Automated Hippocampal Segmentation by Regional Fluid Registration of Serial MRI: Validation and Application in Alzheimer.s Disease

The application of voxel-level three-dimensional registration to serial magnetic resonance imaging (MRI) is described. This fluid registration determines deformation fields modeling brain change, which are consistent with a model describing a viscous fluid. The objective was to validate the measurement of hippocampal volumetric change by fluid registration in Alzheimer's disease (AD) against current methodologies. The hippocampus was chosen for this study because it is difficult to measure reproducibly by manual segmentation and is widely studied; however, the technique is applicable to any structure which can be delineated on a scan. First, suitable values for the viscosity-body-force-ratio, alpha (0.01), and the number of iterations (300), were established and the convergence, repeatability, linearity, and accuracy investigated and compared with expert manual segmentation. A simple model of hippocampal atrophy was used to compare simulated volumetric change against that obtained by fluid registration. Finally the serial segmentation was compared with the current gold standard technique-expert human labeling with a volume repeatability of similar to4%-in 27 subjects (15 normal controls, 12 clinically diagnosed with Alzheimer's disease). The scan-rescan volumetric consistency of serial segmentation by fluid-registration was shown to be superior to human serial segmentors (similar to2%). The mean absolute volume difference between fluid and manual segmentation was 0.7%. Fluid registration has potential importance for tracking longitudinal structural changes in brain particularly in the context of the clinical trial where large numbers of subjects may have multiple MR scans. (C) 2001 Academic Press

How European Union Membership Can Undermine the Rule of Law in Emerging Democracies

The European Union views the spread of economic prosperity and rule of law to countries emerging from dictatorship as among its primary goals when considering countries as candidates for membership. Existing literature often suggests that EU membership confers significant benefits on the accession countries, and these countries are willing to undergo costly and difficult reforms to reap these benefits. Through strict membership conditions, member states force accession countries to commit to democracy. Drawing on theoretical work in the fields of law, politics, and economics, this article reassesses the conventional wisdom. It argues that, under certain conditions, the reforms required of would-be members could have the perverse effect of undermining the establishment of legitimate law in transitional democracies. Using an agent-based model, the article elucidates a theory in which placing laws on the books around which no societal consensus exists can create perverse incentives for citizens and government officials and may lead to an erosion of the rule of law

Association between white matter hyperintensities, cortical volumes, and late-onset epilepsy

ObjectiveTo identify the association between brain vascular changes and cortical volumes on MRI and late-onset epilepsy.MethodsIn 1993-1995, 1,920 participants (median age 62.7, 59.9% female) in the community-based Atherosclerosis Risk in Communities (ARIC) Study underwent MRI, and white matter hyperintensities were measured. In addition, in 2011-2013, 1,964 ARIC participants (median age 72.4, 61.1% female) underwent MRI, and cortical volumes and white matter hyperintensities were measured. We identified cases of late-onset epilepsy (starting at age 60 or later) from ARIC hospitalization records and Medicare claims data. Using the 1993-1995 MRI, we evaluated the association between white matter hyperintensities and subsequent epilepsy using survival analysis. We used the 2011-2013 MRI to conduct cross-sectional logistic regression to examine the association of cortical volumes and white matter hyperintensities with late-onset epilepsy. All models were adjusted for demographics, hypertension, diabetes, smoking, and APOE ϵ4 allele status.ResultsNinety-seven ARIC participants developed epilepsy after having an MRI in 1993-1995 (incidence 3.34 per 1,000 person-years). The degree of white matter hyperintensities measured at ages 49-72 years was associated with the risk of late-onset epilepsy (hazard ratio 1.27 per age-adjusted SD, 95% confidence interval [CI] 1.06-1.54). Lower cortical volume scores were associated cross-sectionally with higher odds of late-onset epilepsy (odds ratio 1.87, 95% CI 1.16-3.02) per age-adjusted SD.ConclusionsThis study demonstrates associations between earlier-life white matter hyperintensities on MRI and later-life incident epilepsy, and between cortical volumes measured later in life and late-onset epilepsy. These findings may help illuminate the causes of late-onset epilepsy

Multi-Phase Feature Representation Learning for Neurodegenerative Disease Diagnosis

Feature learning with high dimensional neuroimaging features has been explored for the applications on neurodegenerative diseases. Low-dimensional biomarkers, such as mental status test scores and cerebrospinal fluid level, are essential in clinical diagnosis of neurological disorders, because they could be simple and effective for the clinicians to assess the disorder’s progression and severity. Rather than only using the low-dimensional biomarkers as inputs for decision making systems, we believe that such low-dimensional biomarkers can be used for enhancing the feature learning pipeline. In this study, we proposed a novel feature representation learning framework, Multi-Phase Feature Representation (MPFR), with low-dimensional biomarkers embedded. MPFR learns high-level neuroimaging features by extracting the associations between the low-dimensional biomarkers and the high-dimensional neuroimaging features with a deep neural network. We validated the proposed framework using the Mini-Mental-State-Examination (MMSE) scores as a low-dimensional biomarker and multi-modal neuroimaging data as the high-dimensional neuroimaging features from the ADNI baseline cohort. The proposed approach outperformed the original neural network in both binary and ternary Alzheimer’s disease classification tasks

T-Duality and Penrose limits of spatially homogeneous and inhomogeneous cosmologies

Penrose limits of inhomogeneous cosmologies admitting two abelian Killing vectors and their abelian T-duals are found in general. The wave profiles of the resulting plane waves are given for particular solutions. Abelian and non-abelian T-duality are used as solution generating techniques. Furthermore, it is found that unlike in the case of abelian T-duality, non-abelian T-duality and taking the Penrose limit are not commutative procedures.Comment: 16 pages, 4 figures. Discussion on non-abelian T-duality expande

Prospective Analysis of Leisure-Time Physical Activity in Midlife and Beyond and Brain Damage on MRI in Older Adults

OBJECTIVE: To test the hypothesis that greater levels of leisure-time moderate to vigorous intensity physical activity (MVPA) in midlife or late life are associated with larger gray matter volumes, less white matter disease, and fewer cerebrovascular lesions measured in late life, we utilized data from 1,604 participants enrolled in the Atherosclerosis Risk in Communities study. METHODS: Leisure-time MVPA was quantified using a past-year recall, interviewer-administered questionnaire at baseline and 25 years later and classified as none, low, middle, and high at each time point. The presence of cerebrovascular lesions, white matter hyperintensities (WMH), white matter integrity (mean fractional anisotropy [FA] and mean diffusivity [MD]), and gray matter volumes were quantified with 3T MRI in late life. The odds of cerebrovascular lesions were estimated with logistic regression. Linear regression estimated the mean differences in WMH, mean FA and MD, and gray matter volumes. RESULTS: Among 1,604 participants (mean age 53 years, 61% female, 27% Black), 550 (34%), 176 (11%), 250 (16%), and 628 (39%) reported no, low, middle, and high MVPA in midlife, respectively. Compared to no MVPA in midlife, high MVPA was associated with more intact white matter integrity in late life (mean FA difference 0.13 per SD [95% confidence interval (CI) 0.004, 0.26]; mean MD difference -0.11 per SD [95% CI -0.21, -0.004]). High MVPA in midlife was also associated with a lower odds of lacunar infarcts (odds ratio 0.68, 95% CI 0.46, 0.99). High MVPA was not associated with gray matter volumes. High MVPA compared to no MVPA in late life was associated with most brain measures. CONCLUSION: Greater levels of physical activity in midlife may protect against cerebrovascular sequelae in late life

An action for the exact string black hole

A local action is constructed describing the exact string black hole discovered by Dijkgraaf, Verlinde and Verlinde in 1992. It turns out to be a special 2D Maxwell-dilaton gravity theory, linear in curvature and field strength. Two constants of motion exist: mass M>1, determined by the level k, and U(1)-charge Q>0, determined by the value of the dilaton at the origin. ADM mass, Hawking temperature T_H \propto \sqrt{1-1/M} and Bekenstein-Hawking entropy are derived and studied in detail. Winding/momentum mode duality implies the existence of a similar action, arising from a branch ambiguity, which describes the exact string naked singularity. In the strong coupling limit the solution dual to AdS_2 is found to be the 5D Schwarzschild black hole. Some applications to black hole thermodynamics and 2D string theory are discussed and generalizations - supersymmetric extension, coupling to matter and critical collapse, quantization - are pointed out.Comment: 41 pages, 2 eps figures, dedicated to Wolfgang Kummer on occasion of his Emeritierung; v2: added ref; v3: extended discussion in sections 3.2, 3.3 and at the end of 5.3 by adding 2 pages of clarifying text; updated refs; corrected typo

Phenomenology of flavor-mediated supersymmetry breaking

The phenomenology of a new economical SUSY model that utilizes dynamical SUSY breaking and gauge-mediation (GM) for the generation of the sparticle spectrum and the hierarchy of fermion masses is discussed. Similarities between the communication of SUSY breaking through a messenger sector, and the generation of flavor using the Froggatt-Nielsen (FN) mechanism are exploited, leading to the identification of vector-like messenger fields with FN fields, and the messenger U(1) as a flavor symmetry. An immediate consequence is that the first and second generation scalars acquire flavor-dependent masses, but do not violate FCNC bounds since their mass scale, consistent with effective SUSY, is of order 10 TeV. We define and advocate a minimal flavor-mediated model (MFMM), recently introduced in the literature, that successfully accommodates the small flavor-breaking parameters of the standard model using order one couplings and ratios of flavon field vevs. The mediation of SUSY breaking occurs via two-loop log-enhanced GM contributions, as well as several one-loop and two-loop Yukawa-mediated contributions for which we provide analytical expressions. The MFMM is parameterized by a small set of masses and couplings, with values restricted by several model constraints and experimental data. The next-to-lightest sparticle (NLSP) always has a decay length that is larger than the scale of a detector, and is either the lightest stau or the lightest neutralino. Similar to ordinary GM models, the best collider search strategies are, respectively, inclusive production of at least one highly ionizing track, or events with many taus plus missing energy. In addition, D^0 - \bar{D}^0 mixing is also a generic low energy signal. Finally, the dynamical generation of the neutrino masses is briefly discussed.Comment: 54 pages, LaTeX, 8 figure

Central arterial stiffness is associated with structural brain damage and poorer cognitive performance: The ARIC study

Background Central arterial stiffening and increased pulsatility, with consequent cerebral hypoperfusion, may result in structural brain damage and cognitive impairment. Methods and Results We analyzed a cross‐sectional sample of ARIC‐NCS(Atherosclerosis Risk in Communities–Neurocognitive Study) participants (aged 67–90 years, 60% women) with measures of cognition (n=3703) and brain magnetic resonance imaging (n=1255). Central arterial hemodynamics were assessed as carotid‐femoral pulse wave velocity and pressure pulsatility (central pulse pressure). We derived factor scores for cognitive domains. Brain magnetic resonance imaging using 3‐Tesla scanners quantified lacunar infarcts; cerebral microbleeds; and volumes of white matter hyperintensities, total brain, and the Alzheimer disease signature region. We used logistic regression, adjusted for demographics, apolipoprotein E ɛ4, heart rate, mean arterial pressure, and select cardiovascular risk factors, to estimate the odds of lacunar infarcts or cerebral microbleeds. Linear regression, additionally adjusted for intracranial volume, estimated the difference in log‐transformed volumes of white matter hyperintensities, total brain, and the Alzheimer diseasesignature region. We estimated the mean difference in cognitive factor scores across quartiles of carotid‐femoral pulse wave velocity or central pulse pressure using linear regression. Compared with participants in the lowest carotid‐femoral pulse wave velocity quartile, participants in the highest quartile of carotid‐femoral pulse wave velocity had a greater burden of white matter hyperintensities (P=0.007 for trend), smaller total brain volumes (−18.30 cm 3 ; 95% CI, −27.54 to −9.07 cm 3 ), and smaller Alzheimer disease signature region volumes (−1.48 cm 3 ; 95% CI, −2.27 to −0.68 cm 3 ). These participants also had lower scores in executive function/processing speed (β=−0.04 z score; 95% CI, −0.07 to −0.01 z score) and general cognition (β=−0.09 z score; 95% CI, −0.15 to −0.03 z score). Similar results were observed for central pulse pressure. Conclusions Central arterial hemodynamics were associated with structural brain damage and poorer cognitive performance among older adults

A Bayesian Nonparametric Regression Model With Normalized Weights - A Study of Hippocampal Atrophy in Alzheimer’s Disease

Hippocampal volume is one of the best established biomarkers for Alzheimer’s disease. However, for appropriate use in clinical trials research, the evolution of hippocampal volume needs to be well understood. Recent theoretical models propose a sigmoidal pattern for its evolution. To support this theory, the use of Bayesian nonparametric regression mixture models seems particularly suitable due to the flexibility that models of this type can achieve and the unsatisfactory predictive properties of semiparametric methods. In this article, our aim is to develop an interpretable Bayesian nonparametric regression model which allows inference with combinations of both continuous and discrete covariates, as required for a full analysis of the dataset. Simple arguments regarding the interpretation of Bayesian nonparametric regression mixtures lead naturally to regression weights based on normalized sums. Difficulty in working with the intractable normalizing constant is overcome thanks to recent advances in MCMC methods and the development of a novel auxiliary variable scheme. We apply the new model and MCMC method to study the dynamics of hippocampal volume, and our results provide statistical evidence in support of the theoretical hypothesis