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Brain-computer interface technology establishes communication between the brain and a computer, allowing users to control devices, machines, or virtual objects using their thoughts. This study investigates optimal conditions to facilitate learning to operate this interface. It compares two biofeedback methods, which dictate the relationship between brain activity and the movement of a virtual ball in a target-hitting task. Preliminary results indicate that a method in which the position of the virtual object directly relates to the amplitude of brain signals is most conducive to success. In addition, this research explores learning in the context of neural signals during training with a BCI task. Specifically, it investigates whether subjects can adapt to parameters of the interface without guidance. This experiment prompts subjects to modulate brain signals spectrally, spatially, and temporally, as well differentially to discriminate between two different targets. However, subjects are not given knowledge regarding these desired changes, nor are they given instruction on how to move the virtual ball. Preliminary analysis of signal trends suggests that some successful participants are able to adapt brain wave activity in certain pre-specified locations and frequency bands over time in order to achieve control. Future studies will further explore these phenomena, and future BCI projects will be advised by these methods, which will give insight into the creation of more intuitive and reliable BCI technology.
ContributorsLancaster, Jenessa Mae (Co-author) / Appavu, Brian (Co-author) / Wahnoun, Remy (Co-author, Committee member) / Helms Tillery, Stephen (Thesis director) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / Department of Psychology (Contributor)
Created2014-05
Description
The mammalian target of rapamycin (mTOR) is integral in regulating cell growth as it maintains a homeostatic balance of proteins by modulating their synthesis and degradation. In the brain, mTOR regulates protein-driven neuroplastic changes that modulate learning and memory. Nevertheless, upregulation of mTOR can cause detrimental effect in spatial memory and synaptic plasticity. The proline-rich Akt-substrate 40 kDa (PRAS40) is a key negative regulator of mTOR, as it binds mTOR and directly reduces its activity. To investigate the role of PRAS40 on learning and memory, we generated a transgenic mouse model in which we used the tetracycline-off system to regulate the expression of PRAS40 specifically in neurons of the hippocampus. After induction, we found that mice overexpressing PRAS40 performed better than control mice in the Morris Water Maze behavioral test. We further show that the improvement in memory was associated with a decrease in mTOR signaling, an increase in dendritic spines in hippocampal pyramidal neurons, and an increase in the levels of brain-derived neurotrophic factor (BDNF), a neurotrophin necessary for learning and memory. This is the first evidence that shows that increasing PRAS40 in the mouse brain enhances learning and memory deficits.
ContributorsSarette, Patrick William (Author) / Oddo, Salvatore (Thesis director) / Caccamo, Antonella (Committee member) / Kelleher, Raymond (Committee member) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05