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.

Optimization of fMRI Processing Parameters for Simutaneous Acquisition of EEG/fMRI in Focal Epilepsy

In the context of focal epilepsy, the simultaneous combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) holds a great promise as a technique by which the hemodynamic correlates of interictal spikes detected on scalp EEG can be identified. The fact that traditional EEG recordings have not been able to overcome the difficulty in correlating the ictal clinical symptoms to the onset in particular areas of the lobes, brings the need of mapping with more precision the epileptogenic cortical regions. On the other hand, fMRI suggested localizations more consistent with the ictal clinical manifestations detected. This study was developed in order to improve the knowledge about the way parameters involved in the physical and mathematical data, produced by the EEG/fMRI technique processing, would influence the final results. The evaluation of the accuracy was made by comparing the BOLD results with: the high resolution EEG maps; the malformative lesions detected in the T1 weighted MR images; and the anatomical localizations of the diagnosed symptomatology of each studied patient. The optimization of the set of parameters used, will provide an important contribution to the diagnosis of epileptogenic focuses, in patients included on an epilepsy surgery evaluation program. The results obtained allowed us to conclude that: by associating the BOLD effect with interictal spikes, the epileptogenic areas are mapped to localizations different from those obtained by the EEG maps representing the electrical potential distribution across the scalp (EEG); there is an important and solid bond between the variation of particular parameters (manipulated during the fMRI data processing) and the optimization of the final results, from which smoothing, deleted volumes, HRF (used to convolve with the activation design), and the shape of the Gamma function can be certainly emphasized.

Conectividade efectiva em epilepsia

A epilepsia é uma das mais comuns patologias que afectam o cérebro humano e caracteriza-se por uma actividade cerebral oscilatória desordenada e excessiva que prejudica gravemente a qualidade de vida do doente. Com o objectivo de detectar o percurso da actividade cerebral anormal a ressonância magnética, em conjunto com a técnica de electroencefalografia (EEG) têm evoluído no sentido de tornar a identificação do foco epiléptico e respectivas vias de propagação mais clara e fácil para o neurocirurgião. Esta detecção pode recorrer ao efeito BOLD (do inglês “Blood Oxygenation Level Dependent”) para, de forma indirecta, obter um mapa de activação neuronal da zona em estudo contribuindo para uma possível intervenção cirúrgica à área epiléptica. No entanto, para chegar a uma conclusão definitiva sobre este mapa neuronal é necessário ter em conta que diferentes regiões podem apresentar HRFs (do inglês “Hemodynamic Response Functions”) diferentes, influenciando o resultado de qualquer análise se este facto não for tido em conta. Na presente dissertação foi aplicado um método de cálculo de influência causal entre regiões do cérebro humano a dados de epilepsia obtidos através da técnica EEG+fMRI. Foram utilizadas técnicas de conectividade efectiva (causalidade de Granger) usando um pacote de software (PyHRF) para estimar com precisão a HRF da região em estudo e permitir a desconvolução do sinal antes do cálculo de conectividade. Foi demonstrada a utilidade desta contribuição metodológica para a caracterização topográfica e dinâmica de uma crise epiléptica.

Clinical characteristics and outcome of patients admitted to a medico-surgical ICU requiring non invasive ventilation (NIV) for hypercapnic respiratory failure

Introduction: Because it decreases intubation rate and mortality, NIV has become first-line treatment in case of hypercapnic respiratory failure (HRF). Whether this approach is equally successful for all categories of HRF patients is however debated. We assessed if any clinical characteristics of HRF patients were associated with NIV intensity, success, and outcome, in order to identify prognostic factors. Methods: Retrospective analysis of the clinical database (clinical information system and MDSi) of patients consecutively admitted to our medico-surgical ICU, presenting with HRF (defined as PaCO2 >50 mm Hg), and receiving NIV between January 2009 and December 2010. Demographic data, medical diagnoses (including documented chronic lung disease), reason for ICU hospitalization, recent surgical interventions, SAPS II and McCabe scores were extracted from the database. Total duration of NIV and the need for tracheal intubation during the 5 days following the first hypercapnia documentation, as well as ICU and hospital mortality were recorded. Results are reported as median [IQR]. Comparisons with Chi2 or Kruskal-Wallis tests, p <0.05 (*). Results: 164 patients were included, 45 (27.4%) of whom were intubated after 10 [2-34] hours, after having received 7 [2-19] hours of NIV. NIV successful patients received 15 [5-22] hours of NIV for up to 5 days. Intubation was correlated with increased ICU (20% vs. 3%, p <0.001) and hospital (46.7% vs. 30.2, p >0.05) mortality. Conclusions: A majority of patients requiring NIV for hypercapnic respiratory failure in our ICU have no diagnosed chronic pulmonary disease. These patients tend to have increased ICUand hospital mortality. The majority of patients were non-surgical, a feature correlated with increased hospital mortality. Beside usual predictors of severity such as age and SAPS II, absence of diagnosed chronic pulmonary disease and non-operative state appear to be associated with increased mortality. Further studies should explore whether these patients are indeed more prone to an adverse outcome and which therapeutic strategies might contribute to alter this course.

El rol de las ONG de España en el internacionalización de la causa de las Damas de Blanco. Estudio de caso: Solidaridad Española con Cuba (2005-2012)

El interés de este estudio de caso es demostrar el rol de la ONG Solidaridad Española con Cuba en la creación de una red transnacional de defensa de las Damas de Blanco, un movimiento social cubano disidente. Esto, tras reconocer que el apoyo por parte de ésta y otras organizaciones e instituciones internacionales es de gran importancia para lograr las reivindicaciones sociales propuestas por las Damas de Blanco, a partir de los hechos ocurridos en la Primavera Negra en el año 2003. Tanto las organizaciones como el movimiento social, aseguran que ha existido una violación sistemática de los Derechos Humanos de los disidentes de este país, y asimismo, una opresión de sus demandas, lo que ha hecho que el apoyo internacional se convierta en la clave de un futuro cambio.

Efficient modeling and inference for event-related fMRI data

Event-related functional magnetic resonance imaging (efMRI) has emerged as a powerful technique for detecting brains' responses to presented stimuli. A primary goal in efMRI data analysis is to estimate the Hemodynamic Response Function (HRF) and to locate activated regions in human brains when specific tasks are performed. This paper develops new methodologies that are important improvements not only to parametric but also to nonparametric estimation and hypothesis testing of the HRF. First, an effective and computationally fast scheme for estimating the error covariance matrix for efMRI is proposed. Second, methodologies for estimation and hypothesis testing of the HRF are developed. Simulations support the effectiveness of our proposed methods. When applied to an efMRI dataset from an emotional control study, our method reveals more meaningful findings than the popular methods offered by AFNI and FSL. (C) 2008 Elsevier B.V. All rights reserved.

Reconhecimento de fragmentos de impressões digitais baseado em cristas e poros

Pós-graduação em Ciência da Computação - IBILCE

Spontaneous healing responses detected by cone-beam computed tomography of horizontal root fractures: a report of two cases

Horizontal root fractures (HRF) usually affect the anterior teeth as a result of trauma, and generally heal spontaneously, depending on the vitality of the pulp. Diagnosis based on clinical findings, sensitivity tests, and radiographic examination is important to determine the presence of a root fracture and to prevent a root fracture from passing unnoticed. Cone-beam computed tomography (CBCT) has been used successfully for diagnosis and prognosis imaging of root fractures and has proved to be superior to other radiographic methods. This study reports two cases of dental trauma caused by a collision and a sports accident. The patients suffered horizontal root fractures in the maxillary left central incisor and in the mandibular left central incisor. The diagnosis of root fracture was confirmed by cone-beam computed tomography (CBCT) images, which also demonstrated spontaneous healing of the fracture line. The repair occurred by interposition of connective tissue in the former case and by interposition of bone and connective tissue in the latter case. The final diagnoses of both cases were based on CBCT images, indicating the importance of a CBCT examination to reach a firm diagnosis and to follow the healing process of root fracture cases, avoiding unnecessary radical endodontic treatment.

Structure, diversity, and spatial patterns in a permanent plot of a high Restinga forest in Southeastern Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Reconhecimento de fragmentos de impressões digitais utilizando características estendidas

Com a evolução dos sensores de captura de impressões digitais e a crescente demanda por sistemas mais seguros, torna-se possível e necessário o uso de um conjunto adicional de características, tais como as cristas e os poros. Este trabalho tem como objetivo avaliar o desempenho de dois dos principais métodos de extração automática de poros, bem como o desempenho das características estendidas em situações onde apenas fragmentos das impressões digitais estão disponíveis. Resultados experimentais realizados sobre a base de dados pública PolyU HRF mostram a superioridade do método de extração de poros baseado em filtros adaptativos, em relação ao baseado em filtros isotrópicos. O reconhecimento de frag-mentos de impressões digitais utilizando características estendidas mostrou-se promissor, principalmente quando a informação das comparações de cristas é utilizada na comparação dos poros.

Nonlinear estimation of neural processing time from BOLD signal with application to decision-making

The extraction of information about neural activity timing from BOLD signal is a challenging task as the shape of the BOLD curve does not directly reflect the temporal characteristics of electrical activity of neurons. In this work, we introduce the concept of neural processing time (NPT) as a parameter of the biophysical model of the hemodynamic response function (HRF). Through this new concept we aim to infer more accurately the duration of neuronal response from the highly nonlinear BOLD effect. The face validity and applicability of the concept of NPT are evaluated through simulations and analysis of experimental time series. The results of both simulation and application were compared with summary measures of HRF shape. The experiment that was analyzed consisted of a decision-making paradigm with simultaneous emotional distracters. We hypothesize that the NPT in primary sensory areas, like the fusiform gyrus, is approximately the stimulus presentation duration. On the other hand, in areas related to processing of an emotional distracter, the NPT should depend on the experimental condition. As predicted, the NPT in fusiform gyrus is close to the stimulus duration and the NPT in dorsal anterior cingulate gyrus depends on the presence of an emotional distracter. Interestingly, the NPT in right but not left dorsal lateral prefrontal cortex depends on the stimulus emotional content. The summary measures of HRF obtained by a standard approach did not detect the variations observed in the NPT. Hum Brain Mapp, 2012. (C) 2010 Wiley Periodicals, Inc.

Structure and function in primary open angle glaucoma

The study utilised a Normal group, an Ocular Hypertensive (OHT) group and a Primary Open Angle Glaucoma (POAG) group to investigate two aspects. Firstly, the within- and between-visit variability for stereometric measurements of the optic nerve head (ONH) using the Heidelberg Retina Tomograph (HRT); retinal nerve fibre layer (RNFL) thickness using the HRT and using optical coherence tomography with the Optical Coherence Tomography Scanner (OCT); the visual field using white-on-white (W-W), short-wavelength (SWAP) and Frequency Doubling perimetry (FDT); and retinal haemodynamics using the Heidelberg Retinal Flowmeter (HRF). Secondly, the association demonstrated between some of the derived variables. The within- and between-visit variability for stereometric measurements of the entire ONH and the between-visit variability for sectoral measurements were similar for Normals and OHTs but greater for POAGs. The within-visit variability of the visual field pointwise parameters for SWAP were greater than for W-W and FDT particularly with increase in eccentricity and for the OHT group. The between-visit variability increased with increase in defect depth for the POAG group, across all types of perimetry. The MS was greater, the MD and PSD smaller and the examination duration shorter in FDT compared to W-W and SWAP across all groups. The within-visit variability was less than the between-visit variability for the OCT circumferential and sector RNFL thickness using the 1.5R, 2.0R and the fixed 1.73mm circular scan radii, across the three groups. The variability increased with decrease in the RNFL thickness, and was least for the 2.0R scan radius.

Parcellation of fMRI datasets with ICA and PLS: a data driven approach

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.