PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
How Functional Connectivity Measures Affect the Outcomes of MST Neuronal Network Characteristics in Patients with Schizophrenia Compared to Healthy Controls
Version 1
: Received: 7 November 2022 / Approved: 8 November 2022 / Online: 8 November 2022 (08:52:46 CET)
How to cite:
Jonak, K.; Marchewka, M.; Podkowiński, A.; Siejka, A.; Plechawska-Wójcik, M.; Krukow, P. How Functional Connectivity Measures Affect the Outcomes of MST Neuronal Network Characteristics in Patients with Schizophrenia Compared to Healthy Controls. Preprints2022, 2022110149. https://doi.org/10.20944/preprints202211.0149.v1
Jonak, K.; Marchewka, M.; Podkowiński, A.; Siejka, A.; Plechawska-Wójcik, M.; Krukow, P. How Functional Connectivity Measures Affect the Outcomes of MST Neuronal Network Characteristics in Patients with Schizophrenia Compared to Healthy Controls. Preprints 2022, 2022110149. https://doi.org/10.20944/preprints202211.0149.v1
Jonak, K.; Marchewka, M.; Podkowiński, A.; Siejka, A.; Plechawska-Wójcik, M.; Krukow, P. How Functional Connectivity Measures Affect the Outcomes of MST Neuronal Network Characteristics in Patients with Schizophrenia Compared to Healthy Controls. Preprints2022, 2022110149. https://doi.org/10.20944/preprints202211.0149.v1
APA Style
Jonak, K., Marchewka, M., Podkowiński, A., Siejka, A., Plechawska-Wójcik, M., & Krukow, P. (2022). How Functional Connectivity Measures Affect the Outcomes of MST Neuronal Network Characteristics in Patients with Schizophrenia Compared to Healthy Controls. Preprints. https://doi.org/10.20944/preprints202211.0149.v1
Chicago/Turabian Style
Jonak, K., Małgorzata Plechawska-Wójcik and Paweł Krukow. 2022 "How Functional Connectivity Measures Affect the Outcomes of MST Neuronal Network Characteristics in Patients with Schizophrenia Compared to Healthy Controls" Preprints. https://doi.org/10.20944/preprints202211.0149.v1
Abstract
Background: Modern computational solutions enabling evaluation of the global neuronal network arrangement seem to be particularly valuable for research on neuronal disconnection in schizophrenia. However, a vast number of algorithms used in these analyzes may be an uncontrolled source of results inconsistency. Objective: Our study aimed to verify whether the comparison of schizophrenia patients with healthy controls, in terms of indexes describing the organization of the neural network, will give analogous results when these parameters are calculated using two different functional connectivity measures. Methods: Resting-state EEG recordings from schizophrenia patients and healthy controls were collected. Based on these data, Minimum Spanning Tree (MST) graphs were computed two times using two different functional connectivity measures (phase lag index, PLI, and phase locking value, PLV). Results: Two series of be-tween-group comparisons regarding MST parameters calculated based on PLI or PLV gave contradictory results, in many cases the values of a given MST index based on PLI were higher in patients, and the results based on PLV were lower in patients than in the controls. Additionally, within the patients' group, selected network measures were significantly different when calculated from PLI or PLV. Conclusions: The selection of FC measures significantly affects the parameters of MST-based neural networks and might be a source of disagreement between the results of network studies on schizophrenia.
Medicine and Pharmacology, Psychiatry and Mental Health
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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