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Evaluation of neuromarketing and its applicability in practice
Kuchtová, Alexandra ; Sigmund, Tomáš (advisor) ; Čermák, Radim (referee)
The main point of the bachelor thesis is to evaluate neuromarketing and its practical applicability from different perspectives. The thesis includes the definition of neuromarketing and also its definition from the closely related sections viewpoints. The history and important milestones of neuromarketing are also briefly described. Furthermore, the thesis deals with theoretical areas that influence customer decision making, which is an important part of researches. In the next part, the work presents methods, used by neuromarketing and then it describes its potential benefits. From a practical point of view, the thesis looks at the most interesting examples of neuromarketing studies and explores the trends. Finally the thesis also describes the basic ethical issues that this scientific department brings and ultimately deals with the overall assessment of neuromarketing.
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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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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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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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