Cognitive abilities such as memory and attention are supported by specialized brain networks made up of specific patches of the cerebral cortex called cortical fields. Cortical fields are thought to be anatomically distinct, with neurons connecting between them. Until recently, cortical fields could only be identified after death, by microscopic examination of autopsy brain tissue. Their number, function, and location in individual brains have been unknown. Now however, Magnetic resonance imaging (MRI) can detect neural activity in the cerebral cortex with relatively high resolution, and diffusion MRI (dMRI) can detect white-matter fibers that connect brain regions. Networks made up of cortical fields become active when individuals accomplish a task, and also spontaneously, when the mind is "at rest." We will use all this information to delineate the specific cortical fields in individual brains as well as patterns of connectivity between them. Cortical fields vary in size up to threefold from person to person, and we intend to study whether this variability is reflected in individual abilities or susceptibilities. The overarching goal is to test the idea that the size of cortical fields matters to the strength and vulnerability of brain networks. We use the MRI approaches outlined above to measure network strength, and we temporarily disrupt networks with transcranial magnetic stimulation (TMS) to assess network vulnerability. The work is important because it will allow us to better understand the reasons people have variable mental abilities.
The project focuses on two established brain networks: the default mode network (DMN) and the lateral frontoparietal network (LFPN), which have components in the inferior parietal lobes. Connectivity-based parcellation distinguishes two angular gyrus fields, PgA and PgP, which are nodes within the LFPN and DMN networks, respectively. We will use dMRI to parcellate the cortex using a probabilistic parcel atlas of the Human Connectome Project data as prior information. Using functional connectivity, we will evaluate if PgP belongs to DMN, and PgA to LFPN. We will also analyze the strength of functional connectivity across network nodes in resting state fMRI using the dual-regression approach and ascertain the degree to which cortical field size variability across subjects is correlated with network-size variability. We will evaluate whether connectivity-defined cortical parcels maximize fMRI task contrast and show higher levels of EEG gamma and theta activities. Finally we relate the variability of cortical parcel size to task vulnerability by applying transcranial magnetic stimulations (TMS) to PgP and PgA. We hypothesize that low-frequency repetitive TMS (rTMS) over PgA will impair task performance on a working memory task and on a flanker task, and more so for individuals with smaller surface area of PgA. Furthermore, because endogenous reduction of DMN activity is associated with successful deployment of attentional resources, we also hypothesize that rTMS over DMN nodes will positively affect performance on the same tasks, and more so for individuals with smaller surface areas of these nodes. This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).
