@phdthesis{RuedtvonCollenberg2021,
  author    = {R{\"u}dt von Collenberg, Cora Freifrau},
  title     = {The role of Ciliary Neurotrophic Factor in hippocampal synaptic plasticity and learning},
  doi       = {10.25972/OPUS-20664},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-206646},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {Ciliary neurotrophic factor (Cntf) acts as a differentiation and survival factor for different types of neurons and glial cells. It is expressed by peripheral Schwann cells and astrocytes in the central nervous system and mediates its effects via a receptor complex involving CntfRα, LifRß and gp130, leading to downstream activation of Stat3. Recent studies by our group have shown that Cntf modulates neuronal microtubule dynamics via Stat3/stathmin interaction. In a mouse model for motor neuron disease, i.e. pmn, Cntf is able to rescue axonal degeneration through Stat3/stathmin signaling. While these findings suggest a role of Cntf in controlling axonal functions in the neuromuscular system, additional data indicate that Cntf might also play a role in synaptic plasticity in the hippocampus. Electrophysiological recordings in hippocampal organotypic cultures and acute slices revealed a deficit in long-term potentiation (LTP) in Cntf -/- mice. This deficit was rescued by 24 h stimulation with Cntf, combined with an acute application of Cntf during LTP-measurements indicating that Cntf is both necessary and sufficient for hippocampal LTP, and possibly synaptic plasticity. Therefore, Cntf knockout mice were investigated to elucidate this possible role of Cntf in hippocampal LTP and synaptic plasticity. First, we validated the presence of Cntf in the target tissue: in the hippocampus, Cntf was localized in Gfap-positive astrocytes surrounding small blood vessels in the fissure and in meningeal areas close to the dentate gyrus. Laser micro-dissection and qPCR analysis showed a similar distribution of Cntf-coding mRNA validating the obtained immunofluorescent results. Despite the strong LTP deficit in organotypic cultures, in vivo behavior of Cntf -/- mice regarding hippocampus-dependent learning and anxiety-related paradigms was largely inconspicuous. However, western blot analysis of hippocampal organotypic cultures revealed a significant reduction of pStat3 levels in Cntf -/- cultures under baseline conditions, which in turn were elevated upon Cntf stimulation. In order to resolve and examine synaptic structures we turned to in vitro analysis of cultured hippocampal neurons which indicated that pStat3 is predominantly located in the presynapse. In line with these findings, presynapses of Cntf -/- cultures were reduced in size and when in contact to astrocytes, contained less pStat3 immunoreactivity compared to presynapses in wildtype cultures. In conclusion, our findings hypothesize that despite of a largely inconspicuous behavioral phenotype of Cntf -/- mice, Cntf appears to have an influence on pStat3 levels at hippocampal synapses. In a next step these two key questions need to be addressed experimentally: 1) is there a compensatory mechanism by members of the Cntf family, possibly downstream of pStat3, which explains the in vivo behavioral results of Cntf -/- mice and can likewise account for the largely inconspicuous phenotype in CNTF-deficient humans? 2) How exactly does Cntf influence LTP through Stat3 signaling? To unravel the underlying mechanism further experiments should therefore investigate whether microtubule dynamics downstream of Stat3 and stathmin signaling are involved in the Cntf-induced modulation of hippocampal synaptic plasticity, similar to as it was shown in motoneurons.},
  subject      = {Hippocampus},
  language  = {en}
}
@phdthesis{Oberdoerfer2021,
  author    = {Oberd{\"o}rfer, Sebastian},
  title     = {Better Learning with Gaming: Knowledge Encoding and Knowledge Learning Using Gamification},
  doi       = {10.25972/OPUS-21970},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-219707},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {Computer games are highly immersive, engaging, and motivating learning environments. By providing a tutorial at the start of a new game, players learn the basics of the game's underlying principles as well as practice how to successfully play the game. During the actual gameplay, players repetitively apply this knowledge, thus improving it due to repetition. Computer games also challenge players with a constant stream of new challenges which increase in difficulty over time. As a result, computer games even require players to transfer their knowledge to master these new challenges. A computer game consists of several game mechanics. Game mechanics are the rules of a computer game and encode the game's underlying principles. They create the virtual environments, generate a game's challenges and allow players to interact with the game. Game mechanics also can encode real world knowledge. This knowledge may be acquired by players via gameplay. However, the actual process of knowledge encoding and knowledge learning using game mechanics has not been thoroughly defined, yet. This thesis therefore proposes a theoretical model to define the knowledge learning using game mechanics: the Gamified Knowledge Encoding. The model is applied to design a serious game for affine transformations, i.e., GEtiT, and to predict the learning outcome of playing a computer game that encodes orbital mechanics in its game mechanics, i.e., Kerbal Space Program. To assess the effects of different visualization technologies on the overall learning outcome, GEtiT visualizes the gameplay in desktop-3D and immersive virtual reality. The model's applicability for effective game design as well as GEtiT's overall design are evaluated in a usability study. The learning outcome of playing GEtiT and Kerbal Space Program is assessed in four additional user studies. The studies' results validate the use of the Gamified Knowledge Encoding for the purpose of developing effective serious games and to predict the learning outcome of existing serious games. GEtiT and Kerbal Space Program yield a similar training effect but a higher motivation to tackle the assignments in comparison to a traditional learning method. In conclusion, this thesis expands the understanding of using game mechanics for an effective learning of knowledge. The presented results are of high importance for researches, educators, and developers as they also provide guidelines for the development of effective serious games.},
  subject      = {Serious game},
  language  = {en}
}