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Mapping of motion artefact in fMRI
Nováková, Marie ; Kremláček, Jan (referee) ; Jan, Jiří (advisor)
This thesis summarizes a theory of magnetic resonance and the method of functional magnetic resonance. It is focused on the influence of motion artifacts and image preprocessing methods, especially realign. It deals with the possibility of using movement parameters obtained in the process of alignment of functional scans to create maps that show the expression of motion artifacts. In this thesis, three different methods were designed, implemented a tested. These methods lead to the creation of probability, power and statistical group maps showing areas typically affected by movement artifacts.
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Design and Creation of Software Application for the Company Obicentrum spol. s r.o.
Kremláček, Jan ; Štepník, Štefan (referee) ; Dydowicz, Petr (advisor)
The thesis is focused on analysing the current situation of OBI Centrum, spol. s r.o., company engaged in manufacturing and assembling of chimneys and chimney parts and on analysing the information system of the company. The thesis is divided into three parts. The first part addresses the theoretical bases. The second part analyses the current situation of the company, evaluating the quality of informational system and the company in general. The last part presents a proposed solution to the problem revealed by the analysis.
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Relationship between Electrophysiological Activity and Dynamic Functional Connectivity of Large-scale Brain Networks in fMRI Data
Lamoš, Martin ; Hlinka, Jaroslav (referee) ; Kremláček, Jan (referee) ; Jan, Jiří (advisor)
Functional brain connectivity is a marker of the brain state. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during EEG data analysis may leave part of the neural activity unrecognized. A proposed approach blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. The blind decomposition of EEG spectrogram by Parallel Factor Analysis has been shown to be a useful technique for uncovering patterns of neural activity where each pattern contains three signatures (spatial, temporal, and spectral). The decomposition takes into account the trilinear structure of EEG data, as compared to the standard approaches of electrode averaging, electrode subset selection or using standard frequency bands. The simultaneously acquired BOLD fMRI data were decomposed by Independent Component Analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and functional connectivity network states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of functional connectivity network states and the fluctuations of EEG spectral patterns. Three patterns related to the dynamics of functional connectivity network states were found. Previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. This work suggests that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.
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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.
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Information System Assessment and Proposal of ICT Modification
Kremláček, Jan ; Novák, Lukáš (referee) ; Koch, Miloš (advisor)
The thesis is focused on the current situation and the information system analysis of the particular retail, which deals with the sale of animal feed and supplies. Furthermore, it provides the improvement proposal, in order to support company sales. The thesis is divided into three parts. The first part determines the theoretical basis. The second part analyses the current situation of the company, evaluates the quality of its information system and the company in general. The content of the practical part is a proposal of a sales promotion system through e-commerce.
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Joint EEG-fMRI analysis based on heuristic model
Janeček, David ; Kremláček, Jan (referee) ; Labounek, René (advisor)
The master thesis deals with the joint EEG-fMRI analysis based on a heuristic model that describes the relationship between changes in blood flow in active brain areas and in the electrical activity of neurons. This work also discusses various methods of extracting of useful information from the EEG and their influence on the final result of joined analysis. There were tested averaging methods of electrodes interest, decomposition by principal components analysis and decomposition by independent component analysis. Methods of averaging and decomposition by PCA give similar results, but information about a stimulus vector can not be extracted. Using ICA decomposition, we are able to obtain information relating to the certain stimulation, but there is the problem in the final interpretation and selection of the right components in a blind search for variability coupled with the experiment. It was found out that although components calculated from the time sequence EEG are independent for each to other, their spectrum shifts are correlated. This spectral dependence was eliminated by PCA / ICA decomposition from vectors of spectrum shifts. For this method, each component brings new information about brain activity. The results of the heuristic approach were compared with the results of the joined analysis based on the relative and absolute power approach from frequency bands of interest. And the similarity between activation maps was founded, especially for the heuristic model and the relative power from the gamma band (20-40Hz).
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Eye-Tracking Control of an Adjustable Bed
Kopeček, Martin ; Kremláček, Jan (advisor) ; Čapek, Lukáš (referee) ; Komzák, Martin (referee)
The origin of this work was based on the need to control an electric positioning bed by patients with no or significantly reduced upper limb motor skills. The key point and objective of the dissertation study was to develop non-contact alternatives to manual controls and to verify that the eye-tracking technique is usable and offers patients a new level of increased self-sufficiency. The thesis is organized into three related parts with experiments conducted at the detached departments and in the laboratory. After an introductory section covering the stages of development and current progressive trends in eye movement tracking, an experimental study of the applicability of bed control with the role of alternating head and leg position changes using on-screen graphical controls is described. This stage was conducted using a virtual bed. In a group of 17 patients with diagnoses of a pentaplegia, tetraplegia, high paraplegia, myopathy, and spinal muscular atrophy, the overall time to solve the task was 67.1 s (median) with a large interindividual variability with interquartile range from 56.7 s to 92.9 s. The solution efficiency (100 % matched to optimal performance) was 45.5 (34.9; 62.0) %. Within each group patients achieved different results for both studied parameters. When evaluating the features of the...
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Information System Assessment and Proposal of ICT Modification
Kremláček, Jan ; Novák, Lukáš (referee) ; Koch, Miloš (advisor)
The thesis is focused on the current situation and the information system analysis of the particular retail, which deals with the sale of animal feed and supplies. Furthermore, it provides the improvement proposal, in order to support company sales. The thesis is divided into three parts. The first part determines the theoretical basis. The second part analyses the current situation of the company, evaluates the quality of its information system and the company in general. The content of the practical part is a proposal of a sales promotion system through e-commerce.
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Relationship between Electrophysiological Activity and Dynamic Functional Connectivity of Large-scale Brain Networks in fMRI Data
Lamoš, Martin ; Hlinka, Jaroslav (referee) ; Kremláček, Jan (referee) ; Jan, Jiří (advisor)
Functional brain connectivity is a marker of the brain state. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during EEG data analysis may leave part of the neural activity unrecognized. A proposed approach blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. The blind decomposition of EEG spectrogram by Parallel Factor Analysis has been shown to be a useful technique for uncovering patterns of neural activity where each pattern contains three signatures (spatial, temporal, and spectral). The decomposition takes into account the trilinear structure of EEG data, as compared to the standard approaches of electrode averaging, electrode subset selection or using standard frequency bands. The simultaneously acquired BOLD fMRI data were decomposed by Independent Component Analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and functional connectivity network states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of functional connectivity network states and the fluctuations of EEG spectral patterns. Three patterns related to the dynamics of functional connectivity network states were found. Previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. This work suggests that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.
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