15 research outputs found

    Accurate localization of brain activity in presurgical fMRI by structure adaptive smoothing

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    An important problem of the analysis of fMRI experiments is to achieve some noise reduction of the data without blurring the shape of the activation areas. As a novel solution to this problem, the Propagation-Separation approach (PS), a structure adaptive smoothing method, has been proposed recently. PS adapts to different shapes of activation areas by generating a spatial structure corresponding to similarities and differences between time series in adjacent locations. In this paper we demonstrate how this method results in more accurate localization of brain activity. First, it is shown in numerical simulations that PS is superior over Gaussian smoothing with respect to the accurate description of the shape of activation clusters and and results in less false detections. Second, in a study of 37 presurgical planning cases we found that PS and Gaussian smoothing often yield different results, and we present examples showing aspects of the superiority of PS as applied to presurgical planning

    Independent Component Analysis of Resting State Activity in Pediatric Obsessive-Compulsive Disorder

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    Obsessive-compulsive disorder (OCD) is an often severely disabling illness with onset generally in childhood or adolescence. Little is known, however, regarding the pattern of brain resting state activity in OCD early in the course of illness. We therefore examined differences in brain resting state activity in patients with pediatric OCD compared with healthy volunteers and their clinical correlates. Twenty-three pediatric OCD patients and 23 healthy volunteers (age range 9-17), matched for sex, age, handedness, and IQ completed a resting state functional magnetic resonance imaging exam at 3T. Patients completed the Children\u27s Yale Brown Obsessive Scale. Data were decomposed into 36 functional networks using spatial group independent component analysis (ICA) and logistic regression was used to identify the components that yielded maximum group separation. Using ICA we identified three components that maximally separated the groups: a middle frontal/dorsal anterior cingulate network, an anterior/posterior cingulate network, and a visual network yielding an overall group classification of 76.1% (sensitivity=78.3% and specificity=73.9%). Independent component expression scores were significantly higher in patients compared with healthy volunteers in the middle frontal/dorsal anterior cingulate and the anterior/posterior cingulate networks, but lower in patients within the visual network. Higher expression scores in the anterior/posterior cingulate network correlated with greater severity of compulsions among patients. These findings implicate resting state fMRI abnormalities within the cingulate cortex and related control regions in the pathogenesis and phenomenology of OCD early in the course of the disorder and prior to extensive pharmacologic intervention. Hum Brain Mapp 35:5306-5315, 2014. (c) 2014 Wiley Periodicals, Inc

    Accurate Localization of Brain Activity in Presurgical fMRI by Structure Adaptive Smoothing

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    An important problem of the analysis of functional magnetic resonance imaging (fMRI) experiments is to achieve some noise reduction of the data without blurring the shape of the activation areas. As a novel solution to this problem, recently the propagation-separation (PS) approach has been proposed. PS is a structure adaptive smoothing method that adapts to different shapes of activation areas. In this paper, we demonstrate how this method results in a more accurate localization of brain activity. First, it is shown in numerical simulations that PS is superior over Gaussian smoothing with respect to the accurate description of the shape of activation clusters and results in less false detections. Second, in a study of 37 presurgical planning cases we found that PS and Gaussian smoothing often yield different results, and we present examples showing aspects of the superiority of PS as applied to presurgical planning
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