Brain maps of general cognitive function and spatial correlations with neurobiological cortical profiles.

In this paper, we attempt to answer two questions: 1) which regions of the human brain, in terms of morphometry, are most strongly related to individual differences in domain-general cognitive functioning ( )? and 2) what are the underlying neurobiological properties of those regions? We meta-analyse vertex-wise -cortical morphometry (volume, surface area, thickness, curvature and sulcal depth) associations using data from 3 cohorts: the UK Biobank (UKB), Generation Scotland (GenScot), and the Lothian Birth Cohort 1936 (LBC1936), with the meta-analytic = 38,379 (age range = 44 to 84 years old). These morphometry associations vary in magnitude and direction across the cortex (|β| range = -0.12 to 0.

Examining the neurostructural architecture of intelligence: The Lothian Birth Cohort 1936 study.

Examining underlying neurostructural correlates of specific cognitive abilities is practically and theoretically complicated by the existence of the positive manifold (all cognitive tests positively correlate): if a brain structure is associated with a cognitive task, how much of this is uniquely related to the cognitive domain, and how much is due to covariance with all other tests across domains (captured by general cognitive functioning, also known as general intelligence, or 'g')? We quantitatively address this question by examining associations between brain structural and diffusion MRI measures (global tissue volumes, white matter hyperintensities, global white matter diffusion fractional anisotropy and mean diffusivity, and FreeSurfer processed vertex-wise cortical volumes, smoothed at 20mm fwhm) with g and cognitive domains (processing speed, crystallised ability, memory, visuospatial ability). The cognitive domains were modelled using confirmatory factor analysis to derive both hierarchical and bifactor solutions using 13 cognitive tests in 697 participants from the Lothian Birth Cohort 1936 study (mean age 72.5 years; SD = .

Life-course neighbourhood deprivation and brain structure in older adults: the Lothian Birth Cohort 1936.

Neighbourhood disadvantage may be associated with brain health but the importance of exposure at different stages of the life course is poorly understood. Utilising the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and local neuroimaging measures at age 73. A total of 689 participants had at least one valid brain measures (53% male); to maximise the sample size structural equation models with full information maximum likelihood were conducted.

A comprehensive hierarchical comparison of structural connectomes in Major Depressive Disorder cases controls in two large population samples.

Background: The brain can be represented as a network, with nodes as brain regions and edges as region-to-region connections. Nodes with the most connections (hubs) are central to efficient brain function. Current findings on structural differences in Major Depressive Disorder (MDD) identified using network approaches remain inconsistent, potentially due to small sample sizes.

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning.

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules.

Strong intercorrelations among global graph-theoretic indices of structural connectivity in the human brain.

Graph-theoretic metrics derived from neuroimaging data have been heralded as powerful tools for uncovering neural mechanisms of psychological traits, psychiatric disorders, and neurodegenerative diseases. In N = 8,185 human structural connectomes from UK Biobank, we examined the extent to which 11 commonly-used global graph-theoretic metrics index distinct versus overlapping information with respect to interindividual differences in brain organization. Using unthresholded, FA-weighted networks we found that all metrics other than Participation Coefficient were highly intercorrelated, both with each other (mean |r| = 0.

Life-course neighbourhood deprivation and brain structure in older adults: The Lothian Birth Cohort 1936.

Neighbourhood disadvantage may be associated with brain health but the importance at different stages of the life course is poorly understood. Utilizing the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and regional neuroimaging measures at age 73. We found that residing in disadvantaged neighbourhoods in mid- to late adulthood was associated with smaller total brain (=-0.

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning.

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules.

Predicting sex, age, general cognition and mental health with machine learning on brain structural connectomes.

There is an increasing expectation that advanced, computationally expensive machine learning (ML) techniques, when applied to large population-wide neuroimaging datasets, will help to uncover key differences in the human brain in health and disease. We take a comprehensive approach to explore how multiple aspects of brain structural connectivity can predict sex, age, general cognitive function and general psychopathology, testing different ML algorithms from deep learning (DL) model (BrainNetCNN) to classical ML methods. We modelled N = 8183 structural connectomes from UK Biobank using six different structural network weightings obtained from diffusion MRI.

Identification of plasma proteins relating to brain neurodegeneration and vascular pathology in cognitively normal individuals.

Introduction: This study aims to first discover plasma proteomic biomarkers relating to neurodegeneration (N) and vascular (V) damage in cognitively normal individuals and second to discover proteins mediating sex-related difference in N and V pathology.

Methods: Five thousand and thirty-two plasma proteins were measured in 1061 cognitively normal individuals (628 females and 433 males), nearly 90% of whom had magnetic resonance imaging measures of hippocampal volume (as N) and white matter hyperintensities (as V).

Results: Differential protein expression analysis and co-expression network analysis revealed different proteins and modules associated with N and V, respectively.

Spectral clustering based on structural magnetic resonance imaging and its relationship with major depressive disorder and cognitive ability.

There is increasing interest in using data-driven unsupervised methods to identify structural underpinnings of common mental illnesses, including major depressive disorder (MDD) and associated traits such as cognition. However, studies are often limited to severe clinical cases with small sample sizes and most do not include replication. Here, we examine two relatively large samples with structural magnetic resonance imaging (MRI), measures of lifetime MDD and cognitive variables: Generation Scotland (GS subsample, N = 980) and UK Biobank (UKB, N = 8,900), for discovery and replication, using an exploratory approach.

Comparison of structural MRI brain measures between 1.5 and 3 T: Data from the Lothian Birth Cohort 1936.

Multi-scanner MRI studies are reliant on understanding the apparent differences in imaging measures between different scanners. We provide a comprehensive analysis of T -weighted and diffusion MRI (dMRI) structural brain measures between a 1.5 T GE Signa Horizon HDx and a 3 T Siemens Magnetom Prisma using 91 community-dwelling older participants (aged 82 years).

Pipeline comparisons of convolutional neural networks for structural connectomes: predicting sex across 3,152 participants.

With several initiatives well underway towards amassing large and high-quality population-based neuroimaging datasets, deep learning is set to push the boundaries of what is possible in classification and prediction in neuroimaging studies. This includes those that derive increasingly popular structural connectomes, which map out the connections (and their relative strengths) between brain regions. Here, we test different Convolutional Neural Network (CNN) models in a benchmark sex prediction task in a large sample of N=3,152 structural connectomes acquired from the UK Biobank, and compare results across different connectome processing choices.

Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines.

Background: Aging-related cognitive decline is a primary risk factor for Alzheimer's disease and related dementias. More precise identification of the neurobiological bases of cognitive decline in aging populations may provide critical insights into the precursors of late-life dementias.

Methods: Using structural and diffusion brain magnetic resonance imaging data from the UK Biobank (n = 8185; age range, 45-78 years), we examined aging of regional gray matter volumes (nodes) and white matter structural connectivity (edges) within 9 well-characterized networks of interest in the human brain connectome.

The effect of network thresholding and weighting on structural brain networks in the UK Biobank.

Whole-brain structural networks can be constructed using diffusion MRI and probabilistic tractography. However, measurement noise and the probabilistic nature of the tracking procedure result in an unknown proportion of spurious white matter connections. Faithful disentanglement of spurious and genuine connections is hindered by a lack of comprehensive anatomical information at the network-level.

Associations between vascular risk factors and brain MRI indices in UK Biobank.

Aims: Several factors are known to increase risk for cerebrovascular disease and dementia, but there is limited evidence on associations between multiple vascular risk factors (VRFs) and detailed aspects of brain macrostructure and microstructure in large community-dwelling populations across middle and older age.

Methods And Results: Associations between VRFs (smoking, hypertension, pulse pressure, diabetes, hypercholesterolaemia, body mass index, and waist-hip ratio) and brain structural and diffusion MRI markers were examined in UK Biobank (N = 9722, age range 44-79 years). A larger number of VRFs was associated with greater brain atrophy, lower grey matter volume, and poorer white matter health.

Integrated open surgical and endovascular embolization treatment of a paracavernous venous plexus fistula: case report.

The authors report the treatment of a rare type of dural arteriovenous fistula of the paracavernous venous plexus. These fistulas can mimic carotid-cavernous fistulas in both imaging characteristics and clinical presentation, but the anatomical differences require differences in management. The authors describe an integrated open surgical and direct endovascular embolization approach and review of the literature pertaining to the anatomy of and treatment options for paracavernous fistulas.

Sensitivity of magnetic resonance imaging in the diagnosis of mobile and nonmobile L4-L5 degenerative spondylolisthesis.

Background Context: Lumbar degenerative spondylolisthesis (LDS) is often diagnosed by conventional supine magnetic resonance imaging (MRI). Numerous studies have shown, however, that the degree of spondylolisthesis can be reduced or disappears when the patient is supine as compared with standing lateral and flexion-extension (SLFE) radiographs.

Purpose: To compare the sensitivity of supine MRI with SLFE radiographs in patients with L4-L5 LDS.

Reduced structural connectivity within a prefrontal-motor-subcortical network in amyotrophic lateral sclerosis.

Background: To investigate white matter structural connectivity changes associated with amyotrophic lateral sclerosis (ALS) using network analysis and compare the results with those obtained using standard voxel-based methods, specifically Tract-based Spatial Statistics (TBSS).

Methods: MRI data were acquired from 30 patients with ALS and 30 age-matched healthy controls. For each subject, 85 grey matter regions (network nodes) were identified from high resolution structural MRI, and network connections formed from the white matter tracts generated by diffusion MRI and probabilistic tractography.

Clinical results of cervical laminectomy and fusion for the treatment of cervical spondylotic myelopathy in 58 consecutive patients.

Background: There are a number of surgical treatment options for cervical spondylotic myelopathy (CSM). In this study, the authors present their clinical results with cervical laminectomy and fusion for the treatment of patients with CSM.

Methods: This retrospective study included 58 consecutive patients who underwent cervical laminectomy and fusion for CSM.

Analysis of 30-day readmissions among neurosurgical patients: surgical complication avoidance as key to quality improvement.

Unlabelled: OBJECT.: In terms of measuring quality of care and hospital performance, an outcome of increasing interest is the 30-day readmission rate. Recent health care policy making has highlighted the necessity of understanding the factors that influence readmission.

Rotational vertebral artery occlusion secondary to adjacent-level degeneration following anterior cervical discectomy and fusion.

Rotational vertebral artery occlusion (RVAO), or bow hunter's syndrome, most often occurs at the C1-2 level on physiological head rotation. It presents with symptoms of vertebrobasilar insufficiency (VBI). Several previously published studies have reported on subaxial sites of vertebral artery (VA) compression by head rotation.

Spontaneous spinal epidural hematoma and spinal cord infarction following orthotopic liver transplantation: Case report and review of the literature.

Background: Spinal epidural hematomas are rare conditions. Although the exact cause remains unknown in up to 40% of cases, anticoagulation therapy, neoplasm, thrombolytic therapy, internal jugular vein thrombosis, and prolonged Valsalva maneuvers associated with pregnancy may be contributing factors. The source of bleeding appears to be the dorsal internal vertebral venous plexus (IVVP).

Test-retest reliability of structural brain networks from diffusion MRI.

Structural brain networks constructed from diffusion MRI (dMRI) and tractography have been demonstrated in healthy volunteers and more recently in various disorders affecting brain connectivity. However, few studies have addressed the reproducibility of the resulting networks. We measured the test-retest properties of such networks by varying several factors affecting network construction using ten healthy volunteers who underwent a dMRI protocol at 1.

Combined analysis of O6-methylguanine-DNA methyltransferase protein expression and promoter methylation provides optimized prognostication of glioblastoma outcome.

Background: Promoter methylation of the DNA repair gene, O-6-methylguanine-DNA methyltransferase (MGMT), is associated with improved treatment outcome for newly diagnosed glioblastoma (GBM) treated with standard chemoradiation. To determine the prognostic significance of MGMT protein expression as assessed by immunohistochemistry (IHC) and its relationship with methylation, we analyzed MGMT expression and promoter methylation with survival in a retrospective patient cohort.

Methods: We identified 418 patients with newly diagnosed GBM at University of California Los Angeles Kaiser Permanente Los Angeles, nearly all of whom received chemoradiation, and determined MGMT expression by IHC, and MGMT promoter methylation by methylation-specific PCR (MSP) and bisulfite sequencing (BiSEQ) of 24 neighboring CpG sites.