Network Patterns of Beta-Amyloid Deposition in Parkinson’s Disease

Connectome analysis of brain functional network alterations in breast cancer survivors with and without chemotherapy

“…Changes in cognitive function could imply functional changes in the brain. Graph theoretical approaches have been applied in exploring Alzheimer disease, schizophrenia, and traumatic brain injury [8][9][10]. Alteration in topological parameters implies that illness may alter human brain connectivity and suggests that cognitive symptoms and functional deficits are the disturbance of the functional network [11].…”

Graph theory analysis of the dopamine D2 receptor network in Parkinson’s disease patients with cognitive decline

“…In the no‐PVEC method, the normalized, averaged BP ND image of each group was input into GAT, along with the delineated ROIs in MNI space, which GAT then used to extract the BP ND of each ROI. We adapted the simple graph model which was used in previous studies with PET (Kim et al, 2019). Using the group level correlation matrices, we created unweighted and undirected binary adjacency matrices for a range of sparsity thresholds from minimum sparsity to 0.34, increasing in 0.01 stepwise intervals.…”

“…We applied AUC and functional density analysis (FDA) approaches found in GAT (Hosseini et al., 2012) to check for statistical significance across different sparsity levels and avoid the selection of a specific thresholding metric (Bassett & Bullmore, 2006; Bassett et al., 2012; Kim et al, 2019). Both the AUC metric and the FDA metric have been used in previous brain network studies for their utility in detecting topological differences in brain disorders (Kim et al, 2019; Zhang et al, 2011). FDA was additionally adopted due to the hypersensitivity of AUC at higher network sparsity which we observed in the D2R network (Bassett et al., 2012; Hosseini et al., 2012).…”

“…FDA was additionally adopted due to the hypersensitivity of AUC at higher network sparsity which we observed in the D2R network (Bassett et al., 2012; Hosseini et al., 2012). Previous research has found that brain networks likely operate optimally with a small‐world regime between 0.05 and 0.34 sparsity and so we limited our sparsity to within this range (Achard & Bullmore, 2007; Kim et al, 2019).…”

“…The application of graph theory analysis to positron emission tomography (PET) imaging data began with a focus on the radiotracers Pittsburgh compound B and [ 18 F] Fluoro‐2‐deoxy‐ d ‐glucose (FDG), which are radiotracers that measure beta‐amyloid plaque density and brain glucose activity, respectively (Kim et al, 2019; Verger et al, 2018). The extension of this method to radiotracers that measure neuroreceptors occurred within the last few years (Ashok et al, 2019; Caminiti, Presotto, et al., 2017; Veronese et al, 2019), and there is no current gold standard for the theoretical and practical methodologies involved in neuroreceptor graph theory analyses.…”