Cannabis use is highly prevalent and often considered to be relatively harmless. Nonetheless, a subset of regular cannabis users may develop dependence, experiencing poorer quality of life and greater mental health problems relative to non-dependent users. The neuroanatomy characterizing cannabis use versus dependence is poorly understood. We aimed to delineate the contributing role of cannabis use and dependence on morphology of the hippocampus, one of the most consistently altered brain regions in cannabis users, in a large multi-site dataset aggregated across four research sites. We compared hippocampal volume and vertex-level hippocampal shape differences (1) between 121 non-using controls and 140 cannabis users; (2) between 106 controls, 50 non-dependent users and 70 dependent users; and (3) between a subset of 41 controls, 41 non-dependent users and 41 dependent users, matched on sample characteristics and cannabis use pattern (onset age and dosage). Cannabis users did not differ from controls in hippocampal volume or shape. However, cannabis-dependent users had significantly smaller right and left hippocampi relative to controls and non-dependent users, irrespective of cannabis dosage. Shape analysis indicated localized deflations in the superior-medial body of the hippocampus. Our findings support neuroscientific theories postulating dependence-specific neuroadaptations in cannabis users. Future efforts should uncover the neurobiological risk and liabilities separating dependent and non-dependent use of cannabis.

White matter hyperintensities (WMH), also known as white matter lesions, are localised white matter areas that appear hyperintense on MRI scans. WMH commonly occur in the ageing population, and are often associated with several factors such as cognitive disorders, cardiovascular risk factors, cerebrovascular and neurodegenerative diseases. Despite the fact that some links between lesion location and parametric factors such as age have already been established, the relationship between voxel-wise spatial distribution of lesions and these factors is not yet well understood. Hence, it would be of clinical importance to model the distribution of lesions at the population-level and quantitatively analyse the effect of various factors on the lesion distribution model. In this work we compare various methods, including our proposed method, to generate voxel-wise distributions of WMH within a population with respect to various factors. Our proposed Bayesian spline method models the spatio-temporal distribution of WMH with respect to a parametric factor of interest, in this case age, within a population. Our probabilistic model takes as input the lesion segmentation binary maps of subjects belonging to various age groups and provides a population-level parametric lesion probability map as output. We used a spline representation to ensure a degree of smoothness in space and the dimension associated with the parameter, and formulated our model using a Bayesian framework. We tested our algorithm output on simulated data and compared our results with those obtained using various existing methods with different levels of algorithmic and computational complexity. We then compared the better performing methods on a real dataset, consisting of 1000 subjects of the UK Biobank, divided in two groups based on hypertension diagnosis. Finally, we applied our method on a clinical dataset of patients with vascular disease. On simulated dataset, the results from our algorithm showed a mean square error (MSE) value of 7.27×10-5, which was lower than the MSE value reported in the literature, with the advantage of being robust and computationally efficient. In the UK Biobank data, we found that the lesion probabilities are higher for the hypertension group compared to the non-hypertension group and further verified this finding using a statistical t-test. Finally, when applying our method on patients with vascular disease, we observed that the overall probability of lesions is significantly higher in later age groups, which is in line with the current literature.

Stuttering is a disorder in which the smooth flow of speech is interrupted. People who stutter show structural and functional abnormalities in the speech and motor system. It is unclear whether functional differences reflect general traits of the disorder or are specifically related to the dysfluent speech state. We used a hierarchical approach to separate state and trait effects within stuttering. We collected sparse-sampled functional MRI during two overt speech tasks (sentence reading and picture description) in 17 people who stutter and 16 fluent controls. Separate analyses identified indicators of: (1) general traits of people who stutter; (2) frequency of dysfluent speech states in subgroups of people who stutter; and (3) the differences between fluent and dysfluent states in people who stutter. We found that reduced activation of left auditory cortex, inferior frontal cortex bilaterally, and medial cerebellum were general traits that distinguished fluent speech in people who stutter from that of controls. The stuttering subgroup with higher frequency of dysfluent states during scanning (n = 9) had reduced activation in the right subcortical grey matter, left temporo-occipital cortex, the cingulate cortex, and medial parieto-occipital cortex relative to the subgroup who were more fluent (n = 8). Finally, during dysfluent states relative to fluent ones, there was greater activation of inferior frontal and premotor cortex extending into the frontal operculum, bilaterally. The above differences were seen across both tasks. Subcortical state effects differed according to the task. Overall, our data emphasise the independence of trait and state effects in stuttering.

BACKGROUND: We have previously shown that increased resting-state functional magnetic resonance imaging (fMRI)-based functional connectivity (FC) within the frontal resting-state networks in Alzheimer's disease (AD) patients reflects residual, possibly compensatory, function. This suggests that symptomatic treatments should aim to enhance FC specifically in these networks. METHODS: 18 patients with probable AD underwent brain MRI and neuropsychological assessment at baseline and after 12 weeks of treatment with donepezil. We tested if changes in cognitive performance after treatment correlated with changes in FC in resting-state networks known to be altered in AD. RESULTS: We found increases in FC in the orbitofrontal network that correlated with cognitive improvement after treatment. The increased FC was greatest in patients who responded most to treatment. CONCLUSION: This 'proof of concept' study suggests that changes in network-specific FC might be a biomarker of pharmacological intervention efficacy in AD.

Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.

Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank.

The Human Connectome Project (HCP) is a major endeavor that will acquire and analyze connectivity data plus other neuroimaging, behavioral, and genetic data from 1,200 healthy adults. It will serve as a key resource for the neuroscience research community, enabling discoveries of how the brain is wired and how it functions in different individuals. To fulfill its potential, the HCP consortium is developing an informatics platform that will handle: (1) storage of primary and processed data, (2) systematic processing and analysis of the data, (3) open-access data-sharing, and (4) mining and exploration of the data. This informatics platform will include two primary components. ConnectomeDB will provide database services for storing and distributing the data, as well as data analysis pipelines. Connectome Workbench will provide visualization and exploration capabilities. The platform will be based on standard data formats and provide an open set of application programming interfaces (APIs) that will facilitate broad utilization of the data and integration of HCP services into a variety of external applications. Primary and processed data generated by the HCP will be openly shared with the scientific community, and the informatics platform will be available under an open source license. This paper describes the HCP informatics platform as currently envisioned and places it into the context of the overall HCP vision and agenda.

Focal lesions and brain atrophy are the most extensively studied aspects of multiple sclerosis (MS), but the image acquisition and analysis techniques used can be further improved, especially those for studying within-patient changes of lesion load and atrophy longitudinally. Improved accuracy and sensitivity will reduce the numbers of patients required to detect a given treatment effect in a trial, and ultimately, will allow reliable characterization of individual patients for personalized treatment. Based on open issues in the field of MS research, and the current state of the art in magnetic resonance image analysis methods for assessing brain lesion load and atrophy, this paper makes recommendations to improve these measures for longitudinal studies of MS. Briefly, they are (1) images should be acquired using 3D pulse sequences, with near-isotropic spatial resolution and multiple image contrasts to allow more comprehensive analyses of lesion load and atrophy, across timepoints. Image artifacts need special attention given their effects on image analysis results. (2) Automated image segmentation methods integrating the assessment of lesion load and atrophy are desirable. (3) A standard dataset with benchmark results should be set up to facilitate development, calibration, and objective evaluation of image analysis methods for MS.

The ability to predict learning performance from brain imaging data has implications for selecting individuals for training or rehabilitation interventions. Here, we used structural MRI to test whether baseline variations in gray matter (GM) volume correlated with subsequent performance after a long-term training of a complex whole-body task. 44 naïve participants were scanned before undertaking daily juggling practice for 6weeks, following either a high intensity or a low intensity training regime. To assess performance across the training period participants' practice sessions were filmed. Greater GM volume in medial occipito-parietal areas at baseline correlated with steeper learning slopes. We also tested whether practice time or performance outcomes modulated the degree of structural brain change detected between the baseline scan and additional scans performed immediately after training and following a further 4weeks without training. Participants with better performance had higher increases in GM volume during the period following training (i.e., between scans 2 and 3) in dorsal parietal cortex and M1. When contrasting brain changes between the practice intensity groups, we did not find any straightforward effects of practice time though practice modulated the relationship between performance and GM volume change in dorsolateral prefrontal cortex. These results suggest that practice time and performance modulate the degree of structural brain change evoked by long-term training regimes.

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

The hormone, relaxin, inhibits aberrant myofibroblast differentiation and collagen deposition by disrupting the TGF-β1/Smad2 axis, via its cognate receptor, Relaxin Family Peptide Receptor 1 (RXFP1), extracellular signal-regulated kinase (ERK)1/2 phosphorylation (pERK) and a neuronal nitric oxide (NO) synthase (nNOS)-NO-cyclic guanosine monophosphate (cGMP)-dependent pathway. However, the signalling pathways involved in its additional ability to increase matrix metalloproteinase (MMP) expression and activity remain unknown. This study investigated the extent to which the NO pathway was involved in human gene-2 (H2) relaxin's ability to positively regulate MMP-1 and its rodent orthologue, MMP-13, MMP-2 and MMP-9 (the main collagen-degrading MMPs) in TGF-β1-stimulated human dermal fibroblasts and primary renal myofibroblasts isolated from injured rats; by gelatin zymography (media) and Western blotting (cell layer). H2 relaxin (10-100 ng/ml) significantly increased MMP-1 (by ~50%), MMP-2 (by ~80%) and MMP-9 (by ~80%) in TGF-β1-stimulated human dermal fibroblasts; and MMP-13 (by ~90%), MMP-2 (by ~130%) and MMP-9 (by ~115%) in rat renal myofibroblasts (all p<0.01 vs untreated cells) over 72 hours. The relaxin-induced up-regulation of these MMPs, however, was significantly blocked by a non-selective NOS inhibitor (L-nitroarginine methyl ester (hydrochloride); L-NAME; 75-100 µM), and specific inhibitors to nNOS (N-propyl-L-arginine; NPLA; 0.2-2 µM), iNOS (1400W; 0.5-1 µM) and guanylyl cyclase (ODQ; 5 µM) (all p<0.05 vs H2 relaxin alone), but not eNOS (L-N-(1-iminoethyl)ornithine dihydrochloride; L-NIO; 0.5-5 µM). However, neither of these inhibitors affected basal MMP expression at the concentrations used. Furthermore, of the NOS isoforms expressed in renal myofibroblasts (nNOS and iNOS), H2 relaxin only stimulated nNOS expression, which in turn, was blocked by the ERK1/2 inhibitor (PD98059; 1 µM). These findings demonstrated that H2 relaxin signals through a RXFP1-pERK-nNOS-NO-cGMP-dependent pathway to mediate its anti-fibrotic actions, and additionally signals through iNOS to up-regulate MMPs; the latter being suppressed by TGF-β1 in myofibroblasts, but released upon H2 relaxin-induced inhibition of the TGF-β1/Smad2 axis.

BACKGROUND: Familial amyloidotic polyneuropathy (FAP) is a peripheral neuropathy caused by the extracellular accumulation and deposition of insoluble transthyretin (TTR) aggregates. However the molecular mechanism that underlies TTR toxicity in peripheral nerves is unclear. Previous studies have suggested that amyloidogenic proteins can aggregate into oligomers which disrupt intracellular calcium homeostasis by increasing the permeability of the plasma membrane to extracellular calcium. The aim of the present study was to examine the effect of TTR on calcium influx in dorsal root ganglion neurons. RESULTS: Levels of intracellular cytosolic calcium were monitored in dorsal root ganglion (DRG) neurons isolated from embryonic rats using the calcium-sensitive fluorescent indicator Fluo4. An amyloidogenic mutant form of TTR, L55P, induced calcium influx into the growth cones of DRG neurons, whereas wild-type TTR had no significant effect. Atomic force microscopy and dynamic light scattering studies confirmed that the L55P TTR contained oligomeric species of TTR. The effect of L55P TTR was decreased by blockers of voltage-gated calcium channels (VGCC), as well as by blockers of Nav1.8 voltage-gated sodium channels and transient receptor potential M8 (TRPM8) channels. siRNA knockdown of TRPM8 channels using three different TRPM8 siRNAs strongly inhibited calcium influx in DRG growth cones. CONCLUSIONS: These data suggest that activation of TRPM8 channels triggers the activation of Nav1.8 channels which leads to calcium influx through VGCC. We suggest that TTR-induced calcium influx into DRG neurons may contribute to the pathophysiology of FAP. Furthermore, we speculate that similar mechanisms may mediate the toxic effects of other amyloidogenic proteins such as the β-amyloid protein of Alzheimer's disease.