{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"Changes in functional neural network organization during working memory task performance: effects of age and task practice","metadata":[{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/78309"},{"label":"dcterms.abstract","value":"The notion that cognitive processing is not only reflected by regional changes in neural activity in the brain but also by global changes in functional connectivity pattern has greatly motivated the network approach in examining the neural substrates of cognition and their relationship with behavior. Recent human neuroimaging evidence suggests specific cognitive processes may involve distinct spatiotemporal patterns of functional connectivity across task conditions. For instance, increased cognitive demand has been shown to evoke greater network integration while changes in functional network architecture have been associated with shifting between cognitive states. However, little is known about individual differences in the functional organization of neural networks during complex tasks. Here, we examined functional connectivity during multiple cognitive tasks in late childhood/early adolescence and during multiple sessions of working memory performance in young adults. We specifically focused on studying the effects of task state and task practice as these two key factors may particularly impact the functional architecture of large-scale neural networks. In the first experiment, the functional network architectures during resting and during three cognitive tasks were examined in children aged 9-12. Children exhibited age-dependent similarity in intrinsic network organization to that in adults and changes in network organization in response to distinct cognitive requirements. Compared to resting state, there was an increase in whole-brain functional integration during tasks. Additionally, major functional modules showed different patterns of stability and flexibility across cognitive states. In the second experiment, we investigated network organizations within and between multiple sessions in individual healthy adults during performance of a working memory task. Our results indicate while there was a broad tendency for whole-brain network integration to increase with working memory performance relative to the resting state, network configuration varied greatly across time and individuals. Furthermore, we found individual-dependent practice-related changes in connectivity patterns for different functional modules. Taken together, these findings suggest functional neural network organization varies in correspondence to changing cognitive demands. Such variability is further influenced by young age, task exposure, and individual differences."},{"label":"dcterms.available","value":"2018-10-10"},{"label":"dcterms.contributor","value":"Advisors: Leung, Hoi-Chung; Parsons, Ryan; Mohanty, Aprijita; Ide, Jaime"},{"label":"dcterms.creator","value":"Le, Thang Manh"},{"label":"dcterms.date","value":"2017"},{"label":"dcterms.dateAccepted","value":"2018-07-03T17:37:23Z"},{"label":"dcterms.dateSubmitted","value":"2018-07-03T17:37:23Z"},{"label":"dcterms.description","value":"Dissertation"},{"label":"dcterms.extent","value":"102 pages"},{"label":"dcterms.format","value":"application/pdf"},{"label":"dcterms.identifier","value":"Le_grad.sunysb_0771E_13607.pdf"},{"label":"dcterms.issued","value":"2017-12-01"},{"label":"dcterms.language","value":"en"},{"label":"dcterms.provenance","value":"Submitted by Jason Torre (fjason.torre@stonybrook.edu) on 2018-07-03T17:37:23Z\nNo. of bitstreams: 1\nLe_grad.sunysb_0771E_13607.pdf: 2397719 bytes, checksum: 5dea6732807af04c04b90ce4624f3753 (MD5)"},{"label":"dcterms.publisher","value":"Stony Brook University"},{"label":"dcterms.subject","value":"fMRI, Neurosciences, functional neural network, graph theory, late childhood, task practice, working memory"},{"label":"dcterms.title","value":"Changes in functional neural network organization during working memory task performance: effects of age and task practice"},{"label":"dcterms.type","value":"Text"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/78%2F60%2F82%2F78608255490272988001761358924241259728/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/78%2F60%2F82%2F78608255490272988001761358924241259728","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}