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dc.contributor.advisorBergman, Aviv
dc.contributor.authorBurke, Kelly M.
dc.date.accessioned2020-04-01T09:11:33Z
dc.date.available2020-04-01T09:11:33Z
dc.date.issued2018
dc.identifier.citationSource: Dissertations Abstracts International, Volume: 80-04, Section: B.;Publisher info.: Dissertation/Thesis.;Advisors: Bergman, Aviv.en_US
dc.identifier.isbn978-0-438-53318-9
dc.identifier.urihttps://yulib002.mc.yu.edu/login?url=http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10997400en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12202/5321
dc.description.abstractHumans perform sub-optimally when juggling more than one task but are nonetheless required to multitask during many daily activities. Rapidly and effectively switching attentional focus between tasks is fundamental to navigating complex environments. Task-switching paradigms in conjunction with neuroimaging and electrophysiology have identified a frontoparietal network underpinning flexible reallocation of cognitive resources. At the same time, there are performance costs such as slowed responses and reduced accuracy associated with switches of task compared to repeats. These costs range widely in the literature, and there is no consensus about which regions are strictly involved. This is likely because there are at least three main sources of competition inherent in task-switching studies: 1) the need to reconfigure the task rules, 2) the immediate history of motor responding, and 3) whether inputs to be acted upon provide congruent or incongruent information regarding the appropriate motor response. No single study has investigated the underlying circuitry of all three sources of competition. To this end, we employed a multi-day approach, collecting an order of magnitude more data per participant than is typical, with both functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) on healthy adults to investigate these aspects of cognitive flexibility. First, we explored how much individual variability there is in the costs associated with these three sources of conflict. Second, we investigated a precise delineation of the subcomponents that regulate each aspect of cognitive control to identify both common (domain-general) and non-overlapping (dissociable) neural circuits. Finally, but importantly, we asked which of these brain region's activity would correlate or predict response times during task-switching, to directly explain the delays in response times. Overall, this work demonstrated wide inter-individual and intra-individual variability in the performance costs associated with these three sources of conflict. Underlying these effects, there were three dissociable networks of brain regions involved in resolving these three aspects of cognitive flexibility, which are described fully. Importantly, the posterior cingulate, a known region in the default mode network, was the region primarily responsible for observed task-switching effects. This work proposes a novel role of the posterior cingulate cortex as an integral hub of information flow for successful cognitive flexibility, whose activity predicts response times. This work took a more thorough approach to understanding task-switching, collecting an order of magnitude more data per participant than is typical, teasing apart three distinct aspects of cognition, and determining which activity can best predict behavior. This work helps solidify inconsistent findings in the literature and helps inform future studies regarding the specific roles each region may play in cognitive flexibility as a whole.en_US
dc.language.isoen_USen_US
dc.publisherProQuest Dissertations & Theses Globalen_US
dc.subjectNeurosciencesen_US
dc.titleDissociable Neural Circuits Underlie Competition During Task Switching, with a Novel Role for the Posterior Cingulate Cortexen_US
dc.typeDissertationen_US
dc.typeThesisen_US


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