Partial Correlation Matrices Research Articles

FNETS: Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series

We propose FNETS, a methodology for network estimation and forecasting of high-dimensional time series exhibiting strong serial- and cross-sectional correlations. We operate under a factor-adjusted vector autoregressive (VAR) model which, after accounting for pervasive co-movements of the variables by common factors, models the remaining idiosyncratic dynamic dependence between the variables as a sparse VAR process. Network estimation of FNETS consists of three steps: (i) factor-adjustment via dynamic principal component analysis, (ii) estimation of the latent VAR process via l 1 -regularized Yule-Walker estimator, and (iii) estimation of partial correlation and long-run partial correlation matrices. In doing so, we learn three networks underpinning the VAR process, namely a directed network representing the Granger causal linkages between the variables, an undirected one embedding their contemporaneous relationships and finally, an undirected network that summarizes both lead-lag and contemporaneous linkages. In addition, FNETS provides a suite of methods for forecasting the factor-driven and the idiosyncratic VAR processes. Under general conditions permitting tails heavier than the Gaussian one, we derive uniform consistency rates for the estimators in both network estimation and forecasting, which hold as the dimension of the panel and the sample size diverge. Simulation studies and real data application confirm the good performance of FNETS.

A Network of two Markets, Correlations for Stocks in the S&P500 Index and Stocks Traded in the BMV

Our goal is to study how stocks from Mexico and United States are interconnected. We apply a novel method based on a graphical model. We estimate partial correlations for every year of the period 2000-2020. Our results based on partial correlation matrices show a systematic level of inter-connectivity across countries that metrics from network theory confirm. An important difference between these countries is how sectors in each market are linked. Most sector graphs in the United States are densely interconnected. In contrast, sectors in Mexico present much less links. We then compare networks in the periods of the subprime mortgage crisis and the crisis triggered by the COVID-19 pandemic. The different propagation speeds of both crises are correctly captured by the metrics. A limitation is derived from information, and it is desirable to include actualized data in the study. The deployed novel method, which led to obtain new results, endow originality to the work. It is concluded that disaggregated data provides a promising venue of research.

PRNP expression predicts imaging findings in sporadic Creutzfeldt-Jakob disease.

We explored the relationship between regional PRNP expression from healthy brain tissue and patterns of increased and decreased diffusion and regional brain atrophy in patients with sporadic Creutzfeldt-Jakob disease (sCJD). We used PRNP microarray data from 6 healthy adult brains from Allen Brain Institute and T1-weighted and diffusion-weighted MRIs from 34 patients diagnosed with sCJD and 30 age- and sex-matched healthy controls to construct partial correlation matrices across brain regions for specific measures of interest: PRNP expression, mean diffusivity, volume, cortical thickness, and local gyrification index, a measure of cortical folding. Regional patterns of PRNP expression in the healthy brain correlated with regional patterns of diffusion signal abnormalities and atrophy in sCJD. Among different measures of cortical morphology, regional patterns of local gyrification index in sCJD most strongly correlated with regional patterns of PRNP expression. At the vertex-wise level, different molecular subtypes of sCJD showed distinct regional correlations in local gyrification index across the cortex. Local gyrification index correlation patterns most closely matched patterns of PRNP expression in sCJD subtypes known to have greatest pathologic involvement of the cerebral cortex. These results suggest that the specific genetic and molecular environment in which the prion protein is expressed confer variable vulnerability to misfolding across different brain regions that is reflected in patterns of imaging findings in sCJD. Further work in larger samples will be needed to determine whether these regional imaging patterns can serve as reliable markers of distinct disease subtypes to improve diagnosis and treatment targeting.

Associations between disrupted functional brain network topology and cognitive impairment in patients with rectal cancer during chemotherapy.

Cognitive impairment has been identified in patients with non-central nervous system cancer received chemotherapy. Chemotherapy-induced changes in the brain are considered as the possible causes of the cognitive deficits of patients. This study aimed to explore chemotherapy-related functional brain changes and cognitive impairment in rectal cancer (RC) patients who had just finished chemotherapy treatment. In this study, RC patients after chemotherapy (on the day patients received the last dose of chemotherapy) (n=30) and matched healthy controls (HCs) (n=30) underwent cognitive assessments, structural magnetic resonance imaging (MRI) and resting-state functional MRI. The functional brain networks were constructed by thresholding the partial correlation matrices of 90 brain regions in the Anatomical Automatic Labeling template and the topologic properties were evaluated by graph theory analysis. Moreover, correlations between altered topological measures and scores of cognitive scales were explored in the patient group. Compared with HCs, RC patients had lower scores of cognitive scales. The functional brain network had preserved small-world topological features but with a tendency towards higher path length in the whole network. In addition, patients had decreased nodal global efficiency (Eglo(i)) in the left superior frontal gyrus (dorsolateral), superior frontal gyrus (orbital part), inferior frontal gyrus (opercular part), inferior frontal gyrus (triangular part) and right inferior frontal gyrus (triangular part). Moreover, values of Eglo(i) in the superior and inferior frontal gyrus were positively associated with cognitive function in the patient group. These results suggested that cognitive impairment was associated with disruptions of the topological organization in functional brain networks of RC patients who had just finished chemotherapy, which provided new insights into the pathophysiology underlying acute effects of chemotherapy on cognitive function.

COVID-19-Related News Consumption Linked with Stress and Worry, but Not Sleep Quality, Early in the Pandemic

ABSTRACT Beginning in early 2020, the novel coronavirus was the subject of frequent and sustained news coverage. Building on prior literature on the stress-inducing effects of consuming news during a large-scale crisis, we used network analysis to investigate the association between coronavirus disease 2019 (COVID-19) news consumption, COVID-19-related psychological stress, worries about oneself and one’s loved ones getting COVID-19, and sleep quality. Data were collected in March 2020 from 586 adults (45.2% female; 72.9% White) recruited via Amazon Mechanical Turk in the U.S. Participants completed online surveys assessing attitudes and behaviors related to COVID-19 and a questionnaire assessing seven domains of sleep quality. Networks were constructed using partial regularized correlation matrices. As hypothesized, COVID-19 news consumption was positively associated with COVID-19-related psychological stress and concerns about one’s loved ones getting COVID-19. However, there were very few associations between COVID-19 news consumption and sleep quality indices, and gender did not moderate any of the observed relationships. This study replicates and extends previous findings that COVID-19-news consumption is linked with psychological stress related to the pandemic, but even under such conditions, sleep quality can be spared due to the pandemic allowing for flexibility in morning work/school schedules.

Diagnosis of Parkinson’s disease using EEG and fMRI

Parkinson’s disease (PD) is a brain disorder that leads to shaking, stiffness, and difficulty with walking, balance, and coordination. Parkinson’s symptoms usually begin gradually and get worse over time. We have developed a framework to find solution for early diagnose of PD by investigating the topological properties of functional brain networks within fMRI and EEG Signals. After the construction partial correlation matrices of 160 regions from Dosenbach brain from fMRI image, six features were extracted. As well as extracted five features from EEG signals and these 11 inputs were given as input to adaboost classifier. This system has produced 93.45% accuracy and the outcome is significantly higher accuracy when compared to earlier works.

Disrupted Brain Functional Network Topology in Essential Tremor Patients With Poor Sleep Quality.

Sleep disturbances, especially poor quality of sleep (QoS), are common among essential tremor (ET) patients and may have adverse effects on their quality of life, but the etiology driving the poor QoS in these individuals remains inadequately understood. Few data are available on the neuroimaging alterations of ET with poor QoS. Thirty-eight ET patients with poor QoS (SleET), 48 ET patients with normal QoS (NorET), and 80 healthy controls (HCs) participated in this study. All subjects underwent a 3.0-T magnetic resonance imaging (MRI) scan for resting-state functional MRI data collection. Then, the whole-brain functional connectome was constructed by thresholding the partial correlation matrices of 116 brain regions. Graph theory and network-based statistical analyses were performed. We used a non-parametric permutation test for group comparisons of topological metrics. Partial correlation analyses between the topographical features and clinical characteristics were conducted. The SleET and NorET groups exhibited decreased clustering coefficients, global efficiency, and local efficiency and increased the characteristic path length. Both of these groups also showed reduced nodal degree and nodal efficiency in the left superior dorsolateral frontal gyrus, superior frontal medial gyrus (SFGmed), posterior cingulate gyrus (PCG), lingual gyrus, superior occipital gyrus, right middle occipital gyrus, and right fusiform gyrus. The SleET group additionally presented reduced nodal degrees and nodal efficiency in the right SFGmed relative to the NorET and HC groups, and nodal efficiency in the right SFGmed was negatively correlated with the Pittsburgh Sleep Quality Index score. The observed impaired topographical organizations of functional brain networks within the central executive network (CEN), default mode network (DMN), and visual network serve to further our knowledge of the complex interactions between tremor and sleep, adding to our understanding of the underlying neural mechanisms of ET with poor QoS.

Disturbed Craving Regulation to Gaming Cues in Internet Gaming Disorder: Implications for Uncontrolled Gaming Behaviors

Although numerous neuroimaging studies have detected structural and functional abnormality in specific brain regions and connections in subjects with Internet gaming disorder (IGD), the topological organization of the whole-brain network in IGD remain unclear. In this study, we applied graph theoretical analysis to explore the intrinsic topological properties of brain networks in Internet gaming disorder (IGD). 37 IGD subjects and 35 matched healthy control (HC) subjects underwent a resting-state functional magnetic resonance imaging scan. The functional networks were constructed by thresholding partial correlation matrices of 90 brain regions. Then we applied graph-based approaches to analysis their topological attributes, including small-worldness, nodal metrics, and efficiency. Both IGD and HC subjects show efficient and economic brain network, and small-world topology. Although there was no significant group difference in global topology metrics, the IGD subjects showed reduced regional centralities in the prefrontal cortex, left posterior cingulate cortex, right amygdala, and bilateral lingual gyrus, and increased functional connectivity in sensory-motor-related brain networks compared to the HC subjects. These results imply that people with IGD may be associated with functional network dysfunction, including impaired executive control and emotional management, but enhanced coordination among visual, sensorimotor, auditory and visuospatial systems.

JEDi: java essential dynamics inspector \u2014 a molecular trajectory analysis toolkit

BackgroundPrincipal component analysis (PCA) is commonly applied to the atomic trajectories of biopolymers to extract essential dynamics that describe biologically relevant motions. Although application of PCA is straightforward, specialized software to facilitate workflows and analysis of molecular dynamics simulation data to fully harness the power of PCA is lacking. The Java Essential Dynamics inspector (JEDi) software is a major upgrade from the previous JED software.ResultsEmploying multi-threading, JEDi features a user-friendly interface to control rapid workflows for interrogating conformational motions of biopolymers at various spatial resolutions and within subregions, including multiple chain proteins. JEDi has options for Cartesian-based coordinates (cPCA) and internal distance pair coordinates (dpPCA) to construct covariance (Q), correlation (R), and partial correlation (P) matrices. Shrinkage and outlier thresholding are implemented for the accurate estimation of covariance. The effect of rare events is quantified using outlier and inlier filters. Applying sparsity thresholds in statistical models identifies latent correlated motions. Within a hierarchical approach, small-scale atomic motion is first calculated with a separate local cPCA calculation per residue to obtain eigenresidues. Then PCA on the eigenresidues yields rapid and accurate description of large-scale motions. Local cPCA on all residue pairs creates a map of all residue-residue dynamical couplings. Additionally, kernel PCA is implemented. JEDi output gives high quality PNG images by default, with options for text files that include aligned coordinates, several metrics that quantify mobility, PCA modes with their eigenvalues, and displacement vector projections onto the top principal modes. JEDi provides PyMol scripts together with PDB files to visualize individual cPCA modes and the essential dynamics occurring within user-selected time scales. Subspace comparisons performed on the most relevant eigenvectors using several statistical metrics quantify similarity/overlap of high dimensional vector spaces. Free energy landscapes are available for both cPCA and dpPCA.ConclusionJEDi is a convenient toolkit that applies best practices in multivariate statistics for comparative studies on the essential dynamics of similar biopolymers. JEDi helps identify functional mechanisms through many integrated tools and visual aids for inspecting and quantifying similarity/differences in mobility and dynamic correlations.

Disrupted Brain Network Topology in Drug-naïve Essential Tremor Patients with and Without Depression : AResting State Functional Magnetic Resonance Imaging Study.

This study was carried out to investigate brain functional connectome and its potential relationships with the disease severity and emotion function in patients with essential tremor with and without depressive symptoms by using resting-state functional magnetic resonance imaging and graph theory approaches. In this study 33 essential tremor patients with depression, 45 essential tremor patients without depression and 79age and gender-matched healthy controls were recruited to undergo a3.0‑T imaging scan. The whole brain functional connectome was constructed by thresholding the partial correlation matrices of 116 brain regions, and the topologic properties were analyzed by using graph theory approaches and network-based statistic approaches. Nonparametric permutation test was also used for group comparisons of topological metrics. Correlation analyses between topographic features and the clinical characteristics were performed. The functional connectome in both essential tremor patients with and without depression showed abnormalities at the global level (decrease in clustering coefficient, global efficiency, and local efficiency but increase in characteristic path length) and at the nodal level (decrease nodal centralities in the cerebellum, motor cortex, prefrontal-limbic regions, default mode network) (p < 0.05, false discovery rate corrected). Moreover, essential tremor patients with depression showed higher node efficiency in superior frontal gyrus and posterior cingulate gyrus compared to essential tremor without depression. Our results may provide insights into the underlying pathophysiology of essential tremor patients with and without depression and aid the development of some potential biomarkers of the depressive symptoms in patients with essential tremor.

The shape of partial correlation matrices

The correlational structure of a set of variables is often conveniently described by the pairwise partial correlations as they contain the same information as the Pearson correlations with the advantage of straightforward identifications of conditional linear independence. For mathematical convenience, multiple matrix representations of the pairwise partial correlations exist in the literature but their properties have not been investigated thoroughly. In this paper, we derive necessary and sufficient conditions for the eigenvalues of differently defined partial correlation matrices so that the correlation structure is a valid one. Equipped with these conditions, we will then emphasize the intricacies of algorithmic generations of correlation structures via partial correlation matrices. Furthermore, we examine the space of valid partial correlation structures and juxtapose it with the space of valid Pearson correlation structures. As these spaces turn out to be equal in volume for every dimension and equivalent with respect to rotation, a simple formula allows the creation of valid partial correlation matrices by the use of current algorithms for the generation and approximation of correlation matrices. Lastly, we derive simple conditions on the partial correlations for frequently assumed sparse structures.

Altered Whole-Brain Functional Networks in Drug-Naïve, First-Episode Adolescents With Major Depression Disorder.

Neuroimaging studies have demonstrated disrupted brain functional networks in major depression disorder (MDD); however, alterations to whole-brain networks specifically associated with adolescent MDD remain poorly understood. To investigate the topological architecture of intrinsic brain functional networks in drug-naïve, first-episode adolescent MDD patients using graph theoretical analysis. Prospective. In all, 109 adolescent MDD patients and 70 healthy control subjects. 3.0T; gradient-echo echo-planar imaging sequence. After the construction of whole-brain functional networks by thresholding partial correlation matrices of 90 brain regions, we calculated the topological properties (eg, small-world, efficiency, and nodal centrality) using graph theoretical analysis. A chi-squared test was used to compare the gender-ratio difference, and a two-sample t-test was used in the comparison of age. We compared network measures between the two groups using nonparametric permutation tests. Exploratory partial correlation analyses were used to determine the relationships between the topological metrics showing significant between-group differences and the clinical variables for adolescent MDD patients. Small-world architecture in brain functional networks was identified for both the MDD and control groups. However, depressed adolescents exhibited lower characteristic path length, normalized characteristic path length and clustering coefficient, and higher global efficiency than controls (false discovery rate [FDR] q < 0.05). Compared with controls, depressed adolescents exhibited increased nodal centralities in the default mode regions, including the right anterior cingulate and paracingulate gyri, left posterior cingulate gyrus, right superior frontal gyrus (medial part), bilateral hippocampus, and bilateral parahippocampal gyrus, and decreased nodal centralities in the orbitofrontal, temporal, and occipital regions (FDR q < 0.05). This study indicated that drug-naïve, first-episode adolescent MDD patients exhibit disruptions in whole-brain functional networks. 1 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1790-1798.

Global and regional connectivity analysis of resting-state function MRI brain images using graph theory in Parkinson’s disease

Objectives Parkinson’s disease (PD) is the second most common neurodegenerative disorder which resists around 10 million people worldwide. It develops when nerve cells in a region of the brain that regulates movement become damaged; the symptoms usually begin gradually and become critical over time. In this study, we proposed to investigate the topological properties of functional brain networks within healthy controls (HCs) and PD patients. Also, we evaluated the gender difference among PD patients through graph theoretical approach. Materials and Methods The rs-fMRI (resting-state functional magnetic resonance imaging) data of fifty-one PD patients and healthy controls was applied to generate the brain functional connectome. The functional whole-brain connectome was constructed by thresholding partial correlation matrices of 160 regions from Dosenbach brain atlas. From the graph theory approach, global and nodal metrics were analysed, and we observed considerable changes in PD patients in comparison with healthy controls. Results Findings suggest that there is a significant difference in the topological characteristics of PD patients, and this was found to be evident in the default mode network (DMN) and occipital regions. Conclusion This study provides essential insights from network changes to the clinically relevant information for the PD progression.

The Effects of Using Partial or Uncorrected Correlation Matrices When Comparing Network and Latent Variable Models.

Network models of the WAIS-IV based on regularized partial correlation matrices have been reported to outperform latent variable models based on uncorrected correlation matrices. The present study sought to compare network and latent variable models using both partial and uncorrected correlation matrices with both types of models. The results show that a network model provided better fit to matrices of partial correlations but latent variable models provided better fit to matrices of full correlations. This result is due to the fact that the use of partial correlations removes most of the covariance common to WAIS-IV tests. Modeling should be based on uncorrected correlations since these represent the majority of shared variance between WAIS-IV test scores.

A preliminary study of disrupted functional network in individuals with Internet gaming disorder: Evidence from the comparison with recreational game users

Although online gaming may lead to Internet gaming disorder (IGD), most players are recreational game users (RGU) who do not develop IGD. So far, the topological organization of whole-brain functional networks in IGD remains poorly understood. The inclusion of RGU as a control group could minimize the potential effects of gaming experience and gaming-related cue familiarity on the neural characteristics of IGD subjects. In the present study, we applied graph theoretical analysis to preliminarily explore the topological organization of intrinsic functional brain networks in IGD. 61 IGD participants and 61 matched RGU participants were recruited to undergo a resting-state functional magnetic resonance imaging scan. The whole-brain functional networks were constructed by thresholding partial correlation matrices of 90 brain regions, and graph-based approaches were applied to analysis their topological attributes, including small-world, efficiency, and nodal centralities. Both of IGD and RGU groups showed efficient and economic small-world topology in brain functional networks. Although there was no significant group difference in global properties, subjects with IGD as compared to those with RGU showed increased nodal centralities in the reward, craving, emotional memory and sensory-motor processing regions. These results suggest that the functional network dysfunction, characterizing by heightened incentive motivation and sensory-motor coordination, may provide a new perspective for understanding the neural characteristics underlying IGD.

Disrupted brain functional networks in drug-naïve children with attention deficit hyperactivity disorder assessed using graph theory analysis.

Neuroimaging studies have revealed functional brain network abnormalities in attention deficit hyperactivity disorder (ADHD), but the results have been inconsistent, potentially related to confounding medication effects. Furthermore, specific topological alterations in functional networks and their role in behavioral inhibition dysfunction remain to be established. Resting-state functional magnetic resonance imaging was performed on 51 drug-naïve children with ADHD and 55 age-matched healthy controls. Brain functional networks were constructed by thresholding the partial correlation matrices of 90 brain regions, and graph theory was used to analyze network topological properties. The Stroop test was used to assess cognitive inhibitory abilities. Nonparametric permutation tests were used to compare the topological architectures in the two groups. Compared with healthy subjects, brain networks in ADHD patients demonstrated altered topological characteristics, including lower global (FDR q = 0.01) and local efficiency (p = 0.032, uncorrected) and a longer path length (FDR q = 0.01). Lower nodal efficiencies were found in the left inferior frontal gyrus and anterior cingulate cortex in the ADHD group (FDR both q < 0.05). Altered global and nodal topological efficiencies were associated with the severity of inhibitory cognitive control deficits and hyperactivity symptoms in ADHD (p <0 .05). Alterations in network topologies in drug-naïve ADHD patients indicate weaker small-worldization with decreased segregation and integration of functional brain networks. Deficits in the cingulo-fronto-parietal attention network were associated with inhibitory control deficits.

Psychosocial factors affecting variation in patient-reported outcomes after elbow fractures

The purpose of this study was to identify factors associated with limitations in function measured by patient-reported outcome measures (PROMs)6-9 months after elbow fractures in adultsfrom a range of demographic, injury, psychological, and social variables measured within a week and 2-4 weeks after injury. We enrolled 191 adult patients sustaining an isolated elbow fracture and invited them to complete PROMs at their initial visit to the orthopedic outpatient clinic (within a maximum of 1 week after fracture), between 2 and 4 weeks, and between 6 and 9 months after injury; 183 patients completed the final assessment. Bivariate analysis was performed, followed by multivariable regression analysis accounting for multicollinearity. This was evaluated using partial R2, correlation matrices, and variable inflation factor assessment. There was a correlation between multiple variables within a week of injury and 2-4 weeks after injury with PROMs 6-9 months after injury in bivariate analysis. Kinesiophobia measured within a week of injury and self-efficacy measured at 2-4 weeks were the strongest predictors of limitations 6-9 months after injury in multivariable regression. Regression models accounted for substantial variance in all PROMs at both time points. Developing effective coping strategies to overcome fears related to movement and reinjuryand finding ways of persevering with activity despite pain within a month of injurymay enhance recovery after elbow fractures. Heightened fears around movement and suboptimal coping ability are modifiable using evidence-based behavioral treatments.

Functional brain network topology in parents who lost their only child in China: Post-traumatic stress disorder and sex effects

Post-traumatic stress disorder (PTSD) is associated with disruption of the brain network topology; however, little is known about the topological changes and sex effects in PTSD patients following a unique trauma, the loss of an only child, in China. Fifty-one lost-only-child parents with PTSD, 93 lost-only-child non-PTSD parents (NPTSD), and 50 healthy subjects underwent resting-state functional MRI. The whole-brain functional network was constructed by thresholding partial correlation matrices of 90 brain regions. Group differences in the topological properties, the diagnosis-by-sex interaction, and the relationships between topological metrics and clinical variables were investigated. Compared with healthy subjects, PTSD and NPTSD groups exhibited significantly shorter path lengths and higher nodal centralities in many brain regions across sexes; however, no significant difference was found between the PTSD and NPTSD groups. Additionally, the global topological metrics did not show any sex difference, whereas the nodal centralities in the left insula, right inferior frontal gyrus, and right posterior cingulate cortex differed significantly only in women, and the nodal centralities in the bilateral anterior cingulate cortices and left hippocampus were significantly different only in men. Furthermore, the nodal centralities of the right parahippocampus demonstrated significant diagnosis-by-sex interaction. Cross-sectional design of this study could not demonstrate the causality. The parents who lost their only child exhibited a shift toward randomization and significant nodal topological alterations independent of PTSD effects. Additionally, sex differences were observed primarily in the topological properties at the nodal level, which may indicate a neurobiological contribution to the greater incidence of PTSD in females.

Factors associated with the magnitude of limitations during recovery from a fracture of the proximal humerus: predictors of limitations after proximal humerus fracture.

The purpose of this study was to identify factors associated with limitations in function, measured by patient-reported outcome measures (PROMs), six to nine months after a proximal humeral fracture, from a range of demographic, injury, psychological, and social variables measured within a week and two to four weeks after injury. We enrolled 177 adult patients who sustained an isolated proximal humeral fracture into the study and invited them to complete PROMs at their initial outpatient visit within one week of injury, between two and four weeks, and between six to nine months after injury. There were 128 women and 49 men; the mean age was 66 years (sd 16; 18 to 95). In all, 173 patients completed the final assessment. Bivariate analysis was performed followed by multivariable regression analysis accounting for multicollinearity using partial R2, correlation matrices, and variable inflation factor. Many variables within a week of injury and between two and four weeks after injury correlated with six- to nine-month PROMs in bivariate analysis. Kinesiophobia measured within a week of injury (Tampa Scale for Kinesiophobia-11: partial R2 = 0.14; p = 0.000) and self-efficacy measured between two and four weeks (Pain Self-efficacy Questionnaire-2: partial R2 = 0.266; p < 0.001) were the strongest predictors of limitations (measured by Patient Reported Outcome Measurement Information System Upper Extremity Physical Function Computer Adaptive Test (PROMIS UE)) at six to nine months in multivariable analysis. Similar findings were observed with other types of PROM. Regression models accounted for a substantial amount of variance in all PROMs at both timepoints (e.g. 66% of the overall variance within one week, and 70% within two to four weeks for PROMIS UE at six to nine months). Recovery from a proximal humeral fracture appears to be enhanced by overcoming fears of movement or reinjury within a week after injury and greater self-efficacy (developing resilience and more effective coping strategies) within a month. Such factors are modifiable using enhanced communication skills and cognitive behavioural treatments. These findings could be a catalyst for the routine assessment and treatment of psychological and social factors in the management of patients with fractures. Cite this article: Bone Joint J 2019;101-B:715-723.

Disrupted Brain Functional Networks in Drug-Naïve Children with ADHD Assessed Using Graph Theory Analysis

Background: Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in childhood characterized by multiple behavioral problems and executive dysfunctions. Neuroimaging studies revealed a variety of abnormalities, but the results were inconsistent, partly owing to confounding medication effects and psychiatric comorbidities. Thus, studies of drug- naive ADHD with limited comorbidities is needed to better define disorder-related abnormalities in brain networks. Methods: Resting state functional magnetic resonance imaging was performed on 51 drug-naive ADHD patients (age 6 to 16) and 55 age-matched healthy controls. Brain functional networks were constructed by thresholding partial correlation matrices of 90 brain regions, and graph theory was used to analyze the network topological properties. The Stroop test was used to assess the cognitive inhibitory abilities in the subjects. The non-parametric permutation tests were used to compare the topological architectures in the two groups. Results: Compared with the healthy subjects, the brain networks in the ADHD patients demonstrated altered topological characteristics including lower global and local efficiency ( p=.002,.026), and longer path length (p=.002). Lower nodal efficiencies were found in the left inferior frontal gyrus and anterior cingulate cortex in the ADHD group (p<.05, corrected for the FDR). Altered global and nodal topological efficiency were associated with severity of inhibitory cognitive control deficits and hyperactivity symptoms in ADHD (p<.05). Conclusions: Alterations in network typologies in drug-naive ADHD indicate a weaker small-worldization with decreased segregation and integration of functional brain networks, notably involving a dysfunction of the cingulo-fronto-parietal attention network that was associated with inhibitory control deficits. Funding Statement: This study was supported by the National Natural Science Foundation (Grant Nos. 81621003，81761128023, 81220108013, 81227002, 81030027, 81671669, 81371536 and 81801358), the Humboldt Foundation, and the Program for Changjiang Scholars and Innovative Research Teams in Universities of China (PCSIRT, Grant No. IRT16R52). Dr. Gong would also like to acknowledge the support from his Changjiang Scholar Professorship Award of China (Award No. T2014190) and American CMB Distinguished Professorship Award (Award No. F510000/ G16916411) administered by the Institute of International Education, USA Declaration of Interests: None of the authors has conflicts of interests to report with regard to this manuscript. Ethics Approval Statement: This study was approved by the research ethics committee of West China Hospital of Sichuan University, written informed consent was obtained from the parents/guardians of all participants, and the assents were obtained from study participants prior to participation.