Show simple item record

dc.contributor.authorBeauchene, Christine Elizabethen_US
dc.date.accessioned2018-05-18T08:00:16Z
dc.date.available2018-05-18T08:00:16Z
dc.date.issued2018-05-17
dc.identifier.othervt_gsexam:14628en_US
dc.identifier.urihttp://hdl.handle.net/10919/83341
dc.description.abstractThe brain is a highly complex network of nonlinear systems with internal dynamic states that are not easily quantified. As a result, it is essential to understand the properties of the connectivity network linking disparate parts of the brain used in complex cognitive processes, such as working memory. Working memory is the system in control of temporary retention and online organization of thoughts for successful goal directed behavior. Individuals exhibit a typically small capacity limit on the number of items that can be simultaneously retained in working memory. To modify network connections and thereby augment working memory capacity, researchers have targeted brain areas using a variety of noninvasive stimulation interventions. However, few existing methods take advantage of the brain's own structure to actively generate and entrain internal oscillatory modulations in locations deep within the auditory pathways. One technique is known as binaural beats, which arises from the brain's interpretation of two pure tones, with a small frequency mismatch, delivered independently to each ear. The mismatch between these tones is perceived as a so-called beat frequency which can be used to modulate behavioral performance and cortical connectivity. Currently, all binaural stimulation therapeutic systems are open-loop "one-size-fits-all" approaches. However, these methods can prove not as effective because each person's brain responds slightly differently to exogenous stimuli. Therefore, the driving motivation for developing a closed-loop stimulation system is to help populations with large individual variability. One such example is persons with mild cognitive impairment (MCI), which causes cognitive impairments beyond those expected based on age. Therefore, applying a closed-loop binaural beat control system to increase the cognitive load level to people with MCI could potentially maintain their quality of life. In this dissertation, I will present a comparison of algorithms to determine brain connectivity, results of open-loop based binaural stimulation, the development of a closed-loop brain network simulation platform, and finally an experimental study to determine the effectiveness of closed-loop control to modulate brain networks hence influencing cognitive abilities.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis item is protected by copyright and/or related rights. Some uses of this item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectBinaural beatsen_US
dc.subjectElectroencephalographyen_US
dc.subjectNeural networksen_US
dc.subjectWorking memoryen_US
dc.titleEEG-Based Control of Working Memory Maintenance Using Closed-Loop Binaural Stimulationen_US
dc.typeDissertationen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineMechanical Engineeringen_US
dc.contributor.committeechairAbaid, Nicole Teresaen_US
dc.contributor.committeechairLeonessa, Alexanderen_US
dc.contributor.committeememberMoran, Rosalyn Jackieen_US
dc.contributor.committeememberDiana, Rachel A.en_US
dc.contributor.committeememberSouthward, Steve C.en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record