|
|
Cortical-subcortical interactions in EEG data of patients with pharmacoresistant epilepsy
Šíma, Jan ; Králík, Martin (referee) ; Lamoš, Martin (advisor)
This bachelor's thesis deals with the elaboration of a literature search on epilepsy and electroencephalography signals with a focus on patients with drug-resistant epilepsy and the analysis of cortico-subcortical relationships. The theoretical part describes the chapters of epilepsy, electroencephalography, the possibility of pre-processing EEG data and analytical methods, which describe the cortico-subcortical interactions. The practical part contains pre-processing of EEG data, analysis of methods used, data analysis, results, discussion, and conclusion. The data analysis itself is performed by the Phase-amplitude coupling method. The discussion discusses the results, limitations, and other possible connections. The conclusion summarizes the whole bachelor thesis.
|
|
|
Acoustic analysis of Mozart effect and its effect in patients with epilepsy
Zemánek, Václav ; Mekyska, Jiří (referee) ; Kiska, Tomáš (advisor)
The music, in generaly, can calm down a human internally. The effect of Mozart’s music can even be measured. Students, who listened Mozart’s music, had higher IQ result and epileptiform activity is describing on patients with epilepsy. This master’s thesis is dealing with design of the evaluation system, which can determine music parameters describing epileptiform activity. In the solution is make detailed analysis of the tracks, signal parameterization, description of data processing and make the Pearson correlation analysis. In the final chapter are described music parameters, which suppress epileptiform activity in the women and the man.
|
|
| |
|
|
Analysis of epileptogenic tissue response to intracranial electrical stimulation
Formánková, Zuzana ; Klimeš, Petr (referee) ; Cimbálník, Jan (advisor)
This work deals with the methods of intracranial electrical stimulation and their usage in the localization of epileptogenic tissue. The aim of the thesis is to assess, with help of the proposed markers, the reaction of pathological tissue on the electrical stimulation. Among the suitable markers high-frequency oscillations were classified, interictal spikes, changes in the connectivity, and the signal power within the frequency zones. The markers were detected on the iEEG records taken at the Fakultní nemocnice u sv. Anny in Brno. A software in the Python language has been designed for the purpose of analysis and detection; the software uses the detection algorithms of the EPYCOM library. In the final part of the thesis, the occurrence of the markers was analyzed in terms of dependency on the electrical stimulation. The influence of the electrical stimulation on the iEEG records of patients with epilepsy has been proved.
|
|
|
Detection of High-Frequency EEG Activity in Epileptic Patients
Cimbálník, Jan ; Kremláček, Jan (referee) ; Jiruška,, Přemysl (referee) ; Jurák, Pavel (advisor)
Tato práce se zabývá automatickou detekcí vysokofrekvenčních oscilací jakožto moderního elektrofyziologického biomarkru epileptogenní tkáně v intrakraniálním EEG, jehož vizuální detekce je zdlouhavý proces, který je ovlivněn subjektivitou hodnotitele. Epilepsie je jedním z nejčastějších neurologických onemocnění postihující 1 % obyvatelstva. Přestože jsou přibližně dvě třetiny případů léčitelné farmakologicky, zbylá třetina pacientů je odkázána zejména na léčbu chirurgickým zákrokem, pro nějž je zapotřebí přesně lokalizovat ložisko patologické tkáně. Vysokofrekvenční oscilace jsou v posledním desetiletí studovány pro jejich potenciál lokalizace patologické tkáně. Součástí této práce je shrnutí dosavadního výzkumu vysokofrekvenčních oscilací a výčet detektorů používaných ve výzkumu. V rámci práce byly vyvinuty či vylepšeny tři detektory vysokofrekvenčních oscilací, na jejichž popis navazuje evaluace z hlediska shody s manuální detekcí, přesnosti výpočtu příznaků oscilací a schopnosti lokalizace patologické tkáně. V závěru práce jsou představeny vyvinuté metody vizualizace vysokofrekvenčních výskytu oscilací a stručně uvedeny dosažené vědecké výsledky.
|
|
| |
|
|
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.
|
|
|
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.
|
|
|
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.
|
|
|
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.
|
guest ::
