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Optimizing Biofeedback and Learning in an EEG-Based Brain-Computer Interface

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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…

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
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The Relationship between Neural Responses to Rejection and Depressive Symptoms in Adolescent Romantic Relationships: a Dual EEG Acquisition Study

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The research question this thesis aims to answer is whether depressive symptoms of adolescents involved in romantic relationships are related to their rejection sensitivity. It was hypothesized that adolescents who have more rejection sensitivity, indicated by a bigger P3b response, will have more depressive symptoms. This hypothesis was tested by…

The research question this thesis aims to answer is whether depressive symptoms of adolescents involved in romantic relationships are related to their rejection sensitivity. It was hypothesized that adolescents who have more rejection sensitivity, indicated by a bigger P3b response, will have more depressive symptoms. This hypothesis was tested by having adolescent couples attend a lab session in which they played a Social Rejection Task while EEG data was being collected. Rejection sensitivity was measured using the activity of the P3b ERP at the Pz electrode. The P3b ERP was chosen to measure rejection sensitivity as it has been used before to measure rejection sensitivity in previous ostracism studies. Depressive symptoms were measured using the 20-item Center for Epidemiological Studies Depression Scale (CES-D, Radloff, 1977). After running a multiple regression analysis, the results did not support the hypothesis; instead, the results showed no relationship between rejection sensitivity and depressive symptoms. The results are also contrary to similar literature which typically shows that the higher the rejection sensitivity, the greater the depressive symptoms.
ContributorsBiera, Alex (Author) / Dishion, Tom (Thesis director) / Ha, Thao (Committee member) / Shore, Danielle (Committee member) / Barrett, The Honors College (Contributor)
Created2015-05