Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions

The Impact of Age-Related Changes on Working Memory Functional Activity

This work investigated associations of age-related brain atrophy and functional neural networks identified using multivariate analyses of BOLD fMRI data in young and elder participants (young, N=37; mean age=25; elders, N=15; mean age=74). Two networks were involved in retaining increasing loads of verbal information in working memory. Network utilizations were used to test associations between function and indices of grey matter volume changes using voxel based morphometry. Global changes in brain volume were not associated with the secondary network. Lower regional grey matter volume in the left pre-central gyrus within the primary network was associated with increased secondary network utilization independent of age group. Decreased regional grey matter volume was associated with increased age only in the elders. Increased secondary network expression was associated with increased slope of reaction times across memory load, in the elders. These results support the theory of neural compensation, that elder participants recruit additional neural resources to maintain task performance in the face of age-related decreases in regional grey matter volume

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions

Brain structural covariance networks in obsessive-compulsive disorder : a graph analysis from the ENIGMA Consortium

In the largest brain structural covariance study of OCD to date, Yun et al. show a less segregated organization of structural covariance networks and a reorganization of brain hubs, including cingulate and orbitofrontal regions, in OCD. The findings point to altered trajectories of brain development and maturation. Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z -score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions

White matter injury predicts disrupted functional connectivity and microstructure in very preterm born neonates

© 2018 The Authors Objective: To determine whether the spatial extent and location of early-identified punctate white matter injury (WMI) is associated with regionally-specific disruptions in thalamocortical-connectivity in very-preterm born neonates. Methods: 37 very-preterm born neonates (median gestational age: 28.1 weeks; interquartile range [IQR]: 27–30) underwent early MRI (median age 32.9 weeks; IQR: 32–35), and WMI was identified in 13 (35%) neonates. Structural T1-weighted, resting-state functional Magnetic Resonance Imaging (rs-fMRI, n = 34) and Diffusion Tensor Imaging (DTI, n = 31) sequences were acquired using 3 T-MRI. A probabilistic map of WMI was developed for the 13 neonates demonstrating brain injury. A neonatal atlas was applied to the WMI maps, rs-fMRI and DTI analyses to extract volumetric, functional and microstructural data from regionally-specific brain areas. Associations of thalamocortical-network strength and alterations in fractional anisotropy (FA, a measure of white-matter microstructure) with WMI volume were assessed in general linear models, adjusting for age at scan and cerebral volumes. Results: WMI volume in the superior (β = −0.007; p =.02) and posterior corona radiata (β = −0.01; p =.01), posterior thalamic radiations (β = −0.01; p =.005) and superior longitudinal fasciculus (β = −0.02; p =.001) was associated with reduced connectivity strength between thalamus and parietal resting-state networks. WMI volume in the left (β = −0.02; p =.02) and right superior corona radiata (β = −0.03; p =.008), left posterior corona radiata (β = −0.03; p =.01), corpus callosum (β = −0.11; p \u3c.0001) and right superior longitudinal fasciculus (β = −0.02; p =.02) was associated with functional connectivity strength between thalamic and sensorimotor networks. Increased WMI volume was also associated with decreased FA values in the corpus callosum (β = −0.004, p =.015). Conclusions: Regionally-specific alterations in early functional and structural network complexity resulting from WMI may underlie impaired outcomes

A mobile terminal leaky-wave antenna for efficient 5G communication

The millimeter-wave 37 –43.5GHz band is proposed to provide the requested multigigabit-per-second (Gb/s) data rates for future 5G cellular communications. As a total wireless-link gain of 37 dBi may be required, the mobile terminal antennas should provide 12 dBi gain –being the remaining 25 dBi for the base station antennas. This high gain is linked to the synthesis of narrow directive radiated beam, which must somehow be scanned into space over a wide field of view (FoV), and thus satisfy the mobility and coverage conditions. Such high-gain beam-scanning antenna design is very challenging, taking into account that high radiation efficiency, compact size/volume, and low-cost are key features for mass-market mm-wave applications. In this sense, most of the proposed 5G mobile-antenna solutions are based on phased arrays, which rely on active scanning/beam-forming networks which might be impractical due to an increase cost and manufacturing complexity. However, owning to their characteristics of high-gain, simple-feeding, planar structure, and inherent frequency-beam-scanning behavior, leaky-wave antennas (LWAs) might offer an interesting solution for high-gain low-cost scanning

Structural and functional cerebral correlates of hypnotic suggestibility

Little is known about the neural bases of hypnotic suggestibility, a cognitive trait referring to the tendency to respond to hypnotic suggestions. In the present magnetic resonance imaging study, we performed regression analyses to assess hypnotic suggestibility-related differences in local gray matter volume, using voxel-based morphometry, and in waking resting state functional connectivity of 10 resting state networks, in 37 healthy women. Hypnotic suggestibility was positively correlated with gray matter volume in portions of the left superior and medial frontal gyri, roughly overlapping with the supplementary and pre-supplementary motor area, and negatively correlated with gray matter volume in the left superior temporal gyrus and insula. In the functional connectivity analysis, hypnotic suggestibility was positively correlated with functional connectivity between medial posterior areas, including bilateral posterior cingulate cortex and precuneus, and both the lateral visual network and the left fronto-parietal network; a positive correlation was also found with functional connectivity between the executive-control network and a right postcentral/parietal area. In contrast, hypnotic suggestibility was negatively correlated with functional connectivity between the right fronto-parietal network and the right lateral thalamus. These findings demonstrate for the first time a correlation between hypnotic suggestibility, the structural features of specific cortical regions, and the functional connectivity during the normal resting state of brain structures involved in imagery and self-monitoring activity

Impairment-aware Virtual Network Embedding Using Time Domain Hybrid Modulation formats in Optical Networks

The rapid increase in bandwidth-intensive applications has resulted in the progressive growth of IP traffic volume, especially in the backbone networks. To address this growth of internet traffic, operators are searching for innovative solutions which avoid new installation and replacement of the existing network infrastructure. In this context, efficient spectrum utilization is one of the key enablers to extract the residual network capacity. This paper proposes an innovative algorithm exploiting electronic traffic grooming and using impairment-aware routing to address the virtual network embedding problem (IA-TG-VNE) in optical networks. We also analyze the networking benefits of using time-domain hybrid modulation formats (TDHMF) over four conventional modulation formats; binary phase-shift keying (BPSK), quadrature phase-shift keying (QPSK), 16 quadrature amplitude modulation (QAM), and 64 QAM. The analysis is performed on a detailed physical layer model based on the Gaussian Noise (GN) model, which includes the effect of both linear and nonlinear impairments. The simulation results are obtained on realistic network topology: a 37-nodes PAN-EU. The simulation results show that TDHMF always performs better than conventional modulation formats for all types of fiber in terms of total network capacity, the average bit rate per lightpath (LP), number of LPs, and request blocking ratio

Gastric residual volume measurement in British neonatal intensive care units: a survey of practice.

OBJECTIVE: Despite little evidence, the practice of routine gastric residual volume (GRV) measurement to guide enteral feeding in neonatal units is widespread. Due to increased interest in this practice, and to examine trial feasibility, we aimed to determine enteral feeding and GRV measurement practices in British neonatal units. DESIGN AND SETTING: An online survey was distributed via email to all neonatal units and networks in England, Scotland and Wales. A clinical nurse, senior doctor and dietitian were invited to collaboratively complete the survey and submit a copy of relevant guidelines. RESULTS: 95/184 (51.6%) approached units completed the survey, 81/95 (85.3%) reported having feeding guidelines and 28 guidelines were submitted for review. The majority of units used intermittent (90/95) gastric feeds as their primary feeding method. 42/95 units reported specific guidance for measuring and interpreting GRV. 20/90 units measured GRV before every feed, 39/90 at regular time intervals (most commonly four to six hourly 35/39) and 26/90 when felt to be clinically indicated. Most units reported uncertainty on the utility of aspirate volume for guiding feeding decisions; 13/90 reported that aspirate volume affected decisions 'very much'. In contrast, aspirate colour was reported to affect decisions 'very much' by 37/90 of responding units. Almost half, 44/90, routinely returned aspirates to the stomach. CONCLUSIONS: Routine GRV measurement is part of standard practice in British neonatal units, although there was inconsistency in how frequently to measure or how to interpret the aspirate. Volume was considered less important than colour of the aspirate