Nonlinear Interactions in a Piezoceramic Bar Transducer Powered by a Vacuum Tube Generated by a Nonideal Source

Interactions between the oscillations of piezoceramic transducer and the mechanism of as excitation-the generator of the electric current of limited power-supply-are analyzed in this paper In practical situations, the dynamics of the forcing function on a vibrating system cannot be considered as given a priori, and it must be taken as a consequence of the dynamics of the whole system. In other words, the forcing source has limited power as that provided by a dc motor for an example, and thus its own dynamics is influenced by that of the vibrating system being forced. This increases the number of degrees of freedom of the problem, and it is called a nonideal problem. In this work, we present certain phenomena as Sommerfeld effect, jump, saturation, and stability, through the influences of the parameters of the governing equations motion. [DOI: 10.1115/1.3007909]

Strategies for genetic model specification in the screening of genome-wide meta-analysis signals for further replication

Background Meta-analysis is increasingly being employed as a screening procedure in large-scale association studies to select promising variants for follow-up studies. However, standard methods for meta-analysis require the assumption of an underlying genetic model, which is typically unknown a priori. This drawback can introduce model misspecifications, causing power to be suboptimal, or the evaluation of multiple genetic models, which augments the number of false-positive associations, ultimately leading to waste of resources with fruitless replication studies. We used simulated meta-analyses of large genetic association studies to investigate naive strategies of genetic model specification to optimize screenings of genome-wide meta-analysis signals for further replication. Methods Different methods, meta-analytical models and strategies were compared in terms of power and type-I error. Simulations were carried out for a binary trait in a wide range of true genetic models, genome-wide thresholds, minor allele frequencies (MAFs), odds ratios and between-study heterogeneity (tau(2)). Results Among the investigated strategies, a simple Bonferroni-corrected approach that fits both multiplicative and recessive models was found to be optimal in most examined scenarios, reducing the likelihood of false discoveries and enhancing power in scenarios with small MAFs either in the presence or in absence of heterogeneity. Nonetheless, this strategy is sensitive to tau(2) whenever the susceptibility allele is common (MAF epsilon 30%), resulting in an increased number of false-positive associations compared with an analysis that considers only the multiplicative model. Conclusion Invoking a simple Bonferroni adjustment and testing for both multiplicative and recessive models is fast and an optimal strategy in large meta-analysis-based screenings. However, care must be taken when examined variants are common, where specification of a multiplicative model alone may be preferable.

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.

Association between symptom severity and internal capsule volume in obsessive-compulsive disorder

Neurobiological models support an involvement of white matter tracts in the pathophysiology of obsessive-compulsive disorder (OCD), but there has been little systematic evaluation of white matter volumes in OCD using magnetic resonance imaging (MRI). We investigated potential differences in the volume of the cingulum bundle (CB) and anterior limb of internal capsule (ALIC) in OCD patients (n = 19) relative to asymptomatic control subjects (n = 15). White matter volumes were assessed using a 1.5T MRI scanner. Between-group comparisons were carried out after spatial normalization and image segmentation using optimized voxel-based morphometry. Correlations between regional white matter volumes in OCD subjects and symptom severity ratings were also investigated. We found significant global white matter reductions in OCD patients compared to control subjects. The voxel-based search for regional abnormalities (with covariance for total white matter volumes) showed no specific white matter volume deficits in brain portions predicted a priori to be affected in OCD (CB and ALIC). However, large clusters of significant positive correlation with OCD severity scores were found bilaterally on the ALIC. These findings provide evidence of OCD-related ALIC abnormalities and suggest a connectivity dysfunction within frontal-striatal-thalamic-cortical circuits. Further studies are warranted to better define the role of such white matter alterations in the pathophysiology of OCD, and may provide clues for a more effectively targeting of neurosurgical treatments for OCD. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Gamma ventral capsulotomy for treatment of resistant obsessive-compulsive disorder: A structural MRI pilot prospective study

Objective: The purpose of this study was to investigate regional structural abnormalities in the brains of five patients with refractory obsessive-compulsive disorder (OCD) submitted to gamma ventral capsulotomy. Methods: We acquired morphometric magnetic resonance imaging (MRI) data before and after 1 year of radiosurgery using a 1.5-T MRI scanner. Images were spatially normalized and segmented using optimized voxel-based morphometry (VBM) methods. Voxelwise statistical comparisons between pre- and post-surgery MRI scans were performed using a general linear model. Findings in regions predicted a priori to show volumetric changes (orbitofrontal cortex, anterior cingulate gyrus, basal ganglia and thalamus) were reported as significant if surpassing a statistical threshold of p<0.001 (uncorrected for multiple comparisons). Results: We detected a significant regional postoperative increase in gray matter volume in the right inferior frontal gyri (Brodmann area 47, BA47) when comparing all patients pre and postoperatively. Conclusions: Our results support the current theory of frontal-striatal-thalamic-cortical (FSTC) circuitry involvement in OCD pathogenesis. Gamma ventral capsulotomy is associated with neurobiological changes in the inferior orbitofrontal cortex in refractory OCD patients. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

Reduced gray matter volume in ventral prefrontal cortex but not amygdala in bipolar disorder: Significant effects of gender and trait anxiety

Neuroimaging studies in bipolar disorder report gray matter volume (GMV) abnormalities in neural regions implicated in emotion regulation. This includes a reduction in ventral/orbital medial prefrontal cortex (OMPFC) GMV and, inconsistently, increases in amygdala GMV. We aimed to examine OMPFC and amygdala GMV in bipolar disorder type 1 patients (BPI) versus healthy control participants (HC), and the potential confounding effects of gender, clinical and illness history variables and psychotropic medication upon any group differences that were demonstrated in OMPFC and amygdala GMV Images were acquired from 27 BPI (17 euthymic, 10 depressed) and 28 age- and gender-matched HC in a 3T Siemens scanner. Data were analyzed with SPM5 using voxel-based morphometry (VBM) to assess main effects of diagnostic group and gender upon whole brain (WB) GMV. Post-hoc analyses were subsequently performed using SPSS to examine the extent to which clinical and illness history variables and psychotropic medication contributed to GMV abnormalities in BPI in a priori and non-a priori regions has demonstrated by the above VBM analyses. BPI showed reduced GMV in bilateral posteromedial rectal gyrus (PMRG), but no abnormalities in amygdala GMV. BPI also showed reduced GMV in two non-a priori regions: left parahippocampal gyrus and left putamen. For left PMRG GMV, there was a significant group by gender by trait anxiety interaction. GMV was significantly reduced in male low-trait anxiety BPI versus male low-trait anxiety HC, and in high-versus low-trait anxiety male BPI. Our results show that in BPI there were significant effects of gender and trait-anxiety, with male BPI and those high in trait-anxiety showing reduced left PMRG GMV. PMRG is part of medial prefrontal network implicated in visceromotor and emotion regulation. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

Whole-Brain Voxel-Based Morphometry in Kallmann Syndrome Associated with Mirror Movements

BACKGROUND AND PURPOSE: There are 2 main hypotheses concerning the cause of mirror movements (MM) in Kallmann syndrome (KS): abnormal development of the primary motor system, involving the ipsilateral corticospinal tract, and lack of contralateral motor cortex inhibitory mechanisms, mainly through the corpus callosum. The purpose of our study was to determine white and gray matter volume changes in a KS population by using optimized voxel-based morphometry (VBM) and to investigate the relationship between the abnormalities and the presence of MM, addressing the 2 mentioned hypotheses. MATERIALS AND METHODS: T1-weighted volumetric images from 21 patients with KS and 16 matched control subjects were analyzed with optimized VBM. Images were segmented and spatially normalized, and these deformation parameters were then applied to the original images before the second segmentation. Patients were divided into groups with and without MM, and a t test statistic was then applied on a voxel-by-voxel basis between the groups and controls to evaluate significant differences. RESULTS: When considering our hypothesis a priori, we found that 2 areas of increased gray matter volume, in the left primary motor and sensorimotor cortex, were demonstrated only in patients with MM, when compared with healthy controls. Regarding white matter alterations, no areas of altered volume involving the corpus callosum or the projection of the corticospinal tract were demonstrated. CONCLUSION: The VBM study did not show significant white matter changes in patients with KS but showed gray matter alterations in keeping with a hypertrophic response to a deficient pyramidal decussation in patients with MM. In addition, gray matter alterations were observed in patients without MM, which can represent more complex mechanisms determining the presence or absence of this symptom.

Detection of Auditory Cortex Activity by fMRI Using a Dependent Component Analysis

Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.