Publication details
Funkční mozkové mikrostavy u pacientů s hraniční poruchou osobnosti
| Title in English | Functional brain microstates in patients with borderline personality disorder |
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| Authors | |
| Year of publication | 2022 |
| Type | Appeared in Conference without Proceedings |
| MU Faculty or unit | |
| Citation | |
| Description | Introduction: borderline personality disorder (BPD) is a common and severe psychiatric disorder. Results of recent imaging studies demonstrate impaired activity of resting-state brain networks in frontolimbic circuits in patients with HPO. The activity of large-scale brain networks can be studied using electroencephalography (EEG) by analyzing functional EEG brain microstates. In recent years, this method has shown promise as a tool to identify EEG correlates of neural abnormalities in psychiatric disorders. However, it has not yet been used to study the neural basis of HPO. A microstate is a global state of brain activity lasting about 100 ms, characterized by a stable topography of the potential distribution on the scalp. The aim of this pilot study was to identify abnormalities in microstate dynamics in patients with HPO. Methods: five healthy controls and five patients with a diagnosis of HPO participated in the study. We analyzed a six-minute recording of resting brain activity captured using a 256-channel EEG system. We assessed the temporal characteristics of microstates in patients and controls. Results: six microstates (1-6) differing in potential distribution on the scalp were identified. Temporal coverage indicates what percentage of the total length of the EEG recording is covered by a given microstate. In patients vs. controls, the average temporal coverage of each microstate was as follows: 24±7% vs. 28±7% (1), 11±6% vs. 7±3% (2), 14±4% vs. 9±3% (3), 17±4% vs. 25±8% (4), 11±5% vs. 7±4% (5), 20±8% vs. 22±7% (6). Conclusion. In contrast, the remaining three microstates had higher coverage in patients than in controls. The pilot results suggest possible abnormalities in the dynamics of resting large-scale brain networks in HPO patients. The finding will be verified in a larger cohort allowing statistical processing. |
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