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Analysis of connections between simultaneous EEG and fMRI data
Labounek, René ; Kremláček,, Jan (referee) ; Lamoš, Martin (advisor)
Electroencephalography and functional magnetic resonance are two different methods for measuring of neural activity. EEG signals have excellent time resolution, fMRI scans capture records of brain activity in excellent spatial resolution. It is assumed that the joint analysis can take advantage of both methods simultaneously. Statistical Parametric Mapping (SPM8) is freely available software which serves to automatic analysis of fMRI data estimated with general linear model. It is not possible to estimate automatic EEG–fMRI analysis with it. Therefore software EEG Regressor Builder was created during master thesis. It preprocesses EEG signals into EEG regressors which are loaded with program SPM8 where joint EEG–fMRI analysis is estimated in general linear model. EEG regressors consist of vectors of temporal changes in absolute or relative power values of EEG signal in the specified frequency bands from selected electrodes due to periods of fMRI acquisition of individual images. The software is tested on the simultaneous EEG-fMRI data of a visual oddball experiment. EEG regressors are calculated for temporal changes in absolute and relative EEG power values in three frequency bands of interest ( 8-12Hz, 12-20Hz a 20-30Hz) from the occipital electrodes (O1, O2 and Oz). Three types of test analyzes is performed. Data from three individuals is examined in the first. Accuracy of results is evaluated due to the possibilities of setting of calculation method of regressor. Group analysis of data from twenty-two healthy patients is performed in the second. Group EEG regressors analysis is realized in the third through the correlation matrix due to the specified type of power and frequency band outside of the general linear model.
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Effect of brain regions coordinates selection on dynamic causal modelling results
Veselá, Martina ; Harabiš, Vratislav (referee) ; Lamoš, Martin (advisor)
Master’s thesis is aimed at familiarization with the principles of measurement and data processing functional magnetic resonance, focusing on the analysis of effective connectivity using dynamic causal modelling (DCM). The practical part includes three main thematic areas relating to the description of the processing and evaluation of measured or simulated data. First, there is on sample dataset described the neuroscientific SPM toolbox to analyze measured data. Then follows introduction of the proposed approach with which is investigated the behavior of the model estimation neural interactions with respect to the change of input parameters. This phenomenon is also simulated and on base of achieved results is recommended optimal approach to analyzing effective connectivity using dynamic causal modeling for the group of subjects. The last circuit in the practical part is assessment of shift the coordinates of brain areas on dynamic causal modelling results for the group of subjects from the data obtained from real measurements. Obtained results from simulated data and the results obtained from measured data are evaluated and discussed in the final part.
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Spatial-temporal analysis of HD-EEG data in pacients with nerodegenerative disease
Jordánek, Tomáš ; Kozumplík, Jiří (referee) ; Lamoš, Martin (advisor)
This master’s thesis deals with diagnostics of prodromal stage of Lewy body disease using microstate analysis. First part of the thesis includes theoretical background which is needed for understanding discussed topics and presented results. This part consists of description of the disease, diagnostic options, electroencephalography, pre-processing of the EEG record and the microstate analysis process. Theoretical background is followed by a practical part of the thesis. In the beginning, there is a chapter about a dataset, used EEG device, and own solution of the pre-processing. Microstate analysis is discussed next, its output parameters were compared between groups with statistical methods. Comparison of the subjects in prodromal stage of Lewy body disease and healthy controls brought significant differences in three parameters of microstates, in rate of unlabelled time frames and also for some counts of transitions between each map or unlabelled sections. Comparison of the subjects in prodromal stage of Lewy body disease and healthy controls brought significant differences in three parameters of microstates, in rate of unlabelled time frames and also for some counts of transitions between each map or unlabelled sections.
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Hemodynamic model in effective brain connectivity analysis using fMRI
Holeček, Tomáš ; Harabiš, Vratislav (referee) ; Lamoš, Martin (advisor)
Modeling of hemodynamic response based on changes of synaptic activity is used for mapping active areas of the brain or functional organization of the brain using functional magnetic resonance imaging. Hemodynamic model is one of the methods for modeling hemodynamic response. Balloon model is the main part of the hemodynamic model. Hemodynamic model is used in the mapping active areas using general linear model and in the effective brain connectivity analysis using dynamic causal modelling. This bachelor´s thesis is focused on description of the hemodynamic model, its parameters and impact of every single parameter of the hemodynamic model on its response.
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Visualisation of tissue surface from volume OCT data
Kostiha, Marek ; Lamoš, Martin (referee) ; Čmiel, Vratislav (advisor)
Display surface is almost commonplace for a man. It uses the difference in brightness of individual objects and surface objects. Use in science, however, is considerably more complicated. Modern computer technologies till not its computing power even the human brain. The maximum achievable resolution with the technology but the human eye cannot cope. Although science and other technical fields are significantly burdened by noise that is needed to suppress and some technologies are very challenging, in many ways surpassed human performance and has become indispensable.
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Hard and soft exudates detection in retinal images
Válková, Hana ; Lamoš, Martin (referee) ; Kolář, Radim (advisor)
The thesis deals with automatic detection of soft and hard exudates in retinal images of the human eye. In its introduction the thesis describes the issue of diabetes in relation to the damage to the retina of the eye. What is described in the first place is diabetic retinopathy, its symptoms and progression of the disease. Another section is devoted to describing DIARETDB1, the freely accessible database which besides other things contains a set of images showing various degrees of disease, evaluation of images from the experts and the evaluation protocol. The next section discusses several methods for automatic detection of hard and soft exudates. The practical part of the bachelor’s thesis is aimed at image pre-processing with respect to the normalization of retinal images, the selected method for adaptive transformation of contrast was implemented. This part also containts description of chosen methology of thresholding, feature extraction based on lesions intensity and its surroundings, use of Ho Kashyap classifier is described, classification of lesions in images is followed. In conclusion realized methods is evaluated.
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Toolbox for neuronal datasets
Malý, Lukáš ; Harabiš, Vratislav (referee) ; Lamoš, Martin (advisor)
The aim of this bachelor's thesis was to create toolbox for functional magnetic resonance (fMRI) and electroencefalography (EEG) data processing in MATLAB enviroment using SPM software package. The first part describes the physiological origin of these data at neuronal level, basics of magnetic resonance imaging, principles of fMRI experiment, preprocessing and processing of fMRI data, their interpretation, then function and principles of EEG are described and at the end is simultaneous EEG-fMRI described. In the second part of the thesis features of each tool from Neural Data Toolbox (NDTb) are described.
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Influence of the reaction time on neuronal response amplitude after the uncommon stimuli in fMRI images
Klimeš, Filip ; Bartoň, Marek (referee) ; Lamoš, Martin (advisor)
The goal of my bachelor’s thesis is to provide basic idea of the functional magnetic resonance imaging. The theoretical part deals with general principles, methods of measurement and analysis of fMRI data. The partial and also key objective is to design ways of modelling reaction time within the concept of general linear model. The goal of the practical part was to become familiar with SPM toolbox and then to implement designed ways on group data. The implementation was carried out at two levels: preprocessing and analysis of measured data. Preprocessed data were subjected to the first level analysis and second level analysis. Next aim is to evaluate the results of both analysis and thus different approaches to the modelling of reaction time and its influence on neuronal response amplitude after uncommon stimuli in functional magnetic resonance images.
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Vztahy mezi oscilacemi a jejich využití u adaptivní hluboké mozkové stimulace
Lamoš, Martin ; Bočková, Martina ; Daniel, Pavel ; Baláž, Marek ; Chrastina, Jan ; Rektor, Ivan
Hluboká mozková stimulace (DBS) patří vedle dopaminergní léčby k nejvýznamnějším terapeutickým přístupům u Parkinsonovy nemoci (PN). Snaha potlačit některé limitace této terapie vede ke zvýšenému zájmu o přístupy jako je adaptivní DBS (aDBS). Stimulace s uzavřenou smyčkou řízená fluktuacemi výkonu v beta pásmu však nemusí být optimální pro všechny pacienty s PN. S cílem nalézt více senzitivní ukazatel než samotnou beta aktivitu byly analyzovány vztahy mezi jednotlivými oscilacemi v kontextu optimální stimulace subthalamického jádra (STN). Vztah fáze beta rytmu a amplitudy vysokofrekvenčních oscilací se jeví jako vhodný parametr pro cílení stimulace.
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Toolbox for automatic EEG data quality assessment
Meloun, Jan ; Gajdoš, Martin (referee) ; Lamoš, Martin (advisor)
This thesis deals with designing a tool for automatically evaluating the quality of electroencephalographic data. In the theoretical part of the thesis, there is a theoretical basis in the anatomy of the central nervous system and the brain, followed by a description of the origin and propagation of the action potential through the nervous system. Furthermore, the theoretical part of the work is devoted to electroencephalography (EEG) and the description of the EEG recording, including typical artefacts in it. The following describes the methods used to detect and remove artefacts. These are primary methods for extracting data quality features. The practical part of the thesis contains a description of the design of a tool for automatic EEG quality assessment and its testing on artificial and real data. The last part of the work is devoted to the discussion of the results of the success of the detection of channels or sections with artefacts and the possible further extension of the tool.
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