Developmental increases in white matter network controllability support a growing diversity of brain dynamics.
Ontology highlight
ABSTRACT:
SUBMITTER: Tang E
PROVIDER: S-EPMC5665937 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:A number of studies have shown an abnormal connectivity of certain white matter pathways in developmental dyslexia, as well as correlations between these white matter pathways and behavioral deficits. However, whether developmental dyslexia presents broader white matter network connectivity disruption is currently unknown. The present study reconstructed white matter networks for 26 dyslexic children (11.61 ± 1.31 years) and 31 age-matched controls (11.49 ± 1.36 years) using constrained spherical deconvolution tractography. Network-based statistics (NBS) analysis was performed to identify network connectivity deficits in dyslexic individuals. Network topological features were measured based on graph theory to examine whether these parameters correlate with literacy skills, and whether they explain additional variance over previously established white matter connectivity abnormalities in dyslexic children. The NBS analysis identified a network connecting the left-occipital-temporal cortex and temporo-parietal cortex that had decreased streamlines in dyslexic children. Four network topological parameters (clustering coefficient, local efficiency, transitivity, and global efficiency) were positively correlated with literacy skills of dyslexic children, and explained a substantial proportion of additional variance in literacy skills beyond connectivity measures of white matter pathways. This study for the first time reports a disconnection in a local subnetwork in the left hemisphere in dyslexia and shows that the global white matter network topological properties contribute to reduced literacy skills in dyslexic children.
| S-EPMC6865529 | biostudies-literature
Project description:White matter aging drives microglial diversity
2021-02-08 | GSE166304 | GEO
Project description:Aging results in both grey and white matter degeneration, but the specific microglial responses are unknown. Using single-cell RNA sequencing from white and grey matter separately, we identified white matter associated microglia (WAM), which share parts of the disease-associated microglia (DAM) gene signature and are characterized by the activation of genes implicated in phagocytic activity and lipid metabolism. WAM depend on triggering receptor expressed on myeloid cells 2 (TREM2) signaling and are aging dependent. In the aged brain, WAM form independently of apolipoprotein E (APOE), which is in contrast to mouse models of Alzheimer’s disease, in which microglia with WAM gene signature are generated prematurely and in an APOE-dependent pathway similar to DAM. Within the white matter, microglia frequently cluster in nodules, where they are engaged in clearing degenerated myelin. Thus, WAM may represent a potentially protective response required to clear degenerated myelin accumulating during white matter aging and disease.
2021-02-18 | GSE166548 | GEO
Project description:Controlling complex networked systems to desired states is a key research goal in contemporary science. Despite recent advances in studying the impact of network topology on controllability, a comprehensive understanding of the synergistic effect of network topology and individual dynamics on controllability is still lacking. Here we offer a theoretical study with particular interest in the diversity of dynamic units characterized by different types of individual dynamics. Interestingly, we find a global symmetry accounting for the invariance of controllability with respect to exchanging the densities of any two different types of dynamic units, irrespective of the network topology. The highest controllability arises at the global symmetry point, at which different types of dynamic units are of the same density. The lowest controllability occurs when all self-loops are either completely absent or present with identical weights. These findings further improve our understanding of network controllability and have implications for devising the optimal control of complex networked systems in a wide range of fields.
| S-EPMC4325315 | biostudies-literature
Project description:Neurological function in patients with slowly growing brain tumors can be preserved even after extensive tumor resection. However, the global process of cortical reshaping and cerebral redistribution cannot be understood without taking into account the white matter tracts. The aim of this study was to predict the functional consequences of tumor-induced white matter damage by computer simulation. A computational model was proposed, incorporating two cortical patches and the white matter connections of the uncinate fasciculus. Tumor-induced structural changes were modeled such that different aspects of the connectivity were altered, mimicking the biological heterogeneity of gliomas. The network performance was quantified by comparing memory pattern recall and the plastic compensatory capacity of the network was analyzed. The model predicts an optimal level of synaptic conductance boost that compensates for tumor-induced connectivity loss. Tumor density appears to change the optimal plasticity regime, but tumor size does not. Compensatory conductance values that are too high lead to performance loss in the network and eventually to epileptic activity. Tumors of different configurations show differences in memory recall performance with slightly lower plasticity values for dense tumors compared to more diffuse tumors. Simulation results also suggest an optimal noise level that is capable of increasing the recall performance in tumor-induced white matter damage. In conclusion, the model presented here is able to capture the influence of different tumor-related parameters on memory pattern recall decline and provides a new way to study the functional consequences of white matter invasion by slowly growing brain tumors.
| S-EPMC3724895 | biostudies-literature
Project description:Injury to the developing brain during the perinatal period often causes hypomyelination, leading to clinical deficits for which there is an unmet therapeutic need. Dysregulation of inflammation and microglia have been implicated, yet the molecular mechanisms linking these to hypomyelination are unclear. Using human infant cerebrospinal fluid (CSF) and postmortem tissue, we found that microglial activation of the pro-inflammatory molecular complex the NLRP3 inflammasome is associated with pathology. By developing a novel mouse brain explant model of microglial inflammasome activation, we demonstrate that blocking the inflammasome rescues myelination. In human and mouse, we discovered a link between the inflammasome product IL1β and increased levels of follistatin, an endogenous inhibitor of activin-A. Follistatin treatment was sufficient to reduce myelination, whereas myelination was rescued in injured explants upon follistatin neutralization or supplementation with exogenous activin-A. Our data reveal that inflammasome activation in microglia drives hypomyelination and identifies novel therapeutic strategies to reinstate myelination following developmental injury.
| S-EPMC8607465 | biostudies-literature
Project description:Control of nonlinear large-scale dynamical networks, e.g., collective behavior of agents interacting via a scale-free connection topology, is a central problem in many scientific and engineering fields. For the linear version of this problem, the so-called controllability Gramian has played an important role to quantify how effectively the dynamical states are reachable by a suitable driving input. In this paper, we first extend the notion of the controllability Gramian to nonlinear dynamics in terms of the Gibbs distribution. Next, we show that, when the networks are open to environmental noise, the newly defined Gramian is equal to the covariance matrix associated with randomly excited, but uncontrolled, dynamical state trajectories. This fact theoretically justifies a simple Monte Carlo simulation that can extract effectively controllable subdynamics in nonlinear complex networks. In addition, the result provides a novel insight into the relationship between controllability and statistical mechanics.
| S-EPMC4893695 | biostudies-other
Project description:Children are becoming increasingly inactive, unfit, and overweight, yet there is relatively little causal evidence regarding the effects of physical activity on brain health during childhood. The present study examined the effects of an after-school physical activity program (FITKids2) on the microstructure of white matter tracts in 7- to 9-year-old children. We measured the microstructural properties of white matter via diffusion tensor imaging in 143 children before and after random assignment to either a 9-month after-school physical activity program (N = 76, mean age = 8.7 years) or a wait list control group (N = 67, mean age = 8.7 years). Our results demonstrate that children who participated in the physical activity program showed increased white matter microstructure in the genu of the corpus callosum, with no changes in white matter microstructure in the wait list control group which reflects typical development. Specifically, children in the physical activity program showed increases in fractional anisotropy (FA) and decreases in radial diffusivity (RD) in the genu from pre- to post-test, thereby suggesting more tightly bundled and structurally compact fibers (FA) and increased myelination (RD), with no changes in estimates of axonal fiber diameter (axial diffusivity, AD). The corpus callosum integrates cognitive, motor, and sensory information between the left and right hemispheres of the brain, and the white matter tract plays a role in cognition and behavior. Our findings reinforce the importance of physical activity for brain health during child development.
| S-EPMC6305717 | biostudies-literature
Project description:White matter hyperintensities (WMHs) that arise with age and/or atherosclerosis constitute a heterogeneous disorder in the white matter of the brain. However, the relationship between age-related risk factors and the prevalence of WMHs is still obscure. More clinical data is needed to confirm the relationship between age and the prevalence of WMHs. We collected 836 patients, who were treated in the Renmin Hospital, Hubei University of Medicine, China from January 2015 to February 2016, for a case-controlled retrospective analysis. According to T2-weighted magnetic resonance imaging results, all patients were divided into a WMHs group (n = 333) and a non-WMHs group (n = 503). The WMHs group contained 159 males and 174 females. The prevalence of WMHs increased with age and was associated with age-related risk factors, such as cardiovascular diseases, smoking, drinking, diabetes, hypertension and history of cerebral infarction. There was no significant difference in sex, education level, hyperlipidemia and hyperhomocysteinemia among the different age ranges. These findings confirm that age is an independent risk factor for the prevalence and severity of WMHs. The age-related risk factors enhance the occurrence of WMHs.
| S-EPMC6199954 | biostudies-literature
Project description:Brain white matter is a dynamic environment that continuously adapts and reorganizes in response to stimuli and pathological changes. Glial cells, especially, play a key role in tissue repair, inflammation modulation, and neural recovery. The movements of glial cells and changes in their concentrations can influence the surrounding axon morphology. We introduce the White Matter Generator (WMG) tool to enable the study of how axon morphology is influenced through such dynamical processes, and how this, in turn, influences the diffusion-weighted MRI signal. This is made possible by allowing interactive changes to the configuration of the phantom generation throughout the optimization process. The phantoms can consist of myelinated axons, unmyelinated axons, and cell clusters, separated by extra-cellular space. Due to morphological flexibility and computational advantages during the optimization, the tool uses ellipsoids as building blocks for all structures; chains of ellipsoids for axons, and individual ellipsoids for cell clusters. After optimization, the ellipsoid representation can be converted to a mesh representation which can be employed in Monte-Carlo diffusion simulations. This offers an effective method for evaluating tissue microstructure models for diffusion-weighted MRI in controlled bio-mimicking white matter environments. Hence, the WMG offers valuable insights into white matter's adaptive nature and implications for diffusion-weighted MRI microstructure models, and thereby holds the potential to advance clinical diagnosis, treatment, and rehabilitation strategies for various neurological disorders and injuries.
| S-EPMC11322502 | biostudies-literature