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Attention and Disruption: Modulating the Interactions between Large-scale Brain Networks and the Properties of Local Cortical Regions


An abundance of research has demonstrated that the brain is both organized into discrete, highly specialized, regions and that distributed regions work together in the form of large-scale networks. It remains unclear, however, how to reconcile these two views of brain function. In this thesis, I present several projects that investigated the specialized properties of individual regions, how these change depending on cognitive demands and external disruption, and how these changes interact with modulations across large-scale networks. Across these projects, I use a combination of methods including psychophysics, univariate and multivariate modeling of functional Magnetic Resonance Imaging (fMRI) data, Transcranial Magnetic Stimulation (TMS), and the study of patients with focal lesions.

The first section of this thesis focuses on visual attention to high-level face stimuli. Here, I demonstrate that highly specialized representations exist for individual faces, but that engaging in sustained top-down attention can cause selective modulations in these representations. This suggests that large-scale networks can interact with, and modify, the properties of local regions in an extremely selective manner.

The second section of the thesis examines how disrupting local regions, through focal brain lesions or TMS, impacts the structure of large-scale networks. The first two chapters in this section examine how acute and chronic disruptions modulate the magnitude of interactions throughout cognitive control networks. An additional project explores methodological considerations involving the variability in TMS effects and how these might be measured most effectively. The final project in this section examines how focal brain lesions also affect the organization of distributed networks. This section illustrates how the properties of local regions can modulate both the magnitude and organization of distributed networks.

In sum, these projects demonstrate that large-scale networks can both drive and be driven by the highly specialized properties of local regions. This research will hopefully provide some insight into how brain regions may concurrently demonstrate highly specialized brain activity and participate in distributed brain networks, and flexibly modify these interactions, in order to carry out complex behavioral functions.

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