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.

The Stability of the Blood Oxygenation Level-Dependent Functional MRI Response to Motor Tasks Is Altered in Patients With Chronic Ischemic Stroke

Background and Purpose-Functional MRI is a powerful tool to investigate recovery of brain function in patients with stroke. An inherent assumption in functional MRI data analysis is that the blood oxygenation level-dependent (BOLD) signal is stable over the course of the examination. In this study, we evaluated the validity of such assumption in patients with chronic stroke. Methods-Fifteen patients performed a simple motor task with repeated epochs using the paretic and the unaffected hand in separate runs. The corresponding BOLD signal time courses were extracted from the primary and supplementary motor areas of both hemispheres. Statistical maps were obtained by the conventional General Linear Model and by a parametric General Linear Model. Results-Stable BOLD amplitude was observed when the task was executed with the unaffected hand. Conversely, the BOLD signal amplitude in both primary and supplementary motor areas was progressively attenuated in every patient when the task was executed with the paretic hand. The conventional General Linear Model analysis failed to detect brain activation during movement of the paretic hand. However, the proposed parametric General Linear Model corrected the misdetection problem and showed robust activation in both primary and supplementary motor areas. Conclusions-The use of data analysis tools that are built on the premise of a stable BOLD signal may lead to misdetection of functional regions and underestimation of brain activity in patients with stroke. The present data urge the use of caution when relying on the BOLD response as a marker of brain reorganization in patients with stroke. (Stroke. 2010; 41:1921-1926.)

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

Increased rates of white matter hyperintensities in late-onset bipolar disorder

Objectives: Magnetic resonance imaging (MRI) studies have reported an increased frequency of white matter hyperintensities (WMH) in association with late-onset (LO) depression, and this has supported the notion that vascular-related mechanisms may be implicated in the pathophysiology of LO mood disorders. Recent clinical studies have also suggested a link between LO bipolar disorder (LO-BD) and cerebrovascular risk factors, but this has been little investigated with neuroimaging techniques. In order to ascertain whether there could be a specific association between WMH and LO-BD, we directly compared WMH rates between LO-BD subjects (illness onset 60 years), early-onset BD subjects (EO-BD, illness onset < 60 years), and elderly healthy volunteers. Methods: T2-weighted MRI data were acquired in LO-BD subjects (n = 10, age = 73.60 +/- 4.09), EO-BD patients (n = 49, age = 67.78 +/- 4.44), and healthy subjects (n = 24, age = 69.00 +/- 7.22). WMH rates were assessed using the Scheltens scale. Results: There was a greater prevalence of WMH in LO-BD patients relative to the two other groups in the deep parietal region (p = 0.018) and basal ganglia (p < 0.045). When between-group comparisons of mean WMH scores were conducted taking account of age differences (ANCOVA), there were more severe scores in LO-BD patients relative to the two other groups in deep frontal and parietal regions, as well as in the putamen (p < 0.05). Conclusions: Our results provide empirical support to the proposed link between vascular risk factors and LO-BD. If extended in future studies with larger samples, these. findings may help to clarify the pathophysiological distinctions between bipolar disorder emerging at early and late stages of life.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Lateral ventricle differences between first-episode schizophrenia and first-episode psychotic bipolar disorder: A population-based morphometric MRI study

Objectives. The extent to which psychotic disorders fall into distinct diagnostic categories or can be regarded as lying on a single continuum is controversial. We compared lateral ventricle volumes between a large sample of patients with first-episode schizophrenia or bipolar disorder and a healthy control group from the same neighbourhood. Methods. Population-based MRI study with 88 first-episode psychosis (FEP) patients, grouped into those with schizophrenia/schizophreniform disorder (N = 62), bipolar disorder (N = 26) and 94 controls. Results. Right and left lateral ventricular and right temporal horn volumes were larger in FEP subjects than controls. Within the FEP sample, post-hoc tests revealed larger left lateral ventricles and larger right and left temporal horns in schizophrenia subjects relative to controls, while there was no difference between patients with bipolar disorder and controls. None of the findings was attributable to effects of antipsychotics. Conclusions. This large-sample population-based MRI study showed that neuroanatomical abnormalities in subjects with schizophrenia relative to controls from the same neighbourhood are evident at the first episode of illness, but are not detectable in bipolar disorder patients. These data are consistent with a model of psychosis in which early brain insults of neurodevelopmental origin are more relevant to schizophrenia than to bipolar disorder.

An MRI-based approach for the measurement of the dorsolateral prefrontal cortex in humans

The dorsolateral prefrontal cortex (DLPFC) has been implicated in the pathophysiology of mental disorders. Previous region-of-interest MRI studies that attempted to delineate this region adopted various landmarks and measurement techniques, with inconsistent results. We developed a new region-of-interest measurement method to obtain morphometric data of this region from structural MRI scans, taking into account knowledge from cytoarchitectonic postmortem studies and the large inter-individual variability of this region. MRI scans of 10 subjects were obtained, and DLPFC tracing was performed in the coronal plane by two independent raters using the semi-automated software Brains2. The intra-class correlation coefficients between two independent raters were 0.94 for the left DLPFC and 0.93 for the right DLPFC. The mean +/- S.D. DLPFC volumes were 9.23 +/- 2.35 ml for the left hemisphere and 8.20 +/- 2.08 ml for the right hemisphere. Our proposed method has high inter-rater reliability and is easy to implement, permitting the standardized measurement of this region for clinical research applications. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Congenital Bilateral Perisylvian Syndrome: Familial Occurrence, Clinical and Psycholinguistic Aspects Correlated with MRI

Objective: Congenital bilateral perisylvian syndrome (CBPS) is frequently caused by polymicrogyria (PMG). The aim of this study was to correlate the clinical and psycholinguistic aspects with neuroradiological data of patients with CBPS. Methods: Thirty-one patients were studied. We performed a clinical investigation of the patients and their families, including MRI scanning, neuropsychological tests and language evaluation. Results: The statistical analysis showed that: a) prenatal events are associated with the non-familial type of PMG; b) diffuse PMG is associated with pseudobulbar signs, as opposed to BPPP; c) motor deficit is associated with diffuse PMG; d) epilepsy is equally present in patients with both familial or non-familial PMG, but is more frequently seen in patients with diffuse PMG; e) dyslexia and SLI can be a feature of both the diffuse or BPPP, and either familial or sporadic cases of PMG. Conclusions: The severity of clinical manifestations in CBPS is correlated with the extent of cortical involvement. Most patients with CBPS have a history of speech delay or language difficulties and no epilepsy. Dyslexia can be found in patients with PMG.

Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data

We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.

Inflammation markers in healthy and periodontitis patients: a preliminary data screening

Advances in diagnostic research are moving towards methods whereby the periodontal risk can be identified and quantified by objective measures using biomarkers. Patients with periodontitis may have elevated circulating levels of specific inflammatory markers that can be correlated to the severity of the disease. The purpose of this study was to evaluate whether differences in the serum levels of inflammatory biomarkers are differentially expressed in healthy and periodontitis patients. Twenty-five patients (8 healthy patients and 17 chronic periodontitis patients) were enrolled in the study. A 15 mL blood sample was used for identification of the inflammatory markers, with a human inflammatory flow cytometry multiplex assay. Among 24 assessed cytokines, only 3 (RANTES, MIG and Eotaxin) were statistically different between groups (p<0.05). In conclusion, some of the selected markers of inflammation are differentially expressed in healthy and periodontitis patients. Cytokine profile analysis may be further explored to distinguish the periodontitis patients from the ones free of disease and also to be used as a measure of risk. The present data, however, are limited and larger sample size studies are required to validate the findings of the specific biomarkers.

Hydrometeor and latent heat profiles of tropical cyclones Conson, Ivan and Catarina using PR/TRMM data

ABSTRACT Microphysical and thermodynamical features of two tropical systems, namely Hurricane Ivan and Typhoon Conson, and one sub-tropical, Catarina, have been analyzed based on space-born radar PR measurements available on the TRMM satellite. The procedure to classify the reflectivity profiles followed the Heymsfield et al (2000) and Steiner et al (1995) methodologies. The water and ice content have been calculated using a relationship obtained with data of the surface SPOL radar and PR in Rondonia State in Brazil. The diabatic heating rate due to latent heat release has been estimated using the methodology developed by Tao et al (1990). A more detailed analysis has been performed for Hurricane Catarina, the first of its kind in South Atlantic. High water content mean value has been found in Conson and Ivan at low levels and close to their centers. Results indicate that hurricane Catarina was shallower than the other two systems, with less water and the water was concentrated closer to its center. The mean ice content in Catarina was about 0.05 g kg-1 while in Conson it was 0.06 g kg-1 and in Ivan 0.08 g kg-1. Conson and Ivan had water content up to 0.3 g kg-1 above the 0ºC layer, while Catarina had less than 0.15 g kg-1. The latent heat released by Catarina showed to be very similar to the other two systems, except in the regions closer to the center.

A new genus and two new species of Stevardiinae (Characiformes: Characidae) with a hypothesis on their relationships based on morphological and histological data

Lepidocharax, new genus, and Lepidocharax diamantina and L. burnsi new species from eastern Brazil are described herein. Lepidocharax is considered a monophyletic genus of the Stevardiinae and can be distinguished from the other members of this subfamily except Planaltina, Pseudocorynopoma, and Xenurobrycon by having the dorsal-fin origin vertically aligned with the anal-fin origin, vs. dorsal fin origin anterior or posterior to anal-fin origin. Additionally the new genus can be distinguished from those three genera by not having the scales extending over the ventral caudal-fin lobe modified to form the dorsal border of the pheromone pouch organ or to represent a pouch scale in sexually mature males. In this paper, we describe these two recently discovered species and the ultrastructure of their spermatozoa.

Natural history and population data of fishes in caves of the Serra do Ramalho karst area, Middle São Francisco basin, northeastern Brazil

During the exploration and mapping of new caves in Serra do Ramalho karst area, southern Bahia state, cavers from the Grupo Bambuí de Pesquisas Espeleológicas - GBPE (Belo Horizonte) noticed the presence of troglomorphic catfishes (species with reduced eyes and/or melanic pigmentation), which we intensively investigated with regards to their ecology and behavior since 2005. Non-troglomorphic fishes regularly found in the studied caves were included in this investigation. We present here data on the natural history of two troglobitic (exclusively subterranean troglomorphic species) fishes - Rhamdia enfurnada Bichuette & Trajano, 2005 (Heptapteridae; Gruna do Enfurnado) and Trichomycterus undescribed species (Trichomycteridae; Lapa dos Peixes and Gruna da Água Clara), and non-troglomorphic Hoplias cf. malabaricus, probably a troglophile (able to form populations both in epigean and subterranean habitats) in the Gruna do Enfurnado, and Pimelodella sp., a species with a sink population in the Lapa dos Peixes.

The impact of spatial data redundancy on SOLAP query performance

Geographic Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis, and the literature proposes several conceptual and logical data models for GDW. However, little effort has been focused on studying how spatial data redundancy affects SOLAP (Spatial On-Line Analytical Processing) query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. We also analyze the issue of indexing, aiming at improving SOLAP query performance on a redundant GDW. Comparisons of the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicate that the SB-index significantly improves the elapsed time in query processing from 25% up to 99% with regard to SOLAP queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. We also investigate the impact of the increase in data volume on the performance. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Performance tests also show that the SB-index is far more compact than the star-join, requiring only a small fraction of at most 0.20% of the volume. Moreover, we propose a specific enhancement of the SB-index to deal with spatial data redundancy. This enhancement improved performance from 80 to 91% for redundant GDW schemas.