Browsing by Subject "Uni"
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(2019)Sleep is one of the most vital functions of newborns and infants, and it is essential for neuronal network development. Therefore, long-term sleep disturbances have been associated with growth delays and behavioral disorders. Commonly reported infant sleep disturbances, such as night awakenings and difficulties falling asleep, cause distress to parents. Yet, the development of infant sleep in the home environment has not been fully elucidated due to lack of objective measurement parameters. In the current study, we assessed the feasibility of a motion sensor, attached to wearable pants, and ECG textile electrodes to monitor sleep-related respiration and heart rate of newborns and infants. First, we compared signals recorded by the motion sensor’s measurement channels to the standard respiratory piezo effort belt’s signal during daytime EEG recordings. According to our results, the motion sensor’s gyroscope proved to measure respiratory rate most accurately, while the ECG signal transmitted by the sensor was reliable in interpretable sections. We then provided wearable garments and smartphones to families with infants to assess overnight home-use. Our results indicate that different sleep states could likely be identified based on respiration fluctuation visible in the gyroscope’s signals. Moreover, the wearable system was considered practical and easy to use by the parents. Future studies should focus on validating the sensor with clinically approved measures, in order to train the algorithms to automatically identify different sleep-wake states. By doing so, the wearable sensor could provide information on natural infant sleep structure development over long time periods. Additionally, clinical validation of the sensor may result in the development of a companion diagnostic tool for infant cardiorespiratory and movement disorders.
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(2019)Memory is based on the brain’s ability to save information from the surroundings of the animal. Memory has three main functions: the encoding and consolidation of new memory traces and the retrieval. Oscillations are cyclic variations occurring in time. Neural oscillations are brain’s electric activity that can be viewed in cellular level or in the level of brain areas. The aim of this thesis is to review recent models about the role of neural oscillations in the encoding and consolidation of long term memories. Memory traces form when the connections of the neurons active in the encoding are strenghtened. New memory traces are stabilized to the long term memory in the consolidation processes. Consolidation contains both the strenghtening of local synaptic connections (synaptic consolidation) and the system consolidation, which solidifies the memory traces to the already existing information networks. According to the standard model of system consolidation new memory traces are saved simultaneously to the short term memory storage in the hippocampus and the long term storage in the cortex. The consolidation of the memory traces occurs when the memory traces in hippocampus are repeatedly reactivated which strengthens the analogous memory traces in the cortex. Neural oscillations are part of the memory processes both in awake state and sleep. In the awake state the main process is the encoding of new memories which for declarative memories is thought to occur mainly in hippocampus, mediated by for example gamma and theta oscillations. During the sleep the processes of the system consolidation are presumably in the main role, mediated by neural oscillations characteristic for different sleep stages (for example sharp-wave ripples and sleep spindles in slow wave sleep). Slow wave sleep is thought to be specifically important for the consolidation occurring in the sleep. On the other hand the role of lighter sleep stages may be greater than it has earlier been assumed. There is no complete understanding of the roles of different sleep stages and sleep time neural oscillations, and different partly contradictory, partly complementary models have been proposed.
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(2022)Objectives: Sleep difficulties are more frequent and have a wide effect on health and mental health. Epigenetics studies the complex interplay of genetics and environmental factors, thus helping to locate networks relating to sleep difficulties. This thesis investigates how epigenetic markers, discovered in 2019 in Health 2000 data, that were associated with sleep difficulties associated with DILGOM 2007 data’s wellbeing factors. We hypothesize that they relate to sleep and mood variables also in this data. Methods: DILGOM 2007 data is a part of THLs FINRISKI 2007 population data and it was originally collected for metabolic syndrome research. The sample size that included methylation data was 511 with ages ranging from 25 to 74. This thesis compares 203 differentially methylated positions (DMP), found in both data sets, to wellbeing variables. At first, correlations were examined between systemic methylation levels and fenotype variables. Then, correlations of white blood cell populations to psychosocial variables were examined. Lastly 5 DMPs were chosen based on previous research for further examination, and regression analyses were conducted to model their methylations. Results and conclusions: In this data DMPs were not significantly related to sleep or mood variables anymore as previously assumed. Instead, DMPs strongly correlated with BMI in the whole data. In white blood cell populations CD8T significantly correlated with psychosocial burden. Additionally antidepressants, BMI and CD8T cells explained the variance of methylation in genes chosen for further examination. High BMI in the data seems to mediate the results reflecting underlying low grade inflammation. Epigenetic markers relating to sleep difficulties could reflect low grade inflammation, which is either caused by sleep difficulties or manifests as sleep difficulties.
Now showing items 1-3 of 3