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dc.contributor.authorKember, Jonah
dc.date.accessioned2022-07-18T16:36:19Z
dc.date.available2022-07-18T16:36:19Z
dc.identifier.urihttp://hdl.handle.net/10464/16406
dc.description.abstractThe heterogeneity of attention-deficit/hyperactivity disorder(ADHD) traits (inattention vs. hyperactivity/impulsivity) complicates diagnosis and intervention. Identifying how the configuration of large-scale functional brain networks during cognitive processing correlate with this heterogeneity could help us understand the neural mechanisms altered across ADHD presentations. Here, we recorded high-density EEG while 62 non-clinical participants (ages 18-24; 32 male) underwent an inhibitory control task (Go/No-Go). Functional EEG networks were created using sensors as nodes and across-trial phase-lag index values as edges. Using cross-validated LASSO regression, we examined whether graph-theory metrics applied to both static networks (averaged across time-windows: -500–0ms, 0–500ms) and dynamic networks (temporally layered with 2ms intervals), were associated with hyperactive/impulsive and inattentive traits. Network configuration during response execution/inhibition was associated with hyperactive/impulsive (mean R2across test sets = .20, SE = .02), but not inattentive traits. Post-stimulus results at higher frequencies (Beta, 14-29Hz; Gamma, 30-90Hz) showed the strongest association with hyperactive/impulsive traits, and predominantly reflected less burst-like integration between modules in oscillatory beta networks during execution, and increased integration/small-worldness in oscillatory gamma networks during inhibition. We interpret the beta network results as reflecting weaker integration between specialized pre-frontal and motor systems during motor response preparation, and the gamma results as reflecting a compensatory mechanism used to integrate processing between less functionally specialized networks. This research demonstrates that the neural network mechanisms underlying response execution/inhibition might be associated with hyperactive/impulsive traits, and that dynamic, task-related changes in EEG functional networks may be useful in disentangling ADHD heterogeneity.en_US
dc.language.isoengen_US
dc.publisherBrock Universityen_US
dc.subjectADHD, EEG, Dynamic Functional Connectivity, Network Neuroscienceen_US
dc.titleDynamic Configuration of Large-Scale Cortical Networks: A Useful Framework for Clarifying the Heterogeneity Found in Attention-Deficit/Hyperactivity Disorderen_US
dc.typeElectronic Thesis or Dissertationen_US
dc.degree.nameM.A. Child and Youth Studiesen_US
dc.degree.levelMastersen_US
dc.contributor.departmentDepartment of Child and Youth Studiesen_US
dc.degree.disciplineFaculty of Social Sciencesen_US
refterms.dateFOA2022-07-18T16:36:19Z


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