at parietal rather than occipital derivations. The results of PLV and DTF demonstrated group differences in fronto-posterior asymmetry following CSD transformation, while for PLI the differences were significant only using REST. The only analysis that identified group differences in inter-hemispheric asymmetry was DTF calculated for REST. Our results suggest that a comparison of different connectivity measures using graph-based indices for each frequency band, separately, may be a useful tool in the study of disconnectivity disorders such as schizophrenia.

5 April 2017 in Journal of Neural Engineering
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Elzbieta OlejarczykElzbieta Olejarczyk
Elzbieta Olejarczyk
LMLaura Marzetti
Laura Marzetti
VPVittorio Pizzella
Vittorio Pizzella
FZFilippo Zappasodi
Filippo Zappasodi
Objective . In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated. Approach . The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory. Main results . The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization. Significance . Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.

10 January 2022 in Scientific Reports
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Elzbieta OlejarczykElzbieta Olejarczyk
Elzbieta Olejarczyk
JGJean Gotman
Jean Gotman
BFBirgit Frauscher
Birgit Frauscher
As the brain is a complex system with occurrence of self-similarity at different levels, a dedicated analysis of the complexity of brain signals is of interest to elucidate the functional role of various brain regions across the various stages of vigilance. We exploited intracranial electroencephalogram data from 38 cortical regions using the Higuchi fractal dimension (HFD) as measure to assess brain complexity, on a dataset of 1772 electrode locations. HFD values depended on sleep stage and topography. HFD increased with higher levels of vigilance, being highest during wakefulness in the frontal lobe. HFD did not change from wake to stage N2 in temporo-occipital regions. The transverse temporal gyrus was the only area in which the HFD did not differ between any two vigilance stages. Interestingly, HFD of wakefulness and stage R were different mainly in the precentral gyrus, possibly reflecting motor inhibition in stage R. The fusiform and parahippocampal gyri were the only areas showing no difference between wakefulness and N2. Stages R and N2 were similar only for the postcentral gyrus. Topographical analysis of brain complexity revealed that sleep stages are clearly differentiated in fronto-central brain regions, but that temporo-occipital regions sleep differently.

28 September 2018 in Frontiers in Physiology
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KLKarolina Lebiecka
Karolina Lebiecka
UZUrszula Zuchowicz
Urszula Zuchowicz
AWAgata Wozniak-Kwasniewska
Agata Wozniak-Kwasniewska
DSDavid Szekely
David Szekely
Elzbieta OlejarczykElzbieta Olejarczyk
Elzbieta Olejarczyk
ODOlivier David
Olivier David
Aim: The aim of this work was to study the neurophysiological effect of repetitive transcranial magnetic stimulation (rTMS) applied to the left dorsolateral prefrontal cortex (DLPFC) in 8 patients with major depression disorder (MDD) and 10 patients with bipolar disorder (BP), considering separately responders and non-responders to rTMS therapy in each of both groups. Methods: The Higuchi’s Fractal Dimension (FD) was analyzed from 64-channels EEG signals in five physiological frequency bands and every channel separately. Changes of FD were analyzed before and after 1st, 10th, and 20th session of rTMS. Results: Some differences in response to the rTMS therapy was found across individual groups. In MDD responders, FD decreased in all bands after longer stimulation (20th session). Whereas, in BP non-responders, FD decreased after 1st session in all bands as well as after 10th session in lower frequencies (delta and theta). In MDD non-responders and BP responders FD increased at the beginning of the therapy (1st and 10th session, respectively), but the final FD value did not changed in comparison to the initial FD value, except the FD decrease for theta band in BP responders. Comparison between groups showed a higher FD in MDD responders than in MDD non-responders in every band before as well as after stimulation. In contrast to MDD patients, FD was lower in BP responders than in BP non-responders in higher frequency bands (alpha, beta, and gamma) in both conditions as well as in lower frequency bands (delta and theta) after stimulation. Comparing both groups of responders, FD was lower in MDD than in BP in every band, except alpha. In case of non-responders, FD was higher in BP than in MDD in all bands in both conditions. Conclusion: The results showed that FD may be useful marker for evaluation of the rTMS effectiveness and the therapy progress as well as for group differentiation between MDD and BP or between responders and non-responders. The changes of FD under the influence of rTMS allow to unambiguously conclude whether the effect of stimulation is positive or negative as well as allow to evaluate an optimal time of rTMS.

12 September 2017 in Frontiers in Neuroscience
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Elzbieta OlejarczykElzbieta Olejarczyk
Elzbieta Olejarczyk
PBPiotr Bogucki
Piotr Bogucki
ASAleksander Sobieszek
Aleksander Sobieszek
Electroencephalographic (EEG) patterns were analyzed in a group of ambulatory patients who ranged widely in age and sex using spectral analysis as well as Directed Transfer Function, a method used to evaluate functional brain connectivity. We tested the impact of window size and choice of reference electrode on the identification of two or more peaks with close frequencies observed in the spectral power distribution, so called ‘split alpha’. Together with the connectivity analysis, examination of spatiotemporal maps that showed the distribution of amplitudes of EEG patterns allowed for better explanation of the mechanisms underlying the generation of split alpha peaks. It was demonstrated that the split alpha spectrum can be generated by two or more independent and interconnected alpha wave generators located in different regions of the cerebral cortex, but not necessarily in the occipital cortex. We also demonstrated the importance of appropriate reference electrode choice during signal recording. In addition, results obtained using the original data were compared with results obtained using re-referenced data, using average reference electrode and reference electrode standardization techniques.

8 April 2021 in Frontiers in Neuroinformatics
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Elzbieta OlejarczykElzbieta Olejarczyk
Elzbieta Olejarczyk
AJAdam Jozwik
Adam Jozwik
VVVladas Valiulis
Vladas Valiulis
KDKastytis Dapsys
Kastytis Dapsys
GGGiedrius Gerulskis
Giedrius Gerulskis
AGArunas Germanavicius
Arunas Germanavicius
Aim: The objective of this work was to demonstrate the usefulness of a novel statistical method to study the impact of transcranial magnetic stimulation (TMS) on brain connectivity in patients with depression using different stimulation protocols, i.e., 1 Hz repetitive TMS over the right dorsolateral prefrontal cortex (DLPFC) (protocol G1), 10 Hz repetitive TMS over the left DLPFC (G2), and intermittent theta burst stimulation (iTBS) consisting of three 50 Hz burst bundle repeated at 5 Hz frequency (G3).Methods: Electroencephalography (EEG) connectivity analysis was performed using Directed Transfer Function (DTF) and a set of 21 indices based on graph theory. The statistical analysis of graph-theoretic indices consisted of a combination of thek-NN rule, the leave-one-out method, and a statistical test using a 2 × 2 contingency table.Results: Our new statistical approach allowed for selection of the best set of graph-based indices derived from DTF, and for differentiation between conditions (i.e., before and after TMS) and between TMS protocols. The effects of TMS was found to differ based on frequency band.Conclusion: A set of four brain asymmetry measures were particularly useful to study protocol- and frequency-dependent effects of TMS on brain connectivity.Significance: The new approach would allow for better evaluation of the therapeutic effects of TMS and choice of the most appropriate stimulation protocol.