INTRODUCTION:Behavioral variant frontotemporal dementia (bvFTD) may present sporadically or due to an autosomal dominant mutation. Characterization of both forms will improve understanding of the generalizability of assessments and treatments.METHODS:A total of 135 sporadic (s-bvFTD; mean age 63.3 years; 34% female) and 99 familial (f-bvFTD; mean age 59.9; 48% female) bvFTD participants were identified. f-bvFTD cases included 43 with known or presumed chromosome 9 open reading frame 72 (C9orf72) gene expansions, 28 with known or presumed microtubule-associated protein tau (MAPT) mutations, 14 with known progranulin (GRN) mutations, and 14 with a strong family history of FTD but no identified mutation.RESULTS:Participants with f-bvFTD were younger and had earlier age at onset. s-bvFTD had higher total Neuropsychiatric Inventory Questionnaire (NPI-Q) scores due to more frequent endorsement of depression and irritability.DISCUSSION:f-bvFTD and s-bvFTD cases are clinically similar, suggesting the generalizability of novel biomarkers, therapies, and clinical tools developed in either form to the other.

BackgroundHippocampal abnormalities have been demonstrated in schizophrenia. It is unclear whether these abnormalities worsen with age, and whether they affect cognition and function.AimsTo determine whether hippocampal abnormalities in chronic schizophrenia are associated with age, cognition and socio-occupational function.MethodUsing 3 T magnetic resonance imaging we scanned 100 persons aged 19–82 years: 51 were out-patients with stable schizophrenia at least 2 years after diagnosis and 49 were healthy volunteers matched for age and gender. Automated analysis was used to determine hippocampal volume and shape.ResultsThere were differential effects of age in the schizophrenia and control samples on total hippocampal volume (group×age interaction: F(1,95) = 6.57, P = 0.012), with steeper age-related reduction in the schizophrenia group. Three-dimensional shape analysis located the age-related deformations predominantly in the mid-body of the hippocampus. In the schizophrenia group similar patterns of morphometric abnormalities were correlated with impaired cognition and poorer socio-occupational function.ConclusionsHippocampal abnormalities are associated with age in people with chronic schizophrenia, with a steeper decline than in healthy individuals. These abnormalities are associated with cognitive and functional deficits, suggesting that hippocampal morphometry may be a biomarker for cognitive decline in older patients with schizophrenia.

The unprecedented growth, availability and accessibility of sophisticated image analysis algorithms and powerful computational resources led to the idea of developing web-based computational infrastructures that could meet users' new requirements. On the other hand the gap between the pace of data generation and the capability to extract clinically or scientifically relevant information is rapidly widening. Integration of the power of sophisticated mathematical models, efficient computational algorithms and advanced hardware infrastructure provides the necessary sensitivity to detect, extract and analyze subtle, dynamic and distributed patterns distinguishing one brain from another, and a diseased brain from a normal brain. neuGRID is the leading e-Infrastructure where neuroscientists can find core services and resources for brain image analysis. The neuGRID platform makes use of grid services and computing, and was developed with the final aim of overcoming the hurdles that the average scientist meets when trying to set up advanced experiments in computational neuroimaging, thereby empowering a larger base of scientists. Although originally built for neuroscientists working in the field of AD, the infrastructure is designed to be expandable to services from other medical fields (e.g. multiple sclerosis, psychiatric conditions). "neuGRID for Users" will provide an e-Science environment by further developing and deploying the neuGRID infrastructure to deliver a Virtual Laboratory offering neuroscientists access to a wide range of datasets and algorithm pipelines, access to computational resources, services, and support. Information from this abstract is intended to make aware researchers working with neuroimaging of all possibilities when it comes to resources.

Funding sources: None. Conflicts of interest: None declared. Madam, A 3‐year‐old girl visited Kanazawa University Hospital with a history of skin lesions on her face lasting several months. At the time of her first visit in March 2007, she had umbilicated vesiculopapules with small necrotic centres and erythematous oedema on her face (Fig. 1a) and upper limbs, as well as aphthous stomatitis. The skin lesions were exacerbated by sun exposure. She also had a low‐grade fever and general malaise. Blood cell and platelet counts were normal. No atypical lymphocytes were found in peripheral blood smears. Computed tomography did not detect any abnormity. Anti‐Epstein–Barr virus (EBV) antibody titres indicated a previous infection pattern of EBV, but a high amount of EBV DNA (4·4 × 105 copies per 106 white blood cells) was detected in peripheral blood mononuclear cells (PBMC). Informed consent was obtained according to the Declaration of Helsinki, and approval for the study was obtained from the Human Research Committee of Kanazawa University.

Abstract (250 words; 250 max.) Diffusion weighted magnetic resonance imaging (DW-MRI) are now widely used to assess brain integrity in clinical populations. The growing interest in mapping brain connectivity has made it vital to consider what scanning parameters affect the accuracy, stability, and signal-to-noise of Diffusion measures. Trade-offs between scan parameters can only be optimized if their effects on various commonly derived measures are better understood. To explore angular versus spatial resolution trade-offs in standard tensor-derived measures, and in measures that use the full angular information in diffusion signal, we scanned eight subjects twice, two weeks apart, using three protocols that took the same amount of time (7 minutes). Scans with 3, 2.7, 2.5mm isotropic voxels were collected using 48, 41, and 37 diffusion-sensitized gradients to equalize scan times. A specially designed DTI phantom was also scanned with the same protocols, and different b-values. We assessed how several diffusion measures including fractional anisotropy (FA), mean diffusivity (MD), and the full 3D orientation distribution function (ODF) depended on the spatial/angular resolution and the SNR. We also created maps of stability over time in the FA, MD, ODF, skeleton FA of 14 TBSS-derived ROIs, and an information uncertainty index derived from the tensor distribution function, which models the signal using a continuous mixture of tensors. In scans of the same duration, higher angular resolution and larger voxels boosted SNR and improved stability over time. The increased partial voluming in large voxels also led to bias in estimating FA, but this was partially addressed by using “beyond-tensor” models of diffusion. Keywords: High Angular Resolution Diffusion Imaging, Diffusion Tensor Imaging, Spatial Resolution, Angular Resolution, Orientation Distribution Function, Tensor Distribution Function, reproducibility

Maps of local tissue compression or expansion are often recovered by comparing MRI scans using nonlinear registration techniques. The resulting changes can be analyzed using tensor-based morphometry (TBM) to make inferences about anatomical differences. Numerous deformation techniques have been developed, although there has not been much theoretical development examining the mathematical/statistical validity of each technique. In this paper, we propose a basic principle that any registration technique should satisfy: realizing unbiased test statistics under null distribution of the displacement. In other words, any registration technique should recover zero change in the test statistic when comparing two images differing only in noise. Based on this principle, we propose a fundamental framework for the construction and analysis of image deformation. Moreover, we argue that logarithmic transform is instrumental in the analysis of deformation maps. Combined with the proposed framework, this leads to a theoretical connection between image registration and other branches of applied mathematics including information theory and grid generation.

The Alzheimer’s Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year research project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer’s disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C-11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid b (Ab) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C-11 Pittsburgh compound B PET, and CSF measurements of Ab and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI-like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD. 2010 The Alzheimer’s Association. All rights reserved.

Deficits in the connectivity between brain regions have been suggested to play a major role in the pathophysiology of schizophrenia. A functional magnetic resonance imaging (fMRI) analysis of schizophrenia was implemented using independent component analysis (ICA) to identify multiple temporally cohesive, spatially distributed regions of brain activity that represent functionally connected networks. We hypothesized that functional connectivity differences would be seen in auditory networks comprised of regions such as superior temporal gyrus as well as executive networks that consisted of frontal-parietal areas. Eight networks were found to be implicated in schizophrenia during the auditory oddball paradigm. These included a bilateral temporal network containing the superior and middle temporal gyrus; a default-mode network comprised of the posterior cingulate, precuneus, and middle frontal gyrus; and multiple dorsal lateral prefrontal cortex networks that constituted various levels of between-group differences. Highly task-related sensory networks were also found. These results indicate that patients with schizophrenia show functional connectivity differences in networks related to auditory processing, executive control, and baseline functional activity. Overall, these findings support the idea that the cognitive deficits associated with schizophrenia are widespread and that a functional connectivity approach can help elucidate the neural correlates of this disorder.