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Alzheimer's Disease Profile in the UDS Neuropsychological Battery
Čihák, Martin ; Nikolai, Tomáš (advisor) ; Děchtěrenko, Filip (referee)
Background: Neuropsychological assessment plays a key role in cognitive impairment diagnosis. Moreover, determining the cognitive profile can help to uncover the aetiology of the impairment. Previous studies found that memory impairment is especially typical for Alzheimer's disease. In UDS 2, one of most common neuropsychological batteries, this is manifested by a low score in Logical Memory test. Aims: To describe a profile of early cognitive deficit in Alzheimer disease using the UDS 2 battery in comparison with deficits of other aetiologies and to assess the ability of UDS 2 to distinguish Alzheimer's disease from other causes of cognitive deficit. Methods: 190 patients with Mild Cognitive Impairment underwent an assessment of Alzheimer's disease biomarkers, UDS 2 battery and other neuropsychological tests. The probability of suffering from Alzheimer's disease was modelled with the use of binominal regression on the neuropsychological assessment results. Results: Using UDS 2 battery, Alzheimer's disease patients can be best discriminated from patients with otherwise caused cognitive deficit with the test of episodic memory (delayed recall score in Logical Memory test). Other tests significantly improved the accuracy of the estimate of probability of suffering from Alzheimer's disease. Therefore,...
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Modelling eye movements during Multiple Object Tracking
Děchtěrenko, Filip ; Lukavský, Jiří (advisor) ; Toth, Peter Gabriel (referee)
In everyday situations people have to track several objects at once (e.g. driving or collective sports). Multiple object tracking paradigm (MOT) plausibly simulate tracking several targets in laboratory conditions. When we track targets in tasks with many other objects in scene, it becomes difficult to discriminate objects in periphery (crowding). Although tracking could be done only using attention, it is interesting question how humans plan their eye movements during tracking. In our study, we conducted a MOT experiment in which we presented participants repeatedly several trials with varied number of distractors, we recorded eye movements and we measured consistency of eye movements using Normalized scanpath saliency (NSS) metric. We created several analytical strategies employing crowding avoidance and compared them with eye data. Beside analytical models, we trained neural networks to predict eye movements in MOT trial. The performance of the proposed models and neuron networks was evaluated in a new MOT experiment. The analytical models explained variability of eye movements well (results comparable to intraindividual noise in the data); predictions based on neural networks were less successful.
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Comparison of scan patterns in dynamic tasks
Děchtěrenko, Filip ; Lukavský, Jiří (advisor) ; Nyström, Marcus (referee) ; Paluš, Milan (referee)
Eye tracking is commonly used in many scientific fields (experimental psychology, neuroscience, behavioral economics, etc.) and can provide us with rigorous data about current allocation of attention. Due to the complexity of data processing and missing methodology, experimental designs are often limited to static stimuli; eye tracking data is analyzed only with respect to basic types of eye movements - fixation and saccades. In dynamic tasks (e.g. with dynamic stimuli, such as showing movies or Multiple Object Tracking task), another type of eye movement is commonly present: smooth pursuit. Importantly, eye tracking data from dynamic tasks is often represented as raw data samples. It requires a different approach to analyze the data, and there are a lot of methodological gaps in analytical tools. This thesis is divided into three parts. In the first part, we gave an overview of current methods for analyzing scan patterns, followed by four simulations, in which we systematically distort scan patterns and measure the similarity using several commonly used metrics. In the second part, we presented the current approaches to statistical testing of differences between groups of scan patterns. We present two novel strategies for analyzing statistically significant differences between groups of scan patterns and...
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Content-based Image Search
Talaš, Josef ; Surynek, Pavel (advisor) ; Děchtěrenko, Filip (referee)
This work aims at content-based image search. Different approaches to this type of search are investigated. The main focus of the thesis is special category of content-based image search called sketch-based image search. The most important descriptor types used for image feature extraction in image search are analyzed. Main contribution of the thesis to this research area is a new feature extraction method based on sketch-based image search. This method is implemented together with search interface. The method was evaluated by three test persons. The testing results show promising properties of new method and suggest further possible improve-ments. Powered by TCPDF (www.tcpdf.org)
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Bayesian models of eye movements
Lux, Erik ; Děchtěrenko, Filip (advisor) ; Toth, Peter Gabriel (referee)
Attention allows us to monitor objects or regions of visual space and extract information from them to use for report or storage. Classical theories of attention assumed a single focus of selection but many everyday activities, such as playing video games, suggest otherwise. Nonetheless, the underlying mechanism which can explain the ability to divide attention has not been well established. Numerous attempts have been made in order to clarify divided attention, including analytical strategies as well as methods working with visual phenomena, even more sophisticated predictors incorporating information about past selection decisions. Virtually all the attempts approach this problem by constructing a simplified model of attention. In this study, we develop a version of the existing Bayesian framework to propose such models, and evaluate their ability to generate eye movement trajectories. For the comparison of models, we use the eye movement trajectories generated by several analytical strategies. We measure the...
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Bayesian models of eye movements
Lux, Erik ; Děchtěrenko, Filip (advisor) ; Toth, Peter Gabriel (referee)
Attention allows us to monitor objects or regions of visual space and extract information from them to use for report or storage. Classical theories of attention assumed a single focus of selection but many everyday activities, such as playing video games, suggest otherwise. Nonetheless, the underlying mechanism which can explain the ability to divide attention has not been well established. Numerous attempts have been made in order to clarify divided attention, including analytical strategies as well as methods working with visual phenomena, even more sophisticated predictors incorporating information about past selection decisions. Virtually all the attempts approach this problem by constructing a simplified model of attention. In this study, we develop a version of the existing Bayesian framework to propose such models, and evaluate their ability to generate eye movement trajectories. For the comparison of models, we use the eye movement trajectories generated by several analytical strategies. We measure the similarity between...
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The Focusing of Mental Attention During Sexual Intercourse and the Ability to Achieve Orgasm in Women
Hůtová, Lucie ; Weiss, Petr (advisor) ; Děchtěrenko, Filip (referee)
The present thesis focuses on the relationship between cognitive distractions and female ability to achieve orgasm and female sexual function. The theoretical part summarises current knowledge about female sexual response, the ability to achieve orgasm and explains the concept of cognitive distractions in the context of the spectatoring theory and cognitive interference. The empirical part is split into two phases. First one describes the process of creation, pilot measurements and psychometric evaluation of own measuring tool, Cognitive distractions questionnaire (Dotazník kognitivních distraktorů, DKD). It presents three independent subscales - sexual behavior (DKD-S), negative body image (DKD- B) and bad timing (DKD-C). All subscales were evauated via confirmatory factorial analysis and showed good reliability. The second phase was designed as an explorative correlation study. It focused on finding a relationship between distractions of each subscale of DKD and female ability to achieve orgasm, which was measured with Female Sexual Function Index (FSFI, Rosen et al., 2000). Data was collected via a snowball method with an online questionnaire. Sample consisted of 352 women in the age between 18 and 56 years. Spearman correlation indicated a negative relationship between distractions of sexual...
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Pareidolia and its evolutionary significance
Grégr, Richard ; Tureček, Petr (advisor) ; Děchtěrenko, Filip (referee)
In our everyday lives, we come across situations where we might get the impression of seeing characters in the clouds, or faces in moon crates. We think that we found a pattern that we can use to beat a slot-machine, that the constellation of the stars influences us, that we hear voices in background noise, or hear tones in it. All these examples are instances of a phenomenon called apophenia. In other words, apophenia denotes situations where we make a pattern recognition error. A special case of apophenia, in which our brains make the error during the immediate sensory information processing, is called pareidolia. Today there is no unified opinion about the definition of apophenia and pareidolia. This thesis is concerned with the findings about pareidolia, whether it is a product of an evolutionary effort to minimize losses and pattern overfitting. Furthermore, it clarifies apophenia with pareidolia as a special case, and offers a more detailed look at face pareidolia; how our brain processes information about faces, differences between the sexes in propensity to face recognition, and a possible explanation of its evolutionary origin. Key words: pareidolia, apophenia, error management, psychotism, perception
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Detection of dynamic Gabor patches in 1/f noise
Šerý, Martin ; Děchtěrenko, Filip (advisor) ; Pilát, Martin (referee)
Research focusing on static scenes with static objects is omitting the time factor from real life examples we are trying to study. Can we say that a lifeguard looking for a drowning man is using the same brain processes that were observed in the laboratory for static scenes? We can conclude that a static scene is a big simplification of the task itself. The aim of this thesis is to prepare a tool which would allow researching dynamic scenes and thus broadening the possibilities of visual detection tasks at hand. Along the tool we also present a couple of simplified examples with which we would like to demonstrate the utilization of the tool. All concluding with a final experiment in which we will try to detect masked patterns in a noisy environment. 1
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Visual Memory in the perception of prototypical scenes
Děchtěrenko, Filip ; Lukavský, Jiří (advisor) ; Kulišťák, Petr (referee)
To be able to operate in the world around us, we need to store visual information for further processing. Since we are able to memorize a vast array of visual scenes (photographs of the outside world), it is still an open question of how we represent these scenes in memory. Research shows that perception and memory for visual scenes is a complex problem that requires contribution from many subfields of vision science. In this work we focused on the visual scene memory on the creation of perceptual prototypes. Using convolutional neural networks, we defined the similarity of scenes in the scene space, which we used in two experiments. In the first experiment, we validated this space using a paradigm for detecting an odd scene. In the second experiment, using the Deese-Roediger-McDermott paradigm, we verified the creation of false memories and thus visual prototypes. The results show that people intuitively understand the scene space (Experiment 1) and that a visual prototype is created even in the case of the complex stimuli such as scenes. The results have wide application either for machine evaluation of image similarities or for visual memory research.
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