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Perception of space in virtual reality environments
Fajnerová, Iveta ; Vlček, Kamil (advisor) ; Vavrečka, Michal (referee)
This thesis attempts to analyze spatial perception for navigation in a virtual arena and to cover neuronal basics of distance estimation. For this purpose, we created a virtual version of Hidden goal task which is an analogy to Morris water maze. The thesis presents results of the experiment with removing orientation cues in a circular arena. The aim of the experiment was to determine, if the assumption of Cognitive mapping theory about orientation cues equivalence is valid for our arena. Experiment outcome indicates that the accuracy of goal position estimation is not only influenced by the number of cues but also by the individual hierarchy of the cues. The hierarchy emerges from the distance of the cue from the goal, although in some cases it can be affected by an outstanding identity of the particular cue. These findings are a basis for the experiment utilizing the functional magnetic resonance method to determine neuronal basics for estimating distances in virtual arena in both the egocentric and allocentric reference frame. Results support the findings of the cited papers about the participation of occipital and parietal lobe in estimating object distance in space. Comparison of the two reference frames showed that whereas the egocentric estimation is related to activity in premotor cortex,...
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Neuromodulation in treatment of selected dystonic syndromes
Havránková, Petra ; Jech, Robert (advisor) ; Štětkářová, Ivana (referee) ; Rokyta, Richard (referee)
Dystonia is a neurological syndrome characterized by the involuntary contraction of opposing muscles, causing twisting movements or abnormal postures (modified by Fahn, 1987). Writer's cramp is the most common form of task-specific focal dystonia. In the first study, patients with writer's cramp were evaluated for differences in cortical activation during movements likely to induce cramps (complex movements) and movements which rarely lead to dystonia (simple movements). Although complex patient movements during fMRI were never associated with dystonic cramps, they exhibited abnormally decreased cortical activity. This was not observed in simple movements and was unrelated to the character of handwriting or the presence/absence of visual feedback. Our results support the theory of dualistic sensorimotor system behavior in writer's cramp. As the somatosensory system is believed to be affected in focal dystonia, we focused on modulation of the primary somatosensory cortex (SI) induced by repetitive transcranial magnetic stimulation (rTMS) in the second study, in order to improve writer's cramp. In conclusion, 1 Hz rTMS of the SI cortex can improve manifestations of writer's cramp while increasing cortical activity in both hemispheres. Handwriting as well as subjective assessment improved in most...
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Inverse values of EEG signal power in joint EEG-fMRI analysis
Sanetrníková, Dominika ; Kolář, Radim (referee) ; Labounek, René (advisor)
The first part of this thesis summarizes the basic theory of brain activity measurement using the BOLD signal and scalp EEG, the effect of noise phenomena in the data and its suppression, the merger of the fusion of the measured data using the general linear model and the current implementation of computational algorithms in the software library EEG Regressor Builder 1.0. Within the own solution of this thesis, the changes of the software library to version 1.1 were realized according to the requirements of the bachelor thesis. The hypothesis that temporal changes of the EEG relative band power (20 - 40Hz) has the same spatial correlates with the BOLD signal as the inverse power in the frequency range 0-12Hz. The hypothesis was rejected based on the calculation of similarity criterions between 3D activation maps for different parameter settings of the joint analysis calculations. As an appropriate criterions were chosen the correlation coefficient and the cosine criterion. The Euclidean distance was proved to be unfit. Also it was proved the inverse power value of EEG signal in the given frequency band brings to the common EEG-fMRI analysis an anti-correlated signal to the normal absolute power in the same frequency band. Furthermore the influence of regressors describing motion artifacts reduces the number of supra-thresholded voxels.
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Tool for analysis of subject's movements in functional magnetic resonance measurements.
Šejnoha, Radim ; Lamoš, Martin (referee) ; Gajdoš, Martin (advisor)
This diploma thesis deals with an analysis of subject’s movement during measurements with funcional magnetic resonance imaging (fMRI). It focuses on methods of a movement artifacts detection and their removal in fMRI images. Thesis deals with metrics which are used for the movement rate of measured subjects evaluation. Metrics and a correction of movement are implemented into the programme in MATLAB. Comparison of subjects suffering from Parkinson’s disease with a group of healthy control was carried out. Tresholds of individual metrics were suggested and a criterion for the removal of subjects with high movement rate was determined.
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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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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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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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Software for automatic data extraction in analysis of brain connectivity
Bujnošková, Eva ; Schwarz, Daniel (referee) ; Jan, Jiří (advisor)
The brain; complex system people want to know about but still they are at the beginning of understanding it. There has been a lot of neuroimaging systems since developement of modern technologies and magnetic resonance imaging is one of them. In last days it isn't enough to examine only structural character of brain, the scientists are dealing with functional states more and more; the functional magnetic resonance imaging is perfectly good tool for this. There is a big amount of researches concerning individual brain regions but also a lot of them dealing with communication across the brain to clear up the causes of human behavior and functional failures. This thesis introduces the brain connectivity exploration, it uses the parcellation by anatomical atlases and it tries to use the knowledge of graph theory as one of the options to determine relations between brain centres and regions. The thesis introduces the software created for extraction of connectivity matrix resulting in graph processing and visualization.
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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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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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