Long-term changes in the small-world organization of brain networks after concussion.
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ABSTRACT:
SUBMITTER: Churchill NW
PROVIDER: S-EPMC7994718 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Quantitative descriptions of network structure can provide fundamental insights into the function of interconnected complex systems. Small-world structure, diagnosed by high local clustering yet short average path length between any two nodes, promotes information flow in coupled systems, a key function that can differ across conditions or between groups. However, current techniques to quantify small-worldness are density dependent and neglect important features such as the strength of network connections, limiting their application in real-world systems. Here, we address both limitations with a novel metric called the Small-World Propensity (SWP). In its binary instantiation, the SWP provides an unbiased assessment of small-world structure in networks of varying densities. We extend this concept to the case of weighted brain networks by developing (i) a standardized procedure for generating weighted small-world networks, (ii) a weighted extension of the SWP, and (iii) a method for mapping observed brain network data onto the theoretical model. In applying these techniques to compare real-world brain networks, we uncover the surprising fact that the canonical biological small-world network, the C. elegans neuronal network, has strikingly low SWP. These metrics, models, and maps form a coherent toolbox for the assessment and comparison of architectural properties in brain networks.
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Project description:Recent findings from developmental neuroimaging studies suggest that the enhancement of cognitive processes during development may be the result of a fine-tuning of the structural and functional organization of brain with maturation. However, the details regarding the developmental trajectory of large-scale structural brain networks are not yet understood. Here, we used graph theory to examine developmental changes in the organization of structural brain networks in 203 normally growing children and adolescents. Structural brain networks were constructed using interregional correlations in cortical thickness for 4 age groups (early childhood: 4.8-8.4 year; late childhood: 8.5-11.3 year; early adolescence: 11.4-14.7 year; late adolescence: 14.8-18.3 year). Late childhood showed prominent changes in topological properties, specifically a significant reduction in local efficiency, modularity, and increased global efficiency, suggesting a shift of topological organization toward a more random configuration. An increase in number and span of distribution of connector hubs was found in this age group. Finally, inter-regional connectivity analysis and graph-theoretic measures indicated early maturation of primary sensorimotor regions and protracted development of higher order association and paralimbic regions. Our finding reveals a time window of plasticity occurring during late childhood which may accommodate crucial changes during puberty and the new developmental tasks that an adolescent faces.
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Project description:Concussion is associated with acute disturbances in brain function and behavior, with potential long-term effects on brain health. However, it is presently unclear whether there are sex differences in acute and long-term brain recovery. In this study, magnetic resonance imaging (MRI) was used to scan 61 participants with sport-related concussion (30 male, 31 female) longitudinally at acute injury, medical clearance to return to play (RTP), and 1-year post-RTP. A large cohort of 167 controls (80 male, 87 female) was also imaged. Each MRI session assessed cerebral blood flow (CBF), along with white matter fractional anisotropy (FA) and mean diffusivity (MD). For concussed athletes, the parameters were converted to difference scores relative to matched control subgroups, and partial least squares modeled the main and sex-specific effects of concussion. Although male and female athletes did not differ in acute symptoms or time to RTP , all MRI measures showed significant sex differences during recovery. Males had greater reductions in occipital-parietal CBF (mean difference and 95%CI: 9.97 ml/100 g/min, [4.84, 15.12] ml/100 g/min, z = 3.73) and increases in callosal MD (9.07 × 10-5 , [-14.14, -3.60] × 10-5 , z = -3.46), with greatest effects at 1-year post-RTP. In contrast, females had greater reductions in FA of the corona radiata (16.50 × 10-3 , [-22.38, -11.08] × 10-3 , z = -5.60), with greatest effects at RTP. These findings provide new insights into how the brain recovers after a concussion, showing sex differences in both the acute and chronic phases of injury.
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Project description:ObjectiveThe BRAIN Study was established to assess the associations between self-reported concussions and cognitive function among retired rugby players.MethodsFormer elite-level male rugby union players (50+ years) in England were recruited. Exposure to rugby-related concussion was collected using the BRAIN-Q tool. The primary outcome measure was the Preclinical Alzheimer Cognitive Composite (PACC). Linear regressions were conducted for the association between concussion and PACC score, adjusting for confounders.ResultsA total of 146 participants were recruited. The mean (standard deviation) length of playing career was 15.8 (5.4) years. A total of 79.5% reported rugby-related concussion(s). No association was found between concussion and PACC (β -0.03 [95% confidence interval (CI): -1.31, 0.26]). However, participants aged 80+ years reporting 3+ concussions had worse cognitive function than those without concussion (β -1.04 [95% CI: -1.62, -0.47]).ConclusionsOverall there was no association between concussion and cognitive function; however, a significant interaction with age revealed an association in older participants.
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Project description:Networks in nature are often formed within a spatial domain in a dynamical manner, gaining links and nodes as they develop over time. Motivated by the growth and development of neuronal networks, we propose a class of spatially-based growing network models and investigate the resulting statistical network properties as a function of the dimension and topology of the space in which the networks are embedded. In particular, we consider two models in which nodes are placed one by one in random locations in space, with each such placement followed by configuration relaxation toward uniform node density, and connection of the new node with spatially nearby nodes. We find that such growth processes naturally result in networks with small-world features, including a short characteristic path length and nonzero clustering. We find no qualitative differences in these properties for two different topologies, and we suggest that results for these properties may not depend strongly on the topology of the embedding space. The results do depend strongly on dimension, and higher-dimensional spaces result in shorter path lengths but less clustering.
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Project description:PD is associated with disrupted connectivity to a large number of distributed brain regions. How the disease alters the functional topological organization of the brain, however, remains poorly understood. Furthermore, how levodopa modulates network topology in PD is largely unknown. The objective of this study was to use resting-state functional MRI and graph theory to determine how small-world architecture is altered in PD and affected by levodopa administration.Twenty-one PD patients and 20 controls underwent functional MRI scanning. PD patients were scanned off medication and 1 hour after 200?mg levodopa. Imaging data were analyzed using 226 nodes comprising 10 intrinsic brain networks. Correlation matrices were generated for each subject and converted into cost-thresholded, binarized adjacency matrices. Cost-integrated whole-brain global and local efficiencies were compared across groups and tested for relationships with disease duration and severity.Data from 2 patients and 4 controls were excluded because of excess motion. Patients off medication showed no significant changes in global efficiency and overall local efficiency, but in a subnetwork analysis did show increased local efficiency in executive (P?=?0.006) and salience (P?=?0.018) networks. Levodopa significantly decreased local efficiency (P?=?0.039) in patients except within the subcortical network, in which it significantly increased local efficiency (P?=?0.007).Levodopa modulates global and local efficiency measures of small-world topology in PD, suggesting that degeneration of nigrostriatal neurons in PD may be associated with a large-scale network reorganization and that levodopa tends to normalize the disrupted network topology in PD. © 2016 International Parkinson and Movement Disorder Society.
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