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Establishing Mutual Links among Brain Structures
Klimeš, Petr ; Hlinka,, Jaroslav (referee) ; Krajča,, Vladimír (referee) ; Halámek, Josef (advisor)
The Human brain consists of mutually connected neuronal populations that build anatomically and functionally separated structures. To understand human brain activity and connectivity, it is crucial to describe how these structures are connected and how information is spread. Commonly used methods often work with data from scalp EEG, with a limited number of contacts, and are incapable of observing dynamic changes during cognitive processes or different behavioural states. In addition, connectivity studies almost never analyse pathological parts of the brain, which can have a crucial impact on pathology research and treatment. The aim of this work is connectivity analysis and its evolution in time during cognitive tasks using data from intracranial EEG. Physiological processes in cognitive stimulation and the local connectivity of pathology in the epileptic brain during wake and sleep were analysed. The results provide new insight into human brain physiology research. This was achieved by an innovative approach which combines connectivity methods with EEG spectral power calculation. The second part of this work focuses on seizure onset zone (SOZ) connectivity in the epileptic brain. The results describe the functional isolation of the SOZ from the surrounding tissue, which may contribute to clinical research and epilepsy treatment.
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The influence of deep brain stimulation on the brain connectivity
Horváthová, Ľubica ; Výtvarová, Eva (referee) ; Klimeš, Petr (advisor)
Hĺbková mozgová stimulácia (DBS) predstavuje účinnú liečbu pre pacientov s Parkinsonovou chorobou (PD) alebo farmakorezistentnou epilepsiou. Avšak mechanizmy, ktorými znižuje počet záchvatov a zlepšuje pohyb, zostávajú ešte do značnej miery neznáme. Pre lepšie pochopenie a určenie, v ktorých frekvenčných pásmach je zmena najdôležitejšia, boli urobené porovnania medzi vypnutou a zapnutou DBS pomocou korelačnej metódy a indexu fázového posunu. Jedenásť pacientov s PD a naimplantovanými neurostimulátormi z firiem Medtronic a St.Jude Medical bolo predmetom nahraných dát použitých v tejto práci. Výsledky dokazujú, že zmena konektivity počas DBS nastane a zároveň, že najviac ovplyvňuje najvyššie frekvencie ako beta, nízka gama a vysoká gama. Zmeny v týchto frekvenciách, zodpovedné za motorickú aktivitu, sústredenie a spracovanie informácií, sú v súlade s klinickou teóriou o PD. Počas tejto choroby je patologická beta aktivita hypersynchronizovaná a gama aktivita je znížená práve v motorických oblastiach. Ak sa gama aktivita počas zapnutej stimulácie zvyšuje, fyziologický stav pacientov sa čiastočne znovuobnovuje a tým zlepšuje ich hybnosť. Metódy a výsledky tejto práce budú použité pre ďalší výskum pacientov s PD a epilepsiou.
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Unsupervised Deep Learning Approach for Seizure Onset Zone localization in Epilepsy
Přidalová, Tereza ; Cimbálník, Jan (referee) ; Mehnen, Lars (advisor)
Epilepsy affects about 50 million people worldwide, with one-third of patients being drugresistant and therefore candidates for an invasive brain resection surgery. Brain resection surgery candidates undergo invasive intracranial encephalography (iEEG) monitoring to determine the seizure onset zone (SOZ). Recorded data can span over weeks and need to be manually reviewed by a physician to assess SOZ. This process can be time-consuming and burdensome due to the vast amount of collected data. This work investigates utilisation of an deep autoencoder for unsupervised data exploration and specifically its ability to discriminate between SOZ and non-SOZ (NSOZ) iEEG channels. The data used in this thesis consists of iEEG collected from 33 patients in two institutes (Mayo Clinic, Rochester, Minnesota, USA and St. Anne´s University Hospital, Brno, Czech Republic - FNUSA) who underwent invasive presurgical monitoring. The autoencoder’s capability to discriminate between SOZ and NSOZ was evaluated using a self-learned embedded feature space representation of the autoencoder network. Autoencoder features were compared to previously established biomarkers for SOZ determination. Discrimination capability was evaluated for both autoencoder features and biomarkers using a Naive Bayes classifier and leave-one-out cross-validation. The achieved area under receiver operating characteristic curve (AUROC) was 0.68 for the FNUSA and 0.56 for the Mayo dataset. Performance in discriminating between SOZ and NSOZ electrodes was not significantly different between the investigated autoencoder features and previously established biomarkers. Selecting the better performing classifier for each patient increased the AUROC to 0.75 and 0.64 for the FNUSA and Mayo dataset, respectively. The results suggest that future approaches combining biomarkers and self-learning methods have a potential to improve the SOZ vs NSOZ discrimination capability of unsupervised iEEG exploration systems, and thus to enhance the surgical management of epilepsy.
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Real-Time Processing of Intracranial EEG Signals
Begáň, Patrik ; Malik, Aamir Saeed (referee) ; Černocký, Jan (advisor)
V této práci jsme navrhli a implementovali nástroj, který je schopen zpracovávat intrakraniální EEG signály v reálném čase. To se provádí aplikací funkcí pro výpočet různých iEEG biomarkerů implementovaných v python knihovně Epycom na příchozí datový tok a uložením výsledků do databáze. Porovnali jsme výsledky vypočítané naším nástrojem s offline výpočty a vyhodnotili, zda je zpracování signálu v reálném čase vhodné pro klinickou praxi.
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Classification of high frequency oscillations in intracranial EEG
Kozlovská, Magda ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
This Master’s thesis deals with investigation of high-frequency oscillations in intracranial electroencephalography in patients with pharmacoresistant epilepsy. It describes individual types of oscillations with respect to their frequency definition, examines their physiological differences and occurrence. In addition to conventional high-frequency oscillations (up to about 600 Hz), it also focuses on oscillations with a frequency component above 1kHz. According to recent studies, these oscillations could have higherspecificity for the determination of pathological tissue in the epileptic brain. The data for this work was obtained by manual labeling and categorization of approximately 1500 sections of the stereoencephalographic record signals of patients undergoing surgical removal of the epileptic foci and subsequently monitored for success in the operation. Differences between individual groups of oscillations and resected or unresected tissues are investigated in this work by methods using calculations of entropy signals or cross frequency coupling. The most significant results were achieved for the classification group (FR + vFR) vs. uFR, methods frequency-amplitude coupling and sample entropy 1. When categorizing according to information about channel resection, the Shannon entropy is the most successful classification parameter.
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Brain connectivity estimation
Sladký, Vladimír ; Jurčo, Juraj (referee) ; Cimbálník, Jan (advisor)
Epileptic disease is connected with change in activity of neuronal clusters. Brain connectivity analysis deals with statistic interdependencies between different neuronal centres. Earlier studies show that changes in connectivity can be seen near primary epileptic site. What is changing connectivity and its characteristic in interictal recordings are yet to be fully known. In this thesis are analyzed data from intracranial EEG electrodes, positioned in and neighboring areas of epileptic site. Changes in connectivity of epileptic site and its surroundings are observed by nonlinear correlation method. Decrease in connectivity of epileptic site during slow wave sleep was detected on frequencies above 80 Hz. Reduced connectivity was measured on the border of epileptic zone and normal tissue. Observed features are accentuated during sleep. It was also found out that connectivity at the border of epileptic zone apears to have nonlinear property. The results show that physiological processes during sleep are influencing connectivity near epileptic site and decrease in connectivity may be related to nonlinear dependence of neuronal activity at the border of epileptic zone. This study confirms hypothesis of the earlier studies and reveals new facts about connectivity of epileptic site from the perspective of nonlinear processes. Consequent study based on this findings might lead to more precise delineation of epileptic site and to better understanding of processes, which are causing epileptic fits.
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Societal and governmental perspective of patients with Dravet syndrome and Lennox-Gastaut syndrome
Krejčová, Martina ; Klimeš, Jiří (advisor) ; Grega, Dominik (referee)
Societal and governmental perspective of patients with Dravet syndrome and Lennox-Gastaut syndrome Author: Martina Krejčová Supervisor: PharmDr. Jiří Klimeš, Ph.D. Consultant: PharmDr. David Suchánek Department of Social and Clinical Pharmacy, Faculty of Pharmacy in Hradec Králové, Charles University Introduction and aims: Dravet syndrome (DS) and Lennox-Gastaut syndrome (LGS) are rare diseases. The orphan drug Epidyolex is indicated to reduce the frequency of seizures in these diseases. The aim of this work is to provide a comprehensive overview of orphan drug legislation and the potential of its reimbursement from health insurance and determine the costs of DS and LGS from a societal and governmental perspective. Methods: The data for the analysis is obtained from the questionnaire focused on the social benefit drawdown, increase in household costs, and loss of productivity of patients and their caregivers. Respondents are recruited in a cooperation with patient organisations and specialised centres. The costs from both perspectives are determined by adding the expenses of the health insurance company and the costs of lost productivity (societal perspective), or the costs to the social security system (governmental perspective). The human capital approach method (HCA) is used for the societal...
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The influence of Mozart's effect on basketball shooting accuracy in professional basketball players.
Kranjčevič, Stefan ; Pánek, David (advisor) ; Pavlů, Dagmar (referee)
Title: Mozart effect on shooting accuracy of professional basketball players Aims: The aim of this thesis is to demonstrate whether the Mozart effect impacts the success rate of free throws in young premier league basketball players compared to shooting without music. Methods: As this is a pilot study, the data acquisition on this topic first started by examining the previously written text on the Mozart. The project is an experimental pilot study involving 21 probands who were randomized into three groups. The experiment is divided into 2 parts. In the first part participants are asked to shoot one hundred free throws in five blocks of twenty. In the second part, the participants are exposed to different types of acoustic stimulus during which they throw another hundred free throws. All measurements were taken after conditioning or shooting practice for the most authentic replication of the game situation. The process of the practical part was carried out in accordance with the CRISP-DM methodology, which is one of the most widely used methodologies for knowledge capture from databases (KCD). Results: The results show a borderline low correlation between shooting with and without music, according to Pearson's correlation coefficient, with a value of 0.33. The aim of using this statistical function...
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Societal and governmental perspective of patients with Dravet syndrome and Lennox-Gastaut syndrome
Krejčová, Martina ; Klimeš, Jiří (advisor) ; Grega, Dominik (referee)
Societal and governmental perspective of patients with Dravet syndrome and Lennox-Gastaut syndrome Author: Martina Krejčová Supervisor: PharmDr. Jiří Klimeš, Ph.D. Consultant: PharmDr. David Suchánek Department of Social and Clinical Pharmacy, Faculty of Pharmacy in Hradec Králové, Charles University Introduction and aims: Dravet syndrome (DS) and Lennox-Gastaut syndrome (LGS) are rare diseases. The orphan drug Epidyolex is indicated to reduce the frequency of seizures in these diseases. The aim of this work is to provide a comprehensive overview of orphan drug legislation and the potential of its reimbursement from health insurance and determine the costs of DS and LGS from a societal and governmental perspective. Methods: The data for the analysis is obtained from the questionnaire focused on the social benefit drawdown, increase in household costs, and loss of productivity of patients and their caregivers. Respondents are recruited in a cooperation with patient organisations and specialised centres. The costs from both perspectives are determined by adding the expenses of the health insurance company and the costs of lost productivity (societal perspective), or the costs to the social security system (governmental perspective). The human capital approach method (HCA) is used for the societal...
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