Detection of neuronal replay of parabolic experiences during sleep in humans, A feasibility study

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dc.contributor.advisorDresler, M.
dc.contributor.advisorFarquhar, J.D.R.
dc.contributor.authorTump, D.W.
dc.date.issued2018-08-20
dc.description.abstractNeuronal replay of recent wake experiences during sleep is thought to be an important concept in memory consolidation. Evidence for replay during human sleep is sparse, however, due to the high number of learning experiences that humans experience during a day. As the novelty of an experience is correlated with the chance of nding neuronal replay, a highly novel experience during wakefulness might be needed for the detection of this replay during sleep. The current project explored the possibility of finding evidence for the existence of neuronal replay by means of extreme vestibular learning events, specifically that of parabolic flights. Due to the limited research on parabolic flights and neuronal replay, this research is mainly conducted in an exploratory fashion. Results show indirect evidence for the existence of neuronal replay with significant differences in sleep characteristics after the experience of a parabolic flight. The use of parabolic flights is therefore a possible method in research towards neuronal replay. The research conducted in this project consists of two main part. The rst part is the in-depth analysis of the flightdata and sleepdata, this is done by rst identifying gravity related changes in EEG signal during the flight and then comparing that to non-invasive EEG measurements during sleep before and after the event. The second part uses these results combined with machine learning techniques to find differences between preflight and post flight sleep. The rst part is the main report, the second part is the additional Artificial Intelligence section of the project.en_US
dc.identifier.urihttps://theses.ubn.ru.nl/handle/123456789/7088
dc.language.isoenen_US
dc.thesis.facultyFaculteit der Sociale Wetenschappenen_US
dc.thesis.specialisationMaster Artificial Intelligenceen_US
dc.thesis.studyprogrammeArtificial Intelligenceen_US
dc.thesis.typeMasteren_US
dc.titleDetection of neuronal replay of parabolic experiences during sleep in humans, A feasibility studyen_US
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