Cognitive decline in Parkinson's disease (PD) is a common sequela of the disorder that has a large impact on patient well-being. Its physiological etiology, however, remains elusive. Our study used graph theory analysis to investigate the large-scale topological patterns of the extrastriatal dopamine D2 receptor network. We used positron emission tomography with [ C]FLB-457 to measure the binding potential of cortical dopamine D2 receptors in two networks: the meso-cortical dopamine network and the meso-limbic dopamine network. We also investigated the application of partial volume effect correction (PVEC) in conjunction with graph theory analysis. Three groups were investigated in this study divided according to their cognitive status as measured by the Montreal Cognitive Assessment score, with a score ≤25 considered cognitively impaired: (a) healthy controls (n = 13, 11 female), (b) cognitively unimpaired PD patients (PD-CU, n = 13, 5 female), and (c) PD patients with mild cognitive impairment (PD-MCI, n = 17, 4 female). In the meso-cortical network, we observed increased small-worldness, normalized clustering, and local efficiency in the PD-CU group compared to the PD-MCI group, as well as a hub shift in the PD-MCI group. Compensatory reorganization of the meso-cortical dopamine D2 receptor network may be responsible for some of the cognitive preservation observed in PD-CU. These results were found without PVEC applied and PVEC proved detrimental to the graph theory analysis. Overall, our findings demonstrate how graph theory analysis can be used to detect subtle changes in the brain that would otherwise be missed by regional comparisons of receptor density.
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http://dx.doi.org/10.1002/jnr.24760 | DOI Listing |
Hum Brain Mapp
January 2025
Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Mexico.
Premature infants, born before 37 weeks of gestation can have alterations in neurodevelopment and cognition, even when no anatomical lesions are evident. Resting-state functional neuroimaging of naturally sleeping babies has shown altered connectivity patterns, but there is limited evidence on the developmental trajectories of functional organization in preterm neonates. By using a large dataset from the developing Human Connectome Project, we explored the differences in graph theory properties between at-term (n = 332) and preterm (n = 115) neonates at term-equivalent age, considering the age subgroups proposed by the World Health Organization for premature birth.
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Department of Psychological Sciences, Rice University, Houston, TX, 77005, USA.
In a sequence, at least two aspects of information-the identity of items and their serial order-are maintained and supported by distinct working memory (WM) capacities. Verbal serial order WM is modulated by spatial processing, reflected in the Spatial Position Association of Response Codes (SPoARC) effect-the left-beginning, right-end positional association between space and serial position of verbal WM memoranda. We investigated the individual differences in this modulation with both behavioral and neurobiological approaches.
View Article and Find Full Text PDFNeurobiol Dis
January 2025
Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China; National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China. Electronic address:
Background: Investigating brain metabolic networks is crucial for understanding the pathogenesis and functional alterations in Creutzfeldt-Jakob disease (CJD). However, studies on presymptomatic individuals remain limited. This study aimed to examine metabolic network topology reconfiguration in asymptomatic carriers of the PRNP G114V mutation.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Advanced Artificial Intelligence Theoretical and Computational Chemistry Laboratory, School of Chemistry, University of Hyderabad, Hyderabad, Telangana 500046, India.
We present a directed electrostatics strategy integrated as a graph neural network (DESIGNN) approach for predicting stable nanocluster structures on their potential energy surfaces (PESs). The DESIGNN approach is a graph neural network (GNN)-based model for building structures of large atomic clusters with specific sizes and point-group symmetry. This model assists in the structure building of atomic metal clusters by predicting molecular electrostatic potential (MESP) topography minima on their structural evolution paths.
View Article and Find Full Text PDFCurr Res Neurobiol
June 2025
Department of Anesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, Germany.
Although the pathophysiology of pain has been investigated tremendously, there are still many open questions with regard to specific pain entities and their pain-related symptoms. To increase the translational impact of (preclinical) animal neuroimaging pain studies, the use of disease-specific pain models, as well as relevant stimulus modalities, are critical. We developed a comprehensive framework for brain network analysis combining functional magnetic resonance imaging (MRI) with graph-theory (GT) and data classification by linear discriminant analysis.
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