PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI.

PubMed

Huang, Huiyuan; Ding, Zhongxiang; Mao, Dewang; Yuan, Jianhua; Zhu, Fangmei; Chen, Shuda; Xu, Yan; Lou, Lin; Feng, Xiaoyan; Qi, Le; Qiu, Wusi; Zhang, Han; Zang, Yu-Feng

2016-10-01

The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.

Real-Time fMRI Pattern Decoding and Neurofeedback Using FRIEND: An FSL-Integrated BCI Toolbox

PubMed Central

Sato, João R.; Basilio, Rodrigo; Paiva, Fernando F.; Garrido, Griselda J.; Bramati, Ivanei E.; Bado, Patricia; Tovar-Moll, Fernanda; Zahn, Roland; Moll, Jorge

2013-01-01

The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI)-based neurofeedback emerged as a promising method, given its superior spatial resolution and ability to gauge deep cortical and subcortical brain regions. In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM), fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. Expansion in this field and its applications critically depend on the existence of freely available, integrated and user-friendly tools for the neuroimaging research community. Here, we introduce FRIEND, a graphic-oriented user-friendly interface package for fMRI neurofeedback and real-time multivoxel pattern decoding. The package integrates routines for image preprocessing in real-time, ROI-based feedback (single-ROI BOLD level and functional connectivity) and brain decoding-based feedback using SVM. FRIEND delivers an intuitive graphic interface with flexible processing pipelines involving optimized procedures embedding widely validated packages, such as FSL and libSVM. In addition, a user-defined visual neurofeedback module allows users to easily design and run fMRI neurofeedback experiments using ROI-based or multivariate classification approaches. FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available. PMID:24312569

Potential pitfalls when denoising resting state fMRI data using nuisance regression.

PubMed

Bright, Molly G; Tench, Christopher R; Murphy, Kevin

2017-07-01

In resting state fMRI, it is necessary to remove signal variance associated with noise sources, leaving cleaned fMRI time-series that more accurately reflect the underlying intrinsic brain fluctuations of interest. This is commonly achieved through nuisance regression, in which the fit is calculated of a noise model of head motion and physiological processes to the fMRI data in a General Linear Model, and the "cleaned" residuals of this fit are used in further analysis. We examine the statistical assumptions and requirements of the General Linear Model, and whether these are met during nuisance regression of resting state fMRI data. Using toy examples and real data we show how pre-whitening, temporal filtering and temporal shifting of regressors impact model fit. Based on our own observations, existing literature, and statistical theory, we make the following recommendations when employing nuisance regression: pre-whitening should be applied to achieve valid statistical inference of the noise model fit parameters; temporal filtering should be incorporated into the noise model to best account for changes in degrees of freedom; temporal shifting of regressors, although merited, should be achieved via optimisation and validation of a single temporal shift. We encourage all readers to make simple, practical changes to their fMRI denoising pipeline, and to regularly assess the appropriateness of the noise model used. By negotiating the potential pitfalls described in this paper, and by clearly reporting the details of nuisance regression in future manuscripts, we hope that the field will achieve more accurate and precise noise models for cleaning the resting state fMRI time-series. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Impact of Autocorrelation on Functional Connectivity

PubMed Central

Arbabshirani, Mohammad R.; Damaraju, Eswar; Phlypo, Ronald; Plis, Sergey; Allen, Elena; Ma, Sai; Mathalon, Daniel; Preda, Adrian; Vaidya, Jatin G.; Adali, Tülay; Calhoun, Vince D.

2014-01-01

Although the impact of serial correlation (autocorrelation) in residuals of general linear models for fMRI time-series has been studied extensively, the effect of autocorrelation on functional connectivity studies has been largely neglected until recently. Some recent studies based on results from economics have questioned the conventional estimation of functional connectivity and argue that not correcting for autocorrelation in fMRI time-series results in “spurious” correlation coefficients. In this paper, first we assess the effect of autocorrelation on Pearson correlation coefficient through theoretical approximation and simulation. Then we present this effect on real fMRI data. To our knowledge this is the first work comprehensively investigating the effect of autocorrelation on functional connectivity estimates. Our results show that although FC values are altered, even following correction for autocorrelation, results of hypothesis testing on FC values remain very similar to those before correction. In real data we show this is true for main effects and also for group difference testing between healthy controls and schizophrenia patients. We further discuss model order selection in the context of autoregressive processes, effects of frequency filtering and propose a preprocessing pipeline for connectivity studies. PMID:25072392

A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series.

PubMed

Patel, Ameera X; Kundu, Prantik; Rubinov, Mikail; Jones, P Simon; Vértes, Petra E; Ersche, Karen D; Suckling, John; Bullmore, Edward T

2014-07-15

The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N=22) and a new dataset on adults with stimulant drug dependence (N=40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www.brainwavelet.org. Copyright © 2014. Published by Elsevier Inc.

A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series

PubMed Central

Patel, Ameera X.; Kundu, Prantik; Rubinov, Mikail; Jones, P. Simon; Vértes, Petra E.; Ersche, Karen D.; Suckling, John; Bullmore, Edward T.

2014-01-01

The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N = 22) and a new dataset on adults with stimulant drug dependence (N = 40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www.brainwavelet.org. PMID:24657353

Automatic analysis (aa): efficient neuroimaging workflows and parallel processing using Matlab and XML.

PubMed

Cusack, Rhodri; Vicente-Grabovetsky, Alejandro; Mitchell, Daniel J; Wild, Conor J; Auer, Tibor; Linke, Annika C; Peelle, Jonathan E

2014-01-01

Recent years have seen neuroimaging data sets becoming richer, with larger cohorts of participants, a greater variety of acquisition techniques, and increasingly complex analyses. These advances have made data analysis pipelines complicated to set up and run (increasing the risk of human error) and time consuming to execute (restricting what analyses are attempted). Here we present an open-source framework, automatic analysis (aa), to address these concerns. Human efficiency is increased by making code modular and reusable, and managing its execution with a processing engine that tracks what has been completed and what needs to be (re)done. Analysis is accelerated by optional parallel processing of independent tasks on cluster or cloud computing resources. A pipeline comprises a series of modules that each perform a specific task. The processing engine keeps track of the data, calculating a map of upstream and downstream dependencies for each module. Existing modules are available for many analysis tasks, such as SPM-based fMRI preprocessing, individual and group level statistics, voxel-based morphometry, tractography, and multi-voxel pattern analyses (MVPA). However, aa also allows for full customization, and encourages efficient management of code: new modules may be written with only a small code overhead. aa has been used by more than 50 researchers in hundreds of neuroimaging studies comprising thousands of subjects. It has been found to be robust, fast, and efficient, for simple-single subject studies up to multimodal pipelines on hundreds of subjects. It is attractive to both novice and experienced users. aa can reduce the amount of time neuroimaging laboratories spend performing analyses and reduce errors, expanding the range of scientific questions it is practical to address.

Automatic Denoising of Functional MRI Data: Combining Independent Component Analysis and Hierarchical Fusion of Classifiers

PubMed Central

Salimi-Khorshidi, Gholamreza; Douaud, Gwenaëlle; Beckmann, Christian F; Glasser, Matthew F; Griffanti, Ludovica; Smith, Stephen M

2014-01-01

Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult. Independent component analysis (ICA) - one of the most widely used techniques for the exploratory analysis of fMRI data - has shown to be a powerful technique in identifying various sources of neuronally-related and artefactual fluctuation in fMRI data (both with the application of external stimuli and with the subject “at rest”). ICA decomposes fMRI data into patterns of activity (a set of spatial maps and their corresponding time series) that are statistically independent and add linearly to explain voxel-wise time series. Given the set of ICA components, if the components representing “signal” (brain activity) can be distinguished form the “noise” components (effects of motion, non-neuronal physiology, scanner artefacts and other nuisance sources), the latter can then be removed from the data, providing an effective cleanup of structured noise. Manual classification of components is labour intensive and requires expertise; hence, a fully automatic noise detection algorithm that can reliably detect various types of noise sources (in both task and resting fMRI) is desirable. In this paper, we introduce FIX (“FMRIB’s ICA-based X-noiseifier”), which provides an automatic solution for denoising fMRI data via accurate classification of ICA components. For each ICA component FIX generates a large number of distinct spatial and temporal features, each describing a different aspect of the data (e.g., what proportion of temporal fluctuations are at high frequencies). The set of features is then fed into a multi-level classifier (built around several different Classifiers). Once trained through the hand-classification of a sufficient number of training datasets, the classifier can then automatically classify new datasets. The noise components can then be subtracted from (or regressed out of) the original data, to provide automated cleanup. On conventional resting-state fMRI (rfMRI) single-run datasets, FIX achieved about 95% overall accuracy. On high-quality rfMRI data from the Human Connectome Project, FIX achieves over 99% classification accuracy, and as a result is being used in the default rfMRI processing pipeline for generating HCP connectomes. FIX is publicly available as a plugin for FSL. PMID:24389422

The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for scientific workflows.

PubMed

Bellec, Pierre; Lavoie-Courchesne, Sébastien; Dickinson, Phil; Lerch, Jason P; Zijdenbos, Alex P; Evans, Alan C

2012-01-01

The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline. The pipeline system for Octave and Matlab (PSOM) is a flexible framework for the implementation of pipelines in the form of Octave or Matlab scripts. PSOM does not introduce new language constructs to specify the steps and structure of the workflow. All steps of analysis are instead described by a regular Matlab data structure, documenting their associated command and options, as well as their input, output, and cleaned-up files. The PSOM execution engine provides a number of automated services: (1) it executes jobs in parallel on a local computing facility as long as the dependencies between jobs allow for it and sufficient resources are available; (2) it generates a comprehensive record of the pipeline stages and the history of execution, which is detailed enough to fully reproduce the analysis; (3) if an analysis is started multiple times, it executes only the parts of the pipeline that need to be reprocessed. PSOM is distributed under an open-source MIT license and can be used without restriction for academic or commercial projects. The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac). We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images (fMRI). The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources.

The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for scientific workflows

PubMed Central

Bellec, Pierre; Lavoie-Courchesne, Sébastien; Dickinson, Phil; Lerch, Jason P.; Zijdenbos, Alex P.; Evans, Alan C.

2012-01-01

The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline. The pipeline system for Octave and Matlab (PSOM) is a flexible framework for the implementation of pipelines in the form of Octave or Matlab scripts. PSOM does not introduce new language constructs to specify the steps and structure of the workflow. All steps of analysis are instead described by a regular Matlab data structure, documenting their associated command and options, as well as their input, output, and cleaned-up files. The PSOM execution engine provides a number of automated services: (1) it executes jobs in parallel on a local computing facility as long as the dependencies between jobs allow for it and sufficient resources are available; (2) it generates a comprehensive record of the pipeline stages and the history of execution, which is detailed enough to fully reproduce the analysis; (3) if an analysis is started multiple times, it executes only the parts of the pipeline that need to be reprocessed. PSOM is distributed under an open-source MIT license and can be used without restriction for academic or commercial projects. The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac). We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images (fMRI). The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources. PMID:22493575

Dynamic causal modelling on infant fNIRS data: A validation study on a simultaneously recorded fNIRS-fMRI dataset.

PubMed

Bulgarelli, Chiara; Blasi, Anna; Arridge, Simon; Powell, Samuel; de Klerk, Carina C J M; Southgate, Victoria; Brigadoi, Sabrina; Penny, William; Tak, Sungho; Hamilton, Antonia

2018-04-12

Tracking the connectivity of the developing brain from infancy through childhood is an area of increasing research interest, and fNIRS provides an ideal method for studying the infant brain as it is compact, safe and robust to motion. However, data analysis methods for fNIRS are still underdeveloped compared to those available for fMRI. Dynamic causal modelling (DCM) is an advanced connectivity technique developed for fMRI data, that aims to estimate the coupling between brain regions and how this might be modulated by changes in experimental conditions. DCM has recently been applied to adult fNIRS, but not to infants. The present paper provides a proof-of-principle for the application of this method to infant fNIRS data and a demonstration of the robustness of this method using a simultaneously recorded fMRI-fNIRS single case study, thereby allowing the use of this technique in future infant studies. fMRI and fNIRS were simultaneously recorded from a 6-month-old sleeping infant, who was presented with auditory stimuli in a block design. Both fMRI and fNIRS data were preprocessed using SPM, and analysed using a general linear model approach. The main challenges that adapting DCM for fNIRS infant data posed included: (i) the import of the structural image of the participant for spatial pre-processing, (ii) the spatial registration of the optodes on the structural image of the infant, (iii) calculation of an accurate 3-layer segmentation of the structural image, (iv) creation of a high-density mesh as well as (v) the estimation of the NIRS optical sensitivity functions. To assess our results, we compared the values obtained for variational Free Energy (F), Bayesian Model Selection (BMS) and Bayesian Model Average (BMA) with the same set of possible models applied to both the fMRI and fNIRS datasets. We found high correspondence in F, BMS, and BMA between fMRI and fNIRS data, therefore showing for the first time high reliability of DCM applied to infant fNIRS data. This work opens new avenues for future research on effective connectivity in infancy by contributing a data analysis pipeline and guidance for applying DCM to infant fNIRS data. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

The secret lives of experiments: methods reporting in the fMRI literature.

PubMed

Carp, Joshua

2012-10-15

Replication of research findings is critical to the progress of scientific understanding. Accordingly, most scientific journals require authors to report experimental procedures in sufficient detail for independent researchers to replicate their work. To what extent do research reports in the functional neuroimaging literature live up to this standard? The present study evaluated methods reporting and methodological choices across 241 recent fMRI articles. Many studies did not report critical methodological details with regard to experimental design, data acquisition, and analysis. Further, many studies were underpowered to detect any but the largest statistical effects. Finally, data collection and analysis methods were highly flexible across studies, with nearly as many unique analysis pipelines as there were studies in the sample. Because the rate of false positive results is thought to increase with the flexibility of experimental designs, the field of functional neuroimaging may be particularly vulnerable to false positives. In sum, the present study documented significant gaps in methods reporting among fMRI studies. Improved methodological descriptions in research reports would yield significant benefits for the field. Copyright © 2012 Elsevier Inc. All rights reserved.

Integration of Functional Magnetic Resonance Imaging and Magnetoencephalography Functional Maps Into a CyberKnife Planning System: Feasibility Study for Motor Activity Localization and Dose Planning.

PubMed

De Martin, Elena; Duran, Dunja; Ghielmetti, Francesco; Visani, Elisa; Aquino, Domenico; Marchetti, Marcello; Sebastiano, Davide Rossi; Cusumano, Davide; Bruzzone, Maria Grazia; Panzica, Ferruccio; Fariselli, Laura

2017-12-01

Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) provide noninvasive localization of eloquent brain areas for presurgical planning. The aim of this study is the integration of MEG and fMRI maps into a CyberKnife (CK) system to optimize dose planning. Four patients with brain metastases in the motor area underwent functional imaging study of the hand motor cortex before radiosurgery. MEG data were acquired during a visually cued hand motor task. Motor activations were identified also using an fMRI block-designed paradigm. MEG and fMRI maps were then integrated into a CK system and contoured as organs at risk for treatment planning optimization. The integration of fMRI data into the CK system was achieved for all patients by means of a standardized protocol. We also implemented an ad hoc pipeline to convert the MEG signal into a DICOM standard, to make sure that it was readable by our CK treatment planning system. Inclusion of the activation areas into the optimization plan allowed the creation of treatment plans that reduced the irradiation of the motor cortex yet not affecting the brain peripheral dose. The availability of advanced neuroimaging techniques is playing an increasingly important role in radiosurgical planning strategy. We successfully imported MEG and fMRI activations into a CK system. This additional information can improve dose sparing of eloquent areas, allowing a more comprehensive investigation of the related dose-volume constraints that in theory could translate into a gain in tumor local control, and a reduction of neurological complications. Copyright © 2017 Elsevier Inc. All rights reserved.

An Investigation of the Relationship Between fMRI and ERP Source Localized Measurements of Brain Activity during Face Processing

PubMed Central

Richards, Todd; Webb, Sara Jane; Murias, Michael; Merkle, Kristen; Kleinhans, Natalia M.; Johnson, L. Clark; Poliakov, Andrew; Aylward, Elizabeth; Dawson, Geraldine

2013-01-01

Brain activity patterns during face processing have been extensively explored with functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs). ERP source localization adds a spatial dimension to the ERP time series recordings, which allows for a more direct comparison and integration with fMRI findings. The goals for this study were (1) to compare the spatial descriptions of neuronal activity during face processing obtained with fMRI and ERP source localization using low-resolution electro-magnetic tomography (LORETA), and (2) to use the combined information from source localization and fMRI to explore how the temporal sequence of brain activity during face processing is summarized in fMRI activation maps. fMRI and high-density ERP data were acquired in separate sessions for 17 healthy adult males for a face and object processing task. LORETA statistical maps for the comparison of viewing faces and viewing houses were coregistered and compared to fMRI statistical maps for the same conditions. The spatial locations of face processing-sensitive activity measured by fMRI and LORETA were found to overlap in a number of areas including the bilateral fusiform gyri, the right superior, middle and inferior temporal gyri, and the bilateral precuneus. Both the fMRI and LORETA solutions additionally demon-strated activity in regions that did not overlap. fMRI and LORETA statistical maps of face processing-sensitive brain activity were found to converge spatially primarily at LORETA solution latencies that were within 18 ms of the N170 latency. The combination of data from these techniques suggested that electrical brain activity at the latency of the N170 is highly represented in fMRI statistical maps. PMID:19322649

The Neuro Bureau ADHD-200 Preprocessed repository.

PubMed

Bellec, Pierre; Chu, Carlton; Chouinard-Decorte, François; Benhajali, Yassine; Margulies, Daniel S; Craddock, R Cameron

2017-01-01

In 2011, the "ADHD-200 Global Competition" was held with the aim of identifying biomarkers of attention-deficit/hyperactivity disorder from resting-state functional magnetic resonance imaging (rs-fMRI) and structural MRI (s-MRI) data collected on 973 individuals. Statisticians and computer scientists were potentially the most qualified for the machine learning aspect of the competition, but generally lacked the specialized skills to implement the necessary steps of data preparation for rs-fMRI. Realizing this barrier to entry, the Neuro Bureau prospectively collaborated with all competitors by preprocessing the data and sharing these results at the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) (http://www.nitrc.org/frs/?group_id=383). This "ADHD-200 Preprocessed" release included multiple analytical pipelines to cater to different philosophies of data analysis. The processed derivatives included denoised and registered 4D fMRI volumes, regional time series extracted from brain parcellations, maps of 10 intrinsic connectivity networks, fractional amplitude of low frequency fluctuation, and regional homogeneity, along with grey matter density maps. The data was used by several teams who competed in the ADHD-200 Global Competition, including the winning entry by a group of biostaticians. To the best of our knowledge, the ADHD-200 Preprocessed release was the first large public resource of preprocessed resting-state fMRI and structural MRI data, and remains to this day the only resource featuring a battery of alternative processing paths. Copyright © 2016 Elsevier Inc. All rights reserved.

Investigating the Group-Level Impact of Advanced Dual-Echo fMRI Combinations

PubMed Central

Kettinger, Ádám; Hill, Christopher; Vidnyánszky, Zoltán; Windischberger, Christian; Nagy, Zoltán

2016-01-01

Multi-echo fMRI data acquisition has been widely investigated and suggested to optimize sensitivity for detecting the BOLD signal. Several methods have also been proposed for the combination of data with different echo times. The aim of the present study was to investigate whether these advanced echo combination methods provide advantages over the simple averaging of echoes when state-of-the-art group-level random-effect analyses are performed. Both resting-state and task-based dual-echo fMRI data were collected from 27 healthy adult individuals (14 male, mean age = 25.75 years) using standard echo-planar acquisition methods at 3T. Both resting-state and task-based data were subjected to a standard image pre-processing pipeline. Subsequently the two echoes were combined as a weighted average, using four different strategies for calculating the weights: (1) simple arithmetic averaging, (2) BOLD sensitivity weighting, (3) temporal-signal-to-noise ratio weighting and (4) temporal BOLD sensitivity weighting. Our results clearly show that the simple averaging of data with the different echoes is sufficient. Advanced echo combination methods may provide advantages on a single-subject level but when considering random-effects group level statistics they provide no benefit regarding sensitivity (i.e., group-level t-values) compared to the simple echo-averaging approach. One possible reason for the lack of clear advantages may be that apart from increasing the average BOLD sensitivity at the single-subject level, the advanced weighted averaging methods also inflate the inter-subject variance. As the echo combination methods provide very similar results, the recommendation is to choose between them depending on the availability of time for collecting additional resting-state data or whether subject-level or group-level analyses are planned. PMID:28018165

Surface-Based fMRI-Driven Diffusion Tractography in the Presence of Significant Brain Pathology: A Study Linking Structure and Function in Cerebral Palsy

PubMed Central

Cunnington, Ross; Boyd, Roslyn N.; Rose, Stephen E.

2016-01-01

Diffusion MRI (dMRI) tractography analyses are difficult to perform in the presence of brain pathology. Automated methods that rely on cortical parcellation for structural connectivity studies often fail, while manually defining regions is extremely time consuming and can introduce human error. Both methods also make assumptions about structure-function relationships that may not hold after cortical reorganisation. Seeding tractography with functional-MRI (fMRI) activation is an emerging method that reduces these confounds, but inherent smoothing of fMRI signal may result in the inclusion of irrelevant pathways. This paper describes a novel fMRI-seeded dMRI-analysis pipeline based on surface-meshes that reduces these issues and utilises machine-learning to generate task specific white matter pathways, minimising the requirement for manually-drawn ROIs. We directly compared this new strategy to a standard voxelwise fMRI-dMRI approach, by investigating correlations between clinical scores and dMRI metrics of thalamocortical and corticomotor tracts in 31 children with unilateral cerebral palsy. The surface-based approach successfully processed more participants (87%) than the voxel-based approach (65%), and provided significantly more-coherent tractography. Significant correlations between dMRI metrics and five clinical scores of function were found for the more superior regions of these tracts. These significant correlations were stronger and more frequently found with the surface-based method (15/20 investigated were significant; R2 = 0.43–0.73) than the voxelwise analysis (2 sig. correlations; 0.38 & 0.49). More restricted fMRI signal, better-constrained tractography, and the novel track-classification method all appeared to contribute toward these differences. PMID:27487011

Using fMRI to study reward processing in humans: past, present, and future

PubMed Central

Wang, Kainan S.; Smith, David V.

2016-01-01

Functional magnetic resonance imaging (fMRI) is a noninvasive tool used to probe cognitive and affective processes. Although fMRI provides indirect measures of neural activity, the advent of fMRI has allowed for 1) the corroboration of significant animal findings in the human brain, and 2) the expansion of models to include more common human attributes that inform behavior. In this review, we briefly consider the neural basis of the blood oxygenation level dependent signal to set up a discussion of how fMRI studies have applied it in examining cognitive models in humans and the promise of using fMRI to advance such models. Specifically, we illustrate the contribution that fMRI has made to the study of reward processing, focusing on the role of the striatum in encoding reward-related learning signals that drive anticipatory and consummatory behaviors. For instance, we discuss how fMRI can be used to link neural signals (e.g., striatal responses to rewards) to individual differences in behavior and traits. While this functional segregation approach has been constructive to our understanding of reward-related functions, many fMRI studies have also benefitted from a functional integration approach that takes into account how interconnected regions (e.g., corticostriatal circuits) contribute to reward processing. We contend that future work using fMRI will profit from using a multimodal approach, such as combining fMRI with noninvasive brain stimulation tools (e.g., transcranial electrical stimulation), that can identify causal mechanisms underlying reward processing. Consequently, advancements in implementing fMRI will promise new translational opportunities to inform our understanding of psychopathologies. PMID:26740530

HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).

PubMed

Makkie, Milad; Zhao, Shijie; Jiang, Xi; Lv, Jinglei; Zhao, Yu; Ge, Bao; Li, Xiang; Han, Junwei; Liu, Tianming

Tremendous efforts have thus been devoted on the establishment of functional MRI informatics systems that recruit a comprehensive collection of statistical/computational approaches for fMRI data analysis. However, the state-of-the-art fMRI informatics systems are especially designed for specific fMRI sessions or studies of which the data size is not really big, and thus has difficulty in handling fMRI 'big data.' Given the size of fMRI data are growing explosively recently due to the advancement of neuroimaging technologies, an effective and efficient fMRI informatics system which can process and analyze fMRI big data is much needed. To address this challenge, in this work, we introduce our newly developed informatics platform, namely, 'HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).' HELPNI implements our recently developed computational framework of sparse representation of whole-brain fMRI signals which is called holistic atlases of functional networks and interactions (HAFNI) for fMRI data analysis. HELPNI provides integrated solutions to archive and process large-scale fMRI data automatically and structurally, to extract and visualize meaningful results information from raw fMRI data, and to share open-access processed and raw data with other collaborators through web. We tested the proposed HELPNI platform using publicly available 1000 Functional Connectomes dataset including over 1200 subjects. We identified consistent and meaningful functional brain networks across individuals and populations based on resting state fMRI (rsfMRI) big data. Using efficient sampling module, the experimental results demonstrate that our HELPNI system has superior performance than other systems for large-scale fMRI data in terms of processing and storing the data and associated results much faster.

HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).

PubMed

Makkie, Milad; Zhao, Shijie; Jiang, Xi; Lv, Jinglei; Zhao, Yu; Ge, Bao; Li, Xiang; Han, Junwei; Liu, Tianming

2015-12-01

Tremendous efforts have thus been devoted on the establishment of functional MRI informatics systems that recruit a comprehensive collection of statistical/computational approaches for fMRI data analysis. However, the state-of-the-art fMRI informatics systems are especially designed for specific fMRI sessions or studies of which the data size is not really big, and thus has difficulty in handling fMRI 'big data.' Given the size of fMRI data are growing explosively recently due to the advancement of neuroimaging technologies, an effective and efficient fMRI informatics system which can process and analyze fMRI big data is much needed. To address this challenge, in this work, we introduce our newly developed informatics platform, namely, 'HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI).' HELPNI implements our recently developed computational framework of sparse representation of whole-brain fMRI signals which is called holistic atlases of functional networks and interactions (HAFNI) for fMRI data analysis. HELPNI provides integrated solutions to archive and process large-scale fMRI data automatically and structurally, to extract and visualize meaningful results information from raw fMRI data, and to share open-access processed and raw data with other collaborators through web. We tested the proposed HELPNI platform using publicly available 1000 Functional Connectomes dataset including over 1200 subjects. We identified consistent and meaningful functional brain networks across individuals and populations based on resting state fMRI (rsfMRI) big data. Using efficient sampling module, the experimental results demonstrate that our HELPNI system has superior performance than other systems for large-scale fMRI data in terms of processing and storing the data and associated results much faster.

The Perfect Neuroimaging-Genetics-Computation Storm: Collision of Petabytes of Data, Millions of Hardware Devices and Thousands of Software Tools

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Zamanyan, Alen; Torri, Federica; Macciardi, Fabio; Hobel, Sam; Moon, Seok Woo; Sung, Young Hee; Jiang, Zhiguo; Labus, Jennifer; Kurth, Florian; Ashe-McNalley, Cody; Mayer, Emeran; Vespa, Paul M.; Van Horn, John D.; Toga, Arthur W.

2013-01-01

The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data. PMID:23975276

Validating a new methodology for optical probe design and image registration in fNIRS studies

PubMed Central

Wijeakumar, Sobanawartiny; Spencer, John P.; Bohache, Kevin; Boas, David A.; Magnotta, Vincent A.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an imaging technique that relies on the principle of shining near-infrared light through tissue to detect changes in hemodynamic activation. An important methodological issue encountered is the creation of optimized probe geometry for fNIRS recordings. Here, across three experiments, we describe and validate a processing pipeline designed to create an optimized, yet scalable probe geometry based on selected regions of interest (ROIs) from the functional magnetic resonance imaging (fMRI) literature. In experiment 1, we created a probe geometry optimized to record changes in activation from target ROIs important for visual working memory. Positions of the sources and detectors of the probe geometry on an adult head were digitized using a motion sensor and projected onto a generic adult atlas and a segmented head obtained from the subject's MRI scan. In experiment 2, the same probe geometry was scaled down to fit a child's head and later digitized and projected onto the generic adult atlas and a segmented volume obtained from the child's MRI scan. Using visualization tools and by quantifying the amount of intersection between target ROIs and channels, we show that out of 21 ROIs, 17 and 19 ROIs intersected with fNIRS channels from the adult and child probe geometries, respectively. Further, both the adult atlas and adult subject-specific MRI approaches yielded similar results and can be used interchangeably. However, results suggest that segmented heads obtained from MRI scans be used for registering children's data. Finally, in experiment 3, we further validated our processing pipeline by creating a different probe geometry designed to record from target ROIs involved in language and motor processing. PMID:25705757

A comparison between EEG source localization and fMRI during the processing of emotional visual stimuli

NASA Astrophysics Data System (ADS)

Hu, Jin; Tian, Jie; Pan, Xiaohong; Liu, Jiangang

2007-03-01

The purpose of this paper is to compare between EEG source localization and fMRI during emotional processing. 108 pictures for EEG (categorized as positive, negative and neutral) and 72 pictures for fMRI were presented to 24 healthy, right-handed subjects. The fMRI data were analyzed using statistical parametric mapping with SPM2. LORETA was applied to grand averaged ERP data to localize intracranial sources. Statistical analysis was implemented to compare spatiotemporal activation of fMRI and EEG. The fMRI results are in accordance with EEG source localization to some extent, while part of mismatch in localization between the two methods was also observed. In the future we should apply the method for simultaneous recording of EEG and fMRI to our study.

ALMA Pipeline: Current Status

NASA Astrophysics Data System (ADS)

Shinnaga, H.; Humphreys, E.; Indebetouw, R.; Villard, E.; Kern, J.; Davis, L.; Miura, R. E.; Nakazato, T.; Sugimoto, K.; Kosugi, G.; Akiyama, E.; Muders, D.; Wyrowski, F.; Williams, S.; Lightfoot, J.; Kent, B.; Momjian, E.; Hunter, T.; ALMA Pipeline Team

2015-12-01

The ALMA Pipeline is the automated data reduction tool that runs on ALMA data. Current version of the ALMA pipeline produces science quality data products for standard interferometric observing modes up to calibration process. The ALMA Pipeline is comprised of (1) heuristics in the form of Python scripts that select the best processing parameters, and (2) contexts that are given for book-keeping purpose of data processes. The ALMA Pipeline produces a "weblog" that showcases detailed plots for users to judge how each step of calibration processes are treated. The ALMA Interferometric Pipeline was conditionally accepted in March 2014 by processing Cycle 0 and Cycle 1 data sets. From Cycle 2, ALMA Pipeline is used for ALMA data reduction and quality assurance for the projects whose observing modes are supported by the ALMA Pipeline. Pipeline tasks are available based on CASA version 4.2.2, and the first public pipeline release called CASA 4.2.2-pipe has been available since October 2014. One can reduce ALMA data both by CASA tasks as well as by pipeline tasks by using CASA version 4.2.2-pipe.

Characterization of Noise Signatures of Involuntary Head Motion in the Autism Brain Imaging Data Exchange Repository

PubMed Central

Caballero, Carla; Mistry, Sejal; Vero, Joe; Torres, Elizabeth B

2018-01-01

The variability inherently present in biophysical data is partly contributed by disparate sampling resolutions across instrumentations. This poses a potential problem for statistical inference using pooled data in open access repositories. Such repositories combine data collected from multiple research sites using variable sampling resolutions. One example is the Autism Brain Imaging Data Exchange repository containing thousands of imaging and demographic records from participants in the spectrum of autism and age-matched neurotypical controls. Further, statistical analyses of groups from different diagnoses and demographics may be challenging, owing to the disparate number of participants across different clinical subgroups. In this paper, we examine the noise signatures of head motion data extracted from resting state fMRI data harnessed under different sampling resolutions. We characterize the quality of the noise in the variability of the raw linear and angular speeds for different clinical phenotypes in relation to age-matched controls. Further, we use bootstrapping methods to ensure compatible group sizes for statistical comparison and report the ranges of physical involuntary head excursions of these groups. We conclude that different sampling rates do affect the quality of noise in the variability of head motion data and, consequently, the type of random process appropriate to characterize the time series data. Further, given a qualitative range of noise, from pink to brown noise, it is possible to characterize different clinical subtypes and distinguish them in relation to ranges of neurotypical controls. These results may be of relevance to the pre-processing stages of the pipeline of analyses of resting state fMRI data, whereby head motion enters the criteria to clean imaging data from motion artifacts. PMID:29556179

Discrete pre-processing step effects in registration-based pipelines, a preliminary volumetric study on T1-weighted images.

PubMed

Muncy, Nathan M; Hedges-Muncy, Ariana M; Kirwan, C Brock

2017-01-01

Pre-processing MRI scans prior to performing volumetric analyses is common practice in MRI studies. As pre-processing steps adjust the voxel intensities, the space in which the scan exists, and the amount of data in the scan, it is possible that the steps have an effect on the volumetric output. To date, studies have compared between and not within pipelines, and so the impact of each step is unknown. This study aims to quantify the effects of pre-processing steps on volumetric measures in T1-weighted scans within a single pipeline. It was our hypothesis that pre-processing steps would significantly impact ROI volume estimations. One hundred fifteen participants from the OASIS dataset were used, where each participant contributed three scans. All scans were then pre-processed using a step-wise pipeline. Bilateral hippocampus, putamen, and middle temporal gyrus volume estimations were assessed following each successive step, and all data were processed by the same pipeline 5 times. Repeated-measures analyses tested for a main effects of pipeline step, scan-rescan (for MRI scanner consistency) and repeated pipeline runs (for algorithmic consistency). A main effect of pipeline step was detected, and interestingly an interaction between pipeline step and ROI exists. No effect for either scan-rescan or repeated pipeline run was detected. We then supply a correction for noise in the data resulting from pre-processing.

Neural Correlates of Temporal Auditory Processing in Developmental Dyslexia during German Vowel Length Discrimination: An fMRI Study

ERIC Educational Resources Information Center

Steinbrink, Claudia; Groth, Katarina; Lachmann, Thomas; Riecker, Axel

2012-01-01

This fMRI study investigated phonological vs. auditory temporal processing in developmental dyslexia by means of a German vowel length discrimination paradigm (Groth, Lachmann, Riecker, Muthmann, & Steinbrink, 2011). Behavioral and fMRI data were collected from dyslexics and controls while performing same-different judgments of vowel duration in…

Discrete pre-processing step effects in registration-based pipelines, a preliminary volumetric study on T1-weighted images

PubMed Central

2017-01-01

Pre-processing MRI scans prior to performing volumetric analyses is common practice in MRI studies. As pre-processing steps adjust the voxel intensities, the space in which the scan exists, and the amount of data in the scan, it is possible that the steps have an effect on the volumetric output. To date, studies have compared between and not within pipelines, and so the impact of each step is unknown. This study aims to quantify the effects of pre-processing steps on volumetric measures in T1-weighted scans within a single pipeline. It was our hypothesis that pre-processing steps would significantly impact ROI volume estimations. One hundred fifteen participants from the OASIS dataset were used, where each participant contributed three scans. All scans were then pre-processed using a step-wise pipeline. Bilateral hippocampus, putamen, and middle temporal gyrus volume estimations were assessed following each successive step, and all data were processed by the same pipeline 5 times. Repeated-measures analyses tested for a main effects of pipeline step, scan-rescan (for MRI scanner consistency) and repeated pipeline runs (for algorithmic consistency). A main effect of pipeline step was detected, and interestingly an interaction between pipeline step and ROI exists. No effect for either scan-rescan or repeated pipeline run was detected. We then supply a correction for noise in the data resulting from pre-processing. PMID:29023597

funcLAB/G-service-oriented architecture for standards-based analysis of functional magnetic resonance imaging in HealthGrids.

PubMed

Erberich, Stephan G; Bhandekar, Manasee; Chervenak, Ann; Kesselman, Carl; Nelson, Marvin D

2007-01-01

Functional MRI is successfully being used in clinical and research applications including preoperative planning, language mapping, and outcome monitoring. However, clinical use of fMRI is less widespread due to its complexity of imaging, image workflow, post-processing, and lack of algorithmic standards hindering result comparability. As a consequence, wide-spread adoption of fMRI as clinical tool is low contributing to the uncertainty of community physicians how to integrate fMRI into practice. In addition, training of physicians with fMRI is in its infancy and requires clinical and technical understanding. Therefore, many institutions which perform fMRI have a team of basic researchers and physicians to perform fMRI as a routine imaging tool. In order to provide fMRI as an advanced diagnostic tool to the benefit of a larger patient population, image acquisition and image post-processing must be streamlined, standardized, and available at any institution which does not have these resources available. Here we describe a software architecture, the functional imaging laboratory (funcLAB/G), which addresses (i) standardized image processing using Statistical Parametric Mapping and (ii) its extension to secure sharing and availability for the community using standards-based Grid technology (Globus Toolkit). funcLAB/G carries the potential to overcome the limitations of fMRI in clinical use and thus makes standardized fMRI available to the broader healthcare enterprise utilizing the Internet and HealthGrid Web Services technology.

Structural Brain Atlases: Design, Rationale, and Applications in Normal and Pathological Cohorts

PubMed Central

Mandal, Pravat K.; Mahajan, Rashima; Dinov, Ivo D.

2015-01-01

Structural magnetic resonance imaging (MRI) provides anatomical information about the brain in healthy as well as in diseased conditions. On the other hand, functional MRI (fMRI) provides information on the brain activity during performance of a specific task. Analysis of fMRI data requires the registration of the data to a reference brain template in order to identify the activated brain regions. Brain templates also find application in other neuroimaging modalities, such as diffusion tensor imaging and multi-voxel spectroscopy. Further, there are certain differences (e.g., brain shape and size) in the brains of populations of different origin and during diseased conditions like in Alzheimer’s disease (AD), population and disease-specific brain templates may be considered crucial for accurate registration and subsequent analysis of fMRI as well as other neuroimaging data. This manuscript provides a comprehensive review of the history, construction and application of brain atlases. A chronological outline of the development of brain template design, starting from the Talairach and Tournoux atlas to the Chinese brain template (to date), along with their respective detailed construction protocols provides the backdrop to this manuscript. The manuscript also provides the automated workflow-based protocol for designing a population-specific brain atlas from structural MRI data using LONI Pipeline graphical workflow environment. We conclude by discussing the scope of brain templates as a research tool and their application in various neuroimaging modalities. PMID:22647262

Modeling fMRI signals can provide insights into neural processing in the cerebral cortex

PubMed Central

Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

2015-01-01

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. PMID:25972586

Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

PubMed

Vanni, Simo; Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

2015-08-01

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. Copyright © 2015 the American Physiological Society.

The role of fMRI in drug development

PubMed Central

Carmichael, Owen; Schwarz, Adam J.; Chatham, Christopher H.; Scott, David; Turner, Jessica A.; Upadhyay, Jaymin; Coimbra, Alexandre; Goodman, James A.; Baumgartner, Richard; English, Brett A.; Apolzan, John W.; Shankapal, Preetham; Hawkins, Keely R.

2017-01-01

Functional magnetic resonance imaging (fMRI) has been known for over a decade to have the potential to greatly enhance the process of developing novel therapeutic drugs for prevalent health conditions. However, the use of fMRI in drug development continues to be relatively limited because of a variety of technical, biological, and strategic barriers that continue to limit progress. Here, we briefly review the roles that fMRI can have in the drug development process and the requirements it must meet to be useful in this setting. We then provide an update on our current understanding of the strengths and limitations of fMRI as a tool for drug developers and recommend activities to enhance its utility. PMID:29154758

78 FR 32010 - Pipeline Safety: Public Workshop on Integrity Verification Process

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-28

.... PHMSA-2013-0119] Pipeline Safety: Public Workshop on Integrity Verification Process AGENCY: Pipeline and... announcing a public workshop to be held on the concept of ``Integrity Verification Process.'' The Integrity Verification Process shares similar characteristics with fitness for service processes. At this workshop, the...

A midas plugin to enable construction of reproducible web-based image processing pipelines

PubMed Central

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A.; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline. PMID:24416016

A midas plugin to enable construction of reproducible web-based image processing pipelines.

PubMed

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

Amateur Image Pipeline Processing using Python plus PyRAF

NASA Astrophysics Data System (ADS)

Green, Wayne

2012-05-01

A template pipeline spanning observing planning to publishing is offered as a basis for establishing a long term observing program. The data reduction pipeline encapsulates all policy and procedures, providing an accountable framework for data analysis and a teaching framework for IRAF. This paper introduces the technical details of a complete pipeline processing environment using Python, PyRAF and a few other languages. The pipeline encapsulates all processing decisions within an auditable framework. The framework quickly handles the heavy lifting of image processing. It also serves as an excellent teaching environment for astronomical data management and IRAF reduction decisions.

A Conceptual Model of the Air Force Logistics Pipeline

DTIC Science & Technology

1989-09-01

Contracting Process . ....... 138 Industrial Capacity .. ......... 140 The Disposal Pipeline Subsystem ....... 142 Collective Pipeline Models...Explosion of " Industry ," Acquisition and Production Process .... ............ 202 60. First Level Explosion of "Attrition," the Disposal Process...Terminology and Phrases, a publication of The American Production and Inventory Control Society ( APICS ). This dictionary defines 5 "pipeline stock" as the

Error-related processing following severe traumatic brain injury: An event-related functional magnetic resonance imaging (fMRI) study

PubMed Central

Sozda, Christopher N.; Larson, Michael J.; Kaufman, David A.S.; Schmalfuss, Ilona M.; Perlstein, William M.

2011-01-01

Continuous monitoring of one’s performance is invaluable for guiding behavior towards successful goal attainment by identifying deficits and strategically adjusting responses when performance is inadequate. In the present study, we exploited the advantages of event-related functional magnetic resonance imaging (fMRI) to examine brain activity associated with error-related processing after severe traumatic brain injury (sTBI). fMRI and behavioral data were acquired while 10 sTBI participants and 12 neurologically-healthy controls performed a task-switching cued-Stroop task. fMRI data were analyzed using a random-effects whole-brain voxel-wise general linear model and planned linear contrasts. Behaviorally, sTBI patients showed greater error-rate interference than neurologically-normal controls. fMRI data revealed that, compared to controls, sTBI patients showed greater magnitude error-related activation in the anterior cingulate cortex (ACC) and an increase in the overall spatial extent of error-related activation across cortical and subcortical regions. Implications for future research and potential limitations in conducting fMRI research in neurologically-impaired populations are discussed, as well as some potential benefits of employing multimodal imaging (e.g., fMRI and event-related potentials) of cognitive control processes in TBI. PMID:21756946

Error-related processing following severe traumatic brain injury: an event-related functional magnetic resonance imaging (fMRI) study.

PubMed

Sozda, Christopher N; Larson, Michael J; Kaufman, David A S; Schmalfuss, Ilona M; Perlstein, William M

2011-10-01

Continuous monitoring of one's performance is invaluable for guiding behavior towards successful goal attainment by identifying deficits and strategically adjusting responses when performance is inadequate. In the present study, we exploited the advantages of event-related functional magnetic resonance imaging (fMRI) to examine brain activity associated with error-related processing after severe traumatic brain injury (sTBI). fMRI and behavioral data were acquired while 10 sTBI participants and 12 neurologically-healthy controls performed a task-switching cued-Stroop task. fMRI data were analyzed using a random-effects whole-brain voxel-wise general linear model and planned linear contrasts. Behaviorally, sTBI patients showed greater error-rate interference than neurologically-normal controls. fMRI data revealed that, compared to controls, sTBI patients showed greater magnitude error-related activation in the anterior cingulate cortex (ACC) and an increase in the overall spatial extent of error-related activation across cortical and subcortical regions. Implications for future research and potential limitations in conducting fMRI research in neurologically-impaired populations are discussed, as well as some potential benefits of employing multimodal imaging (e.g., fMRI and event-related potentials) of cognitive control processes in TBI. Copyright © 2011 Elsevier B.V. All rights reserved.

The Very Large Array Data Processing Pipeline

NASA Astrophysics Data System (ADS)

Kent, Brian R.; Masters, Joseph S.; Chandler, Claire J.; Davis, Lindsey E.; Kern, Jeffrey S.; Ott, Juergen; Schinzel, Frank K.; Medlin, Drew; Muders, Dirk; Williams, Stewart; Geers, Vincent C.; Momjian, Emmanuel; Butler, Bryan J.; Nakazato, Takeshi; Sugimoto, Kanako

2018-01-01

We present the VLA Pipeline, software that is part of the larger pipeline processing framework used for the Karl G. Jansky Very Large Array (VLA), and Atacama Large Millimeter/sub-millimeter Array (ALMA) for both interferometric and single dish observations.Through a collection of base code jointly used by the VLA and ALMA, the pipeline builds a hierarchy of classes to execute individual atomic pipeline tasks within the Common Astronomy Software Applications (CASA) package. Each pipeline task contains heuristics designed by the team to actively decide the best processing path and execution parameters for calibration and imaging. The pipeline code is developed and written in Python and uses a "context" structure for tracking the heuristic decisions and processing results. The pipeline "weblog" acts as the user interface in verifying the quality assurance of each calibration and imaging stage. The majority of VLA scheduling blocks above 1 GHz are now processed with the standard continuum recipe of the pipeline and offer a calibrated measurement set as a basic data product to observatory users. In addition, the pipeline is used for processing data from the VLA Sky Survey (VLASS), a seven year community-driven endeavor started in September 2017 to survey the entire sky down to a declination of -40 degrees at S-band (2-4 GHz). This 5500 hour next-generation large radio survey will explore the time and spectral domains, relying on pipeline processing to generate calibrated measurement sets, polarimetry, and imaging data products that are available to the astronomical community with no proprietary period. Here we present an overview of the pipeline design philosophy, heuristics, and calibration and imaging results produced by the pipeline. Future development will include the testing of spectral line recipes, low signal-to-noise heuristics, and serving as a testing platform for science ready data products.The pipeline is developed as part of the CASA software package by an international consortium of scientists and software developers based at the National Radio Astronomical Observatory (NRAO), the European Southern Observatory (ESO), and the National Astronomical Observatory of Japan (NAOJ).

The Hyper Suprime-Cam software pipeline

NASA Astrophysics Data System (ADS)

Bosch, James; Armstrong, Robert; Bickerton, Steven; Furusawa, Hisanori; Ikeda, Hiroyuki; Koike, Michitaro; Lupton, Robert; Mineo, Sogo; Price, Paul; Takata, Tadafumi; Tanaka, Masayuki; Yasuda, Naoki; AlSayyad, Yusra; Becker, Andrew C.; Coulton, William; Coupon, Jean; Garmilla, Jose; Huang, Song; Krughoff, K. Simon; Lang, Dustin; Leauthaud, Alexie; Lim, Kian-Tat; Lust, Nate B.; MacArthur, Lauren A.; Mandelbaum, Rachel; Miyatake, Hironao; Miyazaki, Satoshi; Murata, Ryoma; More, Surhud; Okura, Yuki; Owen, Russell; Swinbank, John D.; Strauss, Michael A.; Yamada, Yoshihiko; Yamanoi, Hitomi

2018-01-01

In this paper, we describe the optical imaging data processing pipeline developed for the Subaru Telescope's Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope's Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high-level processing steps that generate coadded images and science-ready catalogs as well as low-level detrending and image characterizations.

Key issues in decomposing fMRI during naturalistic and continuous music experience with independent component analysis.

PubMed

Cong, Fengyu; Puoliväli, Tuomas; Alluri, Vinoo; Sipola, Tuomo; Burunat, Iballa; Toiviainen, Petri; Nandi, Asoke K; Brattico, Elvira; Ristaniemi, Tapani

2014-02-15

Independent component analysis (ICA) has been often used to decompose fMRI data mostly for the resting-state, block and event-related designs due to its outstanding advantage. For fMRI data during free-listening experiences, only a few exploratory studies applied ICA. For processing the fMRI data elicited by 512-s modern tango, a FFT based band-pass filter was used to further pre-process the fMRI data to remove sources of no interest and noise. Then, a fast model order selection method was applied to estimate the number of sources. Next, both individual ICA and group ICA were performed. Subsequently, ICA components whose temporal courses were significantly correlated with musical features were selected. Finally, for individual ICA, common components across majority of participants were found by diffusion map and spectral clustering. The extracted spatial maps (by the new ICA approach) common across most participants evidenced slightly right-lateralized activity within and surrounding the auditory cortices. Meanwhile, they were found associated with the musical features. Compared with the conventional ICA approach, more participants were found to have the common spatial maps extracted by the new ICA approach. Conventional model order selection methods underestimated the true number of sources in the conventionally pre-processed fMRI data for the individual ICA. Pre-processing the fMRI data by using a reasonable band-pass digital filter can greatly benefit the following model order selection and ICA with fMRI data by naturalistic paradigms. Diffusion map and spectral clustering are straightforward tools to find common ICA spatial maps. Copyright © 2013 Elsevier B.V. All rights reserved.

The Hyper Suprime-Cam software pipeline

DOE PAGES

Bosch, James; Armstrong, Robert; Bickerton, Steven; ...

2017-10-12

Here in this article, we describe the optical imaging data processing pipeline developed for the Subaru Telescope’s Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope’s Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high-level processing steps that generate coadded images and science-ready catalogs as well as low-level detrendingmore » and image characterizations.« less

The Hyper Suprime-Cam software pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bosch, James; Armstrong, Robert; Bickerton, Steven

Here in this article, we describe the optical imaging data processing pipeline developed for the Subaru Telescope’s Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope’s Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high-level processing steps that generate coadded images and science-ready catalogs as well as low-level detrendingmore » and image characterizations.« less

Middleware Case Study: MeDICi

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wynne, Adam S.

2011-05-05

In many application domains in science and engineering, data produced by sensors, instruments and networks is naturally processed by software applications structured as a pipeline . Pipelines comprise a sequence of software components that progressively process discrete units of data to produce a desired outcome. For example, in a Web crawler that is extracting semantics from text on Web sites, the first stage in the pipeline might be to remove all HTML tags to leave only the raw text of the document. The second step may parse the raw text to break it down into its constituent grammatical parts, suchmore » as nouns, verbs and so on. Subsequent steps may look for names of people or places, interesting events or times so documents can be sequenced on a time line. Each of these steps can be written as a specialized program that works in isolation with other steps in the pipeline. In many applications, simple linear software pipelines are sufficient. However, more complex applications require topologies that contain forks and joins, creating pipelines comprising branches where parallel execution is desirable. It is also increasingly common for pipelines to process very large files or high volume data streams which impose end-to-end performance constraints. Additionally, processes in a pipeline may have specific execution requirements and hence need to be distributed as services across a heterogeneous computing and data management infrastructure. From a software engineering perspective, these more complex pipelines become problematic to implement. While simple linear pipelines can be built using minimal infrastructure such as scripting languages, complex topologies and large, high volume data processing requires suitable abstractions, run-time infrastructures and development tools to construct pipelines with the desired qualities-of-service and flexibility to evolve to handle new requirements. The above summarizes the reasons we created the MeDICi Integration Framework (MIF) that is designed for creating high-performance, scalable and modifiable software pipelines. MIF exploits a low friction, robust, open source middleware platform and extends it with component and service-based programmatic interfaces that make implementing complex pipelines simple. The MIF run-time automatically handles queues between pipeline elements in order to handle request bursts, and automatically executes multiple instances of pipeline elements to increase pipeline throughput. Distributed pipeline elements are supported using a range of configurable communications protocols, and the MIF interfaces provide efficient mechanisms for moving data directly between two distributed pipeline elements.« less

Redefining the Data Pipeline Using GPUs

NASA Astrophysics Data System (ADS)

Warner, C.; Eikenberry, S. S.; Gonzalez, A. H.; Packham, C.

2013-10-01

There are two major challenges facing the next generation of data processing pipelines: 1) handling an ever increasing volume of data as array sizes continue to increase and 2) the desire to process data in near real-time to maximize observing efficiency by providing rapid feedback on data quality. Combining the power of modern graphics processing units (GPUs), relational database management systems (RDBMSs), and extensible markup language (XML) to re-imagine traditional data pipelines will allow us to meet these challenges. Modern GPUs contain hundreds of processing cores, each of which can process hundreds of threads concurrently. Technologies such as Nvidia's Compute Unified Device Architecture (CUDA) platform and the PyCUDA (http://mathema.tician.de/software/pycuda) module for Python allow us to write parallel algorithms and easily link GPU-optimized code into existing data pipeline frameworks. This approach has produced speed gains of over a factor of 100 compared to CPU implementations for individual algorithms and overall pipeline speed gains of a factor of 10-25 compared to traditionally built data pipelines for both imaging and spectroscopy (Warner et al., 2011). However, there are still many bottlenecks inherent in the design of traditional data pipelines. For instance, file input/output of intermediate steps is now a significant portion of the overall processing time. In addition, most traditional pipelines are not designed to be able to process data on-the-fly in real time. We present a model for a next-generation data pipeline that has the flexibility to process data in near real-time at the observatory as well as to automatically process huge archives of past data by using a simple XML configuration file. XML is ideal for describing both the dataset and the processes that will be applied to the data. Meta-data for the datasets would be stored using an RDBMS (such as mysql or PostgreSQL) which could be easily and rapidly queried and file I/O would be kept at a minimum. We believe this redefined data pipeline will be able to process data at the telescope, concurrent with continuing observations, thus maximizing precious observing time and optimizing the observational process in general. We also believe that using this design, it is possible to obtain a speed gain of a factor of 30-40 over traditional data pipelines when processing large archives of data.

Comparison of fMRI data analysis by SPM99 on different operating systems.

PubMed

Shinagawa, Hideo; Honda, Ei-ichi; Ono, Takashi; Kurabayashi, Tohru; Ohyama, Kimie

2004-09-01

The hardware chosen for fMRI data analysis may depend on the platform already present in the laboratory or the supporting software. In this study, we ran SPM99 software on multiple platforms to examine whether we could analyze fMRI data by SPM99, and to compare their differences and limitations in processing fMRI data, which can be attributed to hardware capabilities. Six normal right-handed volunteers participated in a study of hand-grasping to obtain fMRI data. Each subject performed a run that consisted of 98 images. The run was measured using a gradient echo-type echo planar imaging sequence on a 1.5T apparatus with a head coil. We used several personal computer (PC), Unix and Linux machines to analyze the fMRI data. There were no differences in the results obtained on several PC, Unix and Linux machines. The only limitations in processing large amounts of the fMRI data were found using PC machines. This suggests that the results obtained with different machines were not affected by differences in hardware components, such as the CPU, memory and hard drive. Rather, it is likely that the limitations in analyzing a huge amount of the fMRI data were due to differences in the operating system (OS).

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

PubMed Central

Sherwood, Matthew S.; Diller, Emily E.; Ey, Elizabeth; Ganapathy, Subhashini; Nelson, Jeremy T.; Parker, Jason G.

2017-01-01

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain. PMID:28872110

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training.

PubMed

Sherwood, Matthew S; Diller, Emily E; Ey, Elizabeth; Ganapathy, Subhashini; Nelson, Jeremy T; Parker, Jason G

2017-08-24

Neurologic disorders are characterized by abnormal cellular-, molecular-, and circuit-level functions in the brain. New methods to induce and control neuroplastic processes and correct abnormal function, or even shift functions from damaged tissue to physiologically healthy brain regions, hold the potential to dramatically improve overall health. Of the current neuroplastic interventions in development, neurofeedback training (NFT) from functional Magnetic Resonance Imaging (fMRI) has the advantages of being completely non-invasive, non-pharmacologic, and spatially localized to target brain regions, as well as having no known side effects. Furthermore, NFT techniques, initially developed using fMRI, can often be translated to exercises that can be performed outside of the scanner without the aid of medical professionals or sophisticated medical equipment. In fMRI NFT, the fMRI signal is measured from specific regions of the brain, processed, and presented to the participant in real-time. Through training, self-directed mental processing techniques, that regulate this signal and its underlying neurophysiologic correlates, are developed. FMRI NFT has been used to train volitional control over a wide range of brain regions with implications for several different cognitive, behavioral, and motor systems. Additionally, fMRI NFT has shown promise in a broad range of applications such as the treatment of neurologic disorders and the augmentation of baseline human performance. In this article, we present an fMRI NFT protocol developed at our institution for modulation of both healthy and abnormal brain function, as well as examples of using the method to target both cognitive and auditory regions of the brain.

Fixation-related FMRI analysis in the domain of reading research: using self-paced eye movements as markers for hemodynamic brain responses during visual letter string processing.

PubMed

Richlan, Fabio; Gagl, Benjamin; Hawelka, Stefan; Braun, Mario; Schurz, Matthias; Kronbichler, Martin; Hutzler, Florian

2014-10-01

The present study investigated the feasibility of using self-paced eye movements during reading (measured by an eye tracker) as markers for calculating hemodynamic brain responses measured by functional magnetic resonance imaging (fMRI). Specifically, we were interested in whether the fixation-related fMRI analysis approach was sensitive enough to detect activation differences between reading material (words and pseudowords) and nonreading material (line and unfamiliar Hebrew strings). Reliable reading-related activation was identified in left hemisphere superior temporal, middle temporal, and occipito-temporal regions including the visual word form area (VWFA). The results of the present study are encouraging insofar as fixation-related analysis could be used in future fMRI studies to clarify some of the inconsistent findings in the literature regarding the VWFA. Our study is the first step in investigating specific visual word recognition processes during self-paced natural sentence reading via simultaneous eye tracking and fMRI, thus aiming at an ecologically valid measurement of reading processes. We provided the proof of concept and methodological framework for the analysis of fixation-related fMRI activation in the domain of reading research. © The Author 2013. Published by Oxford University Press.

Self-Referential Processing of Negative Stimuli within the Ventral Anterior Cingulate Gyrus and Right Amygdala

ERIC Educational Resources Information Center

Yoshimura, Shinpei; Ueda, Kazutaka; Suzuki, Shin-ichi; Onoda, Keiichi; Okamoto, Yasumasa; Yamawaki, Shigeto

2009-01-01

Neural activity associated with self-referential processing of emotional stimuli was investigated using whole brain functional magnetic resonance imaging (fMRI). Fifteen healthy subjects underwent fMRI scanning while making judgments about positive and negative trait words in four conditions (self-reference, other-reference, semantic processing,…

Corral framework: Trustworthy and fully functional data intensive parallel astronomical pipelines

NASA Astrophysics Data System (ADS)

Cabral, J. B.; Sánchez, B.; Beroiz, M.; Domínguez, M.; Lares, M.; Gurovich, S.; Granitto, P.

2017-07-01

Data processing pipelines represent an important slice of the astronomical software library that include chains of processes that transform raw data into valuable information via data reduction and analysis. In this work we present Corral, a Python framework for astronomical pipeline generation. Corral features a Model-View-Controller design pattern on top of an SQL Relational Database capable of handling: custom data models; processing stages; and communication alerts, and also provides automatic quality and structural metrics based on unit testing. The Model-View-Controller provides concept separation between the user logic and the data models, delivering at the same time multi-processing and distributed computing capabilities. Corral represents an improvement over commonly found data processing pipelines in astronomysince the design pattern eases the programmer from dealing with processing flow and parallelization issues, allowing them to focus on the specific algorithms needed for the successive data transformations and at the same time provides a broad measure of quality over the created pipeline. Corral and working examples of pipelines that use it are available to the community at https://github.com/toros-astro.

Fully automated rodent brain MR image processing pipeline on a Midas server: from acquired images to region-based statistics.

PubMed

Budin, Francois; Hoogstoel, Marion; Reynolds, Patrick; Grauer, Michael; O'Leary-Moore, Shonagh K; Oguz, Ipek

2013-01-01

Magnetic resonance imaging (MRI) of rodent brains enables study of the development and the integrity of the brain under certain conditions (alcohol, drugs etc.). However, these images are difficult to analyze for biomedical researchers with limited image processing experience. In this paper we present an image processing pipeline running on a Midas server, a web-based data storage system. It is composed of the following steps: rigid registration, skull-stripping, average computation, average parcellation, parcellation propagation to individual subjects, and computation of region-based statistics on each image. The pipeline is easy to configure and requires very little image processing knowledge. We present results obtained by processing a data set using this pipeline and demonstrate how this pipeline can be used to find differences between populations.

Research on numerical simulation and protection of transient process in long-distance slurry transportation pipelines

NASA Astrophysics Data System (ADS)

Lan, G.; Jiang, J.; Li, D. D.; Yi, W. S.; Zhao, Z.; Nie, L. N.

2013-12-01

The calculation of water-hammer pressure phenomenon of single-phase liquid is already more mature for a pipeline of uniform characteristics, but less research has addressed the calculation of slurry water hammer pressure in complex pipelines with slurry flows carrying solid particles. In this paper, based on the developments of slurry pipelines at home and abroad, the fundamental principle and method of numerical simulation of transient processes are presented, and several boundary conditions are given. Through the numerical simulation and analysis of transient processes of a practical engineering of long-distance slurry transportation pipeline system, effective protection measures and operating suggestions are presented. A model for calculating the water impact of solid and fluid phases is established based on a practical engineering of long-distance slurry pipeline transportation system. After performing a numerical simulation of the transient process, analyzing and comparing the results, effective protection measures and operating advice are recommended, which has guiding significance to the design and operating management of practical engineering of longdistance slurry pipeline transportation system.

77 FR 15455 - Notice of Delays in Processing of Special Permits Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-15

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration Notice of Delays in Processing of Special Permits Applications AGENCY: Pipeline and Hazardous Materials Safety... and Approvals, Pipeline and Hazardous Materials Safety Administration, U.S. Department of...

BigDataScript: a scripting language for data pipelines.

PubMed

Cingolani, Pablo; Sladek, Rob; Blanchette, Mathieu

2015-01-01

The analysis of large biological datasets often requires complex processing pipelines that run for a long time on large computational infrastructures. We designed and implemented a simple script-like programming language with a clean and minimalist syntax to develop and manage pipeline execution and provide robustness to various types of software and hardware failures as well as portability. We introduce the BigDataScript (BDS) programming language for data processing pipelines, which improves abstraction from hardware resources and assists with robustness. Hardware abstraction allows BDS pipelines to run without modification on a wide range of computer architectures, from a small laptop to multi-core servers, server farms, clusters and clouds. BDS achieves robustness by incorporating the concepts of absolute serialization and lazy processing, thus allowing pipelines to recover from errors. By abstracting pipeline concepts at programming language level, BDS simplifies implementation, execution and management of complex bioinformatics pipelines, resulting in reduced development and debugging cycles as well as cleaner code. BigDataScript is available under open-source license at http://pcingola.github.io/BigDataScript. © The Author 2014. Published by Oxford University Press.

BigDataScript: a scripting language for data pipelines

PubMed Central

Cingolani, Pablo; Sladek, Rob; Blanchette, Mathieu

2015-01-01

Motivation: The analysis of large biological datasets often requires complex processing pipelines that run for a long time on large computational infrastructures. We designed and implemented a simple script-like programming language with a clean and minimalist syntax to develop and manage pipeline execution and provide robustness to various types of software and hardware failures as well as portability. Results: We introduce the BigDataScript (BDS) programming language for data processing pipelines, which improves abstraction from hardware resources and assists with robustness. Hardware abstraction allows BDS pipelines to run without modification on a wide range of computer architectures, from a small laptop to multi-core servers, server farms, clusters and clouds. BDS achieves robustness by incorporating the concepts of absolute serialization and lazy processing, thus allowing pipelines to recover from errors. By abstracting pipeline concepts at programming language level, BDS simplifies implementation, execution and management of complex bioinformatics pipelines, resulting in reduced development and debugging cycles as well as cleaner code. Availability and implementation: BigDataScript is available under open-source license at http://pcingola.github.io/BigDataScript. Contact: pablo.e.cingolani@gmail.com PMID:25189778

Combining fMRI and behavioral measures to examine the process of human learning.

PubMed

Karuza, Elisabeth A; Emberson, Lauren L; Aslin, Richard N

2014-03-01

Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning. Copyright © 2013 Elsevier Inc. All rights reserved.

Combining fMRI and Behavioral Measures to Examine the Process of Human Learning

PubMed Central

Karuza, Elisabeth A.; Emberson, Lauren L.; Aslin, Richard N.

2013-01-01

Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning. PMID:24076012

78 FR 53751 - Dominion NGL Pipelines, LLC; Notice of Petition for Declaratory Order

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-30

... new ethane pipeline (Natrium Ethane Pipeline) extending from a new natural gas processing and... utilize, or pay for, significant capacity on the Natrium Ethane Pipeline (Committed Shipper); and (3) the...

49 CFR 192.937 - What is a continual process of evaluation and assessment to maintain a pipeline's integrity?

Code of Federal Regulations, 2010 CFR

2010-10-01

... Relating to Transportation (Continued) PIPELINE AND HAZARDOUS MATERIALS SAFETY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) PIPELINE SAFETY TRANSPORTATION OF NATURAL AND OTHER GAS BY PIPELINE: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.937 What is a...

Breaking down the barriers: fMRI applications in pain, analgesia and analgesics

PubMed Central

Borsook, David; Becerra, Lino R

2006-01-01

This review summarizes functional magnetic resonance imaging (fMRI) findings that have informed our current understanding of pain, analgesia and related phenomena, and discusses the potential role of fMRI in improved therapeutic approaches to pain. It is divided into 3 main sections: (1) fMRI studies of acute and chronic pain. Physiological studies of pain have found numerous regions of the brain to be involved in the interpretation of the 'pain experience'; studies in chronic pain conditions have identified a significant CNS component; and fMRI studies of surrogate models of chronic pain are also being used to further this understanding. (2) fMRI studies of endogenous pain processing including placebo, empathy, attention or cognitive modulation of pain. (3) The use of fMRI to evaluate the effects of analgesics on brain function in acute and chronic pain. fMRI has already provided novel insights into the neurobiology of pain. These insights should significantly advance therapeutic approaches to chronic pain. PMID:16982005

Functional Brain Activation Differences in Stuttering Identified with a Rapid fMRI Sequence

ERIC Educational Resources Information Center

Loucks, Torrey; Kraft, Shelly Jo; Choo, Ai Leen; Sharma, Harish; Ambrose, Nicoline G.

2011-01-01

The purpose of this study was to investigate whether brain activity related to the presence of stuttering can be identified with rapid functional MRI (fMRI) sequences that involved overt and covert speech processing tasks. The long-term goal is to develop sensitive fMRI approaches with developmentally appropriate tasks to identify deviant speech…

Cortical processing of pitch: Model-based encoding and decoding of auditory fMRI responses to real-life sounds.

PubMed

De Angelis, Vittoria; De Martino, Federico; Moerel, Michelle; Santoro, Roberta; Hausfeld, Lars; Formisano, Elia

2017-11-13

Pitch is a perceptual attribute related to the fundamental frequency (or periodicity) of a sound. So far, the cortical processing of pitch has been investigated mostly using synthetic sounds. However, the complex harmonic structure of natural sounds may require different mechanisms for the extraction and analysis of pitch. This study investigated the neural representation of pitch in human auditory cortex using model-based encoding and decoding analyses of high field (7 T) functional magnetic resonance imaging (fMRI) data collected while participants listened to a wide range of real-life sounds. Specifically, we modeled the fMRI responses as a function of the sounds' perceived pitch height and salience (related to the fundamental frequency and the harmonic structure respectively), which we estimated with a computational algorithm of pitch extraction (de Cheveigné and Kawahara, 2002). First, using single-voxel fMRI encoding, we identified a pitch-coding region in the antero-lateral Heschl's gyrus (HG) and adjacent superior temporal gyrus (STG). In these regions, the pitch representation model combining height and salience predicted the fMRI responses comparatively better than other models of acoustic processing and, in the right hemisphere, better than pitch representations based on height/salience alone. Second, we assessed with model-based decoding that multi-voxel response patterns of the identified regions are more informative of perceived pitch than the remainder of the auditory cortex. Further multivariate analyses showed that complementing a multi-resolution spectro-temporal sound representation with pitch produces a small but significant improvement to the decoding of complex sounds from fMRI response patterns. In sum, this work extends model-based fMRI encoding and decoding methods - previously employed to examine the representation and processing of acoustic sound features in the human auditory system - to the representation and processing of a relevant perceptual attribute such as pitch. Taken together, the results of our model-based encoding and decoding analyses indicated that the pitch of complex real life sounds is extracted and processed in lateral HG/STG regions, at locations consistent with those indicated in several previous fMRI studies using synthetic sounds. Within these regions, pitch-related sound representations reflect the modulatory combination of height and the salience of the pitch percept. Copyright © 2017 Elsevier Inc. All rights reserved.

A Novel Functional Magnetic Resonance Imaging Paradigm for the Preoperative Assessment of Auditory Perception in a Musician Undergoing Temporal Lobe Surgery.

PubMed

Hale, Matthew D; Zaman, Arshad; Morrall, Matthew C H J; Chumas, Paul; Maguire, Melissa J

2018-03-01

Presurgical evaluation for temporal lobe epilepsy routinely assesses speech and memory lateralization and anatomic localization of the motor and visual areas but not baseline musical processing. This is paramount in a musician. Although validated tools exist to assess musical ability, there are no reported functional magnetic resonance imaging (fMRI) paradigms to assess musical processing. We examined the utility of a novel fMRI paradigm in an 18-year-old left-handed pianist who underwent surgery for a left temporal low-grade ganglioglioma. Preoperative evaluation consisted of neuropsychological evaluation, T1-weighted and T2-weighted magnetic resonance imaging, and fMRI. Auditory blood oxygen level-dependent fMRI was performed using a dedicated auditory scanning sequence. Three separate auditory investigations were conducted: listening to, humming, and thinking about a musical piece. All auditory fMRI paradigms activated the primary auditory cortex with varying degrees of auditory lateralization. Thinking about the piece additionally activated the primary visual cortices (bilaterally) and right dorsolateral prefrontal cortex. Humming demonstrated left-sided predominance of auditory cortex activation with activity observed in close proximity to the tumor. This study demonstrated an fMRI paradigm for evaluating musical processing that could form part of preoperative assessment for patients undergoing temporal lobe surgery for epilepsy. Copyright © 2017 Elsevier Inc. All rights reserved.

75 FR 5167 - Office of Hazardous Materials Safety; Notice of Delays In Processing of Special Permits Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-01

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration Office of Hazardous Materials Safety; Notice of Delays In Processing of Special Permits Applications AGENCY: Pipeline..., Office of Hazardous Materials Special Permits and Approvals, Pipeline and Hazardous Materials Safety...

75 FR 78800 - Office of Hazardous Materials Safety; Notice of Delays in Processing of Special Permits Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-16

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration Office of Hazardous Materials Safety; Notice of Delays in Processing of Special Permits Applications AGENCY: Pipeline..., Office of Hazardous Materials Special Permits and Approvals, Pipeline and Hazardous Materials Safety...

The ALMA Science Pipeline: Current Status

NASA Astrophysics Data System (ADS)

Humphreys, Elizabeth; Miura, Rie; Brogan, Crystal L.; Hibbard, John; Hunter, Todd R.; Indebetouw, Remy

2016-09-01

The ALMA Science Pipeline is being developed for the automated calibration and imaging of ALMA interferometric and single-dish data. The calibration Pipeline for interferometric data was accepted for use by ALMA Science Operations in 2014, and for single-dish data end-to-end processing in 2015. However, work is ongoing to expand the use cases for which the Pipeline can be used e.g. for higher frequency and lower signal-to-noise datasets, and for new observing modes. A current focus includes the commissioning of science target imaging for interferometric data. For the Single Dish Pipeline, the line finding algorithm used in baseline subtraction and baseline flagging heuristics have been greately improved since the prototype used for data from the previous cycle. These algorithms, unique to the Pipeline, produce better results than standard manual processing in many cases. In this poster, we report on the current status of the Pipeline capabilities, present initial results from the Imaging Pipeline, and the smart line finding and flagging algorithm used in the Single Dish Pipeline. The Pipeline is released as part of CASA (the Common Astronomy Software Applications package).

The Stroop Effect in Kana and Kanji Scripts in Native Japanese Speakers: An fMRI Study

PubMed Central

Coderre, Emily L.; Filippi, Christopher G.; Newhouse, Paul A.; Dumas, Julie A.

2008-01-01

Prior research has shown that the two writing systems of the Japanese orthography are processed differently: kana (syllabic symbols) are processed like other phonetic languages such as English, while kanji (a logographic writing system) are processed like other logographic languages like Chinese. Previous work done with the Stroop task in Japanese has shown that these differences in processing strategies create differences in Stroop effects. This study investigated the Stroop effect in kanji and kana using functional magnetic resonance imaging (fMRI) to examine the similarities and differences in brain processing between logographic and phonetic languages. Nine native Japanese speakers performed the Stroop task both in kana and kanji scripts during fMRI. Both scripts individually produced significant Stroop effects as measured by the behavioral reaction time data. The imaging data for both scripts showed brain activation in the anterior cingulate gyrus, an area involved in inhibiting automatic processing. Though behavioral data showed no significant differences between the Stroop effects in kana and kanji, there were differential areas of activation in fMRI found for each writing system. In fMRI, the Stroop task activated an area in the left inferior parietal lobule during the kana task and the left inferior frontal gyrus during the kanji task. The results of the present study suggest that the Stroop task in Japanese kana and kanji elicits differential activation in brain regions involved in conflict detection and resolution for syllabic and logographic writing systems. PMID:18325582

Item Memory, Context Memory and the Hippocampus: fMRI Evidence

ERIC Educational Resources Information Center

Rugg, Michael D.; Vilberg, Kaia L.; Mattson, Julia T.; Yu, Sarah S.; Johnson, Jeffrey D.; Suzuki, Maki

2012-01-01

Dual-process models of recognition memory distinguish between the retrieval of qualitative information about a prior event (recollection), and judgments of prior occurrence based on an acontextual sense of familiarity. fMRI studies investigating the neural correlates of memory encoding and retrieval conducted within the dual-process framework have…

Neural Correlates of Metonymy Resolution

ERIC Educational Resources Information Center

Rapp, Alexander M.; Erb, Michael; Grodd, Wolfgang; Bartels, Mathias; Markert, Katja

2011-01-01

Metonymies are exemplary models for complex semantic association processes at the sentence level. We investigated processing of metonymies using event-related functional magnetic resonance imaging (fMRI). During an 1.5 Tesla fMRI scan, 14 healthy subjects (12 female) read 124 short German sentences with either literal (like "Africa is arid"),…

Resting-state fMRI and social cognition: An opportunity to connect.

PubMed

Doruyter, Alex; Groenewold, Nynke A; Dupont, Patrick; Stein, Dan J; Warwick, James M

2017-09-01

Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain. Copyright © 2017 John Wiley & Sons, Ltd.

Functional quantitative susceptibility mapping (fQSM).

PubMed

Balla, Dávid Z; Sanchez-Panchuelo, Rosa M; Wharton, Samuel J; Hagberg, Gisela E; Scheffler, Klaus; Francis, Susan T; Bowtell, Richard

2014-10-15

Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a powerful technique, typically based on the statistical analysis of the magnitude component of the complex time-series. Here, we additionally interrogated the phase data of the fMRI time-series and used quantitative susceptibility mapping (QSM) in order to investigate the potential of functional QSM (fQSM) relative to standard magnitude BOLD fMRI. High spatial resolution data (1mm isotropic) were acquired every 3 seconds using zoomed multi-slice gradient-echo EPI collected at 7 T in single orientation (SO) and multiple orientation (MO) experiments, the latter involving 4 repetitions with the subject's head rotated relative to B0. Statistical parametric maps (SPM) were reconstructed for magnitude, phase and QSM time-series and each was subjected to detailed analysis. Several fQSM pipelines were evaluated and compared based on the relative number of voxels that were coincidentally found to be significant in QSM and magnitude SPMs (common voxels). We found that sensitivity and spatial reliability of fQSM relative to the magnitude data depended strongly on the arbitrary significance threshold defining "activated" voxels in SPMs, and on the efficiency of spatio-temporal filtering of the phase time-series. Sensitivity and spatial reliability depended slightly on whether MO or SO fQSM was performed and on the QSM calculation approach used for SO data. Our results present the potential of fQSM as a quantitative method of mapping BOLD changes. We also critically discuss the technical challenges and issues linked to this intriguing new technique. Copyright © 2014 Elsevier Inc. All rights reserved.

Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

The role of fMRI in cognitive neuroscience: where do we stand?

PubMed

Poldrack, Russell A

2008-04-01

Functional magnetic resonance imaging (fMRI) has quickly become the most prominent tool in cognitive neuroscience. In this article, I outline some of the limits on the kinds of inferences that can be supported by fMRI, focusing particularly on reverse inference, in which the engagement of specific mental processes is inferred from patterns of brain activation. Although this form of inference is weak, newly developed methods from the field of machine learning offer the potential to formalize and strengthen reverse inferences. I conclude by discussing the increasing presence of fMRI results in the popular media and the ethical implications of the increasing predictive power of fMRI.

SUPRA: open-source software-defined ultrasound processing for real-time applications : A 2D and 3D pipeline from beamforming to B-mode.

PubMed

Göbl, Rüdiger; Navab, Nassir; Hennersperger, Christoph

2018-06-01

Research in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of code difficult. Second, most pipelines are implemented in special hardware, resulting in limited flexibility of implemented processing steps on such platforms. With SUPRA, we propose an open-source pipeline for fully software-defined ultrasound processing for real-time applications to alleviate these problems. Covering all steps from beamforming to output of B-mode images, SUPRA can help improve the reproducibility of results and make modifications to the image acquisition mode accessible to the research community. We evaluate the pipeline qualitatively, quantitatively, and regarding its run time. The pipeline shows image quality comparable to a clinical system and backed by point spread function measurements a comparable resolution. Including all processing stages of a usual ultrasound pipeline, the run-time analysis shows that it can be executed in 2D and 3D on consumer GPUs in real time. Our software ultrasound pipeline opens up the research in image acquisition. Given access to ultrasound data from early stages (raw channel data, radiofrequency data), it simplifies the development in imaging. Furthermore, it tackles the reproducibility of research results, as code can be shared easily and even be executed without dedicated ultrasound hardware.

Development of Protective Coatings for Co-Sequestration Processes and Pipelines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bierwagen, Gordon; Huang, Yaping

2011-11-30

The program, entitled Development of Protective Coatings for Co-Sequestration Processes and Pipelines, examined the sensitivity of existing coating systems to supercritical carbon dioxide (SCCO2) exposure and developed new coating system to protect pipelines from their corrosion under SCCO2 exposure. A literature review was also conducted regarding pipeline corrosion sensors to monitor pipes used in handling co-sequestration fluids. Research was to ensure safety and reliability for a pipeline involving transport of SCCO2 from the power plant to the sequestration site to mitigate the greenhouse gas effect. Results showed that one commercial coating and one designed formulation can both be supplied asmore » potential candidates for internal pipeline coating to transport SCCO2.« less

An integrated SNP mining and utilization (ISMU) pipeline for next generation sequencing data.

PubMed

Azam, Sarwar; Rathore, Abhishek; Shah, Trushar M; Telluri, Mohan; Amindala, BhanuPrakash; Ruperao, Pradeep; Katta, Mohan A V S K; Varshney, Rajeev K

2014-01-01

Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.

The neuroscience of investing: fMRI of the reward system.

PubMed

Peterson, Richard L

2005-11-15

Functional magnetic resonance imaging (fMRI) has proven a useful tool for observing neural BOLD signal changes during complex cognitive and emotional tasks. Yet the meaning and applicability of the fMRI data being gathered is still largely unknown. The brain's reward system underlies the fundamental neural processes of goal evaluation, preference formation, positive motivation, and choice behavior. fMRI technology allows researchers to dynamically visualize reward system processes. Experimenters can then correlate reward system BOLD activations with experimental behavior from carefully controlled experiments. In the SPAN lab at Stanford University, directed by Brian Knutson Ph.D., researchers have been using financial tasks during fMRI scanning to correlate emotion, behavior, and cognition with the reward system's fundamental neural activations. One goal of the SPAN lab is the development of predictive models of behavior. In this paper we extrapolate our fMRI results toward understanding and predicting individual behavior in the uncertain and high-risk environment of the financial markets. The financial market price anomalies of "value versus glamour" and "momentum" may be real-world examples of reward system activation biasing collective behavior. On the individual level, the investor's bias of overconfidence may similarly be related to reward system activation. We attempt to understand selected "irrational" investor behaviors and anomalous financial market price patterns through correlations with findings from fMRI research of the reward system.

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks

PubMed Central

Mantini, D.; Marzetti, L.; Corbetta, M.; Romani, G.L.; Del Gratta, C.

2017-01-01

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes. PMID:20052528

A distributed pipeline for DIDSON data processing

USGS Publications Warehouse

Li, Liling; Danner, Tyler; Eickholt, Jesse; McCann, Erin L.; Pangle, Kevin; Johnson, Nicholas

2018-01-01

Technological advances in the field of ecology allow data on ecological systems to be collected at high resolution, both temporally and spatially. Devices such as Dual-frequency Identification Sonar (DIDSON) can be deployed in aquatic environments for extended periods and easily generate several terabytes of underwater surveillance data which may need to be processed multiple times. Due to the large amount of data generated and need for flexibility in processing, a distributed pipeline was constructed for DIDSON data making use of the Hadoop ecosystem. The pipeline is capable of ingesting raw DIDSON data, transforming the acoustic data to images, filtering the images, detecting and extracting motion, and generating feature data for machine learning and classification. All of the tasks in the pipeline can be run in parallel and the framework allows for custom processing. Applications of the pipeline include monitoring migration times, determining the presence of a particular species, estimating population size and other fishery management tasks.

The Kepler Science Data Processing Pipeline Source Code Road Map

NASA Technical Reports Server (NTRS)

Wohler, Bill; Jenkins, Jon M.; Twicken, Joseph D.; Bryson, Stephen T.; Clarke, Bruce Donald; Middour, Christopher K.; Quintana, Elisa Victoria; Sanderfer, Jesse Thomas; Uddin, Akm Kamal; Sabale, Anima;

Risk Analysis using Corrosion Rate Parameter on Gas Transmission Pipeline

NASA Astrophysics Data System (ADS)

Sasikirono, B.; Kim, S. J.; Haryadi, G. D.; Huda, A.

2017-05-01

In the oil and gas industry, the pipeline is a major component in the transmission and distribution process of oil and gas. Oil and gas distribution process sometimes performed past the pipeline across the various types of environmental conditions. Therefore, in the transmission and distribution process of oil and gas, a pipeline should operate safely so that it does not harm the surrounding environment. Corrosion is still a major cause of failure in some components of the equipment in a production facility. In pipeline systems, corrosion can cause failures in the wall and damage to the pipeline. Therefore it takes care and periodic inspections or checks on the pipeline system. Every production facility in an industry has a level of risk for damage which is a result of the opportunities and consequences of damage caused. The purpose of this research is to analyze the level of risk of 20-inch Natural Gas Transmission Pipeline using Risk-based inspection semi-quantitative based on API 581 associated with the likelihood of failure and the consequences of the failure of a component of the equipment. Then the result is used to determine the next inspection plans. Nine pipeline components were observed, such as a straight pipes inlet, connection tee, and straight pipes outlet. The risk assessment level of the nine pipeline’s components is presented in a risk matrix. The risk level of components is examined at medium risk levels. The failure mechanism that is used in this research is the mechanism of thinning. Based on the results of corrosion rate calculation, remaining pipeline components age can be obtained, so the remaining lifetime of pipeline components are known. The calculation of remaining lifetime obtained and the results vary for each component. Next step is planning the inspection of pipeline components by NDT external methods.

Attention and Semantic Processing during Speech: An fMRI Study

ERIC Educational Resources Information Center

Rama, Pia; Relander-Syrjanen, Kristiina; Carlson, Synnove; Salonen, Oili; Kujala, Teija

2012-01-01

This fMRI study was conducted to investigate whether language semantics is processed even when attention is not explicitly directed to word meanings. In the "unattended" condition, the subjects performed a visual detection task while hearing semantically related and unrelated word pairs. In the "phoneme" condition, the subjects made phoneme…

Methodology for reducing energy and resource costs in construction of trenchless crossover of pipelines

NASA Astrophysics Data System (ADS)

Toropov, V. S.

2018-05-01

The paper suggests a set of measures to select the equipment and its components in order to reduce energy costs in the process of pulling the pipeline into the well in the constructing the trenchless pipeline crossings of various materials using horizontal directional drilling technology. A methodology for reducing energy costs has been developed by regulating the operation modes of equipment during the process of pulling the working pipeline into a drilled and pre-expanded well. Since the power of the drilling rig is the most important criterion in the selection of equipment for the construction of a trenchless crossover, an algorithm is proposed for calculating the required capacity of the rig when operating in different modes in the process of pulling the pipeline into the well.

Increased fMRI signal with age in familial Alzheimer’s disease mutation carriers

PubMed Central

Braskie, Meredith N.; Medina, Luis D.; Rodriguez-Agudelo, Yaneth; Geschwind, Daniel H.; Macias-Islas, Miguel Angel; Cummings, Jeffrey L.; Bookheimer, Susan Y.; Ringman, John M.

2010-01-01

Although many Alzheimer’s disease (AD) patients have a family history of the disease, it is rarely inherited in a predictable way. Functional magnetic resonance imaging (fMRI) studies of non-demented adults carrying familial AD mutations provide an opportunity to prospectively identify brain differences associated with early AD-related changes. We compared fMRI activity of 18 non-demented autosomal dominant AD mutation carriers with fMRI activity in 8 of their non-carrier relatives as they performed a novelty encoding task in which they viewed novel and repeated images. Because age of disease onset is relatively consistent within families, we also correlated fMRI activity with subjects’ distance from the median age of diagnosis for their family. Mutation carriers did not show significantly different voxelwise fMRI activity from non-carriers as a group. However, as they approached their family age of disease diagnosis, only mutation carriers showed increased fMRI activity in the fusiform and middle temporal gyri. This suggests that during novelty encoding, increased fMRI activity in the temporal lobe may relate to incipient AD processes. PMID:21129823

Future trends in Neuroimaging: Neural processes as expressed within real-life contexts

PubMed Central

Hasson, Uri; Honey, Christopher J.

2012-01-01

Human neuroscience research has changed dramatically with the proliferation and refinement of functional magnetic resonance imaging (fMRI) technologies. The early years of the technique were largely devoted to methods development and validation, and to the coarse-grained mapping of functional topographies. This paper will cover three emerging trends that we believe will be central to fMRI research in the coming decade. In the first section of this paper, we argue in favor of a shift from fine-grained functional labeling toward the characterization of underlying neural processes. In the second section, we examine three methodological developments that have improved our ability to characterize underlying neural processes using fMRI. In the last section, we highlight the trend towards more ecologically valid fMRI experiments, which engage neural circuits in real life conditions. We note that many of our cognitive faculties emerge from interpersonal interactions, and that a complete understanding of the cognitive processes within a single individual's brain cannot be achieved without understanding the interactions among individuals. Looking forward to the future of human fMRI, we conclude that the major constraint on new discoveries will not be related to the spatiotemporal resolution of the BOLD signal, which is constantly improving, but rather to the precision of our hypotheses and the creativity of our methods for testing them. PMID:22348879

DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.

PubMed

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-08-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/.

DDBJ Read Annotation Pipeline: A Cloud Computing-Based Pipeline for High-Throughput Analysis of Next-Generation Sequencing Data

PubMed Central

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-01-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/. PMID:23657089

Comparing diffuse optical tomography and functional magnetic resonance imaging signals during a cognitive task: pilot study

PubMed Central

Hernández-Martin, Estefania; Marcano, Francisco; Casanova, Oscar; Modroño, Cristian; Plata-Bello, Julio; González-Mora, Jose Luis

2017-01-01

Abstract. Diffuse optical tomography (DOT) measures concentration changes in both oxy- and deoxyhemoglobin providing three-dimensional images of local brain activations. A pilot study, which compares both DOT and functional magnetic resonance imaging (fMRI) volumes through t-maps given by canonical statistical parametric mapping (SPM) processing for both data modalities, is presented. The DOT series were processed using a method that is based on a Bayesian filter application on raw DOT data to remove physiological changes and minimum description length application index to select a number of singular values, which reduce the data dimensionality during image reconstruction and adaptation of DOT volume series to normalized standard space. Therefore, statistical analysis is performed with canonical SPM software in the same way as fMRI analysis is done, accepting DOT volumes as if they were fMRI volumes. The results show the reproducibility and ruggedness of the method to process DOT series on group analysis using cognitive paradigms on the prefrontal cortex. Difficulties such as the fact that scalp–brain distances vary between subjects or cerebral activations are difficult to reproduce due to strategies used by the subjects to solve arithmetic problems are considered. T-images given by fMRI and DOT volume series analyzed in SPM show that at the functional level, both DOT and fMRI measures detect the same areas, although DOT provides complementary information to fMRI signals about cerebral activity. PMID:28386575

Text-based Analytics for Biosurveillance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Charles, Lauren E.; Smith, William P.; Rounds, Jeremiah

The ability to prevent, mitigate, or control a biological threat depends on how quickly the threat is identified and characterized. Ensuring the timely delivery of data and analytics is an essential aspect of providing adequate situational awareness in the face of a disease outbreak. This chapter outlines an analytic pipeline for supporting an advanced early warning system that can integrate multiple data sources and provide situational awareness of potential and occurring disease situations. The pipeline, includes real-time automated data analysis founded on natural language processing (NLP), semantic concept matching, and machine learning techniques, to enrich content with metadata related tomore » biosurveillance. Online news articles are presented as an example use case for the pipeline, but the processes can be generalized to any textual data. In this chapter, the mechanics of a streaming pipeline are briefly discussed as well as the major steps required to provide targeted situational awareness. The text-based analytic pipeline includes various processing steps as well as identifying article relevance to biosurveillance (e.g., relevance algorithm) and article feature extraction (who, what, where, why, how, and when). The ability to prevent, mitigate, or control a biological threat depends on how quickly the threat is identified and characterized. Ensuring the timely delivery of data and analytics is an essential aspect of providing adequate situational awareness in the face of a disease outbreak. This chapter outlines an analytic pipeline for supporting an advanced early warning system that can integrate multiple data sources and provide situational awareness of potential and occurring disease situations. The pipeline, includes real-time automated data analysis founded on natural language processing (NLP), semantic concept matching, and machine learning techniques, to enrich content with metadata related to biosurveillance. Online news articles are presented as an example use case for the pipeline, but the processes can be generalized to any textual data. In this chapter, the mechanics of a streaming pipeline are briefly discussed as well as the major steps required to provide targeted situational awareness. The text-based analytic pipeline includes various processing steps as well as identifying article relevance to biosurveillance (e.g., relevance algorithm) and article feature extraction (who, what, where, why, how, and when).« less

75 FR 35632 - Transparency Provisions of Section 23 of the Natural Gas Act

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-23

... pipeline- quality natural gas. For instance, some Respondents questioned whether pipeline-quality natural gas that is sold directly into an interstate or intrastate natural gas pipeline without processing... reported transactions of pipeline-quality gas under the assumption that ``unprocessed natural gas'' was...

Development and Applications of Pipeline Steel in Long-Distance Gas Pipeline of China

NASA Astrophysics Data System (ADS)

Chunyong, Huo; Yang, Li; Lingkang, Ji

In past decades, with widely utilizing of Microalloying and Thermal Mechanical Control Processing (TMCP) technology, the good matching of strength, toughness, plasticity and weldability on pipeline steel has been reached so that oil and gas pipeline has been greatly developed in China to meet the demand of strong domestic consumption of energy. In this paper, development history of pipeline steel and gas pipeline in china is briefly reviewed. The microstructure characteristic and mechanical performance of pipeline steel used in some representative gas pipelines of china built in different stage are summarized. Through the analysis on the evolution of pipeline service environment, some prospective development trend of application of pipeline steel in China is also presented.

TESS Data Processing and Quick-look Pipeline

NASA Astrophysics Data System (ADS)

Fausnaugh, Michael; Huang, Xu; Glidden, Ana; Guerrero, Natalia; TESS Science Office

2018-01-01

We describe the data analysis procedures and pipelines for the Transiting Exoplanet Survey Satellite (TESS). We briefly review the processing pipeline developed and implemented by the Science Processing Operations Center (SPOC) at NASA Ames, including pixel/full-frame image calibration, photometric analysis, pre-search data conditioning, transiting planet search, and data validation. We also describe data-quality diagnostic analyses and photometric performance assessment tests. Finally, we detail a "quick-look pipeline" (QLP) that has been developed by the MIT branch of the TESS Science Office (TSO) to provide a fast and adaptable routine to search for planet candidates in the 30 minute full-frame images.

ARTIP: Automated Radio Telescope Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Sharma, Ravi; Gyanchandani, Dolly; Kulkarni, Sarang; Gupta, Neeraj; Pathak, Vineet; Pande, Arti; Joshi, Unmesh

2018-02-01

The Automated Radio Telescope Image Processing Pipeline (ARTIP) automates the entire process of flagging, calibrating, and imaging for radio-interferometric data. ARTIP starts with raw data, i.e. a measurement set and goes through multiple stages, such as flux calibration, bandpass calibration, phase calibration, and imaging to generate continuum and spectral line images. Each stage can also be run independently. The pipeline provides continuous feedback to the user through various messages, charts and logs. It is written using standard python libraries and the CASA package. The pipeline can deal with datasets with multiple spectral windows and also multiple target sources which may have arbitrary combinations of flux/bandpass/phase calibrators.

77 FR 26760 - Kinder Morgan, Inc.; Analysis of Proposed Agreement Containing Consent Orders To Aid Public Comment

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-07

... to as natural gas liquids or NGLs. Interstate pipelines have a limit on how much NGLs natural gas can... gas processing plant to remove those liquids before it can be transported on interstate pipelines... Gas Transmission, and Trailblazer pipelines, as well as associated processing and storage capacity. On...

Laminar fMRI and computational theories of brain function.

PubMed

Stephan, K E; Petzschner, F H; Kasper, L; Bayer, J; Wellstein, K V; Stefanics, G; Pruessmann, K P; Heinzle, J

2017-11-02

Recently developed methods for functional MRI at the resolution of cortical layers (laminar fMRI) offer a novel window into neurophysiological mechanisms of cortical activity. Beyond physiology, laminar fMRI also offers an unprecedented opportunity to test influential theories of brain function. Specifically, hierarchical Bayesian theories of brain function, such as predictive coding, assign specific computational roles to different cortical layers. Combined with computational models, laminar fMRI offers a unique opportunity to test these proposals noninvasively in humans. This review provides a brief overview of predictive coding and related hierarchical Bayesian theories, summarises their predictions with regard to layered cortical computations, examines how these predictions could be tested by laminar fMRI, and considers methodological challenges. We conclude by discussing the potential of laminar fMRI for clinically useful computational assays of layer-specific information processing. Copyright © 2017 Elsevier Inc. All rights reserved.

Differences in Processing of Taxonomic and Sequential Relations in Semantic Memory: An fMRI Investigation

ERIC Educational Resources Information Center

Kuchinke, Lars; van der Meer, Elke; Krueger, Frank

2009-01-01

Conceptual knowledge of our world is represented in semantic memory in terms of concepts and semantic relations between concepts. We used functional magnetic resonance imaging (fMRI) to examine the cortical regions underlying the processing of sequential and taxonomic relations. Participants were presented verbal cues and performed three tasks:…

Functional Connectivity in an fMRI Study of Semantic and Phonological Processes and the Effect of L-Dopa

ERIC Educational Resources Information Center

Tivarus, Madalina E.; Hillier, Ashleigh; Schmalbrock, Petra; Beversdorf, David Q.

2008-01-01

We describe an fMRI experiment examining the functional connectivity (FC) between regions of the brain associated with semantic and phonological processing. We wished to explore whether L-Dopa administration affects the interaction between language network components in semantic and phonological categorization tasks, as revealed by FC. We…

Dual-Task Processing in Younger and Older Adults: Similarities and Differences Revealed by fMRI

ERIC Educational Resources Information Center

Hartley, Alan A.; Jonides, John; Sylvester, Ching-Yune C.

2011-01-01

fMRI was used to explore age differences in the neural substrate of dual-task processing. Brain activations when there was a 100 ms SOA between tasks, and task overlap was high, were contrasted with activations when there was a 1000 ms SOA, and first task processing was largely complete before the second task began. Younger adults (M = 21 yrs)…

Data as a Service: A Seismic Web Service Pipeline

NASA Astrophysics Data System (ADS)

Martinez, E.

2016-12-01

Publishing data as a service pipeline provides an improved, dynamic approach over static data archives. A service pipeline is a collection of micro web services that each perform a specific task and expose the results of that task. Structured request/response formats allow micro web services to be chained together into a service pipeline to provide more complex results. The U.S. Geological Survey adopted service pipelines to publish seismic hazard and design data supporting both specific and generalized audiences. The seismic web service pipeline starts at source data and exposes probability and deterministic hazard curves, response spectra, risk-targeted ground motions, and seismic design provision metadata. This pipeline supports public/private organizations and individual engineers/researchers. Publishing data as a service pipeline provides a variety of benefits. Exposing the component services enables advanced users to inspect or use the data at each processing step. Exposing a composite service enables new users quick access to published data with a very low barrier to entry. Advanced users may re-use micro web services by chaining them in new ways or injecting new micros services into the pipeline. This allows the user to test hypothesis and compare their results to published results. Exposing data at each step in the pipeline enables users to review and validate the data and process more quickly and accurately. Making the source code open source, per USGS policy, further enables this transparency. Each micro service may be scaled independent of any other micro service. This ensures data remains available and timely in a cost-effective manner regardless of load. Additionally, if a new or more efficient approach to processing the data is discovered, this new approach may replace the old approach at any time, keeping the pipeline running while not affecting other micro services.

Significantly reducing the processing times of high-speed photometry data sets using a distributed computing model

NASA Astrophysics Data System (ADS)

Doyle, Paul; Mtenzi, Fred; Smith, Niall; Collins, Adrian; O'Shea, Brendan

2012-09-01

The scientific community is in the midst of a data analysis crisis. The increasing capacity of scientific CCD instrumentation and their falling costs is contributing to an explosive generation of raw photometric data. This data must go through a process of cleaning and reduction before it can be used for high precision photometric analysis. Many existing data processing pipelines either assume a relatively small dataset or are batch processed by a High Performance Computing centre. A radical overhaul of these processing pipelines is required to allow reduction and cleaning rates to process terabyte sized datasets at near capture rates using an elastic processing architecture. The ability to access computing resources and to allow them to grow and shrink as demand fluctuates is essential, as is exploiting the parallel nature of the datasets. A distributed data processing pipeline is required. It should incorporate lossless data compression, allow for data segmentation and support processing of data segments in parallel. Academic institutes can collaborate and provide an elastic computing model without the requirement for large centralized high performance computing data centers. This paper demonstrates how a base 10 order of magnitude improvement in overall processing time has been achieved using the "ACN pipeline", a distributed pipeline spanning multiple academic institutes.

Numerical research on the lateral global buckling characteristics of a high temperature and pressure pipeline with two initial imperfections

PubMed Central

Liu, Wenbin; Liu, Aimin

2018-01-01

With the exploitation of offshore oil and gas gradually moving to deep water, higher temperature differences and pressure differences are applied to the pipeline system, making the global buckling of the pipeline more serious. For unburied deep-water pipelines, the lateral buckling is the major buckling form. The initial imperfections widely exist in the pipeline system due to manufacture defects or the influence of uneven seabed, and the distribution and geometry features of initial imperfections are random. They can be divided into two kinds based on shape: single-arch imperfections and double-arch imperfections. This paper analyzed the global buckling process of a pipeline with 2 initial imperfections by using a numerical simulation method and revealed how the ratio of the initial imperfection’s space length to the imperfection’s wavelength and the combination of imperfections affects the buckling process. The results show that a pipeline with 2 initial imperfections may suffer the superposition of global buckling. The growth ratios of buckling displacement, axial force and bending moment in the superposition zone are several times larger than no buckling superposition pipeline. The ratio of the initial imperfection’s space length to the imperfection’s wavelength decides whether a pipeline suffers buckling superposition. The potential failure point of pipeline exhibiting buckling superposition is as same as the no buckling superposition pipeline, but the failure risk of pipeline exhibiting buckling superposition is much higher. The shape and direction of two nearby imperfections also affects the failure risk of pipeline exhibiting global buckling superposition. The failure risk of pipeline with two double-arch imperfections is higher than pipeline with two single-arch imperfections. PMID:29554123

Using functional neuroimaging combined with a think-aloud protocol to explore clinical reasoning expertise in internal medicine.

PubMed

Durning, Steven J; Graner, John; Artino, Anthony R; Pangaro, Louis N; Beckman, Thomas; Holmboe, Eric; Oakes, Terrance; Roy, Michael; Riedy, Gerard; Capaldi, Vincent; Walter, Robert; van der Vleuten, Cees; Schuwirth, Lambert

2012-09-01

Clinical reasoning is essential to medical practice, but because it entails internal mental processes, it is difficult to assess. Functional magnetic resonance imaging (fMRI) and think-aloud protocols may improve understanding of clinical reasoning as these methods can more directly assess these processes. The objective of our study was to use a combination of fMRI and think-aloud procedures to examine fMRI correlates of a leading theoretical model in clinical reasoning based on experimental findings to date: analytic (i.e., actively comparing and contrasting diagnostic entities) and nonanalytic (i.e., pattern recognition) reasoning. We hypothesized that there would be functional neuroimaging differences between analytic and nonanalytic reasoning theory. 17 board-certified experts in internal medicine answered and reflected on validated U.S. Medical Licensing Exam and American Board of Internal Medicine multiple-choice questions (easy and difficult) during an fMRI scan. This procedure was followed by completion of a formal think-aloud procedure. fMRI findings provide some support for the presence of analytic and nonanalytic reasoning systems. Statistically significant activation of prefrontal cortex distinguished answering incorrectly versus correctly (p < 0.01), whereas activation of precuneus and midtemporal gyrus distinguished not guessing from guessing (p < 0.01). We found limited fMRI evidence to support analytic and nonanalytic reasoning theory, as our results indicate functional differences with correct vs. incorrect answers and guessing vs. not guessing. However, our findings did not suggest one consistent fMRI activation pattern of internal medicine expertise. This model of employing fMRI correlates offers opportunities to enhance our understanding of theory, as well as improve our teaching and assessment of clinical reasoning, a key outcome of medical education.

76 FR 54531 - Pipeline Safety: Potential for Damage to Pipeline Facilities Caused by the Passage of Hurricanes

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-01

... production and processing is prone to disruption by hurricanes. In 2005, Hurricanes Katrina and Rita caused... Hurricanes AGENCY: Pipeline and Hazardous Materials Safety Administration (PHMSA), DOT. ACTION: Notice... the passage of Hurricanes. ADDRESSES: This document can be viewed on the Office of Pipeline Safety...

75 FR 17397 - Hydrogen Energy California's Integrated Gasification Combined Cycle Project, Kern County, CA...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-06

... and potable water pipelines, a transmission line, a natural gas supply pipeline, a CO 2 pipeline... line. HECA would also construct an approximately 8-mile natural gas supply pipeline extending southeast... produce synthesis gas (syngas), which would then be processed and purified to produce a hydrogen-rich fuel...

Gaussian process based independent analysis for temporal source separation in fMRI.

PubMed

Hald, Ditte Høvenhoff; Henao, Ricardo; Winther, Ole

2017-05-15

Functional Magnetic Resonance Imaging (fMRI) gives us a unique insight into the processes of the brain, and opens up for analyzing the functional activation patterns of the underlying sources. Task-inferred supervised learning with restrictive assumptions in the regression set-up, restricts the exploratory nature of the analysis. Fully unsupervised independent component analysis (ICA) algorithms, on the other hand, can struggle to detect clear classifiable components on single-subject data. We attribute this shortcoming to inadequate modeling of the fMRI source signals by failing to incorporate its temporal nature. fMRI source signals, biological stimuli and non-stimuli-related artifacts are all smooth over a time-scale compatible with the sampling time (TR). We therefore propose Gaussian process ICA (GPICA), which facilitates temporal dependency by the use of Gaussian process source priors. On two fMRI data sets with different sampling frequency, we show that the GPICA-inferred temporal components and associated spatial maps allow for a more definite interpretation than standard temporal ICA methods. The temporal structures of the sources are controlled by the covariance of the Gaussian process, specified by a kernel function with an interpretable and controllable temporal length scale parameter. We propose a hierarchical model specification, considering both instantaneous and convolutive mixing, and we infer source spatial maps, temporal patterns and temporal length scale parameters by Markov Chain Monte Carlo. A companion implementation made as a plug-in for SPM can be downloaded from https://github.com/dittehald/GPICA. Copyright © 2017 Elsevier Inc. All rights reserved.

Towards neural correlates of auditory stimulus processing: A simultaneous auditory evoked potentials and functional magnetic resonance study using an odd-ball paradigm

PubMed Central

Milner, Rafał; Rusiniak, Mateusz; Lewandowska, Monika; Wolak, Tomasz; Ganc, Małgorzata; Piątkowska-Janko, Ewa; Bogorodzki, Piotr; Skarżyński, Henryk

2014-01-01

Background The neural underpinnings of auditory information processing have often been investigated using the odd-ball paradigm, in which infrequent sounds (deviants) are presented within a regular train of frequent stimuli (standards). Traditionally, this paradigm has been applied using either high temporal resolution (EEG) or high spatial resolution (fMRI, PET). However, used separately, these techniques cannot provide information on both the location and time course of particular neural processes. The goal of this study was to investigate the neural correlates of auditory processes with a fine spatio-temporal resolution. A simultaneous auditory evoked potentials (AEP) and functional magnetic resonance imaging (fMRI) technique (AEP-fMRI), together with an odd-ball paradigm, were used. Material/Methods Six healthy volunteers, aged 20–35 years, participated in an odd-ball simultaneous AEP-fMRI experiment. AEP in response to acoustic stimuli were used to model bioelectric intracerebral generators, and electrophysiological results were integrated with fMRI data. Results fMRI activation evoked by standard stimuli was found to occur mainly in the primary auditory cortex. Activity in these regions overlapped with intracerebral bioelectric sources (dipoles) of the N1 component. Dipoles of the N1/P2 complex in response to standard stimuli were also found in the auditory pathway between the thalamus and the auditory cortex. Deviant stimuli induced fMRI activity in the anterior cingulate gyrus, insula, and parietal lobes. Conclusions The present study showed that neural processes evoked by standard stimuli occur predominantly in subcortical and cortical structures of the auditory pathway. Deviants activate areas non-specific for auditory information processing. PMID:24413019

Is Broca's Area Involved in the Processing of Passive Sentences? An Event-Related fMRI Study

ERIC Educational Resources Information Center

Yokoyama, Satoru; Watanabe, Jobu; Iwata, Kazuki; Ikuta, Naho; Haji, Tomoki; Usui, Nobuo; Taira, Masato; Miyamoto, Tadao; Nakamura, Wataru; Sato, Shigeru; Horie, Kaoru; Kawashima, Ryuta

2007-01-01

We used functional magnetic resonance imaging (fMRI) to investigate whether activation in Broca's area is greater during the processing of passive versus active sentences in the brains of healthy subjects. Twenty Japanese native speakers performed a visual sentence comprehension task in which they were asked to read a visually presented sentence…

fMRI Evidence for Dorsal Stream Processing Abnormality in Adults Born Preterm

ERIC Educational Resources Information Center

Chaminade, Thierry; Leutcher, Russia Ha-Vinh; Millet, Veronique; Deruelle, Christine

2013-01-01

We investigated the consequences of premature birth on the functional neuroanatomy of the dorsal stream of visual processing. fMRI was recorded while sixteen healthy participants, 8 (two men) adults (19 years 6 months old, SD 10 months) born premature (mean gestational age 30 weeks), referred to as Premas, and 8 (two men) matched controls (20…

An fMRI Investigation of the Neural Correlates Underlying the Processing of Novel Metaphoric Expressions

ERIC Educational Resources Information Center

Mashal, N.; Faust, M.; Hendler, T.; Jung-Beeman, M.

2007-01-01

The neural networks associated with processing related pairs of words forming literal, novel, and conventional metaphorical expressions and unrelated pairs of words were studied in a group of 15 normal adults using fMRI. Subjects read the four types of linguistic expressions and decided which relation exists between the two words (metaphoric,…

Assessing fugitive emissions of CH4 from high-pressure gas pipelines

NASA Astrophysics Data System (ADS)

Worrall, Fred; Boothroyd, Ian; Davies, Richard

2017-04-01

The impact of unconventional natural gas production using hydraulic fracturing methods from shale gas basins has been assessed using life-cycle emissions inventories, covering areas such as pre-production, production and transmission processes. The transmission of natural gas from well pad to processing plants and its transport to domestic sites is an important source of fugitive CH4, yet emissions factors and fluxes from transmission processes are often based upon ver out of date measurements. It is important to determine accurate measurements of natural gas losses when compressed and transported between production and processing facilities so as to accurately determine life-cycle CH4 emissions. This study considers CH4 emissions from the UK National Transmission System (NTS) of high pressure natural gas pipelines. Mobile surveys of CH4 emissions using a Picarro Surveyor cavity-ring-down spectrometer were conducted across four areas in the UK, with routes bisecting high pressure pipelines and separate control routes away from the pipelines. A manual survey of soil gas measurements was also conducted along one of the high pressure pipelines using a tunable diode laser. When wind adjusted 92 km of high pressure pipeline and 72 km of control route were drive over a 10 day period. When wind and distance adjusted CH4 fluxes were significantly greater on routes with a pipeline than those without. The smallest leak detectable was 3% above ambient (1.03 relative concentration) with any leaks below 3% above ambient assumed ambient. The number of leaks detected along the pipelines correlate to the estimated length of pipe joints, inferring that there are constant fugitive CH4 emissions from these joints. When scaled up to the UK's National Transmission System pipeline length of 7600 km gives a fugitive CH4 flux of 4700 ± 2864 kt CH4/yr - this fugitive emission from high pressure pipelines is 0.016% of the annual gas supply.

An Integrated SNP Mining and Utilization (ISMU) Pipeline for Next Generation Sequencing Data

PubMed Central

Azam, Sarwar; Rathore, Abhishek; Shah, Trushar M.; Telluri, Mohan; Amindala, BhanuPrakash; Ruperao, Pradeep; Katta, Mohan A. V. S. K.; Varshney, Rajeev K.

2014-01-01

Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software. PMID:25003610

Comparison of fMRI data from passive listening and active-response story processing tasks in children.

PubMed

Vannest, Jennifer J; Karunanayaka, Prasanna R; Altaye, Mekibib; Schmithorst, Vincent J; Plante, Elena M; Eaton, Kenneth J; Rasmussen, Jerod M; Holland, Scott K

2009-04-01

To use functional MRI (fMRI) methods to visualize a network of auditory and language-processing brain regions associated with processing an aurally-presented story. We compare a passive listening (PL) story paradigm to an active-response (AR) version including online performance monitoring and a sparse acquisition technique. Twenty children (ages 11-13 years) completed PL and AR story processing tasks. The PL version presented alternating 30-second blocks of stories and tones; the AR version presented story segments, comprehension questions, and 5-second tone sequences, with fMRI acquisitions between stimuli. fMRI data was analyzed using a general linear model approach and paired t-test identifying significant group activation. Both tasks showed activation in the primary auditory cortex, superior temporal gyrus bilaterally, and left inferior frontal gyrus (IFG). The AR task demonstrated more extensive activation, including the dorsolateral prefrontal cortex and anterior/posterior cingulate cortex. Comparison of effect size in each paradigm showed a larger effect for the AR paradigm in a left inferior frontal region-of-interest (ROI). Activation patterns for story processing in children are similar in PL and AR tasks. Increases in extent and magnitude of activation in the AR task are likely associated with memory and attention resources engaged across acquisition intervals.

P300 amplitude variation is related to ventral striatum BOLD response during gain and loss anticipation: an EEG and fMRI experiment.

PubMed

Pfabigan, Daniela M; Seidel, Eva-Maria; Sladky, Ronald; Hahn, Andreas; Paul, Katharina; Grahl, Arvina; Küblböck, Martin; Kraus, Christoph; Hummer, Allan; Kranz, Georg S; Windischberger, Christian; Lanzenberger, Rupert; Lamm, Claus

2014-08-01

The anticipation of favourable or unfavourable events is a key component in our daily life. However, the temporal dynamics of anticipation processes in relation to brain activation are still not fully understood. A modified version of the monetary incentive delay task was administered during separate functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) sessions in the same 25 participants to assess anticipatory processes with a multi-modal neuroimaging set-up. During fMRI, gain and loss anticipation were both associated with heightened activation in ventral striatum and reward-related areas. EEG revealed most pronounced P300 amplitudes for gain anticipation, whereas CNV amplitudes distinguished neutral from gain and loss anticipation. Importantly, P300, but not CNV amplitudes, were correlated to neural activation in the ventral striatum for both gain and loss anticipation. Larger P300 amplitudes indicated higher ventral striatum blood oxygen level dependent (BOLD) response. Early stimulus evaluation processes indexed by EEG seem to be positively related to higher activation levels in the ventral striatum, indexed by fMRI, which are usually associated with reward processing. The current results, however, point towards a more general motivational mechanism processing salient stimuli during anticipation. Copyright © 2014. Published by Elsevier Inc.

The PREP pipeline: standardized preprocessing for large-scale EEG analysis.

PubMed

Bigdely-Shamlo, Nima; Mullen, Tim; Kothe, Christian; Su, Kyung-Min; Robbins, Kay A

2015-01-01

The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can reduce the signal-to-noise ratio and introduce unwanted artifacts into the data, particularly for computations done in single precision. We demonstrate that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results. We also show that identification of noisy channels depends on the reference and examine the complex interaction of filtering, noisy channel identification, and referencing. We introduce a multi-stage robust referencing scheme to deal with the noisy channel-reference interaction. We propose a standardized early-stage EEG processing pipeline (PREP) and discuss the application of the pipeline to more than 600 EEG datasets. The pipeline includes an automatically generated report for each dataset processed. Users can download the PREP pipeline as a freely available MATLAB library from http://eegstudy.org/prepcode.

78 FR 56268 - Pipeline Safety: Public Workshop on Integrity Verification Process, Comment Extension

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-12

.... PHMSA-2013-0119] Pipeline Safety: Public Workshop on Integrity Verification Process, Comment Extension... public workshop on ``Integrity Verification Process'' which took place on August 7, 2013. The notice also sought comments on the proposed ``Integrity Verification Process.'' In response to the comments received...

An EEG Finger-Print of fMRI deep regional activation.

PubMed

Meir-Hasson, Yehudit; Kinreich, Sivan; Podlipsky, Ilana; Hendler, Talma; Intrator, Nathan

2014-11-15

This work introduces a general framework for producing an EEG Finger-Print (EFP) which can be used to predict specific brain activity as measured by fMRI at a given deep region. This new approach allows for improved EEG spatial resolution based on simultaneous fMRI activity measurements. Advanced signal processing and machine learning methods were applied on EEG data acquired simultaneously with fMRI during relaxation training guided by on-line continuous feedback on changing alpha/theta EEG measure. We focused on demonstrating improved EEG prediction of activation in sub-cortical regions such as the amygdala. Our analysis shows that a ridge regression model that is based on time/frequency representation of EEG data from a single electrode, can predict the amygdala related activity significantly better than a traditional theta/alpha activity sampled from the best electrode and about 1/3 of the times, significantly better than a linear combination of frequencies with a pre-defined delay. The far-reaching goal of our approach is to be able to reduce the need for fMRI scanning for probing specific sub-cortical regions such as the amygdala as the basis for brain-training procedures. On the other hand, activity in those regions can be characterized with higher temporal resolution than is obtained by fMRI alone thus revealing additional information about their processing mode. Copyright © 2013 Elsevier Inc. All rights reserved.

Inclusion of attentional networks in the pre-surgical neuroimaging assessment of a large deep hemispheric cavernous malformation: an FMRI case report.

PubMed

Mickleborough, Marla J S; Kelly, Michael E; Gould, Layla; Ekstrand, Chelsea; Lorentz, Eric; Ellchuk, Tasha; Babyn, Paul; Borowsky, Ron

2015-01-01

Functional magnetic resonance imaging (fMRI) is a noninvasive and reliable tool for mapping eloquent cortex in patients prior to brain surgery. Ensuring intact perceptual and cognitive processing is a key goal for neurosurgeons, and recent research has indicated the value of including attentional network processing in pre-surgical fMRI in order to help preserve such abilities, including reading, after surgery. We report a 42-year-old patient with a large cavernous malformation, near the left basal ganglia. The lesion measured 3.8 × 1.7 × 1.8 cm. In consultation with the patient and the multidisciplinary cerebrovascular team, the decision was made to offer the patient surgical resection. The surgical resection involved planned access via the left superior parietal lobule using stereotactic location. The patient declined an awake craniotomy; therefore, direct electrocortical stimulation (ECS) could not be used for intraoperative language localization in this case. Pre-surgical planning included fMRI localization of language, motor, sensory, and attentional processing. The key finding was that both reading and attention-processing tasks revealed consistent activation of the left superior parietal lobule, part of the attentional control network, and the site of the planned surgical access. Given this information, surgical access was adjusted to avoid interference with the attentional control network. The lesion was removed via the left inferior parietal lobule. The patient had no new neurologic deficits postoperatively but did develop mild neuropathic pain in the left hand. This case report supports recent research that indicates the value of including fMRI maps of attentional tasks along with traditional language-processing tasks in preoperative planning in patients undergoing neurosurgery procedures. © 2015 S. Karger AG, Basel.

Data processing pipeline for Herschel HIFI

NASA Astrophysics Data System (ADS)

Shipman, R. F.; Beaulieu, S. F.; Teyssier, D.; Morris, P.; Rengel, M.; McCoey, C.; Edwards, K.; Kester, D.; Lorenzani, A.; Coeur-Joly, O.; Melchior, M.; Xie, J.; Sanchez, E.; Zaal, P.; Avruch, I.; Borys, C.; Braine, J.; Comito, C.; Delforge, B.; Herpin, F.; Hoac, A.; Kwon, W.; Lord, S. D.; Marston, A.; Mueller, M.; Olberg, M.; Ossenkopf, V.; Puga, E.; Akyilmaz-Yabaci, M.

2017-12-01

Context. The HIFI instrument on the Herschel Space Observatory performed over 9100 astronomical observations, almost 900 of which were calibration observations in the course of the nearly four-year Herschel mission. The data from each observation had to be converted from raw telemetry into calibrated products and were included in the Herschel Science Archive. Aims: The HIFI pipeline was designed to provide robust conversion from raw telemetry into calibrated data throughout all phases of the HIFI missions. Pre-launch laboratory testing was supported as were routine mission operations. Methods: A modular software design allowed components to be easily added, removed, amended and/or extended as the understanding of the HIFI data developed during and after mission operations. Results: The HIFI pipeline processed data from all HIFI observing modes within the Herschel automated processing environment as well as within an interactive environment. The same software can be used by the general astronomical community to reprocess any standard HIFI observation. The pipeline also recorded the consistency of processing results and provided automated quality reports. Many pipeline modules were in use since the HIFI pre-launch instrument level testing. Conclusions: Processing in steps facilitated data analysis to discover and address instrument artefacts and uncertainties. The availability of the same pipeline components from pre-launch throughout the mission made for well-understood, tested, and stable processing. A smooth transition from one phase to the next significantly enhanced processing reliability and robustness. Herschel was an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

The JCSG high-throughput structural biology pipeline.

PubMed

Elsliger, Marc André; Deacon, Ashley M; Godzik, Adam; Lesley, Scott A; Wooley, John; Wüthrich, Kurt; Wilson, Ian A

2010-10-01

The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years. The JCSG has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe, as well as making substantial inroads into structural coverage of an entire organism. Targets are processed through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize and optimize each target prior to selection for structure determination. The pipeline uses parallel processing methods at almost every step in the process and can adapt to a wide range of protein targets from bacterial to human. The construction, expansion and optimization of the JCSG gene-to-structure pipeline over the years have resulted in many technological and methodological advances and developments. The vast number of targets and the enormous amounts of associated data processed through the multiple stages of the experimental pipeline required the development of variety of valuable resources that, wherever feasible, have been converted to free-access web-based tools and applications.

Rapid Processing of Radio Interferometer Data for Transient Surveys

NASA Astrophysics Data System (ADS)

Bourke, S.; Mooley, K.; Hallinan, G.

2014-05-01

We report on a software infrastructure and pipeline developed to process large radio interferometer datasets. The pipeline is implemented using a radical redesign of the AIPS processing model. An infrastructure we have named AIPSlite is used to spawn, at runtime, minimal AIPS environments across a cluster. The pipeline then distributes and processes its data in parallel. The system is entirely free of the traditional AIPS distribution and is self configuring at runtime. This software has so far been used to process a EVLA Stripe 82 transient survey, the data for the JVLA-COSMOS project, and has been used to process most of the EVLA L-Band data archive imaging each integration to search for short duration transients.

Study of sleeper’s impact on the deep-water pipeline lateral global buckling

NASA Astrophysics Data System (ADS)

Liu, Wenbin; Li, Bin

2017-08-01

Pipelines are the most important transportation way for offshore oil and gas, and the lateral buckling is the main global buckling form for deep-water pipelines. The sleeper is an economic and efficient device to trigger the lateral buckling in preset location. This paper analyzed the lateral buckling features for on-bottom pipeline and pipeline with sleeper. The stress and strain variation during buckling process is shown to reveal the impact of sleeper on buckling.

Neural mechanisms of the mind, Aristotle, Zadeh, and fMRI.

PubMed

Perlovsky, Leonid I

2010-05-01

Processes in the mind: perception, cognition, concepts, instincts, emotions, and higher cognitive abilities for abstract thinking, beautiful music are considered here within a neural modeling fields (NMFs) paradigm. Its fundamental mathematical mechanism is a process "from vague-fuzzy to crisp," called dynamic logic (DL). This paper discusses why this paradigm is necessary mathematically, and relates it to a psychological description of the mind. Surprisingly, the process from "vague to crisp" corresponds to Aristotelian understanding of mental functioning. Recent functional magnetic resonance imaging (fMRI) measurements confirmed this process in neural mechanisms of perception.

The cortical basis of true memory and false memory for motion.

PubMed

Karanian, Jessica M; Slotnick, Scott D

2014-02-01

Behavioral evidence indicates that false memory, like true memory, can be rich in sensory detail. By contrast, there is fMRI evidence that true memory for visual information produces greater activity in earlier visual regions than false memory, which suggests true memory is associated with greater sensory detail. However, false memory in previous fMRI paradigms may have lacked sufficient sensory detail to recruit earlier visual processing regions. To investigate this possibility in the present fMRI study, we employed a paradigm that produced feature-specific false memory with a high degree of visual detail. During the encoding phase, moving or stationary abstract shapes were presented to the left or right of fixation. During the retrieval phase, shapes from encoding were presented at fixation and participants classified each item as previously "moving" or "stationary" within each visual field. Consistent with previous fMRI findings, true memory but not false memory for motion activated motion processing region MT+, while both true memory and false memory activated later cortical processing regions. In addition, false memory but not true memory for motion activated language processing regions. The present findings indicate that true memory activates earlier visual regions to a greater degree than false memory, even under conditions of detailed retrieval. Thus, the dissociation between previous behavioral findings and fMRI findings do not appear to be task dependent. Future work will be needed to assess whether the same pattern of true memory and false memory activity is observed for different sensory modalities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Connectome Signatures of Neurocognitive Abnormalities in Euthymic Bipolar I Disorder

PubMed Central

Ajilore, Olusola; Vizueta, Nathalie; Walshaw, Patricia; Zhan, Liang; Leow, Alex; Altshuler, Lori L.

2015-01-01

Objectives Connectomics have allowed researchers to study integrative patterns of neural connectivity in humans. Yet, it is unclear how connectomics may elucidate structure-function relationships in bipolar I disorder (BPI). Expanding on our previous structural connectome study, here we used an overlapping sample with additional psychometric and fMRI data to relate structural connectome properties to both fMRI signals and cognitive performance. Methods 42 subjects completed a neuropsychological (NP) battery covering domains of processing speed, verbal memory, working memory, and cognitive flexibility. 32 subjects also had fMRI data performing a Go/NoGo task. Results Bipolar participants had lower NP performance across all domains, but only working memory reached statistical significance. In BPI participants, processing speed was significantly associated with both white matter integrity (WMI) in the corpus callosum and interhemispheric network integration. Mediation models further revealed that the relationship between interhemispheric integration and processing speed was mediated by WMI, and processing speed mediated the relationship between WMI and working memory. Bipolar subjects had significantly decreased BA47 activation during NoGo vs. Go. Significant predictors of BA47 fMRI activations during the Go/NoGo task were its nodal path length (left hemisphere) and its nodal clustering coefficient (right hemisphere). Conclusions This study suggests that structural connectome changes underlie abnormalities in fMRI activation and cognitive performance in euthymic BPI subjects. Results support that BA47 structural connectome changes may be a trait marker for BPI. Future studies are needed to determine if these “connectome signatures” may also confer a biological risk and/or serve as predictors of relapse. PMID:26228398

The future of fMRI in cognitive neuroscience.

PubMed

Poldrack, Russell A

2012-08-15

Over the last 20 years, fMRI has revolutionized cognitive neuroscience. Here I outline a vision for what the next 20 years of fMRI in cognitive neuroscience might look like. Some developments that I hope for include increased methodological rigor, an increasing focus on connectivity and pattern analysis as opposed to "blobology", a greater focus on selective inference powered by open databases, and increased use of ontologies and computational models to describe underlying processes. Copyright © 2011 Elsevier Inc. All rights reserved.

Functional Magnetic Resonance Imaging Methods

PubMed Central

Chen, Jingyuan E.; Glover, Gary H.

2015-01-01

Since its inception in 1992, Functional Magnetic Resonance Imaging (fMRI) has become an indispensible tool for studying cognition in both the healthy and dysfunctional brain. FMRI monitors changes in the oxygenation of brain tissue resulting from altered metabolism consequent to a task-based evoked neural response or from spontaneous fluctuations in neural activity in the absence of conscious mentation (the “resting state”). Task-based studies have revealed neural correlates of a large number of important cognitive processes, while fMRI studies performed in the resting state have demonstrated brain-wide networks that result from brain regions with synchronized, apparently spontaneous activity. In this article, we review the methods used to acquire and analyze fMRI signals. PMID:26248581

Integration of a neuroimaging processing pipeline into a pan-canadian computing grid

NASA Astrophysics Data System (ADS)

Lavoie-Courchesne, S.; Rioux, P.; Chouinard-Decorte, F.; Sherif, T.; Rousseau, M.-E.; Das, S.; Adalat, R.; Doyon, J.; Craddock, C.; Margulies, D.; Chu, C.; Lyttelton, O.; Evans, A. C.; Bellec, P.

2012-02-01

The ethos of the neuroimaging field is quickly moving towards the open sharing of resources, including both imaging databases and processing tools. As a neuroimaging database represents a large volume of datasets and as neuroimaging processing pipelines are composed of heterogeneous, computationally intensive tools, such open sharing raises specific computational challenges. This motivates the design of novel dedicated computing infrastructures. This paper describes an interface between PSOM, a code-oriented pipeline development framework, and CBRAIN, a web-oriented platform for grid computing. This interface was used to integrate a PSOM-compliant pipeline for preprocessing of structural and functional magnetic resonance imaging into CBRAIN. We further tested the capacity of our infrastructure to handle a real large-scale project. A neuroimaging database including close to 1000 subjects was preprocessed using our interface and publicly released to help the participants of the ADHD-200 international competition. This successful experiment demonstrated that our integrated grid-computing platform is a powerful solution for high-throughput pipeline analysis in the field of neuroimaging.

The posterior parietal paradox: Why do functional magnetic resonance imaging and lesion studies on episodic memory produce conflicting results?

PubMed

Schoo, L A; van Zandvoort, M J E; Biessels, G J; Kappelle, L J; Postma, A; de Haan, E H F

2011-03-01

Recent functional magnetic resonance imaging (fMRI) studies addressing healthy subjects point towards posterior parietal cortex (PPC) involvement in episodic memory tasks. This is noteworthy, since neuropsychological studies usually do not connect parietal lesions to episodic memory impairments. Therefore an inventory of the possible factors behind this apparent paradox is warranted. This review compared fMRI studies which demonstrated PPC activity in episodic memory tasks, with findings with studies of patients with PPC lesions. A systematic evaluation of possible explanations for the posterior parietal paradox indicates that PPC activation in fMRI studies does not appear to be attributable to confounding cognitive/psychomotor processes, such as button pressing or stimulus processing. What may be of more importance is the extent to which an episodic memory task loads on three closely related cognitive processes: effort and attention, self-related activity, and scene and image construction. We discuss to what extent these cognitive processes can account for the paradox between lesion and fMRI results. They are strongly intertwined with the episodic memory and may critically determine in how far the PPC plays a role in a given memory task. Future patient studies might profit from specifically taking these cognitive factors into consideration in the task design. ©2010 The British Psychological Society.

Unfolding the Spatial and Temporal Neural Processing of Making Dishonest Choices

PubMed Central

Wang, Zhaoxin; Chan, Chetwyn C. H.

2016-01-01

To understand the neural processing that underpins dishonest behavior in an economic exchange game task, this study employed both functional magnetic resonance imaging (fMRI) and event-related potential (ERP) methodologies to examine the neural conditions of 25 participants while they were making either dishonest or honest choices. It was discovered that dishonest choices, contrary to honest choices, elicited stronger fMRI activations in bilateral striatum and anterior insula. It also induced fluctuations in ERP amplitudes within two time windows, which are 270–30 milliseconds before and 110–290 milliseconds after the response, respectively. Importantly, when making either dishonest or honest choices, human and computer counterparts were associated with distinct fMRI activations in the left insula and different ERP amplitudes at medial and right central sites from 80 milliseconds before to 250 milliseconds after the response. These results support the hypothesis that there would be distinct neural processing during making dishonest decisions, especially when the subject considers the interests of the counterpart. Furthermore, the fMRI and ERP findings, together with ERP source reconstruction, clearly delineate the temporal sequence of the neural processes of a dishonest decision: the striatum is activated before response, then the left insula is involved around the time of response, and finally the thalamus is activated after response. PMID:27096474

Bioinformatic pipelines in Python with Leaf

PubMed Central

2013-01-01

Background An incremental, loosely planned development approach is often used in bioinformatic studies when dealing with custom data analysis in a rapidly changing environment. Unfortunately, the lack of a rigorous software structuring can undermine the maintainability, communicability and replicability of the process. To ameliorate this problem we propose the Leaf system, the aim of which is to seamlessly introduce the pipeline formality on top of a dynamical development process with minimum overhead for the programmer, thus providing a simple layer of software structuring. Results Leaf includes a formal language for the definition of pipelines with code that can be transparently inserted into the user’s Python code. Its syntax is designed to visually highlight dependencies in the pipeline structure it defines. While encouraging the developer to think in terms of bioinformatic pipelines, Leaf supports a number of automated features including data and session persistence, consistency checks between steps of the analysis, processing optimization and publication of the analytic protocol in the form of a hypertext. Conclusions Leaf offers a powerful balance between plan-driven and change-driven development environments in the design, management and communication of bioinformatic pipelines. Its unique features make it a valuable alternative to other related tools. PMID:23786315

The PREP pipeline: standardized preprocessing for large-scale EEG analysis

PubMed Central

Bigdely-Shamlo, Nima; Mullen, Tim; Kothe, Christian; Su, Kyung-Min; Robbins, Kay A.

2015-01-01

The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can reduce the signal-to-noise ratio and introduce unwanted artifacts into the data, particularly for computations done in single precision. We demonstrate that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results. We also show that identification of noisy channels depends on the reference and examine the complex interaction of filtering, noisy channel identification, and referencing. We introduce a multi-stage robust referencing scheme to deal with the noisy channel-reference interaction. We propose a standardized early-stage EEG processing pipeline (PREP) and discuss the application of the pipeline to more than 600 EEG datasets. The pipeline includes an automatically generated report for each dataset processed. Users can download the PREP pipeline as a freely available MATLAB library from http://eegstudy.org/prepcode. PMID:26150785

Remaining Sites Verification Package for the 100-F-26:12, 1.8-m (72-in.) Main Process Sewer Pipeline, Waste Site Reclassification Form 2007-034

DOE Office of Scientific and Technical Information (OSTI.GOV)

J. M. Capron

2008-04-29

The 100-F-26:12 waste site was an approximately 308-m-long, 1.8-m-diameter east-west-trending reinforced concrete pipe that joined the North Process Sewer Pipelines (100-F-26:1) and the South Process Pipelines (100-F-26:4) with the 1.8-m reactor cooling water effluent pipeline (100-F-19). In accordance with this evaluation, the verification sampling results support a reclassification of this site to Interim Closed Out. The results of verification sampling show that residual contaminant concentrations do not preclude any future uses and allow for unrestricted use of shallow zone soils. The results also demonstrate that residual contaminant concentrations are protective of groundwater and the Columbia River.

From Pipelines to Tasting Lemonade: Reconceptualizing College Access

ERIC Educational Resources Information Center

Pitcher, Erich N.; Shahjahan, Riyad A.

2017-01-01

Pipeline metaphors are ubiquitous in theorizing and interpreting college access processes. In this conceptual article, we explore how a lemonade metaphor can open new possibilities to reimagining higher education access and going processes. We argue that using food metaphors, particularly the processes of mixing, tasting, and digesting lemonade,…

Multimodal imaging of repetition priming: Using fMRI, MEG, and intracranial EEG to reveal spatiotemporal profiles of word processing.

PubMed

McDonald, Carrie R; Thesen, Thomas; Carlson, Chad; Blumberg, Mark; Girard, Holly M; Trongnetrpunya, Amy; Sherfey, Jason S; Devinsky, Orrin; Kuzniecky, Rubin; Dolye, Werner K; Cash, Sydney S; Leonard, Matthew K; Hagler, Donald J; Dale, Anders M; Halgren, Eric

2010-11-01

Repetition priming is a core feature of memory processing whose anatomical correlates remain poorly understood. In this study, we use advanced multimodal imaging (functional magnetic resonance imaging (fMRI) and magnetoencephalography; MEG) to investigate the spatiotemporal profile of repetition priming. We use intracranial electroencephalography (iEEG) to validate our fMRI/MEG measurements. Twelve controls completed a semantic judgment task with fMRI and MEG that included words presented once (new, 'N') and words that repeated (old, 'O'). Six patients with epilepsy completed the same task during iEEG recordings. Blood-oxygen level dependent (BOLD) responses for N vs. O words were examined across the cortical surface and within regions of interest. MEG waveforms for N vs. O words were estimated using a noise-normalized minimum norm solution, and used to interpret the timecourse of fMRI. Spatial concordance was observed between fMRI and MEG repetition effects from 350 to 450 ms within bilateral occipitotemporal and medial temporal, left prefrontal, and left posterior temporal cortex. Additionally, MEG revealed widespread sources within left temporoparietal regions, whereas fMRI revealed bilateral reductions in occipitotemporal and left superior frontal, and increases in inferior parietal, precuneus, and dorsolateral prefrontal activity. BOLD suppression in left posterior temporal, left inferior prefrontal, and right occipitotemporal cortex correlated with MEG repetition-related reductions. IEEG responses from all three regions supported the timecourse of MEG and localization of fMRI. Furthermore, iEEG decreases to repeated words were associated with decreased gamma power in several regions, providing evidence that gamma oscillations are tightly coupled to cognitive phenomena and reflect regional activations seen in the BOLD signal. Copyright 2010 Elsevier Inc. All rights reserved.

Multimodal imaging of repetition priming: Using fMRI, MEG, and intracranial EEG to reveal spatiotemporal profiles of word processing

PubMed Central

McDonald, Carrie R.; Thesen, Thomas; Carlson, Chad; Blumberg, Mark; Girard, Holly M.; Trongnetrpunya, Amy; Sherfey, Jason S.; Devinsky, Orrin; Kuzniecky, Rubin; Dolye, Werner K.; Cash, Sydney S.; Leonard, Matt K.; Hagler, Donald J.; Dale, Anders M.; Halgren, Eric

2010-01-01

Repetition priming is a core feature of memory processing whose anatomical correlates remain poorly understood. In this study, we use advanced multimodal imaging (functional magnetic resonance imaging (fMRI) and magnetoencephalography; MEG) to investigate the spatiotemporal profile of repetition priming. We use intracranial electroencephalography (iEEG) to validate our fMRI/MEG measurements. Twelve controls completed a semantic judgment task with fMRI and MEG that included words presented once (new, ‘N’) and words that repeated (old, ‘O’). Six patients with epilepsy completed the same task during iEEG recordings. Blood-oxygen level dependent (BOLD) responses for N vs O words were examined across the cortical surface and within regions of interest. MEG waveforms for N vs O words were estimated using a noise-normalized minimum norm solution, and used to interpret the timecourse of fMRI. Spatial concordance was observed between fMRI and MEG repetition effects from 350–450ms within bilateral occipitotemporal and medial temporal, left prefrontal, and left posterior temporal cortex. Additionally, MEG revealed widespread sources within left temporoparietal regions, whereas fMRI revealed bilateral reductions in occipitotemporal and left superior frontal, and increases in inferior parietal, precuneus, and dorsolateral prefrontal activity. BOLD suppression in left posterior temporal, left inferior prefrontal, and right occipitotemporal cortex correlated with MEG repetition-related reductions. IEEG responses from all three regions supported the timecourse of MEG and localization of fMRI. Furthermore, iEEG decreases to repeated words were associated with decreased gamma power in several regions, providing evidence that gamma oscillations are tightly coupled to cognitive phenomena and reflect regional activations seen in the BOLD signal. PMID:20620212

Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data.

PubMed

Power, Jonathan D; Plitt, Mark; Gotts, Stephen J; Kundu, Prantik; Voon, Valerie; Bandettini, Peter A; Martin, Alex

2018-02-27

"Functional connectivity" techniques are commonplace tools for studying brain organization. A critical element of these analyses is to distinguish variance due to neurobiological signals from variance due to nonneurobiological signals. Multiecho fMRI techniques are a promising means for making such distinctions based on signal decay properties. Here, we report that multiecho fMRI techniques enable excellent removal of certain kinds of artifactual variance, namely, spatially focal artifacts due to motion. By removing these artifacts, multiecho techniques reveal frequent, large-amplitude blood oxygen level-dependent (BOLD) signal changes present across all gray matter that are also linked to motion. These whole-brain BOLD signals could reflect widespread neural processes or other processes, such as alterations in blood partial pressure of carbon dioxide (pCO 2 ) due to ventilation changes. By acquiring multiecho data while monitoring breathing, we demonstrate that whole-brain BOLD signals in the resting state are often caused by changes in breathing that co-occur with head motion. These widespread respiratory fMRI signals cannot be isolated from neurobiological signals by multiecho techniques because they occur via the same BOLD mechanism. Respiratory signals must therefore be removed by some other technique to isolate neurobiological covariance in fMRI time series. Several methods for removing global artifacts are demonstrated and compared, and were found to yield fMRI time series essentially free of motion-related influences. These results identify two kinds of motion-associated fMRI variance, with different physical mechanisms and spatial profiles, each of which strongly and differentially influences functional connectivity patterns. Distance-dependent patterns in covariance are nearly entirely attributable to non-BOLD artifacts.

Material specific lateralization of medial temporal lobe function: An fMRI investigation.

PubMed

Dalton, Marshall A; Hornberger, Michael; Piguet, Olivier

2016-03-01

The theory of material specific lateralization of memory function posits that left and right MTL regions are asymmetrically involved in mnemonic processing of verbal and nonverbal material respectively. Lesion and functional imaging (fMRI) studies provide robust evidence for a left MTL asymmetry in the verbal memory domain. Evidence for a right MTL/nonverbal asymmetry is not as robust. A handful of fMRI studies have investigated this issue but have generally utilised nonverbal stimuli which are amenable to semantic elaboration. This fMRI study aimed to investigate the neural correlates of recognition memory processing in 20 healthy young adults (mean age = 26 years) for verbal stimuli and nonverbal stimuli that were specifically designed to minimize verbalisation. Analyses revealed that the neural correlates of recognition memory processing for verbal and nonverbal stimuli were differentiable and asymmetrically recruited the left and right MTL respectively. The right perirhinal cortex and hippocampus were preferentially involved in successful recognition memory of items devoid of semantic information. In contrast, the left anterior hippocampus was preferentially involved in successful recognition memory of stimuli which contained semantic meaning. These results suggest that the left MTL is preferentially involved in mnemonic processing of verbal/semantic information. In contrast, the right MTL is preferentially involved in visual/non-semantic mnemonic processing. We propose that during development, the left MTL becomes specialised for verbal mnemonic processing due to its proximity with left lateralised cortical language processing areas while visual/non-semantic mnemonic processing gets 'crowded out' to become predominantly, but not completely, the domain of the right MTL. © 2015 Wiley Periodicals, Inc.

Gender differences in the processing of standard emotional visual stimuli: integrating ERP and fMRI results

NASA Astrophysics Data System (ADS)

Yang, Lei; Tian, Jie; Wang, Xiaoxiang; Hu, Jin

2005-04-01

The comprehensive understanding of human emotion processing needs consideration both in the spatial distribution and the temporal sequencing of neural activity. The aim of our work is to identify brain regions involved in emotional recognition as well as to follow the time sequence in the millisecond-range resolution. The effect of activation upon visual stimuli in different gender by International Affective Picture System (IAPS) has been examined. Hemodynamic and electrophysiological responses were measured in the same subjects. Both fMRI and ERP study were employed in an event-related study. fMRI have been obtained with 3.0 T Siemens Magnetom whole-body MRI scanner. 128-channel ERP data were recorded using an EGI system. ERP is sensitive to millisecond changes in mental activity, but the source localization and timing is limited by the ill-posed 'inversed' problem. We try to investigate the ERP source reconstruction problem in this study using fMRI constraint. We chose ICA as a pre-processing step of ERP source reconstruction to exclude the artifacts and provide a prior estimate of the number of dipoles. The results indicate that male and female show differences in neural mechanism during emotion visual stimuli.

Age-related differences in the neural bases of phonological and semantic processes

PubMed Central

Diaz, Michele T.; Johnson, Micah A.; Burke, Deborah M.; Madden, David J.

2014-01-01

Changes in language functions during normal aging are greater for phonological compared to semantic processes. To investigate the behavioral and neural basis for these age-related differences, we used functional magnetic resonance imaging (fMRI) to examine younger and older adults who made semantic and phonological decisions about pictures. The behavioral performance of older adults was less accurate and less efficient than younger adults’ in the phonological task, but did not differ in the semantic task. In the fMRI analyses, the semantic task activated left-hemisphere language regions, while the phonological task activated bilateral cingulate and ventral precuneus. Age-related effects were widespread throughout the brain, and most often expressed as greater activation for older adults. Activation was greater for younger compared to older adults in ventral brain regions involved in visual and object processing. Although there was not a significant Age x Condition interaction in the whole-brain fMRI results, correlations examining the relationship between behavior and fMRI activation were stronger for younger compared to older adults. Our results suggest that the relationship between behavior and neural activation declines with age and this may underlie some of the observed declines in performance. PMID:24893737

Posterior Parietal Cortex Drives Inferotemporal Activations During Three-Dimensional Object Vision.

PubMed

Van Dromme, Ilse C; Premereur, Elsie; Verhoef, Bram-Ernst; Vanduffel, Wim; Janssen, Peter

2016-04-01

The primate visual system consists of a ventral stream, specialized for object recognition, and a dorsal visual stream, which is crucial for spatial vision and actions. However, little is known about the interactions and information flow between these two streams. We investigated these interactions within the network processing three-dimensional (3D) object information, comprising both the dorsal and ventral stream. Reversible inactivation of the macaque caudal intraparietal area (CIP) during functional magnetic resonance imaging (fMRI) reduced fMRI activations in posterior parietal cortex in the dorsal stream and, surprisingly, also in the inferotemporal cortex (ITC) in the ventral visual stream. Moreover, CIP inactivation caused a perceptual deficit in a depth-structure categorization task. CIP-microstimulation during fMRI further suggests that CIP projects via posterior parietal areas to the ITC in the ventral stream. To our knowledge, these results provide the first causal evidence for the flow of visual 3D information from the dorsal stream to the ventral stream, and identify CIP as a key area for depth-structure processing. Thus, combining reversible inactivation and electrical microstimulation during fMRI provides a detailed view of the functional interactions between the two visual processing streams.

Posterior Parietal Cortex Drives Inferotemporal Activations During Three-Dimensional Object Vision

PubMed Central

Van Dromme, Ilse C.; Premereur, Elsie; Verhoef, Bram-Ernst; Vanduffel, Wim; Janssen, Peter

2016-01-01

The primate visual system consists of a ventral stream, specialized for object recognition, and a dorsal visual stream, which is crucial for spatial vision and actions. However, little is known about the interactions and information flow between these two streams. We investigated these interactions within the network processing three-dimensional (3D) object information, comprising both the dorsal and ventral stream. Reversible inactivation of the macaque caudal intraparietal area (CIP) during functional magnetic resonance imaging (fMRI) reduced fMRI activations in posterior parietal cortex in the dorsal stream and, surprisingly, also in the inferotemporal cortex (ITC) in the ventral visual stream. Moreover, CIP inactivation caused a perceptual deficit in a depth-structure categorization task. CIP-microstimulation during fMRI further suggests that CIP projects via posterior parietal areas to the ITC in the ventral stream. To our knowledge, these results provide the first causal evidence for the flow of visual 3D information from the dorsal stream to the ventral stream, and identify CIP as a key area for depth-structure processing. Thus, combining reversible inactivation and electrical microstimulation during fMRI provides a detailed view of the functional interactions between the two visual processing streams. PMID:27082854

Integrating the ODI-PPA scientific gateway with the QuickReduce pipeline for on-demand processing

NASA Astrophysics Data System (ADS)

Young, Michael D.; Kotulla, Ralf; Gopu, Arvind; Liu, Wilson

2014-07-01

As imaging systems improve, the size of astronomical data has continued to grow, making the transfer and processing of data a significant burden. To solve this problem for the WIYN Observatory One Degree Imager (ODI), we developed the ODI-Portal, Pipeline, and Archive (ODI-PPA) science gateway, integrating the data archive, data reduction pipelines, and a user portal. In this paper, we discuss the integration of the QuickReduce (QR) pipeline into PPA's Tier 2 processing framework. QR is a set of parallelized, stand-alone Python routines accessible to all users, and operators who can create master calibration products and produce standardized calibrated data, with a short turn-around time. Upon completion, the data are ingested into the archive and portal, and made available to authorized users. Quality metrics and diagnostic plots are generated and presented via the portal for operator approval and user perusal. Additionally, users can tailor the calibration process to their specific science objective(s) by selecting custom datasets, applying preferred master calibrations or generating their own, and selecting pipeline options. Submission of a QuickReduce job initiates data staging, pipeline execution, and ingestion of output data products all while allowing the user to monitor the process status, and to download or further process/analyze the output within the portal. User-generated data products are placed into a private user-space within the portal. ODI-PPA leverages cyberinfrastructure at Indiana University including the Big Red II supercomputer, the Scholarly Data Archive tape system and the Data Capacitor shared file system.

The Chandra Source Catalog 2.0: Data Processing Pipelines

NASA Astrophysics Data System (ADS)

Miller, Joseph; Allen, Christopher E.; Budynkiewicz, Jamie A.; Gibbs, Danny G., II; Paxson, Charles; Chen, Judy C.; Anderson, Craig S.; Burke, Douglas; Civano, Francesca Maria; D'Abrusco, Raffaele; Doe, Stephen M.; Evans, Ian N.; Evans, Janet D.; Fabbiano, Giuseppina; Glotfelty, Kenny J.; Graessle, Dale E.; Grier, John D.; Hain, Roger; Hall, Diane M.; Harbo, Peter N.; Houck, John C.; Lauer, Jennifer L.; Laurino, Omar; Lee, Nicholas P.; Martínez-Galarza, Juan Rafael; McCollough, Michael L.; McDowell, Jonathan C.; McLaughlin, Warren; Morgan, Douglas L.; Mossman, Amy E.; Nguyen, Dan T.; Nichols, Joy S.; Nowak, Michael A.; Plummer, David A.; Primini, Francis Anthony; Rots, Arnold H.; Siemiginowska, Aneta; Sundheim, Beth A.; Tibbetts, Michael; Van Stone, David W.; Zografou, Panagoula

2018-01-01

With the construction of the Second Chandra Source Catalog (CSC2.0), came new requirements and new techniques to create a software system that can process 10,000 observations and identify nearly 320,000 point and compact X-ray sources. A new series of processing pipelines have been developed to allow for deeper more complete exploration of the Chanda observations. In CSC1.0 there were 4 general pipelines, whereas in CSC2.0 there are 20 data processing pipelines that have been organized into 3 distinct phases of operation - detection, master matching and source property characterization.With CSC2.0, observations within one arcminute of each other are stacked before searching for sources. The detection phase of processing combines the data, adjusts for shifts in fine astrometry, detects sources, and assesses the likelihood that sources are real. During the master source phase, detections across stacks of observations are analyzed for coverage of the same source to produce a master source. Finally, in the source property phase, each source is characterized with aperture photometry, spectrometry, variability and other properties at theobservation, stack and master levels over several energy bands.We present how these pipelines were constructed and the challenges we faced in how we processed data ranging from virtually no counts to millions of counts, how pipelines were tuned to work optimally on a computational cluster, and how we ensure the data produced was correct through various quality assurance steps.This work has been supported by NASA under contract NAS 8-03060 to the Smithsonian Astrophysical Observatory for operation of the Chandra X-ray Center.

Improved coal-slurry pipeline

NASA Technical Reports Server (NTRS)

Dowler, W. L.

1979-01-01

High strength steel pipeline carries hot mixture of powdered coal and coal derived oil to electric-power-generating station. Slurry is processed along way to remove sulfur, ash, and nitrogen and to recycle part of oil. System eliminates hazards and limitations associated with anticipated coal/water-slurry pipelines.

Differential fMRI Activation Patterns to Noxious Heat and Tactile Stimuli in the Primate Spinal Cord

PubMed Central

Yang, Pai-Feng; Wang, Feng

2015-01-01

Mesoscale local functional organizations of the primate spinal cord are largely unknown. Using high-resolution fMRI at 9.4 T, we identified distinct interhorn and intersegment fMRI activation patterns to tactile versus nociceptive heat stimulation of digits in lightly anesthetized monkeys. Within a spinal segment, 8 Hz vibrotactile stimuli elicited predominantly fMRI activations in the middle part of ipsilateral dorsal horn (iDH), along with significantly weaker activations in ipsilateral (iVH) and contralateral (cVH) ventral horns. In contrast, nociceptive heat stimuli evoked widespread strong activations in the superficial part of iDH, as well as in iVH and contralateral dorsal (cDH) horns. As controls, only weak signal fluctuations were detected in the white matter. The iDH responded most strongly to both tactile and heat stimuli, whereas the cVH and cDH responded selectively to tactile versus nociceptive heat, respectively. Across spinal segments, iDH activations were detected in three consecutive segments in both tactile and heat conditions. Heat responses, however, were more extensive along the cord, with strong activations in iVH and cDH in two consecutive segments. Subsequent subunit B of cholera toxin tracer histology confirmed that the spinal segments showing fMRI activations indeed received afferent inputs from the stimulated digits. Comparisons of the fMRI signal time courses in early somatosensory area 3b and iDH revealed very similar hemodynamic stimulus–response functions. In summary, we identified with fMRI distinct segmental networks for the processing of tactile and nociceptive heat stimuli in the cervical spinal cord of nonhuman primates. SIGNIFICANCE STATEMENT This is the first fMRI demonstration of distinct intrasegmental and intersegmental nociceptive heat and touch processing circuits in the spinal cord of nonhuman primates. This study provides novel insights into the local functional organizations of the primate spinal cord for pain and touch, information that will be valuable for designing and optimizing therapeutic interventions for chronic pain management. PMID:26203144

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hansen, E.A.; Smed, P.F.; Bryndum, M.B.

The paper describes the numerical program, PIPESIN, that simulates the behavior of a pipeline placed on an erodible seabed. PIPEline Seabed INteraction from installation until a stable pipeline seabed configuration has occurred is simulated in the time domain including all important physical processes. The program is the result of the joint research project, ``Free Span Development and Self-lowering of Offshore Pipelines`` sponsored by EU and a group of companies and carried out by the Danish Hydraulic Institute and Delft Hydraulics. The basic modules of PIPESIN are described. The description of the scouring processes has been based on and verified throughmore » physical model tests carried out as part of the research project. The program simulates a section of the pipeline (typically 500 m) in the time domain, the main input being time series of the waves and current. The main results include predictions of the onset of free spans, their length distribution, their variation in time, and the lowering of the pipeline as function of time.« less

Lateral instability of high temperature pipelines, the 20-in. Sleipner Vest pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saevik, S.; Levold, E.; Johnsen, O.K.

1996-12-01

The present paper addresses methods to control snaking behavior of high temperature pipelines resting on a flat sea bed. A case study is presented based on the detail engineering of the 12.5 km long 20 inch gas pipeline connecting the Sleipner Vest wellhead platform to the Sleipner T processing platform in the North Sea. The study includes screening and evaluation of alternative expansion control methods, ending up with a recommended method. The methodology and philosophy, used as basis to ensure sufficient structural strength throughout the lifetime of the pipeline, are thereafter presented. The results show that in order to findmore » the optimum technical solution to control snaking behavior, many aspects need to be considered such as process requirements, allowable strain, hydrodynamic stability, vertical profile, pipelay installation and trawlboard loading. It is concluded that by proper consideration of all the above aspects, the high temperature pipeline can be designed to obtain sufficient safety level.« less

fMRI paradigm designing and post-processing tools

PubMed Central

James, Jija S; Rajesh, PG; Chandran, Anuvitha VS; Kesavadas, Chandrasekharan

2014-01-01

In this article, we first review some aspects of functional magnetic resonance imaging (fMRI) paradigm designing for major cognitive functions by using stimulus delivery systems like Cogent, E-Prime, Presentation, etc., along with their technical aspects. We also review the stimulus presentation possibilities (block, event-related) for visual or auditory paradigms and their advantage in both clinical and research setting. The second part mainly focus on various fMRI data post-processing tools such as Statistical Parametric Mapping (SPM) and Brain Voyager, and discuss the particulars of various preprocessing steps involved (realignment, co-registration, normalization, smoothing) in these software and also the statistical analysis principles of General Linear Modeling for final interpretation of a functional activation result. PMID:24851001

Brain atrophy can introduce age-related differences in BOLD response.

PubMed

Liu, Xueqing; Gerraty, Raphael T; Grinband, Jack; Parker, David; Razlighi, Qolamreza R

2017-04-11

Use of functional magnetic resonance imaging (fMRI) in studies of aging is often hampered by uncertainty about age-related differences in the amplitude and timing of the blood oxygenation level dependent (BOLD) response (i.e., hemodynamic impulse response function (HRF)). Such uncertainty introduces a significant challenge in the interpretation of the fMRI results. Even though this issue has been extensively investigated in the field of neuroimaging, there is currently no consensus about the existence and potential sources of age-related hemodynamic alterations. Using an event-related fMRI experiment with two robust and well-studied stimuli (visual and auditory), we detected a significant age-related difference in the amplitude of response to auditory stimulus. Accounting for brain atrophy by circumventing spatial normalization and processing the data in subjects' native space eliminated these observed differences. In addition, we simulated fMRI data using age differences in brain morphology while controlling HRF shape. Analyzing these simulated fMRI data using standard image processing resulted in differences in HRF amplitude, which were eliminated when the data were analyzed in subjects' native space. Our results indicate that age-related atrophy introduces inaccuracy in co-registration to standard space, which subsequently appears as attenuation in BOLD response amplitude. Our finding could explain some of the existing contradictory reports regarding age-related differences in the fMRI BOLD responses. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Enhancement of Hydrodynamic Processes in Oil Pipelines Considering Rheologically Complex High-Viscosity Oils

NASA Astrophysics Data System (ADS)

Konakhina, I. A.; Khusnutdinova, E. M.; Khamidullina, G. R.; Khamidullina, A. F.

2016-06-01

This paper describes a mathematical model of flow-related hydrodynamic processes for rheologically complex high-viscosity bitumen oil and oil-water suspensions and presents methods to improve the design and performance of oil pipelines.

Load-dependent dysfunction of the putamen during attentional processing in patients with clinically isolated syndrome suggestive of multiple sclerosis.

PubMed

Tortorella, C; Romano, R; Direnzo, V; Taurisano, P; Zoccolella, S; Iaffaldano, P; Fazio, L; Viterbo, R; Popolizio, T; Blasi, G; Bertolino, A; Trojano, M

2013-08-01

Load-related functional magnetic resonance imaging (fMRI) abnormalities of brain activity during performance of attention tasks have been described in definite multiple sclerosis (MS). No data are available in clinically isolated syndrome (CIS) suggestive of MS. The objective of this research is to evaluate in CIS patients the fMRI pattern of brain activation during an attention task and to explore the effect of increasing task load demand on neurofunctional modifications. Twenty-seven untreated CIS patients and 32 age- and sex-matched healthy controls (HCs) underwent fMRI while performing the Variable Attentional Control (VAC) task, a cognitive paradigm requiring increasing levels of attentional control processing. Random-effects models were used for statistical analyses of fMRI data. CIS patients had reduced accuracy and greater reaction time at the VAC task compared with HCs (p=0.007). On blood oxygenation level-dependent (BOLD)-fMRI, CIS patients had greater activity in the right parietal cortex (p=0.0004) compared with HCs. Furthermore, CIS patients had greater activity at the lower (p=0.05) and reduced activity at the greater (p=0.04) level of attentional control demand in the left putamen, compared with HCs. This study demonstrates the failure of attentional control processing in CIS. The load-related fMRI dysfunction of the putamen supports the role of basal ganglia in the failure of attention observed at the earliest stage of MS.

Natural language processing pipelines to annotate BioC collections with an application to the NCBI disease corpus

PubMed Central

Comeau, Donald C.; Liu, Haibin; Islamaj Doğan, Rezarta; Wilbur, W. John

2014-01-01

BioC is a new format and associated code libraries for sharing text and annotations. We have implemented BioC natural language preprocessing pipelines in two popular programming languages: C++ and Java. The current implementations interface with the well-known MedPost and Stanford natural language processing tool sets. The pipeline functionality includes sentence segmentation, tokenization, part-of-speech tagging, lemmatization and sentence parsing. These pipelines can be easily integrated along with other BioC programs into any BioC compliant text mining systems. As an application, we converted the NCBI disease corpus to BioC format, and the pipelines have successfully run on this corpus to demonstrate their functionality. Code and data can be downloaded from http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net PMID:24935050

Multistability of the Brain Network for Self-other Processing

PubMed Central

Chen, Yi-An; Huang, Tsung-Ren

2017-01-01

Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate “self-specific” and “other-specific” regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns. Combining an automated synthesis of fMRI data with a presumption-free diffusion spectrum image (DSI) fibre-tracking algorithm, we isolated a network putatively composed of brain areas and white matter tracts involved in self-other processing. We sampled synchronisation patterns from the dynamical systems of this network using various combinations of physiological parameters. Our results showed that the self-other processing network, with simulated gamma-band activity, tended to stabilise at a number of distinct synchronisation patterns. This phenomenon, termed “multistability,” could serve as an alternative model in theorising the mechanism of processing self-other information. PMID:28256520

Age-Related Variability in Cortical Activity during Language Processing

ERIC Educational Resources Information Center

Fridriksson, Julius; Morrow, K. Leigh; Moser, Dana; Baylis, Gordon C.

2006-01-01

Purpose: The present study investigated the extent of cortical activity during overt picture naming using functional magnetic resonance imaging (fMRI). Method: Participants comprised 20 healthy, adult participants with ages ranging from 20 to 82 years. While undergoing fMRI, participants completed a picture-naming task consisting of 60…

77 FR 58217 - Notice of Delays in Processing of Special Permits Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-19

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration Notice of Delays in Processing of Special Permits Applications AGENCY: Pipeline and Hazardous Materials Safety.... FOR FURTHER INFORMATION CONTACT: Ryan Paquet, Director, Office of Hazardous Materials Special Permits...

77 FR 64846 - Notice of Delays in Processing of Special Permits Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-23

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration Notice of Delays in Processing of Special Permits Applications AGENCY: Pipeline and Hazardous Materials Safety.... FOR FURTHER INFORMATION CONTACT: Ryan Paquet, Director, Office of Hazardous Materials Special Permits...

HiCUP: pipeline for mapping and processing Hi-C data.

PubMed

Wingett, Steven; Ewels, Philip; Furlan-Magaril, Mayra; Nagano, Takashi; Schoenfelder, Stefan; Fraser, Peter; Andrews, Simon

2015-01-01

HiCUP is a pipeline for processing sequence data generated by Hi-C and Capture Hi-C (CHi-C) experiments, which are techniques used to investigate three-dimensional genomic organisation. The pipeline maps data to a specified reference genome and removes artefacts that would otherwise hinder subsequent analysis. HiCUP also produces an easy-to-interpret yet detailed quality control (QC) report that assists in refining experimental protocols for future studies. The software is freely available and has already been used for processing Hi-C and CHi-C data in several recently published peer-reviewed studies.

Enhanced Thalamic Functional Connectivity with No fMRI Responses to Affected Forelimb Stimulation in Stroke-Recovered Rats.

PubMed

Shim, Woo H; Suh, Ji-Yeon; Kim, Jeong K; Jeong, Jaeseung; Kim, Young R

2016-01-01

Neurological recovery after stroke has been extensively investigated to provide better understanding of neurobiological mechanism, therapy, and patient management. Recent advances in neuroimaging techniques, particularly functional MRI (fMRI), have widely contributed to unravel the relationship between the altered neural function and stroke-affected brain areas. As results of previous investigations, the plastic reorganization and/or gradual restoration of the hemodynamic fMRI responses to neural stimuli have been suggested as relevant mechanisms underlying the stroke recovery process. However, divergent study results and modality-dependent outcomes have clouded the proper interpretation of variable fMRI signals. Here, we performed both evoked and resting state fMRI (rs-fMRI) to clarify the link between the fMRI phenotypes and post-stroke functional recovery. The experiments were designed to examine the altered neural activity within the contra-lesional hemisphere and other undamaged brain regions using rat models with large unilateral stroke, which despite the severe injury, exhibited nearly full recovery at ∼6 months after stroke. Surprisingly, both blood oxygenation level-dependent and blood volume-weighted (CBVw) fMRI activities elicited by electrical stimulation of the stroke-affected forelimb were completely absent, failing to reveal the neural origin of the behavioral recovery. In contrast, the functional connectivity maps showed highly robust rs-fMRI activity concentrated in the contra-lesional ventromedial nucleus of thalamus (VM). The negative finding in the stimuli-induced fMRI study using the popular rat middle cerebral artery model denotes weak association between the fMRI hemodynamic responses and neurological improvement. The results strongly caution the indiscreet interpretation of stroke-affected fMRI signals and demonstrate rs-fMRI as a complementary tool for efficiently characterizing stroke recovery.

The Perception of Dynamic and Static Facial Expressions of Happiness and Disgust Investigated by ERPs and fMRI Constrained Source Analysis

PubMed Central

Trautmann-Lengsfeld, Sina Alexa; Domínguez-Borràs, Judith; Escera, Carles; Herrmann, Manfred; Fehr, Thorsten

2013-01-01

A recent functional magnetic resonance imaging (fMRI) study by our group demonstrated that dynamic emotional faces are more accurately recognized and evoked more widespread patterns of hemodynamic brain responses than static emotional faces. Based on this experimental design, the present study aimed at investigating the spatio-temporal processing of static and dynamic emotional facial expressions in 19 healthy women by means of multi-channel electroencephalography (EEG), event-related potentials (ERP) and fMRI-constrained regional source analyses. ERP analysis showed an increased amplitude of the LPP (late posterior positivity) over centro-parietal regions for static facial expressions of disgust compared to neutral faces. In addition, the LPP was more widespread and temporally prolonged for dynamic compared to static faces of disgust and happiness. fMRI constrained source analysis on static emotional face stimuli indicated the spatio-temporal modulation of predominantly posterior regional brain activation related to the visual processing stream for both emotional valences when compared to the neutral condition in the fusiform gyrus. The spatio-temporal processing of dynamic stimuli yielded enhanced source activity for emotional compared to neutral conditions in temporal (e.g., fusiform gyrus), and frontal regions (e.g., ventromedial prefrontal cortex, medial and inferior frontal cortex) in early and again in later time windows. The present data support the view that dynamic facial displays trigger more information reflected in complex neural networks, in particular because of their changing features potentially triggering sustained activation related to a continuing evaluation of those faces. A combined fMRI and EEG approach thus provides an advanced insight to the spatio-temporal characteristics of emotional face processing, by also revealing additional neural generators, not identifiable by the only use of an fMRI approach. PMID:23818974

Biology and therapy of fibromyalgia. Functional magnetic resonance imaging findings in fibromyalgia

PubMed Central

Williams, David A; Gracely, Richard H

2006-01-01

Techniques in neuroimaging such as functional magnetic resonance imaging (fMRI) have helped to provide insights into the role of supraspinal mechanisms in pain perception. This review focuses on studies that have applied fMRI in an attempt to gain a better understanding of the mechanisms involved in the processing of pain associated with fibromyalgia. This article provides an overview of the nociceptive system as it functions normally, reviews functional brain imaging methods, and integrates the existing literature utilizing fMRI to study central pain mechanisms in fibromyalgia. PMID:17254318

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave.

PubMed

Oosterhof, Nikolaas N; Connolly, Andrew C; Haxby, James V

2016-01-01

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA.

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave

PubMed Central

Oosterhof, Nikolaas N.; Connolly, Andrew C.; Haxby, James V.

2016-01-01

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA PMID:27499741

Natural language processing pipelines to annotate BioC collections with an application to the NCBI disease corpus.

PubMed

Comeau, Donald C; Liu, Haibin; Islamaj Doğan, Rezarta; Wilbur, W John

2014-01-01

BioC is a new format and associated code libraries for sharing text and annotations. We have implemented BioC natural language preprocessing pipelines in two popular programming languages: C++ and Java. The current implementations interface with the well-known MedPost and Stanford natural language processing tool sets. The pipeline functionality includes sentence segmentation, tokenization, part-of-speech tagging, lemmatization and sentence parsing. These pipelines can be easily integrated along with other BioC programs into any BioC compliant text mining systems. As an application, we converted the NCBI disease corpus to BioC format, and the pipelines have successfully run on this corpus to demonstrate their functionality. Code and data can be downloaded from http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net. © The Author(s) 2014. Published by Oxford University Press.

Practice guideline summary: Use of fMRI in the presurgical evaluation of patients with epilepsy

PubMed Central

Szaflarski, Jerzy P.; Gloss, David; Binder, Jeffrey R.; Gaillard, William D.; Golby, Alexandra J.; Holland, Scott K.; Ojemann, Jeffrey; Spencer, David C.; Swanson, Sara J.; French, Jacqueline A.; Theodore, William H.

2017-01-01

Objective: To assess the diagnostic accuracy and prognostic value of functional MRI (fMRI) in determining lateralization and predicting postsurgical language and memory outcomes. Methods: An 11-member panel evaluated and rated available evidence according to the 2004 American Academy of Neurology process. At least 2 panelists reviewed the full text of 172 articles and selected 37 for data extraction. Case reports, reports with <15 cases, meta-analyses, and editorials were excluded. Results and recommendations: The use of fMRI may be considered an option for lateralizing language functions in place of intracarotid amobarbital procedure (IAP) in patients with medial temporal lobe epilepsy (MTLE; Level C), temporal epilepsy in general (Level C), or extratemporal epilepsy (Level C). For patients with temporal neocortical epilepsy or temporal tumors, the evidence is insufficient (Level U). fMRI may be considered to predict postsurgical language deficits after anterior temporal lobe resection (Level C). The use of fMRI may be considered for lateralizing memory functions in place of IAP in patients with MTLE (Level C) but is of unclear utility in other epilepsy types (Level U). fMRI of verbal memory or language encoding should be considered for predicting verbal memory outcome (Level B). fMRI using nonverbal memory encoding may be considered for predicting visuospatial memory outcomes (Level C). Presurgical fMRI could be an adequate alternative to IAP memory testing for predicting verbal memory outcome (Level C). Clinicians should carefully advise patients of the risks and benefits of fMRI vs IAP during discussions concerning choice of specific modality in each case. PMID:28077494

Kepler Science Operations Center Architecture

NASA Technical Reports Server (NTRS)

Middour, Christopher; Klaus, Todd; Jenkins, Jon; Pletcher, David; Cote, Miles; Chandrasekaran, Hema; Wohler, Bill; Girouard, Forrest; Gunter, Jay P.; Uddin, Kamal;

The insula is not specifically involved in disgust processing: an fMRI study.

PubMed

Schienle, A; Stark, R; Walter, B; Blecker, C; Ott, U; Kirsch, P; Sammer, G; Vaitl, D

2002-11-15

fMRI studies have shown that the perception of facial disgust expressions specifically activates the insula. The present fMRI study investigated whether this structure is also involved in the processing of visual stimuli depicting non-mimic disgust elicitors compared to fear-inducing and neutral scenes. Twelve female subjects were scanned while viewing alternating blocks of 40 disgust-inducing, 40 fear-inducing and 40 affectively neutral pictures, shown for 1.5 s each. Afterwards, affective ratings were assessed. The disgust pictures, rated as highly repulsive, induced activation in the insula, the amygdala, the orbitofrontal and occipito-temporal cortex. Since during the fear condition the insula was also involved, our findings do not fit the idea of the insula as a specific disgust processor.

Interleaved EPI based fMRI improved by multiplexed sensitivity encoding (MUSE) and simultaneous multi-band imaging.

PubMed

Chang, Hing-Chiu; Gaur, Pooja; Chou, Ying-hui; Chu, Mei-Lan; Chen, Nan-kuei

2014-01-01

Functional magnetic resonance imaging (fMRI) is a non-invasive and powerful imaging tool for detecting brain activities. The majority of fMRI studies are performed with single-shot echo-planar imaging (EPI) due to its high temporal resolution. Recent studies have demonstrated that, by increasing the spatial-resolution of fMRI, previously unidentified neuronal networks can be measured. However, it is challenging to improve the spatial resolution of conventional single-shot EPI based fMRI. Although multi-shot interleaved EPI is superior to single-shot EPI in terms of the improved spatial-resolution, reduced geometric distortions, and sharper point spread function (PSF), interleaved EPI based fMRI has two main limitations: 1) the imaging throughput is lower in interleaved EPI; 2) the magnitude and phase signal variations among EPI segments (due to physiological noise, subject motion, and B0 drift) are translated to significant in-plane aliasing artifact across the field of view (FOV). Here we report a method that integrates multiple approaches to address the technical limitations of interleaved EPI-based fMRI. Firstly, the multiplexed sensitivity-encoding (MUSE) post-processing algorithm is used to suppress in-plane aliasing artifacts resulting from time-domain signal instabilities during dynamic scans. Secondly, a simultaneous multi-band interleaved EPI pulse sequence, with a controlled aliasing scheme incorporated, is implemented to increase the imaging throughput. Thirdly, the MUSE algorithm is then generalized to accommodate fMRI data obtained with our multi-band interleaved EPI pulse sequence, suppressing both in-plane and through-plane aliasing artifacts. The blood-oxygenation-level-dependent (BOLD) signal detectability and the scan throughput can be significantly improved for interleaved EPI-based fMRI. Our human fMRI data obtained from 3 Tesla systems demonstrate the effectiveness of the developed methods. It is expected that future fMRI studies requiring high spatial-resolvability and fidelity will largely benefit from the reported techniques.

Real-time fMRI processing with physiological noise correction - Comparison with off-line analysis.

PubMed

Misaki, Masaya; Barzigar, Nafise; Zotev, Vadim; Phillips, Raquel; Cheng, Samuel; Bodurka, Jerzy

2015-12-30

While applications of real-time functional magnetic resonance imaging (rtfMRI) are growing rapidly, there are still limitations in real-time data processing compared to off-line analysis. We developed a proof-of-concept real-time fMRI processing (rtfMRIp) system utilizing a personal computer (PC) with a dedicated graphic processing unit (GPU) to demonstrate that it is now possible to perform intensive whole-brain fMRI data processing in real-time. The rtfMRIp performs slice-timing correction, motion correction, spatial smoothing, signal scaling, and general linear model (GLM) analysis with multiple noise regressors including physiological noise modeled with cardiac (RETROICOR) and respiration volume per time (RVT). The whole-brain data analysis with more than 100,000voxels and more than 250volumes is completed in less than 300ms, much faster than the time required to acquire the fMRI volume. Real-time processing implementation cannot be identical to off-line analysis when time-course information is used, such as in slice-timing correction, signal scaling, and GLM. We verified that reduced slice-timing correction for real-time analysis had comparable output with off-line analysis. The real-time GLM analysis, however, showed over-fitting when the number of sampled volumes was small. Our system implemented real-time RETROICOR and RVT physiological noise corrections for the first time and it is capable of processing these steps on all available data at a given time, without need for recursive algorithms. Comprehensive data processing in rtfMRI is possible with a PC, while the number of samples should be considered in real-time GLM. Copyright © 2015 Elsevier B.V. All rights reserved.

Encoding model of temporal processing in human visual cortex.

PubMed

Stigliani, Anthony; Jeska, Brianna; Grill-Spector, Kalanit

2017-12-19

How is temporal information processed in human visual cortex? Visual input is relayed to V1 through segregated transient and sustained channels in the retina and lateral geniculate nucleus (LGN). However, there is intense debate as to how sustained and transient temporal channels contribute to visual processing beyond V1. The prevailing view associates transient processing predominately with motion-sensitive regions and sustained processing with ventral stream regions, while the opposing view suggests that both temporal channels contribute to neural processing beyond V1. Using fMRI, we measured cortical responses to time-varying stimuli and then implemented a two temporal channel-encoding model to evaluate the contributions of each channel. Different from the general linear model of fMRI that predicts responses directly from the stimulus, the encoding approach first models neural responses to the stimulus from which fMRI responses are derived. This encoding approach not only predicts cortical responses to time-varying stimuli from milliseconds to seconds but also, reveals differential contributions of temporal channels across visual cortex. Consistent with the prevailing view, motion-sensitive regions and adjacent lateral occipitotemporal regions are dominated by transient responses. However, ventral occipitotemporal regions are driven by both sustained and transient channels, with transient responses exceeding the sustained. These findings propose a rethinking of temporal processing in the ventral stream and suggest that transient processing may contribute to rapid extraction of the content of the visual input. Importantly, our encoding approach has vast implications, because it can be applied with fMRI to decipher neural computations in millisecond resolution in any part of the brain. Copyright © 2017 the Author(s). Published by PNAS.

A Pipeline Tool for CCD Image Processing

NASA Astrophysics Data System (ADS)

Bell, Jon F.; Young, Peter J.; Roberts, William H.; Sebo, Kim M.

MSSSO is part of a collaboration developing a wide field imaging CCD mosaic (WFI). As part of this project, we have developed a GUI based pipeline tool that is an integrated part of MSSSO's CICADA data acquisition environment and processes CCD FITS images as they are acquired. The tool is also designed to run as a stand alone program to process previously acquired data. IRAF tasks are used as the central engine, including the new NOAO mscred package for processing multi-extension FITS files. The STScI OPUS pipeline environment may be used to manage data and process scheduling. The Motif GUI was developed using SUN Visual Workshop. C++ classes were written to facilitate launching of IRAF and OPUS tasks. While this first version implements calibration processing up to and including flat field corrections, there is scope to extend it to other processing.

Typical and Atypical Neurodevelopment for Face Specialization: An fMRI Study

ERIC Educational Resources Information Center

Joseph, Jane E.; Zhu, Xun; Gundran, Andrew; Davies, Faraday; Clark, Jonathan D.; Ruble, Lisa; Glaser, Paul; Bhatt, Ramesh S.

2015-01-01

Individuals with autism spectrum disorder (ASD) and their relatives process faces differently from typically developed (TD) individuals. In an fMRI face-viewing task, TD and undiagnosed sibling (SIB) children (5-18 years) showed face specialization in the right amygdala and ventromedial prefrontal cortex, with left fusiform and right amygdala face…

Decoding Overlapping Memories in the Medial Temporal Lobes Using High-Resolution fMRI

ERIC Educational Resources Information Center

Chadwick, Martin J.; Hassabis, Demis; Maguire, Eleanor A.

2011-01-01

The hippocampus is proposed to process overlapping episodes as discrete memory traces, although direct evidence for this in human episodic memory is scarce. Using green-screen technology we created four highly overlapping movies of everyday events. Participants were scanned using high-resolution fMRI while recalling the movies. Multivariate…

Neural Changes after Phonological Treatment for Anomia: An fMRI Study

ERIC Educational Resources Information Center

Rochon, Elizabeth; Leonard, Carol; Burianova, Hana; Laird, Laura; Soros, Peter; Graham, Simon; Grady, Cheryl

2010-01-01

Functional magnetic resonance imaging (fMRI) was used to investigate the neural processing characteristics associated with word retrieval abilities after a phonologically-based treatment for anomia in two stroke patients with aphasia. Neural activity associated with a phonological and a semantic task was compared before and after treatment with…

76 FR 56009 - Mandatory Reporting of Greenhouse Gases: Technical Revisions to the Electronics Manufacturing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-09

... Pipeline transportation of natural gas. 221210 Natural gas distribution facilities. 211 Extractors of crude... natural gas processing facilities in transmission pipelines or into storage. 40 CFR Sec. 98.230(a)(4). A... and inaccuracies in reporting''. Pipeline Quality Yes. Natural Gas. CEC/ AXPC asserted that ``[t]here...

76 FR 60478 - Record of Decision, Texas Clean Energy Project

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-29

... the plant with one or both of the nearby power grids; process water supply pipelines; a natural gas... per year. The CO 2 will be delivered through a regional pipeline network to existing oil fields in the... proposed Fort Stockton Holdings water supply pipeline; Possible changes in discharges to Monahans Draw and...

Relationship between Pipeline Wall Thickness (Gr. X60) and Water Depth towards Avoiding Failure during Installation

NASA Astrophysics Data System (ADS)

Razak, K. Abdul; Othman, M. I. H.; Mat Yusuf, S.; Fuad, M. F. I. Ahmad; yahaya, Effah

2018-05-01

Oil and gas today being developed at different water depth characterized as shallow, deep and ultra-deep waters. Among the major components involved during the offshore installation is pipelines. Pipelines are a transportation method of material through a pipe. In oil and gas industry, pipeline come from a bunch of line pipe that welded together to become a long pipeline and can be divided into two which is gas pipeline and oil pipeline. In order to perform pipeline installation, we need pipe laying barge or pipe laying vessel. However, pipe laying vessel can be divided into two types: S-lay vessel and J-lay vessel. The function of pipe lay vessel is not only to perform pipeline installation. It also performed installation of umbilical or electrical cables. In the simple words, pipe lay vessel is performing the installation of subsea in all the connecting infrastructures. Besides that, the installation processes of pipelines require special focus to make the installation succeed. For instance, the heavy pipelines may exceed the lay vessel’s tension capacities in certain kind of water depth. Pipeline have their own characteristic and we can group it or differentiate it by certain parameters such as grade of material, type of material, size of diameter, size of wall thickness and the strength. For instances, wall thickness parameter studies indicate that if use the higher steel grade of the pipelines will have a significant contribution in pipeline wall thickness reduction. When running the process of pipe lay, water depth is the most critical thing that we need to monitor and concern about because of course we cannot control the water depth but we can control the characteristic of the pipe like apply line pipe that have wall thickness suitable with current water depth in order to avoid failure during the installation. This research will analyse whether the pipeline parameter meet the requirements limit and minimum yield stress. It will overlook to simulate pipe grade API 5L X60 which size from 8 to 20mm thickness with a water depth of 50 to 300m. Result shown that pipeline installation will fail from the wall thickness of 18mm onwards since it has been passed the critical yield percentage.

Unipro UGENE NGS pipelines and components for variant calling, RNA-seq and ChIP-seq data analyses.

PubMed

Golosova, Olga; Henderson, Ross; Vaskin, Yuriy; Gabrielian, Andrei; Grekhov, German; Nagarajan, Vijayaraj; Oler, Andrew J; Quiñones, Mariam; Hurt, Darrell; Fursov, Mikhail; Huyen, Yentram

2014-01-01

The advent of Next Generation Sequencing (NGS) technologies has opened new possibilities for researchers. However, the more biology becomes a data-intensive field, the more biologists have to learn how to process and analyze NGS data with complex computational tools. Even with the availability of common pipeline specifications, it is often a time-consuming and cumbersome task for a bench scientist to install and configure the pipeline tools. We believe that a unified, desktop and biologist-friendly front end to NGS data analysis tools will substantially improve productivity in this field. Here we present NGS pipelines "Variant Calling with SAMtools", "Tuxedo Pipeline for RNA-seq Data Analysis" and "Cistrome Pipeline for ChIP-seq Data Analysis" integrated into the Unipro UGENE desktop toolkit. We describe the available UGENE infrastructure that helps researchers run these pipelines on different datasets, store and investigate the results and re-run the pipelines with the same parameters. These pipeline tools are included in the UGENE NGS package. Individual blocks of these pipelines are also available for expert users to create their own advanced workflows.

The Dark Energy Survey Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Morganson, E.; Gruendl, R. A.; Menanteau, F.; Carrasco Kind, M.; Chen, Y.-C.; Daues, G.; Drlica-Wagner, A.; Friedel, D. N.; Gower, M.; Johnson, M. W. G.; Johnson, M. D.; Kessler, R.; Paz-Chinchón, F.; Petravick, D.; Pond, C.; Yanny, B.; Allam, S.; Armstrong, R.; Barkhouse, W.; Bechtol, K.; Benoit-Lévy, A.; Bernstein, G. M.; Bertin, E.; Buckley-Geer, E.; Covarrubias, R.; Desai, S.; Diehl, H. T.; Goldstein, D. A.; Gruen, D.; Li, T. S.; Lin, H.; Marriner, J.; Mohr, J. J.; Neilsen, E.; Ngeow, C.-C.; Paech, K.; Rykoff, E. S.; Sako, M.; Sevilla-Noarbe, I.; Sheldon, E.; Sobreira, F.; Tucker, D. L.; Wester, W.; DES Collaboration

2018-07-01

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg2 survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of ∼24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ∼27 deg2. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

The Kepler Science Operations Center Pipeline Framework Extensions

NASA Technical Reports Server (NTRS)

Klaus, Todd C.; Cote, Miles T.; McCauliff, Sean; Girouard, Forrest R.; Wohler, Bill; Allen, Christopher; Chandrasekaran, Hema; Bryson, Stephen T.; Middour, Christopher; Caldwell, Douglas A.;

Functional brain segmentation using inter-subject correlation in fMRI.

PubMed

Kauppi, Jukka-Pekka; Pajula, Juha; Niemi, Jari; Hari, Riitta; Tohka, Jussi

2017-05-01

The human brain continuously processes massive amounts of rich sensory information. To better understand such highly complex brain processes, modern neuroimaging studies are increasingly utilizing experimental setups that better mimic daily-life situations. A new exploratory data-analysis approach, functional segmentation inter-subject correlation analysis (FuSeISC), was proposed to facilitate the analysis of functional magnetic resonance (fMRI) data sets collected in these experiments. The method provides a new type of functional segmentation of brain areas, not only characterizing areas that display similar processing across subjects but also areas in which processing across subjects is highly variable. FuSeISC was tested using fMRI data sets collected during traditional block-design stimuli (37 subjects) as well as naturalistic auditory narratives (19 subjects). The method identified spatially local and/or bilaterally symmetric clusters in several cortical areas, many of which are known to be processing the types of stimuli used in the experiments. The method is not only useful for spatial exploration of large fMRI data sets obtained using naturalistic stimuli, but also has other potential applications, such as generation of a functional brain atlases including both lower- and higher-order processing areas. Finally, as a part of FuSeISC, a criterion-based sparsification of the shared nearest-neighbor graph was proposed for detecting clusters in noisy data. In the tests with synthetic data, this technique was superior to well-known clustering methods, such as Ward's method, affinity propagation, and K-means ++. Hum Brain Mapp 38:2643-2665, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A Comparison of Five FMRI Protocols for Mapping Speech Comprehension Systems

PubMed Central

Binder, Jeffrey R.; Swanson, Sara J.; Hammeke, Thomas A.; Sabsevitz, David S.

2008-01-01

Aims Many fMRI protocols for localizing speech comprehension have been described, but there has been little quantitative comparison of these methods. We compared five such protocols in terms of areas activated, extent of activation, and lateralization. Methods FMRI BOLD signals were measured in 26 healthy adults during passive listening and active tasks using words and tones. Contrasts were designed to identify speech perception and semantic processing systems. Activation extent and lateralization were quantified by counting activated voxels in each hemisphere for each participant. Results Passive listening to words produced bilateral superior temporal activation. After controlling for pre-linguistic auditory processing, only a small area in the left superior temporal sulcus responded selectively to speech. Active tasks engaged an extensive, bilateral attention and executive processing network. Optimal results (consistent activation and strongly lateralized pattern) were obtained by contrasting an active semantic decision task with a tone decision task. There was striking similarity between the network of brain regions activated by the semantic task and the network of brain regions that showed task-induced deactivation, suggesting that semantic processing occurs during the resting state. Conclusions FMRI protocols for mapping speech comprehension systems differ dramatically in pattern, extent, and lateralization of activation. Brain regions involved in semantic processing were identified only when an active, non-linguistic task was used as a baseline, supporting the notion that semantic processing occurs whenever attentional resources are not controlled. Identification of these lexical-semantic regions is particularly important for predicting language outcome in patients undergoing temporal lobe surgery. PMID:18513352

Different brain activation under left and right ventricular stimulation: an fMRI study in anesthetized rats.

PubMed

Suzuki, Hideaki; Sumiyoshi, Akira; Kawashima, Ryuta; Shimokawa, Hiroaki

2013-01-01

Myocardial ischemia in the anterior wall of the left ventricule (LV) and in the inferior wall and/or right ventricle (RV) shows different manifestations that can be explained by the different innervations of cardiac afferent nerves. However, it remains unclear whether information from different areas of the heart, such as the LV and RV, are differently processed in the brain. In this study, we investigated the brain regions that process information from the LV or RV using cardiac electrical stimulation and functional magnetic resonance imaging (fMRI) in anesthetized rats because the combination of these two approaches cannot be used in humans. An electrical stimulation catheter was inserted into the LV or RV (n = 12 each). Brain fMRI scans were recorded during LV or RV stimulation (9 Hz and 0.3 ms width) over 10 blocks consisting of alternating periods of 2 mA for 30 sec followed by 0.2 mA for 60 sec. The validity of fMRI signals was confirmed by first and second-level analyses and temporal profiles. Increases in fMRI signals were observed in the anterior cingulate cortex and the right somatosensory cortex under LV stimulation. In contrast, RV stimulation activated the right somatosensory cortex, which was identified more anteriorly compared with LV stimulation but did not activate the anterior cingulate cortex. This study provides the first evidence for differences in brain activation under LV and RV stimulation. These different brain processes may be associated with different clinical manifestations between anterior wall and inferoposterior wall and/or RV myocardial ischemia.

Coil compression in simultaneous multislice functional MRI with concentric ring slice-GRAPPA and SENSE.

PubMed

Chu, Alan; Noll, Douglas C

2016-10-01

Simultaneous multislice (SMS) imaging is a useful way to accelerate functional magnetic resonance imaging (fMRI). As acceleration becomes more aggressive, an increasingly larger number of receive coils are required to separate the slices, which significantly increases the computational burden. We propose a coil compression method that works with concentric ring non-Cartesian SMS imaging and should work with Cartesian SMS as well. We evaluate the method on fMRI scans of several subjects and compare it to standard coil compression methods. The proposed method uses a slice-separation k-space kernel to simultaneously compress coil data into a set of virtual coils. Five subjects were scanned using both non-SMS fMRI and SMS fMRI with three simultaneous slices. The SMS fMRI scans were processed using the proposed method, along with other conventional methods. Code is available at https://github.com/alcu/sms. The proposed method maintained functional activation with a fewer number of virtual coils than standard SMS coil compression methods. Compression of non-SMS fMRI maintained activation with a slightly lower number of virtual coils than the proposed method, but does not have the acceleration advantages of SMS fMRI. The proposed method is a practical way to compress and reconstruct concentric ring SMS data and improves the preservation of functional activation over standard coil compression methods in fMRI. Magn Reson Med 76:1196-1209, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Functional MR imaging assessment of a non-responsive brain injured patient.

PubMed

Moritz, C H; Rowley, H A; Haughton, V M; Swartz, K R; Jones, J; Badie, B

2001-10-01

Functional magnetic resonance imaging (fMRI) was requested to assist in the evaluation of a comatose 38-year-old woman who had sustained multiple cerebral contusions from a motor vehicle accident. Previous electrophysiologic studies suggested absence of thalamocortical processing in response to median nerve stimulation. Whole-brain fMRI was performed utilizing visual, somatosensory, and auditory stimulation paradigms. Results demonstrated intact task-correlated sensory and cognitive blood oxygen level dependent (BOLD) hemodynamic response to stimuli. Electrodiagnostic studies were repeated and evoked potentials indicated supratentorial recovery in the cerebrum. At 3-months post trauma the patient had recovered many cognitive & sensorimotor functions, accurately reflecting the prognostic fMRI evaluation. These results indicate that fMRI examinations may provide a useful evaluation for brain function in non-responsive brain trauma patients.

Practical Approach for Hyperspectral Image Processing in Python

NASA Astrophysics Data System (ADS)

Annala, L.; Eskelinen, M. A.; Hämäläinen, J.; Riihinen, A.; Pölönen, I.

2018-04-01

Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.

Inner experience in the scanner: can high fidelity apprehensions of inner experience be integrated with fMRI?

PubMed Central

Kühn, Simone; Fernyhough, Charles; Alderson-Day, Benjamin; Hurlburt, Russell T.

2014-01-01

To provide full accounts of human experience and behavior, research in cognitive neuroscience must be linked to inner experience, but introspective reports of inner experience have often been found to be unreliable. The present case study aimed at providing proof of principle that introspection using one method, descriptive experience sampling (DES), can be reliably integrated with fMRI. A participant was trained in the DES method, followed by nine sessions of sampling within an MRI scanner. During moments where the DES interview revealed ongoing inner speaking, fMRI data reliably showed activation in classic speech processing areas including left inferior frontal gyrus. Further, the fMRI data validated the participant’s DES observations of the experiential distinction between inner speaking and innerly hearing her own voice. These results highlight the precision and validity of the DES method as a technique of exploring inner experience and the utility of combining such methods with fMRI. PMID:25538649

UOE Pipe Numerical Model: Manufacturing Process And Von Mises Residual Stresses Resulted After Each Technological Step

NASA Astrophysics Data System (ADS)

Delistoian, Dmitri; Chirchor, Mihael

2017-12-01

Fluid transportation from production areas to final customer is effectuated by pipelines. For oil and gas industry, pipeline safety and reliability represents a priority. From this reason, pipe quality guarantee directly influence pipeline designed life, but first of all protects environment. A significant number of longitudinally welded pipes, for onshore/offshore pipelines, are manufactured by UOE method. This method is based on cold forming. In present study, using finite element method is modeled UOE pipe manufacturing process and is obtained von Mises stresses for each step. Numerical simulation is performed for L415 MB (X60) steel plate with 7,9 mm thickness, length 30 mm and width 1250mm, as result it is obtained a DN 400 pipe.

fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli.

PubMed

Alink, Arjen; Krugliak, Alexandra; Walther, Alexander; Kriegeskorte, Nikolaus

2013-01-01

The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low resolution (3-mm isotropic voxels). This finding has suggested that columnar-level neuronal information might be accessible to fMRI at 3T. However, orientation decodability might alternatively arise from global orientation-preference maps. Such global maps across V1 could result from bottom-up processing, if the preferences of V1 neurons were biased toward particular orientations (e.g., radial from fixation, or cardinal, i.e., vertical or horizontal). Global maps could also arise from local recurrent or top-down processing, reflecting pre-attentive perceptual grouping, attention spreading, or predictive coding of global form. Here we investigate whether fMRI orientation decoding with 2-mm voxels requires (a) globally coherent orientation stimuli and/or (b) global-scale patterns of V1 activity. We used opposite-orientation gratings (balanced about the cardinal orientations) and spirals (balanced about the radial orientation), along with novel patch-swapped variants of these stimuli. The two stimuli of a patch-swapped pair have opposite orientations everywhere (like their globally coherent parent stimuli). However, the two stimuli appear globally similar, a patchwork of opposite orientations. We find that all stimulus pairs are robustly decodable, demonstrating that fMRI orientation decoding does not require globally coherent orientation stimuli. Furthermore, decoding remained robust after spatial high-pass filtering for all stimuli, showing that fine-grained components of the fMRI patterns reflect visual orientations. Consistent with previous studies, we found evidence for global radial and vertical preference maps in V1. However, these were weak or absent for patch-swapped stimuli, suggesting that global preference maps depend on globally coherent orientations and might arise through recurrent or top-down processes related to the perception of global form.

An image processing pipeline to detect and segment nuclei in muscle fiber microscopic images.

PubMed

Guo, Yanen; Xu, Xiaoyin; Wang, Yuanyuan; Wang, Yaming; Xia, Shunren; Yang, Zhong

2014-08-01

Muscle fiber images play an important role in the medical diagnosis and treatment of many muscular diseases. The number of nuclei in skeletal muscle fiber images is a key bio-marker of the diagnosis of muscular dystrophy. In nuclei segmentation one primary challenge is to correctly separate the clustered nuclei. In this article, we developed an image processing pipeline to automatically detect, segment, and analyze nuclei in microscopic image of muscle fibers. The pipeline consists of image pre-processing, identification of isolated nuclei, identification and segmentation of clustered nuclei, and quantitative analysis. Nuclei are initially extracted from background by using local Otsu's threshold. Based on analysis of morphological features of the isolated nuclei, including their areas, compactness, and major axis lengths, a Bayesian network is trained and applied to identify isolated nuclei from clustered nuclei and artifacts in all the images. Then a two-step refined watershed algorithm is applied to segment clustered nuclei. After segmentation, the nuclei can be quantified for statistical analysis. Comparing the segmented results with those of manual analysis and an existing technique, we find that our proposed image processing pipeline achieves good performance with high accuracy and precision. The presented image processing pipeline can therefore help biologists increase their throughput and objectivity in analyzing large numbers of nuclei in muscle fiber images. © 2014 Wiley Periodicals, Inc.

Comparison of fMRI paradigms assessing visuospatial processing: Robustness and reproducibility

PubMed Central

Herholz, Peer; Zimmermann, Kristin M.; Westermann, Stefan; Frässle, Stefan; Jansen, Andreas

2017-01-01

The development of brain imaging techniques, in particular functional magnetic resonance imaging (fMRI), made it possible to non-invasively study the hemispheric lateralization of cognitive brain functions in large cohorts. Comprehensive models of hemispheric lateralization are, however, still missing and should not only account for the hemispheric specialization of individual brain functions, but also for the interactions among different lateralized cognitive processes (e.g., language and visuospatial processing). This calls for robust and reliable paradigms to study hemispheric lateralization for various cognitive functions. While numerous reliable imaging paradigms have been developed for language, which represents the most prominent left-lateralized brain function, the reliability of imaging paradigms investigating typically right-lateralized brain functions, such as visuospatial processing, has received comparatively less attention. In the present study, we aimed to establish an fMRI paradigm that robustly and reliably identifies right-hemispheric activation evoked by visuospatial processing in individual subjects. In a first study, we therefore compared three frequently used paradigms for assessing visuospatial processing and evaluated their utility to robustly detect right-lateralized brain activity on a single-subject level. In a second study, we then assessed the test-retest reliability of the so-called Landmark task–the paradigm that yielded the most robust results in study 1. At the single-voxel level, we found poor reliability of the brain activation underlying visuospatial attention. This suggests that poor signal-to-noise ratios can become a limiting factor for test-retest reliability. This represents a common detriment of fMRI paradigms investigating visuospatial attention in general and therefore highlights the need for careful considerations of both the possibilities and limitations of the respective fMRI paradigm–in particular, when being interested in effects at the single-voxel level. Notably, however, when focusing on the reliability of measures of hemispheric lateralization (which was the main goal of study 2), we show that hemispheric dominance (quantified by the lateralization index, LI, with |LI| >0.4) of the evoked activation could be robustly determined in more than 62% and, if considering only two categories (i.e., left, right), in more than 93% of our subjects. Furthermore, the reliability of the lateralization strength (LI) was “fair” to “good”. In conclusion, our results suggest that the degree of right-hemispheric dominance during visuospatial processing can be reliably determined using the Landmark task, both at the group and single-subject level, while at the same time stressing the need for future refinements of experimental paradigms and more sophisticated fMRI data acquisition techniques. PMID:29059201

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT.

PubMed

Schenk, Andreas D; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-05-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library and Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. Copyright © 2013 Elsevier Inc. All rights reserved.

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT

PubMed Central

Schenk, Andreas D.; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-01-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library & Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. PMID:23500887

A functional Magnetic Resonance Imaging study of neurohemodynamic abnormalities during emotion processing in subjects at high risk for schizophrenia

PubMed Central

Venkatasubramanian, Ganesan; Puthumana, Dawn Thomas K.; Jayakumar, Peruvumba N.; Gangadhar, B. N.

2010-01-01

Background: Emotion processing abnormalities are considered among the core deficits in schizophrenia. Subjects at high risk (HR) for schizophrenia also show these deficits. Structural neuroimaging studies examining unaffected relatives at high risk for schizophrenia have demonstrated neuroanatomical abnormalities involving neo-cortical and sub-cortical brain regions related to emotion processing. The brain functional correlates of emotion processing in these HR subjects in the context of ecologically valid, real-life dynamic images using functional Magnetic Resonance Imaging (fMRI) has not been examined previously. Aim: To examine the neurohemodynamic abnormalities during emotion processing in unaffected subjects at high risk for schizophrenia in comparison with age-, sex-, handedness- and education-matched healthy controls, using fMRI. Materials and Methods: HR subjects for schizophrenia (n=17) and matched healthy controls (n=16) were examined. The emotion processing of fearful facial expression was examined using a culturally appropriate and valid tool for Indian subjects. The fMRI was performed in a 1.5-T scanner during an implicit emotion processing paradigm. The fMRI analyses were performed using the Statistical Parametric Mapping 2 (SPM2) software. Results: HR subjects had significantly reduced brain activations in left insula, left medial frontal gyrus, left inferior frontal gyrus, right cingulate gyrus, right precentral gyrus and right inferior parietal lobule. Hypothesis-driven region-of-interest analysis revealed hypoactivation of right amygdala in HR subjects. Conclusions: Study findings suggest that neurohemodynamic abnormalities involving limbic and frontal cortices could be potential indicators for increased vulnerability toward schizophrenia. The clinical utility of these novel findings in predicting the development of psychosis needs to be evaluated. PMID:21267363

Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect

PubMed Central

Folia, Vasiliki; Petersson, Karl Magnus

2014-01-01

In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs. PMID:24550865

Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect.

PubMed

Folia, Vasiliki; Petersson, Karl Magnus

2014-01-01

In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.

The connectome mapper: an open-source processing pipeline to map connectomes with MRI.

PubMed

Daducci, Alessandro; Gerhard, Stephan; Griffa, Alessandra; Lemkaddem, Alia; Cammoun, Leila; Gigandet, Xavier; Meuli, Reto; Hagmann, Patric; Thiran, Jean-Philippe

2012-01-01

Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org.

77 FR 48112 - Pipeline Safety: Administrative Procedures; Updates and Technical Corrections

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-13

...This Notice of Proposed Rulemaking updates the administrative civil penalty maximums for violation of the pipeline safety regulations to conform to current law, updates the informal hearing and adjudication process for pipeline enforcement matters to conform to current law, amends other administrative procedures used by PHMSA personnel, and makes other technical corrections and updates to certain administrative procedures. The proposed amendments do not impose any new operating, maintenance, or other substantive requirements on pipeline owners or operators.

Sensitivity and specificity considerations for fMRI encoding, decoding, and mapping of auditory cortex at ultra-high field.

PubMed

Moerel, Michelle; De Martino, Federico; Kemper, Valentin G; Schmitter, Sebastian; Vu, An T; Uğurbil, Kâmil; Formisano, Elia; Yacoub, Essa

2018-01-01

Following rapid technological advances, ultra-high field functional MRI (fMRI) enables exploring correlates of neuronal population activity at an increasing spatial resolution. However, as the fMRI blood-oxygenation-level-dependent (BOLD) contrast is a vascular signal, the spatial specificity of fMRI data is ultimately determined by the characteristics of the underlying vasculature. At 7T, fMRI measurement parameters determine the relative contribution of the macro- and microvasculature to the acquired signal. Here we investigate how these parameters affect relevant high-end fMRI analyses such as encoding, decoding, and submillimeter mapping of voxel preferences in the human auditory cortex. Specifically, we compare a T 2 * weighted fMRI dataset, obtained with 2D gradient echo (GE) EPI, to a predominantly T 2 weighted dataset obtained with 3D GRASE. We first investigated the decoding accuracy based on two encoding models that represented different hypotheses about auditory cortical processing. This encoding/decoding analysis profited from the large spatial coverage and sensitivity of the T 2 * weighted acquisitions, as evidenced by a significantly higher prediction accuracy in the GE-EPI dataset compared to the 3D GRASE dataset for both encoding models. The main disadvantage of the T 2 * weighted GE-EPI dataset for encoding/decoding analyses was that the prediction accuracy exhibited cortical depth dependent vascular biases. However, we propose that the comparison of prediction accuracy across the different encoding models may be used as a post processing technique to salvage the spatial interpretability of the GE-EPI cortical depth-dependent prediction accuracy. Second, we explored the mapping of voxel preferences. Large-scale maps of frequency preference (i.e., tonotopy) were similar across datasets, yet the GE-EPI dataset was preferable due to its larger spatial coverage and sensitivity. However, submillimeter tonotopy maps revealed biases in assigned frequency preference and selectivity for the GE-EPI dataset, but not for the 3D GRASE dataset. Thus, a T 2 weighted acquisition is recommended if high specificity in tonotopic maps is required. In conclusion, different fMRI acquisitions were better suited for different analyses. It is therefore critical that any sequence parameter optimization considers the eventual intended fMRI analyses and the nature of the neuroscience questions being asked. Copyright © 2017 Elsevier Inc. All rights reserved.

Practice guideline summary: Use of fMRI in the presurgical evaluation of patients with epilepsy: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology.

PubMed

Szaflarski, Jerzy P; Gloss, David; Binder, Jeffrey R; Gaillard, William D; Golby, Alexandra J; Holland, Scott K; Ojemann, Jeffrey; Spencer, David C; Swanson, Sara J; French, Jacqueline A; Theodore, William H

2017-01-24

To assess the diagnostic accuracy and prognostic value of functional MRI (fMRI) in determining lateralization and predicting postsurgical language and memory outcomes. An 11-member panel evaluated and rated available evidence according to the 2004 American Academy of Neurology process. At least 2 panelists reviewed the full text of 172 articles and selected 37 for data extraction. Case reports, reports with <15 cases, meta-analyses, and editorials were excluded. The use of fMRI may be considered an option for lateralizing language functions in place of intracarotid amobarbital procedure (IAP) in patients with medial temporal lobe epilepsy (MTLE; Level C), temporal epilepsy in general (Level C), or extratemporal epilepsy (Level C). For patients with temporal neocortical epilepsy or temporal tumors, the evidence is insufficient (Level U). fMRI may be considered to predict postsurgical language deficits after anterior temporal lobe resection (Level C). The use of fMRI may be considered for lateralizing memory functions in place of IAP in patients with MTLE (Level C) but is of unclear utility in other epilepsy types (Level U). fMRI of verbal memory or language encoding should be considered for predicting verbal memory outcome (Level B). fMRI using nonverbal memory encoding may be considered for predicting visuospatial memory outcomes (Level C). Presurgical fMRI could be an adequate alternative to IAP memory testing for predicting verbal memory outcome (Level C). Clinicians should carefully advise patients of the risks and benefits of fMRI vs IAP during discussions concerning choice of specific modality in each case. © 2017 American Academy of Neurology.

78 FR 50087 - Notice of Intent To Prepare a Supplemental Environmental Impact Statement for the Alpine...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-16

... the majority of the infield road and pipeline route. CPAI proposes placement of fill material on 73.1..., gas, and water produced from the reservoir would be carried via pipeline to CD-1 for processing. Sales... construct, operate, and maintain a drill site, access road, pipelines, and ancillary facilities to support...

Non-biological synthetic spike-in controls and the AMPtk software pipeline improve mycobiome data

Treesearch

Jonathan M. Palmer; Michelle A. Jusino; Mark T. Banik; Daniel L. Lindner

2018-01-01

High-throughput amplicon sequencing (HTAS) of conserved DNA regions is a powerful technique to characterize microbial communities. Recently, spike-in mock communities have been used to measure accuracy of sequencing platforms and data analysis pipelines. To assess the ability of sequencing platforms and data processing pipelines using fungal internal transcribed spacer...

Re-Evaluating Dissociations between Implicit and Explicit Category Learning: An Event-Related fMRI Study

ERIC Educational Resources Information Center

Gureckis, Todd M.; James, Thomas W.; Nosofsky, Robert M.

2011-01-01

Recent fMRI studies have found that distinct neural systems may mediate perceptual category learning under implicit and explicit learning conditions. In these previous studies, however, different stimulus-encoding processes may have been associated with implicit versus explicit learning. The present design was aimed at decoupling the influence of…

Gender Differences in the Cognitive Control of Emotion: An fMRI Study

ERIC Educational Resources Information Center

Koch, Kathrin; Pauly, Katharina; Kellermann, Thilo; Seiferth, Nina Y.; Reske, Martina; Backes, Volker; Stocker, Tony; Shah, N. Jon; Amunts, Katrin; Kircher, Tilo; Schneider, Frank; Habel, Ute

2007-01-01

The interaction of emotion and cognition has become a topic of major interest. However, the influence of gender on the interplay between the two processes, along with its neural correlates have not been fully analysed so far. In this functional magnetic resonance imaging (fMRI) study we induced negative emotion using negative olfactory stimulation…

Perceiving Age and Gender in Unfamiliar Faces: An fMRI Study on Face Categorization

ERIC Educational Resources Information Center

Wiese, Holger; Kloth, Nadine; Gullmar, Daniel; Reichenbach, Jurgen R.; Schweinberger, Stefan R.

2012-01-01

Efficient processing of unfamiliar faces typically involves their categorization (e.g., into old vs. young or male vs. female). However, age and gender categorization may pose different perceptual demands. In the present study, we employed functional magnetic resonance imaging (fMRI) to compare the activity evoked during age vs. gender…

Generation of ethylene tracer by noncatalytic pyrolysis of natural gas at elevated pressure

USGS Publications Warehouse

Lu, Y.; Chen, S.; Rostam-Abadi, M.; Ruch, R.; Coleman, D.; Benson, L.J.

2005-01-01

There is a critical need within the pipeline gas industry for an inexpensive and reliable technology to generate an identification tag or tracer that can be added to pipeline gas to identify gas that may escape and improve the deliverability and management of gas in underground storage fields. Ethylene is an ideal tracer, because it does not exist naturally in the pipeline gas, and because its physical properties are similar to the pipeline gas components. A pyrolysis process, known as the Tragen process, has been developed to continuously convert the ???2%-4% ethane component present in pipeline gas into ethylene at common pipeline pressures of 800 psi. In our studies of the Tragen process, pyrolysis without steam addition achieved a maximum ethylene yield of 28%-35% at a temperature range of 700-775 ??C, corresponding to an ethylene concentration of 4600-5800 ppm in the product gas. Coke deposition was determined to occur at a significant rate in the pyrolysis reactor without steam addition. The ?? 13C isotopic analysis of gas components showed a ?? 13C value of ethylene similar to ethane in the pipeline gas, indicating that most of the ethylene was generated from decomposition of the ethane in the raw gas. However, ?? 13C isotopic analysis of the deposited coke showed that coke was primarily produced from methane, rather than from ethane or other heavier hydrocarbons. No coke deposition was observed with the addition of steam at concentrations of > 20% by volume. The dilution with steam also improved the ethylene yield. ?? 2005 American Chemical Society.

An FMRI-compatible Symbol Search task.

PubMed

Liebel, Spencer W; Clark, Uraina S; Xu, Xiaomeng; Riskin-Jones, Hannah H; Hawkshead, Brittany E; Schwarz, Nicolette F; Labbe, Donald; Jerskey, Beth A; Sweet, Lawrence H

2015-03-01

Our objective was to determine whether a Symbol Search paradigm developed for functional magnetic resonance imaging (FMRI) is a reliable and valid measure of cognitive processing speed (CPS) in healthy older adults. As all older adults are expected to experience cognitive declines due to aging, and CPS is one of the domains most affected by age, establishing a reliable and valid measure of CPS that can be administered inside an MR scanner may prove invaluable in future clinical and research settings. We evaluated the reliability and construct validity of a newly developed FMRI Symbol Search task by comparing participants' performance in and outside of the scanner and to the widely used and standardized Symbol Search subtest of the Wechsler Adult Intelligence Scale (WAIS). A brief battery of neuropsychological measures was also administered to assess the convergent and discriminant validity of the FMRI Symbol Search task. The FMRI Symbol Search task demonstrated high test-retest reliability when compared to performance on the same task administered out of the scanner (r=.791; p<.001). The criterion validity of the new task was supported, as it exhibited a strong positive correlation with the WAIS Symbol Search (r=.717; p<.001). Predicted convergent and discriminant validity patterns of the FMRI Symbol Search task were also observed. The FMRI Symbol Search task is a reliable and valid measure of CPS in healthy older adults and exhibits expected sensitivity to the effects of age on CPS performance.

Prospects of functional magnetic resonance imaging as lie detector.

PubMed

Rusconi, Elena; Mitchener-Nissen, Timothy

2013-09-24

Following the demise of the polygraph, supporters of assisted scientific lie detection tools have enthusiastically appropriated neuroimaging technologies "as the savior of scientifically verifiable lie detection in the courtroom" (Gerard, 2008: 5). These proponents believe the future impact of neuroscience "will be inevitable, dramatic, and will fundamentally alter the way the law does business" (Erickson, 2010: 29); however, such enthusiasm may prove premature. For in nearly every article published by independent researchers in peer reviewed journals, the respective authors acknowledge that fMRI research, processes, and technology are insufficiently developed and understood for gatekeepers to even consider introducing these neuroimaging measures into criminal courts as they stand today for the purpose of determining the veracity of statements made. Regardless of how favorable their analyses of fMRI or its future potential, they all acknowledge the presence of issues yet to be resolved. Even assuming a future where these issues are resolved and an appropriate fMRI lie-detection process is developed, its integration into criminal trials is not assured for the very success of such a future system may necessitate its exclusion from courtrooms on the basis of existing legal and ethical prohibitions. In this piece, aimed for a multidisciplinary readership, we seek to highlight and bring together the multitude of hurdles which would need to be successfully overcome before fMRI can (if ever) be a viable applied lie detection system. We argue that the current status of fMRI studies on lie detection meets neither basic legal nor scientific standards. We identify four general classes of hurdles (scientific, legal and ethical, operational, and social) and provide an overview on the stages and operations involved in fMRI studies, as well as the difficulties of translating these laboratory protocols into a practical criminal justice environment. It is our overall conclusion that fMRI is unlikely to constitute a viable lie detector for criminal courts.

Prospects of functional magnetic resonance imaging as lie detector

PubMed Central

Rusconi, Elena; Mitchener-Nissen, Timothy

2013-01-01

Following the demise of the polygraph, supporters of assisted scientific lie detection tools have enthusiastically appropriated neuroimaging technologies “as the savior of scientifically verifiable lie detection in the courtroom” (Gerard, 2008: 5). These proponents believe the future impact of neuroscience “will be inevitable, dramatic, and will fundamentally alter the way the law does business” (Erickson, 2010: 29); however, such enthusiasm may prove premature. For in nearly every article published by independent researchers in peer reviewed journals, the respective authors acknowledge that fMRI research, processes, and technology are insufficiently developed and understood for gatekeepers to even consider introducing these neuroimaging measures into criminal courts as they stand today for the purpose of determining the veracity of statements made. Regardless of how favorable their analyses of fMRI or its future potential, they all acknowledge the presence of issues yet to be resolved. Even assuming a future where these issues are resolved and an appropriate fMRI lie-detection process is developed, its integration into criminal trials is not assured for the very success of such a future system may necessitate its exclusion from courtrooms on the basis of existing legal and ethical prohibitions. In this piece, aimed for a multidisciplinary readership, we seek to highlight and bring together the multitude of hurdles which would need to be successfully overcome before fMRI can (if ever) be a viable applied lie detection system. We argue that the current status of fMRI studies on lie detection meets neither basic legal nor scientific standards. We identify four general classes of hurdles (scientific, legal and ethical, operational, and social) and provide an overview on the stages and operations involved in fMRI studies, as well as the difficulties of translating these laboratory protocols into a practical criminal justice environment. It is our overall conclusion that fMRI is unlikely to constitute a viable lie detector for criminal courts. PMID:24065912

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reggio, R.; Haun, R.

This paper reviews the engineering and design work along with the installation procedures for a Persian Gulf natural gas pipeline. OPMI Ltd., a joint venture of Offshore Pipelines, Inc., Houston, and Maritime Industrial Services Co., Ltd., United Arab Emirates (UAE), successfully completed this 57.4 mile, 16-inch gas export pipeline for Consolidated Transmissions Inc. The pipeline begins at a platform in the Mubarek field offshore Sharjah, UAE, and runs to a beach termination at the Dugas treatment plant, Jebel Ali, Dubai. The paper describes the site preparation required for installation of the pipeline along with the specific design of the pipelinemore » itself to deal with corrosion, welding processes, condensate dropout, and temperature gradients.« less

Brain correlates of discourse processing: An fMRI investigation of irony and conventional metaphor comprehension

PubMed Central

Eviatar, Zohar; Just, Marcel Adam

2006-01-01

Higher levels of discourse processing evoke patterns of cognition and brain activation that extend beyond the literal comprehension of sentences. We used fMRI to examine brain activation patterns while 16 healthy participants read brief three-sentence stories that concluded with either a literal, metaphoric, or ironic sentence. The fMRI images acquired during the reading of the critical sentence revealed a selective response of the brain to the two types of nonliteral utterances. Metaphoric utterances resulted in significantly higher levels of activation in the left inferior frontal gyrus and in bilateral inferior temporal cortex than the literal and ironic utterances. Ironic statements resulted in significantly higher activation levels than literal statements in the right superior and middle temporal gyri, with metaphoric statements resulting in intermediate levels in these regions. The findings show differential hemispheric sensitivity to these aspects of figurative language, and are relevant to models of the functional cortical architecture of language processing in connected discourse. PMID:16806316

Ageing differentially affects neural processing of different conflict types-an fMRI study.

PubMed

Korsch, Margarethe; Frühholz, Sascha; Herrmann, Manfred

2014-01-01

Interference control and conflict resolution is affected by ageing. There is increasing evidence that ageing does not compromise interference control in general but rather shows distinctive effects on different components of interference control. Different conflict types, [e.g., stimulus-stimulus (S-S) or stimulus-response (S-R) conflicts] trigger different cognitive processes and thus activate different neural networks. In the present functional magnetic resonance imaging (fMRI) study, we used a combined Flanker and Stimulus Response Conflict (SRC) task to investigate the effect of ageing on S-S and S-R conflicts. Behavioral data analysis revealed larger SRC effects in elderly. fMRI Results show that both age groups recruited similar regions [caudate nucleus, cingulate gyrus and middle occipital gyrus (MOG)] during Flanker conflict processing. Furthermore, elderly show an additional activation pattern in parietal and frontal areas. In contrast, no common activation of both age groups was found in response to the SRC. These data suggest that ageing has distinctive effects on S-S and S-R conflicts.

Graded motor imagery and the impact on pain processing in a case of CRPS.

PubMed

Walz, Andrea D; Usichenko, Taras; Moseley, G Lorimer; Lotze, Martin

2013-03-01

Graded motor imagery (GMI) shows promising results for patients with complex regional pain syndrome (CRPS). In a case with chronic unilateral CRPS type I, we applied GMI for 6 weeks and recorded clinical parameters and cerebral activation using functional magnetic resonance imaging (fMRI; pre-GMI, after each GMI block, and after 6 mo). Changes in fMRI activity were mapped during movement execution in areas associated with pain processing. A healthy participant served as a control for habituation effects. Pain intensity decreased over the course of GMI, and relief was maintained at follow-up. fMRI during movement execution revealed marked changes in S1 and S2 (areas of discriminative pain processing), which seemed to be associated with pain reduction, but none in the anterior insula and the anterior cingulate cortex (areas of affective pain processing). After mental rotation training, the activation intensity of the posterior parietal cortex was reduced to one third. Our case report develops a design capable of differentiating cerebral changes associated with behavioral therapy of CRPS type I study.

Integrated pipeline for inferring the evolutionary history of a gene family embedded in the species tree: a case study on the STIMATE gene family.

PubMed

Song, Jia; Zheng, Sisi; Nguyen, Nhung; Wang, Youjun; Zhou, Yubin; Lin, Kui

2017-10-03

Because phylogenetic inference is an important basis for answering many evolutionary problems, a large number of algorithms have been developed. Some of these algorithms have been improved by integrating gene evolution models with the expectation of accommodating the hierarchy of evolutionary processes. To the best of our knowledge, however, there still is no single unifying model or algorithm that can take all evolutionary processes into account through a stepwise or simultaneous method. On the basis of three existing phylogenetic inference algorithms, we built an integrated pipeline for inferring the evolutionary history of a given gene family; this pipeline can model gene sequence evolution, gene duplication-loss, gene transfer and multispecies coalescent processes. As a case study, we applied this pipeline to the STIMATE (TMEM110) gene family, which has recently been reported to play an important role in store-operated Ca 2+ entry (SOCE) mediated by ORAI and STIM proteins. We inferred their phylogenetic trees in 69 sequenced chordate genomes. By integrating three tree reconstruction algorithms with diverse evolutionary models, a pipeline for inferring the evolutionary history of a gene family was developed, and its application was demonstrated.

The visual and radiological inspection of a pipeline using a teleoperated pipe crawler

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fogle, R.F.; Kuelske, K.; Kellner, R.

1995-01-01

In the 1950s, the Savannah River Site built an open, unlined retention basin to temporarily store potentially radionuclide contaminated cooling water from a chemical separations process and storm water drainage from a nearby waste management facility that stored large quantities of nuclear fission byproducts in carbon steel tanks. The retention basin was retired from service in 1972 when a new, lined basin was completed. In 1978, the old retention basin was excavated, backfilled with uncontaminated dirt, and covered with grass. At the same time, much of the underground process pipeline leading to the basin was abandoned. Since the closure ofmore » the retention basin, new environmental regulations require that the basin undergo further assessment to determine whether additional remediation is required. A visual and radiological inspection of the pipeline was necessary to aid in the remediation decision making process for the retention basin system. A teleoperated pipe crawler inspection system was developed to survey the abandoned sections of underground pipelines leading to the retired retention basin. This paper will describe the background to this project, the scope of the investigation, the equipment requirements, and the results of the pipeline inspection.« less

The inspection of a radiologically contaminated pipeline using a teleoperated pipe crawler

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fogle, R.F.; Kuelske, K.; Kellner, R.A.

1995-08-01

In the 1950s, the Savannah River Site built an open, unlined retention basin to temporarily store potentially radionuclide contaminated cooling water from a chemical separations process and storm water drainage from a nearby waste management facility that stored large quantities of nuclear fission byproducts in carbon steel tanks. The retention basin was retired from service in 1972 when a new, lined basin was completed. In 1978, the old retention basin was excavated, backfilled with uncontaminated dirt, and covered with grass. At the same time, much of the underground process pipeline leading to the basin was abandoned. Since the closure ofmore » the retention basin, new environmental regulations require that the basin undergo further assessment to determine whether additional remediation is required. A visual and radiological inspection of the pipeline was necessary to aid in the remediation decision making process for the retention basin system. A teleoperated pipe crawler inspection system was developed to survey the abandoned sections of underground pipelines leading to the retired retention basin. This paper will describe the background to this project, the scope of the investigation, the equipment requirements, and the results of the pipeline inspection.« less

Multinode reconfigurable pipeline computer

NASA Technical Reports Server (NTRS)

Nosenchuck, Daniel M. (Inventor); Littman, Michael G. (Inventor)

1989-01-01

A multinode parallel-processing computer is made up of a plurality of innerconnected, large capacity nodes each including a reconfigurable pipeline of functional units such as Integer Arithmetic Logic Processors, Floating Point Arithmetic Processors, Special Purpose Processors, etc. The reconfigurable pipeline of each node is connected to a multiplane memory by a Memory-ALU switch NETwork (MASNET). The reconfigurable pipeline includes three (3) basic substructures formed from functional units which have been found to be sufficient to perform the bulk of all calculations. The MASNET controls the flow of signals from the memory planes to the reconfigurable pipeline and vice versa. the nodes are connectable together by an internode data router (hyperspace router) so as to form a hypercube configuration. The capability of the nodes to conditionally configure the pipeline at each tick of the clock, without requiring a pipeline flush, permits many powerful algorithms to be implemented directly.

Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal.

PubMed

Wen, Haiguang; Liu, Zhongming

2016-06-01

Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels. This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed with resting-state fMRI, respectively. Copyright © 2016 the authors 0270-6474/16/366030-11$15.00/0.

Natural Language Processing Accurately Calculates Adenoma and Sessile Serrated Polyp Detection Rates.

PubMed

Nayor, Jennifer; Borges, Lawrence F; Goryachev, Sergey; Gainer, Vivian S; Saltzman, John R

2018-07-01

ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured or free text data. (1) To develop and validate an accurate automated process for calculation of adenoma detection rate (ADR) and serrated polyp detection rate (SDR) on data stored in widely used electronic health record systems, specifically Epic electronic health record system, Provation ® endoscopy reporting system, and Sunquest PowerPath pathology reporting system. Screening colonoscopies performed between June 2010 and August 2015 were identified using the Provation ® reporting tool. An NLP pipeline was developed to identify adenomas and sessile serrated polyps (SSPs) on pathology reports corresponding to these colonoscopy reports. The pipeline was validated using a manual search. Precision, recall, and effectiveness of the natural language processing pipeline were calculated. ADR and SDR were then calculated. We identified 8032 screening colonoscopies that were linked to 3821 pathology reports (47.6%). The NLP pipeline had an accuracy of 100% for adenomas and 100% for SSPs. Mean total ADR was 29.3% (range 14.7-53.3%); mean male ADR was 35.7% (range 19.7-62.9%); and mean female ADR was 24.9% (range 9.1-51.0%). Mean total SDR was 4.0% (0-9.6%). We developed and validated an NLP pipeline that accurately and automatically calculates ADRs and SDRs using data stored in Epic, Provation ® and Sunquest PowerPath. This NLP pipeline can be used to evaluate colonoscopy quality parameters at both individual and practice levels.

Fast parallel algorithm for slicing STL based on pipeline

NASA Astrophysics Data System (ADS)

Ma, Xulong; Lin, Feng; Yao, Bo

2016-05-01

In Additive Manufacturing field, the current researches of data processing mainly focus on a slicing process of large STL files or complicated CAD models. To improve the efficiency and reduce the slicing time, a parallel algorithm has great advantages. However, traditional algorithms can't make full use of multi-core CPU hardware resources. In the paper, a fast parallel algorithm is presented to speed up data processing. A pipeline mode is adopted to design the parallel algorithm. And the complexity of the pipeline algorithm is analyzed theoretically. To evaluate the performance of the new algorithm, effects of threads number and layers number are investigated by a serial of experiments. The experimental results show that the threads number and layers number are two remarkable factors to the speedup ratio. The tendency of speedup versus threads number reveals a positive relationship which greatly agrees with the Amdahl's law, and the tendency of speedup versus layers number also keeps a positive relationship agreeing with Gustafson's law. The new algorithm uses topological information to compute contours with a parallel method of speedup. Another parallel algorithm based on data parallel is used in experiments to show that pipeline parallel mode is more efficient. A case study at last shows a suspending performance of the new parallel algorithm. Compared with the serial slicing algorithm, the new pipeline parallel algorithm can make full use of the multi-core CPU hardware, accelerate the slicing process, and compared with the data parallel slicing algorithm, the new slicing algorithm in this paper adopts a pipeline parallel model, and a much higher speedup ratio and efficiency is achieved.

Resting-state functional magnetic resonance imaging in hepatic encephalopathy: current status and perspectives.

PubMed

Zhang, Long Jiang; Wu, Shengyong; Ren, Jiaqian; Lu, Guang Ming

2014-09-01

Hepatic encephalopathy (HE) is a neuropsychiatric syndrome which develops in patients with severe liver diseases and/or portal-systemic shunting. Minimal HE, the earliest manifestation of HE, has drawn increasing attention in the last decade. Minimal HE is associated with a series of brain functional changes, such as attention, working memory, and so on. Blood oxygen level dependent (BOLD) functional MRI (fMRI), especially resting-state fMRI has been used to explore the brain functional changes of HE, yielding important insights for understanding pathophysiological mechanisms and functional reorganization of HE. This paper briefly reviews the principles of BOLD fMRI, potential applications of resting-state fMRI with advanced post-processing algorithms such as regional homogeneity, amplitude of low frequency fluctuation, functional connectivity and future research perspective in this field.

Planck 2015 results. II. Low Frequency Instrument data processings

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Ballardini, M.; Banday, A. J.; Barreiro, R. B.; Bartolo, N.; Basak, S.; Battaglia, P.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Castex, G.; Catalano, A.; Chamballu, A.; Christensen, P. R.; Colombi, S.; Colombo, L. P. L.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Franceschet, C.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kiiveri, K.; Kisner, T. S.; Knoche, J.; Krachmalnicoff, N.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leahy, J. P.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; Lindholm, V.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; Mazzotta, P.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Montier, L.; Morgante, G.; Morisset, N.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Novikov, D.; Novikov, I.; Oppermann, N.; Paci, F.; Pagano, L.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Peel, M.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Pierpaoli, E.; Pietrobon, D.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renzi, A.; Rocha, G.; Romelli, E.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Tavagnacco, D.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Türler, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vassallo, T.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Watson, R.; Wehus, I. K.; Wilkinson, A.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present an updated description of the Planck Low Frequency Instrument (LFI) data processing pipeline, associated with the 2015 data release. We point out the places where our results and methods have remained unchanged since the 2013 paper and we highlight the changes made for the 2015 release, describing the products (especially timelines) and the ways in which they were obtained. We demonstrate that the pipeline is self-consistent (principally based on simulations) and report all null tests. For the first time, we present LFI maps in Stokes Q and U polarization. We refer to other related papers where more detailed descriptions of the LFI data processing pipeline may be found if needed.

Functional magnetic resonance imaging (FMRI) with auditory stimulation in songbirds.

PubMed

Van Ruijssevelt, Lisbeth; De Groof, Geert; Van der Kant, Anne; Poirier, Colline; Van Audekerke, Johan; Verhoye, Marleen; Van der Linden, Annemie

2013-06-03

The neurobiology of birdsong, as a model for human speech, is a pronounced area of research in behavioral neuroscience. Whereas electrophysiology and molecular approaches allow the investigation of either different stimuli on few neurons, or one stimulus in large parts of the brain, blood oxygenation level dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) allows combining both advantages, i.e. compare the neural activation induced by different stimuli in the entire brain at once. fMRI in songbirds is challenging because of the small size of their brains and because their bones and especially their skull comprise numerous air cavities, inducing important susceptibility artifacts. Gradient-echo (GE) BOLD fMRI has been successfully applied to songbirds (1-5) (for a review, see (6)). These studies focused on the primary and secondary auditory brain areas, which are regions free of susceptibility artifacts. However, because processes of interest may occur beyond these regions, whole brain BOLD fMRI is required using an MRI sequence less susceptible to these artifacts. This can be achieved by using spin-echo (SE) BOLD fMRI (7,8) . In this article, we describe how to use this technique in zebra finches (Taeniopygia guttata), which are small songbirds with a bodyweight of 15-25 g extensively studied in behavioral neurosciences of birdsong. The main topic of fMRI studies on songbirds is song perception and song learning. The auditory nature of the stimuli combined with the weak BOLD sensitivity of SE (compared to GE) based fMRI sequences makes the implementation of this technique very challenging.

Single-trial EEG-informed fMRI analysis of emotional decision problems in hot executive function.

PubMed

Guo, Qian; Zhou, Tiantong; Li, Wenjie; Dong, Li; Wang, Suhong; Zou, Ling

2017-07-01

Executive function refers to conscious control in psychological process which relates to thinking and action. Emotional decision is a part of hot executive function and contains emotion and logic elements. As a kind of important social adaptation ability, more and more attention has been paid in recent years. Gambling task can be well performed in the study of emotional decision. As fMRI researches focused on gambling task show not completely consistent brain activation regions, this study adopted EEG-fMRI fusion technology to reveal brain neural activity related with feedback stimuli. In this study, an EEG-informed fMRI analysis was applied to process simultaneous EEG-fMRI data. First, relative power-spectrum analysis and K-means clustering method were performed separately to extract EEG-fMRI features. Then, Generalized linear models were structured using fMRI data and using different EEG features as regressors. The results showed that in the win versus loss stimuli, the activated regions almost covered the caudate, the ventral striatum (VS), the orbital frontal cortex (OFC), and the cingulate. Wide activation areas associated with reward and punishment were revealed by the EEG-fMRI integration analysis than the conventional fMRI results, such as the posterior cingulate and the OFC. The VS and the medial prefrontal cortex (mPFC) were found when EEG power features were performed as regressors of GLM compared with results entering the amplitudes of feedback-related negativity (FRN) as regressors. Furthermore, the brain region activation intensity was the strongest when theta-band power was used as a regressor compared with the other two fusion results. The EEG-based fMRI analysis can more accurately depict the whole-brain activation map and analyze emotional decision problems.

Parametric design and correlational analyses help integrating fMRI and electrophysiological data during face processing.

PubMed

Horovitz, Silvina G; Rossion, Bruno; Skudlarski, Pawel; Gore, John C

2004-08-01

Face perception is typically associated with activation in the inferior occipital, superior temporal (STG), and fusiform gyri (FG) and with an occipitotemporal electrophysiological component peaking around 170 ms on the scalp, the N170. However, the relationship between the N170 and the multiple face-sensitive activations observed in neuroimaging is unclear. It has been recently shown that the amplitude of the N170 component monotonically decreases as gaussian noise is added to a picture of a face [Jemel et al., 2003]. To help clarify the sources of the N170 without a priori assumptions regarding their number and locations, ERPs and fMRI were recorded in five subjects in the same experiment, in separate sessions. We used a parametric paradigm in which the amplitude of the N170 was modulated by varying the level of noise in a picture, and identified regions where the percent signal change in fMRI correlated with the ERP data. N170 signals were observed for pictures of both cars and faces but were stronger for faces. A monotonic decrease with added noise was observed for the N170 at right hemisphere sites but was less clear on the left and occipital central sites. Correlations between fMRI signal and N170 amplitudes for faces were highly significant (P < 0.001) in bilateral fusiform gyrus and superior temporal gyrus. For cars, the strongest correlations were observed in the parahippocampal region and in the STG (P < 0.005). Besides contributing to clarify the spatiotemporal course of face processing, this study illustrates how ERP information may be used synergistically in fMRI analyses. Parametric designs may be developed further to provide some timing information on fMRI activity and help identify the generators of ERP signals.

Brain correlates of autonomic modulation: combining heart rate variability with fMRI.

PubMed

Napadow, Vitaly; Dhond, Rupali; Conti, Giulia; Makris, Nikos; Brown, Emery N; Barbieri, Riccardo

2008-08-01

The central autonomic network (CAN) has been described in animal models but has been difficult to elucidate in humans. Potential confounds include physiological noise artifacts affecting brainstem neuroimaging data, and difficulty in deriving non-invasive continuous assessments of autonomic modulation. We have developed and implemented a new method which relates cardiac-gated fMRI timeseries with continuous-time heart rate variability (HRV) to estimate central autonomic processing. As many autonomic structures of interest are in brain regions strongly affected by cardiogenic pulsatility, we chose to cardiac-gate our fMRI acquisition to increase sensitivity. Cardiac-gating introduces T1-variability, which was corrected by transforming fMRI data to a fixed TR using a previously published method [Guimaraes, A.R., Melcher, J.R., et al., 1998. Imaging subcortical auditory activity in humans. Hum. Brain Mapp. 6(1), 33-41]. The electrocardiogram was analyzed with a novel point process adaptive-filter algorithm for computation of the high-frequency (HF) index, reflecting the time-varying dynamics of efferent cardiovagal modulation. Central command of cardiovagal outflow was inferred by using the resample HF timeseries as a regressor to the fMRI data. A grip task was used to perturb the autonomic nervous system. Our combined HRV-fMRI approach demonstrated HF correlation with fMRI activity in the hypothalamus, cerebellum, parabrachial nucleus/locus ceruleus, periaqueductal gray, amygdala, hippocampus, thalamus, and dorsomedial/dorsolateral prefrontal, posterior insular, and middle temporal cortices. While some regions consistent with central cardiovagal control in animal models gave corroborative evidence for our methodology, other mostly higher cortical or limbic-related brain regions may be unique to humans. Our approach should be optimized and applied to study the human brain correlates of autonomic modulation for various stimuli in both physiological and pathological states.

Comparison of glomerular activity patterns by fMRI and wide-field calcium imaging: implications for principles underlying odor mapping

PubMed Central

Sanganahalli, Basavaraju G.; Rebello, Michelle R.; Herman, Peter; Papademetris, Xenophon; Shepherd, Gordon M.; Verhagen, Justus V.; Hyder, Fahmeed

2015-01-01

Functional imaging signals arise from distinct metabolic and hemodynamic events at the neuropil, but how these processes are influenced by pre- and post-synaptic activities need to be understood for quantitative interpretation of stimulus-evoked mapping data. The olfactory bulb (OB) glomeruli, spherical neuropil regions with well-defined neuronal circuitry, can provide insights into this issue. Optical calcium-sensitive fluorescent dye imaging (OICa2+) reflects dynamics of pre-synaptic input to glomeruli, whereas high-resolution functional magnetic resonance imaging (fMRI) using deoxyhemoglobin contrast reveals neuropil function within the glomerular layer where both pre- and post-synaptic activities contribute. We imaged odor-specific activity patterns of the dorsal OB in the same anesthetized rats with fMRI and OICa2+ and then co-registered the respective maps to compare patterns in the same space. Maps by each modality were very reproducible as trial-to-trial patterns for a given odor, overlapping by ~80%. Maps evoked by ethyl butyrate and methyl valerate for a given modality overlapped by ~80%, suggesting activation of similar dorsal glomerular networks by these odors. Comparison of maps generated by both methods for a given odor showed ~70% overlap, indicating similar odor-specific maps by each method. These results suggest that odor-specific glomerular patterns by high-resolution fMRI primarily tracks pre-synaptic input to the OB. Thus combining OICa2+ and fMRI lays the framework for studies of OB processing over a range of spatiotemporal scales, where OICa2+ can feature the fast dynamics of dorsal glomerular clusters and fMRI can map the entire glomerular sheet in the OB. PMID:26631819

A unified framework for group independent component analysis for multi-subject fMRI data

PubMed Central

Guo, Ying; Pagnoni, Giuseppe

2008-01-01

Independent component analysis (ICA) is becoming increasingly popular for analyzing functional magnetic resonance imaging (fMRI) data. While ICA has been successfully applied to single-subject analysis, the extension of ICA to group inferences is not straightforward and remains an active topic of research. Current group ICA models, such as the GIFT (Calhoun et al., 2001) and tensor PICA (Beckmann and Smith, 2005), make different assumptions about the underlying structure of the group spatio-temporal processes and are thus estimated using algorithms tailored for the assumed structure, potentially leading to diverging results. To our knowledge, there are currently no methods for assessing the validity of different model structures in real fMRI data and selecting the most appropriate one among various choices. In this paper, we propose a unified framework for estimating and comparing group ICA models with varying spatio-temporal structures. We consider a class of group ICA models that can accommodate different group structures and include existing models, such as the GIFT and tensor PICA, as special cases. We propose a maximum likelihood (ML) approach with a modified Expectation-Maximization (EM) algorithm for the estimation of the proposed class of models. Likelihood ratio tests (LRT) are presented to compare between different group ICA models. The LRT can be used to perform model comparison and selection, to assess the goodness-of-fit of a model in a particular data set, and to test group differences in the fMRI signal time courses between subject subgroups. Simulation studies are conducted to evaluate the performance of the proposed method under varying structures of group spatio-temporal processes. We illustrate our group ICA method using data from an fMRI study that investigates changes in neural processing associated with the regular practice of Zen meditation. PMID:18650105

Distinct iEEG activity patterns in temporal-limbic and prefrontal sites induced by emotional intentionality

PubMed Central

Singer, Neomi; Podlipsky, Ilana; Esposito, Fabrizio; Okon-Singer, Hadas; Andelman, Fani; Kipervasser, Svetlana; Neufeld, Miri Y.; Goebel, Rainer; Fried, Itzhak; Hendler, Talma

2015-01-01

Our emotions tend to be directed towards someone or something. Such emotional intentionality calls for the integration between two streams of information; abstract hedonic value and its associated concrete content. In a previous functional magnetic resonance imaging (fMRI) study we found that the combination of these two streams, as modeled by short emotional music excerpts and neutral film clips, was associated with synergistic activation in both temporal-limbic (TL) and ventral-lateral PFC (vLPFC) regions. This additive effect implies the integration of domain-specific ‘affective’ and ‘cognitive’ processes. Yet, the low temporal resolution of the fMRI limits the characterization of such cross-domain integration. To this end, we complemented the fMRI data with intracranial electroencephalogram (iEEG) recordings from twelve patients with intractable epilepsy. As expected, the additive fMRI activation in the amygdala and vLPFC was associated with distinct spatio-temporal iEEG patterns among electrodes situated within the vicinity of the fMRI activation foci. On the one hand, TL channels exhibited a transient (0–500 msec) increase in gamma power (61–69 Hz), possibly reflecting initial relevance detection or hedonic value tagging. On the other hand, vLPFC channels showed sustained (1–12 sec) suppression of low frequency power (2.3–24 Hz), possibly mediating changes in gating, enabling an on-going readiness for content-based processing of emotionally tagged signals. Moreover, an additive effect in delta-gamma phase-amplitude coupling (PAC) was found among the TL channels, possibly reflecting the integration between distinct domain specific processes. Together, this study provides a multi-faceted neurophysiological signature for computations that possibly underlie emotional intentionality in humans. PMID:25288171

Distinct iEEG activity patterns in temporal-limbic and prefrontal sites induced by emotional intentionality.

PubMed

Singer, Neomi; Podlipsky, Ilana; Esposito, Fabrizio; Okon-Singer, Hadas; Andelman, Fani; Kipervasser, Svetlana; Neufeld, Miri Y; Goebel, Rainer; Fried, Itzhak; Hendler, Talma

2014-11-01

Our emotions tend to be directed towards someone or something. Such emotional intentionality calls for the integration between two streams of information; abstract hedonic value and its associated concrete content. In a previous functional magnetic resonance imaging (fMRI) study we found that the combination of these two streams, as modeled by short emotional music excerpts and neutral film clips, was associated with synergistic activation in both temporal-limbic (TL) and ventral-lateral PFC (vLPFC) regions. This additive effect implies the integration of domain-specific 'affective' and 'cognitive' processes. Yet, the low temporal resolution of the fMRI limits the characterization of such cross-domain integration. To this end, we complemented the fMRI data with intracranial electroencephalogram (iEEG) recordings from twelve patients with intractable epilepsy. As expected, the additive fMRI activation in the amygdala and vLPFC was associated with distinct spatio-temporal iEEG patterns among electrodes situated within the vicinity of the fMRI activation foci. On the one hand, TL channels exhibited a transient (0-500 msec) increase in gamma power (61-69 Hz), possibly reflecting initial relevance detection or hedonic value tagging. On the other hand, vLPFC channels showed sustained (1-12 sec) suppression of low frequency power (2.3-24 Hz), possibly mediating changes in gating, enabling an on-going readiness for content-based processing of emotionally tagged signals. Moreover, an additive effect in delta-gamma phase-amplitude coupling (PAC) was found among the TL channels, possibly reflecting the integration between distinct domain specific processes. Together, this study provides a multi-faceted neurophysiological signature for computations that possibly underlie emotional intentionality in humans. Copyright © 2014 Elsevier Ltd. All rights reserved.

30 CFR 250.1003 - Installation, testing, and repair requirements for DOI pipelines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... installed in water depths of less than 200 feet shall be buried to a depth of at least 3 feet unless they... damage potential exists. (b)(1) Pipelines shall be pressure tested with water at a stabilized pressure of... repair, the pipeline shall be pressure tested with water or processed natural gas at a minimum stabilized...

A Mitigation Process for Impacts of the All American Pipeline on Oak Woodlands in Santa Barbara County

Treesearch

Germaine Reyes-French; Timothy J. Cohen

1991-01-01

This paper outlines a mitigation program for pipeline construction impacts to oak tree habitat by describing the requirements for the Offsite Oak Mitigation Program for the All American Pipeline (AAPL) in Santa Barbara County, California. After describing the initial environmental analysis, the County regulatory structure is described under which the plan was required...

ORAC-DR: Astronomy data reduction pipeline

NASA Astrophysics Data System (ADS)

Jenness, Tim; Economou, Frossie; Cavanagh, Brad; Currie, Malcolm J.; Gibb, Andy

2013-10-01

ORAC-DR is a generic data reduction pipeline infrastructure; it includes specific data processing recipes for a number of instruments. It is used at the James Clerk Maxwell Telescope, United Kingdom Infrared Telescope, AAT, and LCOGT. This pipeline runs at the JCMT Science Archive hosted by CADC to generate near-publication quality data products; the code has been in use since 1998.

Open source pipeline for ESPaDOnS reduction and analysis

NASA Astrophysics Data System (ADS)

Martioli, Eder; Teeple, Doug; Manset, Nadine; Devost, Daniel; Withington, Kanoa; Venne, Andre; Tannock, Megan

2012-09-01

OPERA is a Canada-France-Hawaii Telescope (CFHT) open source collaborative software project currently under development for an ESPaDOnS echelle spectro-polarimetric image reduction pipeline. OPERA is designed to be fully automated, performing calibrations and reduction, producing one-dimensional intensity and polarimetric spectra. The calibrations are performed on two-dimensional images. Spectra are extracted using an optimal extraction algorithm. While primarily designed for CFHT ESPaDOnS data, the pipeline is being written to be extensible to other echelle spectrographs. A primary design goal is to make use of fast, modern object-oriented technologies. Processing is controlled by a harness, which manages a set of processing modules, that make use of a collection of native OPERA software libraries and standard external software libraries. The harness and modules are completely parametrized by site configuration and instrument parameters. The software is open- ended, permitting users of OPERA to extend the pipeline capabilities. All these features have been designed to provide a portable infrastructure that facilitates collaborative development, code re-usability and extensibility. OPERA is free software with support for both GNU/Linux and MacOSX platforms. The pipeline is hosted on SourceForge under the name "opera-pipeline".

Intrusive Memories of Distressing Information: An fMRI Study

PubMed Central

Battaglini, Eva; Liddell, Belinda; Das, Pritha; Malhi, Gin; Felmingham, Kim

2016-01-01

Although intrusive memories are characteristic of many psychological disorders, the neurobiological underpinning of these involuntary recollections are largely unknown. In this study we used functional magentic resonance imaging (fMRI) to identify the neural networks associated with encoding of negative stimuli that are subsequently experienced as intrusive memories. Healthy partipants (N = 42) viewed negative and neutral images during a visual/verbal processing task in an fMRI context. Two days later they were assessed on the Impact of Event Scale for occurrence of intrusive memories of the encoded images. A sub-group of participants who reported significant intrusions (n = 13) demonstrated stronger activation in the amygdala, bilateral ACC and parahippocampal gyrus during verbal encoding relative to a group who reported no intrusions (n = 13). Within-group analyses also revealed that the high intrusion group showed greater activity in the dorsomedial (dmPFC) and dorsolateral prefrontal cortex (dlPFC), inferior frontal gyrus and occipital regions during negative verbal processing compared to neutral verbal processing. These results do not accord with models of intrusions that emphasise visual processing of information at encoding but are consistent with models that highlight the role of inhibitory and suppression processes in the formation of subsequent intrusive memories. PMID:27685784

Valence Scaling of Dynamic Facial Expressions Is Altered in High-Functioning Subjects with Autism Spectrum Disorders: An FMRI Study

ERIC Educational Resources Information Center

Rahko, Jukka S.; Paakki, Jyri-Johan; Starck, Tuomo H.; Nikkinen, Juha; Pauls, David L.; Katsyri, Jari V.; Jansson-Verkasalo, Eira M.; Carter, Alice S.; Hurtig, Tuula M.; Mattila, Marja-Leena; Jussila, Katja K.; Remes, Jukka J.; Kuusikko-Gauffin, Sanna A.; Sams, Mikko E.; Bolte, Sven; Ebeling, Hanna E.; Moilanen, Irma K.; Tervonen, Osmo; Kiviniemi, Vesa

2012-01-01

FMRI was performed with the dynamic facial expressions fear and happiness. This was done to detect differences in valence processing between 25 subjects with autism spectrum disorders (ASDs) and 27 typically developing controls. Valence scaling was abnormal in ASDs. Positive valence induces lower deactivation and abnormally strong activity in ASD…

Sentence Syntax and Content in the Human Temporal Lobe: An fMRI Adaptation Study in Auditory and Visual Modalities

ERIC Educational Resources Information Center

Devauchelle, Anne-Dominique; Oppenheim, Catherine; Rizzi, Luigi; Dehaene, Stanislas; Pallier, Christophe

2009-01-01

Priming effects have been well documented in behavioral psycholinguistics experiments: The processing of a word or a sentence is typically facilitated when it shares lexico-semantic or syntactic features with a previously encountered stimulus. Here, we used fMRI priming to investigate which brain areas show adaptation to the repetition of a…

Event-Related fMRI Studies of Episodic Encoding and Retrieval: Meta-Analyses Using Activation Likelihood Estimation

ERIC Educational Resources Information Center

Spaniol, Julia; Davidson, Patrick S. R.; Kim, Alice S. N.; Han, Hua; Moscovitch, Morris; Grady, Cheryl L.

2009-01-01

The recent surge in event-related fMRI studies of episodic memory has generated a wealth of information about the neural correlates of encoding and retrieval processes. However, interpretation of individual studies is hampered by methodological differences, and by the fact that sample sizes are typically small. We submitted results from studies of…

VizieR Online Data Catalog: New Kepler planetary candidates (Ofir+, 2013)

NASA Astrophysics Data System (ADS)

Ofir, A.; Dreizler, S.

2013-10-01

We present first results of our efforts to re-analyze the Kepler photometric dataset, searching for planetary transits using an alternative processing pipeline to the one used by the Kepler mission The SARS pipeline was tried and tested extensively by processing all available CoRoT mission data. For this first paper of the series we used this pipeline to search for (additional) planetary transits only in a small subset of stars - the Kepler objects of interest (KOIs), which are already known to include at least one promising planet candidate. (2 data files).

Nine Years of XMM-Newton Pipeline: Experience and Feedback

NASA Astrophysics Data System (ADS)

Michel, Laurent; Motch, Christian

2009-05-01

The Strasbourg Astronomical Observatory is member of the Survey Science Centre (SSC) of the XMM-Newton satellite. Among other responsibilities, we provide a database access to the 2XMMi catalogue and run the part of the data processing pipeline performing the cross-correlation of EPIC sources with archival catalogs. These tasks were all developed in Strasbourg. Pipeline processing is flawlessly in operation since 1999. We describe here the work load and infrastructure setup in Strasbourg to support SSC activities. Our nine year long SSC experience could be used in the framework of the Simbol-X ground segment.

Role of fMRI in the decision-making process: epilepsy surgery for children.

PubMed

Liégeois, Frédérique; Cross, J Helen; Gadian, David G; Connelly, Alan

2006-06-01

Functional MRI (fMRI) is increasingly being used to evaluate children and adolescents who are candidates for surgical treatment of intractable epilepsy. It has the advantage of being noninvasive and well tolerated by young people. By identifying important functional regions within the brain, including unpredictable patterns of functional reorganization, it can aid in surgical decision-making. Here we illustrate this using a number of case studies from the pediatric epilepsy surgery program at our institution. We describe how fMRI, used in conjunction with conventional investigative methods such as neuropsychological assessment, MRI, and electrophysiology, can 1) help to improve functional outcome by enabling resective surgery that spares functional cortex, 2) guide surgical intervention by revealing when reorganization of function has occurred, and 3) show when abnormal cortex is also functionally active, and hence that surgery may not be the best option. Altogether, these roles have reduced the need for invasive procedures that can be both risky and distressing for young people with epilepsy. In our experience, fMRI has significantly contributed to the decision-making process, and improved the counseling and management of young people with intractable epilepsy. Copyright 2006 Wiley-Liss, Inc.

Processing of Intentional and Automatic Number Magnitudes in Children Born Prematurely: Evidence From fMRI

PubMed Central

Klein, Elise; Moeller, Korbinian; Kiechl-Kohlendorfer, Ursula; Kremser, Christian; Starke, Marc; Cohen Kadosh, Roi; Pupp-Peglow, Ulrike; Schocke, Michael; Kaufmann, Liane

2014-01-01

This study examined the neural correlates of intentional and automatic number processing (indexed by number comparison and physical Stroop task, respectively) in 6- and 7-year-old children born prematurely. Behavioral results revealed significant numerical distance and size congruity effects. Imaging results disclosed (1) largely overlapping fronto-parietal activation for intentional and automatic number processing, (2) a frontal to parietal shift of activation upon considering the risk factors gestational age and birth weight, and (3) a task-specific link between math proficiency and functional magnetic resonance imaging (fMRI) signal within distinct regions of the parietal lobes—indicating commonalities but also specificities of intentional and automatic number processing. PMID:25090014

The Dark Energy Survey Image Processing Pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morganson, E.; et al.

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a 5000 square degree survey of the southern sky in five optical bands (g,r,i,z,Y) to a depth of ~24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g,r,i,z) over 27 square degrees. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On amore » bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.« less

Quantification technology study on flaws in steam-filled pipelines based on image processing

NASA Astrophysics Data System (ADS)

Sun, Lina; Yuan, Peixin

2009-07-01

Starting from exploiting the applied detection system of gas transmission pipeline, a set of X-ray image processing methods and pipeline flaw quantificational evaluation methods are proposed. Defective and non-defective strings and rows in gray image were extracted and oscillogram was obtained. We can distinguish defects in contrast with two gray images division. According to the gray value of defects with different thicknesses, the gray level depth curve is founded. Through exponential and polynomial fitting way to obtain the attenuation mathematical model which the beam penetrates pipeline, thus attain flaw deep dimension. This paper tests on the PPR pipe in the production of simulated holes flaw and cracks flaw, 135KV used the X-ray source on the testing. Test results show that X-ray image processing method, which meet the needs of high efficient flaw detection and provide quality safeguard for thick oil recovery, can be used successfully in detecting corrosion of insulated pipe.

Quantification technology study on flaws in steam-filled pipelines based on image processing

NASA Astrophysics Data System (ADS)

Yuan, Pei-xin; Cong, Jia-hui; Chen, Bo

2008-03-01

Starting from exploiting the applied detection system of gas transmission pipeline, a set of X-ray image processing methods and pipeline flaw quantificational evaluation methods are proposed. Defective and non-defective strings and rows in gray image were extracted and oscillogram was obtained. We can distinguish defects in contrast with two gray images division. According to the gray value of defects with different thicknesses, the gray level depth curve is founded. Through exponential and polynomial fitting way to obtain the attenuation mathematical model which the beam penetrates pipeline, thus attain flaw deep dimension. This paper tests on the PPR pipe in the production of simulated holes flaw and cracks flaw. The X-ray source tube voltage was selected as 130kv and valve current was 1.5mA.Test results show that X-ray image processing methods, which meet the needs of high efficient flaw detection and provide quality safeguard for thick oil recovery, can be used successfully in detecting corrosion of insulated pipe.

sTools - a data reduction pipeline for the GREGOR Fabry-Pérot Interferometer and the High-resolution Fast Imager at the GREGOR solar telescope

NASA Astrophysics Data System (ADS)

Kuckein, C.; Denker, C.; Verma, M.; Balthasar, H.; González Manrique, S. J.; Louis, R. E.; Diercke, A.

2017-10-01

A huge amount of data has been acquired with the GREGOR Fabry-Pérot Interferometer (GFPI), large-format facility cameras, and since 2016 with the High-resolution Fast Imager (HiFI). These data are processed in standardized procedures with the aim of providing science-ready data for the solar physics community. For this purpose, we have developed a user-friendly data reduction pipeline called ``sTools'' based on the Interactive Data Language (IDL) and licensed under creative commons license. The pipeline delivers reduced and image-reconstructed data with a minimum of user interaction. Furthermore, quick-look data are generated as well as a webpage with an overview of the observations and their statistics. All the processed data are stored online at the GREGOR GFPI and HiFI data archive of the Leibniz Institute for Astrophysics Potsdam (AIP). The principles of the pipeline are presented together with selected high-resolution spectral scans and images processed with sTools.

Seqping: gene prediction pipeline for plant genomes using self-training gene models and transcriptomic data.

PubMed

Chan, Kuang-Lim; Rosli, Rozana; Tatarinova, Tatiana V; Hogan, Michael; Firdaus-Raih, Mohd; Low, Eng-Ti Leslie

2017-01-27

Gene prediction is one of the most important steps in the genome annotation process. A large number of software tools and pipelines developed by various computing techniques are available for gene prediction. However, these systems have yet to accurately predict all or even most of the protein-coding regions. Furthermore, none of the currently available gene-finders has a universal Hidden Markov Model (HMM) that can perform gene prediction for all organisms equally well in an automatic fashion. We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure). Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.

Historical analysis of US pipeline accidents triggered by natural hazards

NASA Astrophysics Data System (ADS)

Girgin, Serkan; Krausmann, Elisabeth

2015-04-01

Natural hazards, such as earthquakes, floods, landslides, or lightning, can initiate accidents in oil and gas pipelines with potentially major consequences on the population or the environment due to toxic releases, fires and explosions. Accidents of this type are also referred to as Natech events. Many major accidents highlight the risk associated with natural-hazard impact on pipelines transporting dangerous substances. For instance, in the USA in 1994, flooding of the San Jacinto River caused the rupture of 8 and the undermining of 29 pipelines by the floodwaters. About 5.5 million litres of petroleum and related products were spilled into the river and ignited. As a results, 547 people were injured and significant environmental damage occurred. Post-incident analysis is a valuable tool for better understanding the causes, dynamics and impacts of pipeline Natech accidents in support of future accident prevention and mitigation. Therefore, data on onshore hazardous-liquid pipeline accidents collected by the US Pipeline and Hazardous Materials Safety Administration (PHMSA) was analysed. For this purpose, a database-driven incident data analysis system was developed to aid the rapid review and categorization of PHMSA incident reports. Using an automated data-mining process followed by a peer review of the incident records and supported by natural hazard databases and external information sources, the pipeline Natechs were identified. As a by-product of the data-collection process, the database now includes over 800,000 incidents from all causes in industrial and transportation activities, which are automatically classified in the same way as the PHMSA record. This presentation describes the data collection and reviewing steps conducted during the study, provides information on the developed database and data analysis tools, and reports the findings of a statistical analysis of the identified hazardous liquid pipeline incidents in terms of accident dynamics and consequences.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction.

PubMed

Makropoulos, Antonios; Robinson, Emma C; Schuh, Andreas; Wright, Robert; Fitzgibbon, Sean; Bozek, Jelena; Counsell, Serena J; Steinweg, Johannes; Vecchiato, Katy; Passerat-Palmbach, Jonathan; Lenz, Gregor; Mortari, Filippo; Tenev, Tencho; Duff, Eugene P; Bastiani, Matteo; Cordero-Grande, Lucilio; Hughes, Emer; Tusor, Nora; Tournier, Jacques-Donald; Hutter, Jana; Price, Anthony N; Teixeira, Rui Pedro A G; Murgasova, Maria; Victor, Suresh; Kelly, Christopher; Rutherford, Mary A; Smith, Stephen M; Edwards, A David; Hajnal, Joseph V; Jenkinson, Mark; Rueckert, Daniel

2018-06-01

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity. Copyright © 2018 Elsevier Inc. All rights reserved.

Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project.

PubMed

Bastiani, Matteo; Andersson, Jesper L R; Cordero-Grande, Lucilio; Murgasova, Maria; Hutter, Jana; Price, Anthony N; Makropoulos, Antonios; Fitzgibbon, Sean P; Hughes, Emer; Rueckert, Daniel; Victor, Suresh; Rutherford, Mary; Edwards, A David; Smith, Stephen M; Tournier, Jacques-Donald; Hajnal, Joseph V; Jbabdi, Saad; Sotiropoulos, Stamatios N

2018-05-28

The developing Human Connectome Project is set to create and make available to the scientific community a 4-dimensional map of functional and structural cerebral connectivity from 20 to 44 weeks post-menstrual age, to allow exploration of the genetic and environmental influences on brain development, and the relation between connectivity and neurocognitive function. A large set of multi-modal MRI data from fetuses and newborn infants is currently being acquired, along with genetic, clinical and developmental information. In this overview, we describe the neonatal diffusion MRI (dMRI) image processing pipeline and the structural connectivity aspect of the project. Neonatal dMRI data poses specific challenges, and standard analysis techniques used for adult data are not directly applicable. We have developed a processing pipeline that deals directly with neonatal-specific issues, such as severe motion and motion-related artefacts, small brain sizes, high brain water content and reduced anisotropy. This pipeline allows automated analysis of in-vivo dMRI data, probes tissue microstructure, reconstructs a number of major white matter tracts, and includes an automated quality control framework that identifies processing issues or inconsistencies. We here describe the pipeline and present an exemplar analysis of data from 140 infants imaged at 38-44 weeks post-menstrual age. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Microcomputers, software combine to provide daily product, movement inventory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cable, T.

1985-06-01

This paper describes the efforts of Sante Fe Pipelines Inc. in keeping track of product inventory on the 810 mile, 12-in. Chapparal Pipeline and the 1,913 mile, 8- and 10-in. Gulf Central Pipeline. The decision to use a PC for monitoring the inventory was significant. The application was completed by TRON, Inc. The system is actually two major subsystems. The pipeline system accounts for injections into the pipeline and deliveries of product. This feeds the storage and the terminal inventory system where inventories are maintained at storage locations by shipper and supplier account. The paper further explains the inventory monitoringmore » process in detail. Communications software is described as well.« less

Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline

PubMed Central

Dinov, Ivo; Lozev, Kamen; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Pierce, Jonathan; Zamanyan, Alen; Chakrapani, Shruthi; Van Horn, John; Parker, D. Stott; Magsipoc, Rico; Leung, Kelvin; Gutman, Boris; Woods, Roger; Toga, Arthur

2010-01-01

Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges—management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu. PMID:20927408

Unobtrusive integration of data management with fMRI analysis.

PubMed

Poliakov, Andrew V; Hertzenberg, Xenia; Moore, Eider B; Corina, David P; Ojemann, George A; Brinkley, James F

2007-01-01

This note describes a software utility, called X-batch which addresses two pressing issues typically faced by functional magnetic resonance imaging (fMRI) neuroimaging laboratories (1) analysis automation and (2) data management. The first issue is addressed by providing a simple batch mode processing tool for the popular SPM software package (http://www.fil.ion. ucl.ac.uk/spm/; Welcome Department of Imaging Neuroscience, London, UK). The second is addressed by transparently recording metadata describing all aspects of the batch job (e.g., subject demographics, analysis parameters, locations and names of created files, date and time of analysis, and so on). These metadata are recorded as instances of an extended version of the Protégé-based Experiment Lab Book ontology created by the Dartmouth fMRI Data Center. The resulting instantiated ontology provides a detailed record of all fMRI analyses performed, and as such can be part of larger systems for neuroimaging data management, sharing, and visualization. The X-batch system is in use in our own fMRI research, and is available for download at http://X-batch.sourceforge.net/.

Memory Performance and fMRI Signal in Presymptomatic Familial Alzheimer’s Disease

PubMed Central

Braskie, Meredith N.; Medina, Luis D.; Rodriguez-Agudelo, Yaneth; Geschwind, Daniel H.; Macias-Islas, Miguel Angel; Thompson, Paul M.; Cummings, Jeffrey L.; Bookheimer, Susan Y.; Ringman, John M.

2013-01-01

Rare autosomal dominant mutations result in familial Alzheimer’s disease (FAD) with a relatively consistent age of onset within families. This provides an estimate of years until disease onset (relative age) in mutation carriers. Increased AD risk has been associated with differences in functional magnetic resonance imaging (fMRI) activity during memory tasks, but most of these studies have focused on possession of apolipoprotein E allele 4 (APOE4), a risk factor, but not causative variant, of late-onset AD. Evaluation of fMRI activity in presymptomatic FAD mutation carriers versus noncarriers provides insight into preclinical changes in those who will certainly develop AD in a prescribed period of time. Adults from FAD mutation-carrying families (nine mutation carriers, eight noncarriers) underwent fMRI scanning while performing a memory task. We examined fMRI signal differences between carriers and noncarriers, and how signal related to fMRI task performance within mutation status group, controlling for relative age and education. Mutation noncarriers had greater retrieval period activity than carriers in several AD-relevant regions, including the left hippocampus. Better performing noncarriers showed greater encoding period activity including in the parahippocampal gyrus. Poorer performing carriers showed greater retrieval period signal, including in the frontal and temporal lobes, suggesting underlying pathological processes. PMID:22806961

From Pixels to Planets

NASA Technical Reports Server (NTRS)

Brownston, Lee; Jenkins, Jon M.

2015-01-01

The Kepler Mission was launched in 2009 as NASAs first mission capable of finding Earth-size planets in the habitable zone of Sun-like stars. Its telescope consists of a 1.5-m primary mirror and a 0.95-m aperture. The 42 charge-coupled devices in its focal plane are read out every half hour, compressed, and then downlinked monthly. After four years, the second of four reaction wheels failed, ending the original mission. Back on earth, the Science Operations Center developed the Science Pipeline to analyze about 200,000 target stars in Keplers field of view, looking for evidence of periodic dimming suggesting that one or more planets had crossed the face of its host star. The Pipeline comprises several steps, from pixel-level calibration, through noise and artifact removal, to detection of transit-like signals and the construction of a suite of diagnostic tests to guard against false positives. The Kepler Science Pipeline consists of a pipeline infrastructure written in the Java programming language, which marshals data input to and output from MATLAB applications that are executed as external processes. The pipeline modules, which underwent continuous development and refinement even after data started arriving, employ several analytic techniques, many developed for the Kepler Project. Because of the large number of targets, the large amount of data per target and the complexity of the pipeline algorithms, the processing demands are daunting. Some pipeline modules require days to weeks to process all of their targets, even when run on NASA's 128-node Pleiades supercomputer. The software developers are still seeking ways to increase the throughput. To date, the Kepler project has discovered more than 4000 planetary candidates, of which more than 1000 have been independently confirmed or validated to be exoplanets. Funding for this mission is provided by NASAs Science Mission Directorate.

Functional MRI in the Investigation of Blast-Related Traumatic Brain Injury

PubMed Central

Graner, John; Oakes, Terrence R.; French, Louis M.; Riedy, Gerard

2012-01-01

This review focuses on the application of functional magnetic resonance imaging (fMRI) to the investigation of blast-related traumatic brain injury (bTBI). Relatively little is known about the exact mechanisms of neurophysiological injury and pathological and functional sequelae of bTBI. Furthermore, in mild bTBI, standard anatomical imaging techniques (MRI and computed tomography) generally fail to show focal lesions and most of the symptoms present as subjective clinical functional deficits. Therefore, an objective test of brain functionality has great potential to aid in patient diagnosis and provide a sensitive measurement to monitor disease progression and treatment. The goal of this review is to highlight the relevant body of blast-related TBI literature and present suggestions and considerations in the development of fMRI studies for the investigation of bTBI. The review begins with a summary of recent bTBI publications followed by discussions of various elements of blast-related injury. Brief reviews of some fMRI techniques that focus on mental processes commonly disrupted by bTBI, including working memory, selective attention, and emotional processing, are presented in addition to a short review of resting state fMRI. Potential strengths and weaknesses of these approaches as regards bTBI are discussed. Finally, this review presents considerations that must be made when designing fMRI studies for bTBI populations, given the heterogeneous nature of bTBI and its high rate of comorbidity with other physical and psychological injuries. PMID:23460082

Validating the performance of one-time decomposition for fMRI analysis using ICA with automatic target generation process.

PubMed

Yao, Shengnan; Zeng, Weiming; Wang, Nizhuan; Chen, Lei

2013-07-01

Independent component analysis (ICA) has been proven to be effective for functional magnetic resonance imaging (fMRI) data analysis. However, ICA decomposition requires to optimize the unmixing matrix iteratively whose initial values are generated randomly. Thus the randomness of the initialization leads to different ICA decomposition results. Therefore, just one-time decomposition for fMRI data analysis is not usually reliable. Under this circumstance, several methods about repeated decompositions with ICA (RDICA) were proposed to reveal the stability of ICA decomposition. Although utilizing RDICA has achieved satisfying results in validating the performance of ICA decomposition, RDICA cost much computing time. To mitigate the problem, in this paper, we propose a method, named ATGP-ICA, to do the fMRI data analysis. This method generates fixed initial values with automatic target generation process (ATGP) instead of being produced randomly. We performed experimental tests on both hybrid data and fMRI data to indicate the effectiveness of the new method and made a performance comparison of the traditional one-time decomposition with ICA (ODICA), RDICA and ATGP-ICA. The proposed method demonstrated that it not only could eliminate the randomness of ICA decomposition, but also could save much computing time compared to RDICA. Furthermore, the ROC (Receiver Operating Characteristic) power analysis also denoted the better signal reconstruction performance of ATGP-ICA than that of RDICA. Copyright © 2013 Elsevier Inc. All rights reserved.

Data processing pipeline for serial femtosecond crystallography at SACLA.

PubMed

Nakane, Takanori; Joti, Yasumasa; Tono, Kensuke; Yabashi, Makina; Nango, Eriko; Iwata, So; Ishitani, Ryuichiro; Nureki, Osamu

2016-06-01

A data processing pipeline for serial femtosecond crystallography at SACLA was developed, based on Cheetah [Barty et al. (2014). J. Appl. Cryst. 47 , 1118-1131] and CrystFEL [White et al. (2016). J. Appl. Cryst. 49 , 680-689]. The original programs were adapted for data acquisition through the SACLA API, thread and inter-node parallelization, and efficient image handling. The pipeline consists of two stages: The first, online stage can analyse all images in real time, with a latency of less than a few seconds, to provide feedback on hit rate and detector saturation. The second, offline stage converts hit images into HDF5 files and runs CrystFEL for indexing and integration. The size of the filtered compressed output is comparable to that of a synchrotron data set. The pipeline enables real-time feedback and rapid structure solution during beamtime.

Proposal and design of a natural gas liquefaction process recovering the energy obtained from the pressure reducing stations of high-pressure pipelines

NASA Astrophysics Data System (ADS)

Tan, Hongbo; Zhao, Qingxuan; Sun, Nannan; Li, Yanzhong

2016-12-01

Taking advantage of the refrigerating effect in the expansion at an appropriate temperature, a fraction of high-pressure natural gas transported by pipelines could be liquefied in a city gate station through a well-organized pressure reducing process without consuming any extra energy. The authors proposed such a new process, which mainly consists of a turbo-expander driven booster, throttle valves, multi-stream heat exchangers and separators, to yield liquefied natural gas (LNG) and liquid light hydrocarbons (LLHs) utilizing the high-pressure of the pipelines. Based on the assessment of the effects of several key parameters on the system performance by a steady-state simulation in Aspen HYSYS, an optimal design condition of the proposed process was determined. The results showed that the new process is more appropriate to be applied in a pressure reducing station (PRS) for the pipelines with higher pressure. For the feed gas at the pressure of 10 MPa, the maximum total liquefaction rate (ytot) of 15.4% and the maximum exergy utilizing rate (EUR) of 21.7% could be reached at the optimal condition. The present process could be used as a small-scale natural gas liquefying and peak-shaving plant at a city gate station.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform.

PubMed

Moutsatsos, Ioannis K; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J; Jenkins, Jeremy L; Holway, Nicholas; Tallarico, John; Parker, Christian N

2017-03-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an "off-the-shelf," open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform

PubMed Central

Moutsatsos, Ioannis K.; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J.; Jenkins, Jeremy L.; Holway, Nicholas; Tallarico, John; Parker, Christian N.

2016-01-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an “off-the-shelf,” open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community. PMID:27899692

Tajikistan Country Profile

DTIC Science & Technology

2009-07-01

light industry and therefore was largely an agricultural support base for the economy. Aluminum and uranium production and processing were the major...Tajikistan is not a producer/exporter of energy resources although has oil and natural gas reserves. The country has a pipeline importing natural gas from...Uzbekistan. The country also imports gas from Uzbekistan. The total length of gas pipeline is 549 km and 38 km of oil pipelines. Railroads

High-field fMRI unveils orientation columns in humans.

PubMed

Yacoub, Essa; Harel, Noam; Ugurbil, Kâmil

2008-07-29

Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90 degrees (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.

Forecasting and Evaluation of Gas Pipelines Geometric Forms Breach Hazard

NASA Astrophysics Data System (ADS)

Voronin, K. S.

2016-10-01

Main gas pipelines during operation are under the influence of the permanent pressure drops which leads to their lengthening and as a result, to instability of their position in space. In dynamic systems that have feedback, phenomena, preceding emergencies, should be observed. The article discusses the forced vibrations of the gas pipeline cylindrical surface under the influence of dynamic loads caused by pressure surges, and the process of its geometric shape deformation. Frequency of vibrations, arising in the pipeline at the stage preceding its bending, is being determined. Identification of this frequency can be the basis for the development of a method of monitoring the technical condition of the gas pipeline, and forecasting possible emergency situations allows planning and carrying out in due time reconstruction works on sections of gas pipeline with a possible deviation from the design position.

Complementary fMRI and EEG evidence for more efficient neural processing of rhythmic vs. unpredictably timed sounds

PubMed Central

van Atteveldt, Nienke; Musacchia, Gabriella; Zion-Golumbic, Elana; Sehatpour, Pejman; Javitt, Daniel C.; Schroeder, Charles

2015-01-01

The brain’s fascinating ability to adapt its internal neural dynamics to the temporal structure of the sensory environment is becoming increasingly clear. It is thought to be metabolically beneficial to align ongoing oscillatory activity to the relevant inputs in a predictable stream, so that they will enter at optimal processing phases of the spontaneously occurring rhythmic excitability fluctuations. However, some contexts have a more predictable temporal structure than others. Here, we tested the hypothesis that the processing of rhythmic sounds is more efficient than the processing of irregularly timed sounds. To do this, we simultaneously measured functional magnetic resonance imaging (fMRI) and electro-encephalograms (EEG) while participants detected oddball target sounds in alternating blocks of rhythmic (e.g., with equal inter-stimulus intervals) or random (e.g., with randomly varied inter-stimulus intervals) tone sequences. Behaviorally, participants detected target sounds faster and more accurately when embedded in rhythmic streams. The fMRI response in the auditory cortex was stronger during random compared to random tone sequence processing. Simultaneously recorded N1 responses showed larger peak amplitudes and longer latencies for tones in the random (vs. the rhythmic) streams. These results reveal complementary evidence for more efficient neural and perceptual processing during temporally predictable sensory contexts. PMID:26579044

16 CFR 802.3 - Acquisitions of carbon-based mineral reserves.

Code of Federal Regulations, 2014 CFR

2014-01-01

... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands together with... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands and associated... pipeline and pipeline system or processing facility which transports or processes oil and gas after it...

16 CFR 802.3 - Acquisitions of carbon-based mineral reserves.

Code of Federal Regulations, 2010 CFR

2010-01-01

... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands together with... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands and associated... pipeline and pipeline system or processing facility which transports or processes oil and gas after it...

16 CFR 802.3 - Acquisitions of carbon-based mineral reserves.

Code of Federal Regulations, 2013 CFR

2013-01-01

... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands together with... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands and associated... pipeline and pipeline system or processing facility which transports or processes oil and gas after it...

16 CFR 802.3 - Acquisitions of carbon-based mineral reserves.

Code of Federal Regulations, 2012 CFR

2012-01-01

... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands together with... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands and associated... pipeline and pipeline system or processing facility which transports or processes oil and gas after it...

16 CFR 802.3 - Acquisitions of carbon-based mineral reserves.

Code of Federal Regulations, 2011 CFR

2011-01-01

... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands together with... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands and associated... pipeline and pipeline system or processing facility which transports or processes oil and gas after it...

18 CFR 157.21 - Pre-filing procedures and review process for LNG terminal facilities and other natural gas...

Code of Federal Regulations, 2010 CFR

2010-04-01

... the pre-filing review of any pipeline or other natural gas facilities, including facilities not... from the subject LNG terminal facilities to the existing natural gas pipeline infrastructure. (b) Other... and review process for LNG terminal facilities and other natural gas facilities prior to filing of...

Planck 2015 results: II. Low Frequency Instrument data processings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ade, P. A. R.; Aghanim, N.; Ashdown, M.

In this paper, we present an updated description of the Planck Low Frequency Instrument (LFI) data processing pipeline, associated with the 2015 data release. We point out the places where our results and methods have remained unchanged since the 2013 paper and we highlight the changes made for the 2015 release, describing the products (especially timelines) and the ways in which they were obtained. We demonstrate that the pipeline is self-consistent (principally based on simulations) and report all null tests. For the first time, we present LFI maps in Stokes Q and U polarization. Finally, we refer to other relatedmore » papers where more detailed descriptions of the LFI data processing pipeline may be found if needed.« less

Planck 2015 results: II. Low Frequency Instrument data processings

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Ashdown, M.; ...

2016-09-20

In this paper, we present an updated description of the Planck Low Frequency Instrument (LFI) data processing pipeline, associated with the 2015 data release. We point out the places where our results and methods have remained unchanged since the 2013 paper and we highlight the changes made for the 2015 release, describing the products (especially timelines) and the ways in which they were obtained. We demonstrate that the pipeline is self-consistent (principally based on simulations) and report all null tests. For the first time, we present LFI maps in Stokes Q and U polarization. Finally, we refer to other relatedmore » papers where more detailed descriptions of the LFI data processing pipeline may be found if needed.« less

Comparison of a semi-automatic annotation tool and a natural language processing application for the generation of clinical statement entries.

PubMed

Lin, Ching-Heng; Wu, Nai-Yuan; Lai, Wei-Shao; Liou, Der-Ming

2015-01-01

Electronic medical records with encoded entries should enhance the semantic interoperability of document exchange. However, it remains a challenge to encode the narrative concept and to transform the coded concepts into a standard entry-level document. This study aimed to use a novel approach for the generation of entry-level interoperable clinical documents. Using HL7 clinical document architecture (CDA) as the example, we developed three pipelines to generate entry-level CDA documents. The first approach was a semi-automatic annotation pipeline (SAAP), the second was a natural language processing (NLP) pipeline, and the third merged the above two pipelines. We randomly selected 50 test documents from the i2b2 corpora to evaluate the performance of the three pipelines. The 50 randomly selected test documents contained 9365 words, including 588 Observation terms and 123 Procedure terms. For the Observation terms, the merged pipeline had a significantly higher F-measure than the NLP pipeline (0.89 vs 0.80, p<0.0001), but a similar F-measure to that of the SAAP (0.89 vs 0.87). For the Procedure terms, the F-measure was not significantly different among the three pipelines. The combination of a semi-automatic annotation approach and the NLP application seems to be a solution for generating entry-level interoperable clinical documents. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.comFor numbered affiliation see end of article.

Strain-Based Design Methodology of Large Diameter Grade X80 Linepipe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lower, Mark D.

2014-04-01

Continuous growth in energy demand is driving oil and natural gas production to areas that are often located far from major markets where the terrain is prone to earthquakes, landslides, and other types of ground motion. Transmission pipelines that cross this type of terrain can experience large longitudinal strains and plastic circumferential elongation as the pipeline experiences alignment changes resulting from differential ground movement. Such displacements can potentially impact pipeline safety by adversely affecting structural capacity and leak tight integrity of the linepipe steel. Planning for new long-distance transmission pipelines usually involves consideration of higher strength linepipe steels because theirmore » use allows pipeline operators to reduce the overall cost of pipeline construction and increase pipeline throughput by increasing the operating pressure. The design trend for new pipelines in areas prone to ground movement has evolved over the last 10 years from a stress-based design approach to a strain-based design (SBD) approach to further realize the cost benefits from using higher strength linepipe steels. This report presents an overview of SBD for pipelines subjected to large longitudinal strain and high internal pressure with emphasis on the tensile strain capacity of high-strength microalloyed linepipe steel. The technical basis for this report involved engineering analysis and examination of the mechanical behavior of Grade X80 linepipe steel in both the longitudinal and circumferential directions. Testing was conducted to assess effects on material processing including as-rolled, expanded, and heat treatment processing intended to simulate coating application. Elastic-plastic and low-cycle fatigue analyses were also performed with varying internal pressures. Proposed SBD models discussed in this report are based on classical plasticity theory and account for material anisotropy, triaxial strain, and microstructural damage effects developed from test data. The results are intended to enhance SBD and analysis methods for producing safe and cost effective pipelines capable of accommodating large plastic strains in seismically active arctic areas.« less

Aging effects on functional auditory and visual processing using fMRI with variable sensory loading.

PubMed

Cliff, Michael; Joyce, Dan W; Lamar, Melissa; Dannhauser, Thomas; Tracy, Derek K; Shergill, Sukhwinder S

2013-05-01

Traditionally, studies investigating the functional implications of age-related structural brain alterations have focused on higher cognitive processes; by increasing stimulus load, these studies assess behavioral and neurophysiological performance. In order to understand age-related changes in these higher cognitive processes, it is crucial to examine changes in visual and auditory processes that are the gateways to higher cognitive functions. This study provides evidence for age-related functional decline in visual and auditory processing, and regional alterations in functional brain processing, using non-invasive neuroimaging. Using functional magnetic resonance imaging (fMRI), younger (n=11; mean age=31) and older (n=10; mean age=68) adults were imaged while observing flashing checkerboard images (passive visual stimuli) and hearing word lists (passive auditory stimuli) across varying stimuli presentation rates. Younger adults showed greater overall levels of temporal and occipital cortical activation than older adults for both auditory and visual stimuli. The relative change in activity as a function of stimulus presentation rate showed differences between young and older participants. In visual cortex, the older group showed a decrease in fMRI blood oxygen level dependent (BOLD) signal magnitude as stimulus frequency increased, whereas the younger group showed a linear increase. In auditory cortex, the younger group showed a relative increase as a function of word presentation rate, while older participants showed a relatively stable magnitude of fMRI BOLD response across all rates. When analyzing participants across all ages, only the auditory cortical activation showed a continuous, monotonically decreasing BOLD signal magnitude as a function of age. Our preliminary findings show an age-related decline in demand-related, passive early sensory processing. As stimulus demand increases, visual and auditory cortex do not show increases in activity in older compared to younger people. This may negatively impact on the fidelity of information available to higher cognitive processing. Such evidence may inform future studies focused on cognitive decline in aging. Copyright © 2012 Elsevier Ltd. All rights reserved.

Reasons for decision in the matter of Maritimes and Northeast Pipeline Management Ltd. application dated 24 February 1998 for approval of the plan, profile and book of reference respecting the detailed pipeline route from Goldboro, N.S. to St. Stephen, N.B.: MH-3-98

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1998-12-31

In December 1997, Maritimes and Northeast Pipeline Management Ltd. received approval to construct and operate a natural gas pipeline consisting of about 558 kilometers of 762-millimeter pipe to be located within a one-kilometer-wide corridor extending from Goldboro, Nova Scotia to the international border near St. Stephen, New Brunswick. This report covers the second stage of the pipeline approval process where the detailed route is determined. It presents the views of the pipeline company, various landowners and mineral rights holders objecting to the proposed detailed route, and the National Energy Board with regard to two issues: The best possible detailed routemore » for the pipeline, and the most appropriate methods and timing of constructing the pipeline. Specific land/mineral rights owner cases including the nature of the objection, possible alternate routes, and the Board decision in each case are described.« less

Presurgical motor, somatosensory and language fMRI: Technical feasibility and limitations in 491 patients over 13 years.

PubMed

Tyndall, Anthony J; Reinhardt, Julia; Tronnier, Volker; Mariani, Luigi; Stippich, Christoph

2017-01-01

To analyse the long-term feasibility and limitations of presurgical fMRI in a cohort of tumour and epilepsy patients with different MR-scanners at 1.5 and 3.0 T. Four hundred and ninety-one consecutive patients undergoing presurgical fMRI between 2000 and 2012 on five different MR-scanners using established paradigms and semi-automated data processing were included. Success rates of task performance and BOLD-activation were determined for motor and somatosensory somatotopic mapping and language localisation. Procedural success, failures and imaging artifacts were analysed. MR-field strengths were compared. Two thousand three hundred fifteen of 2348 (98.6 %) attempted paradigms (1033 motor, 1220 speech, 95 somatosensory) were successfully performed. 100 paradigms (4.3 %) were repetition runs. 23 speech, 6 motor and 2 sensory paradigms failed for non-compliance and technical issues. Most language paradigm failures were noted in overt sentence generation. Average significant BOLD-activation was higher for motor than language paradigms (95.8 vs. 81.6 %). Most language paradigms showed significantly higher activation rates at 3 T compared to 1.5 T, whereas no significant difference was found for motor paradigms. fMRI proved very robust for the presurgical localisation of the different motor and somatosensory body representations, as well as Broca's and Wernicke's language areas across different MR-scanners at 1.5 and 3.0 T over 13 years. • Standardised presurgical motor and language fMRI is robust across various MRI platforms. • Motor fMRI is less dependent on field strength than language fMRI. • fMRI task failures are relatively low and are reduced by paradigm repetition.

PICARD - A PIpeline for Combining and Analyzing Reduced Data

NASA Astrophysics Data System (ADS)

Gibb, Andrew G.; Jenness, Tim; Economou, Frossie

PICARD is a facility for combining and analyzing reduced data, normally the output from the ORAC-DR data reduction pipeline. This document describes an introduction to using PICARD for processing instrument-independent data.

Full Scenes Produce More Activation than Close-Up Scenes and Scene-Diagnostic Objects in Parahippocampal and Retrosplenial Cortex: An fMRI Study

ERIC Educational Resources Information Center

Henderson, John M.; Larson, Christine L.; Zhu, David C.

2008-01-01

We used fMRI to directly compare activation in two cortical regions previously identified as relevant to real-world scene processing: retrosplenial cortex and a region of posterior parahippocampal cortex functionally defined as the parahippocampal place area (PPA). We compared activation in these regions to full views of scenes from a global…

FMRI Brain Activation in a Finnish Family with Specific Language Impairment Compared with a Normal Control Group

ERIC Educational Resources Information Center

Hugdahl, Kenneth; Gundersen, Hilde; Brekke, Cecilie; Thomsen, Tormod; Rimol, Lars Morten; Ersland, Lars; Niemi, Jussi

2004-01-01

The aim of the present study was to investigate differences in brain activation in a family with SLI as compared to intact individuals with normally developed language during processing of language stimuli. Functional magnetic resonance imaging (fMRI) was used to monitor changes in neuronal activation in temporal and frontal lobe areas in 5…

The Neurotopography of Written Word Production: An fMRI Investigation of the Distribution of Sensitivity to Length and Frequency

ERIC Educational Resources Information Center

Rapp, Brenda; Dufor, Olivier

2011-01-01

This research is directed at charting the neurotopography of the component processes of the spelling system by using fMRI to identify the neural substrates that are sensitive to the factors of lexical frequency and word length. In spelling, word frequency effects index orthographic long-term memory whereas length effects, as measured by the number…

Exploring Possible Neural Mechanisms of Intelligence Differences Using Processing Speed and Working Memory Tasks: An fMRI Study

ERIC Educational Resources Information Center

Waiter, Gordon D.; Deary, Ian J.; Staff, Roger T.; Murray, Alison D.; Fox, Helen C.; Starr, John M.; Whalley, Lawrence J.

2009-01-01

To explore the possible neural foundations of individual differences in intelligence test scores, we examined the associations between Raven's Matrices scores and two tasks that were administered in a functional magnetic resonance imaging (fMRI) setting. The two tasks were an n-back working memory (N = 37) task and inspection time (N = 47). The…

Distinct and overlapping fMRI activation networks for processing of novel identities and locations of objects.

PubMed

Pihlajamäki, Maija; Tanila, Heikki; Könönen, Mervi; Hänninen, Tuomo; Aronen, Hannu J; Soininen, Hilkka

2005-10-01

The ventral visual stream processes information about the identity of objects ('what'), whereas the dorsal stream processes the spatial locations of objects ('where'). There is a corresponding, although disputed, distinction for the ventrolateral and dorsolateral prefrontal areas. Furthermore, there seems to be a distinction between the anterior and posterior medial temporal lobe (MTL) structures in the processing of novel items and new spatial arrangements, respectively. Functional differentiation of the intermediary mid-line cortical and temporal neocortical structures that communicate with the occipitotemporal, occipitoparietal, prefrontal, and MTL structures, however, is unclear. Therefore, in the present functional magnetic resonance imaging (fMRI) study, we examined whether the distinction among the MTL structures extends to these closely connected cortical areas. The most striking difference in the fMRI responses during visual presentation of changes in either items or their locations was the bilateral activation of the temporal lobe and ventrolateral prefrontal cortical areas for novel object identification in contrast to wide parietal and dorsolateral prefrontal activation for the novel locations of objects. An anterior-posterior distinction of fMRI responses similar to the MTL was observed in the cingulate/retrosplenial, and superior and middle temporal cortices. In addition to the distinct areas of activation, certain frontal, parietal, and temporo-occipital areas responded to both object and spatial novelty, suggesting a common attentional network for both types of changes in the visual environment. These findings offer new insights to the functional roles and intrinsic specialization of the cingulate/retrosplenial, and lateral temporal cortical areas in visuospatial cognition.

Intrinsic Brain Connectivity in Chronic Pain: A Resting-State fMRI Study in Patients with Rheumatoid Arthritis

PubMed Central

Flodin, Pär; Martinsen, Sofia; Altawil, Reem; Waldheim, Eva; Lampa, Jon; Kosek, Eva; Fransson, Peter

2016-01-01

Background: Rheumatoid arthritis (RA) is commonly accompanied by pain that is discordant with the degree of peripheral pathology. Very little is known about the cerebral processes involved in pain processing in RA. Here we investigated resting-state brain connectivity associated with prolonged pain in RA. Methods: 24 RA subjects and 19 matched controls were compared with regard to both behavioral measures of pain perception and resting-resting state fMRI data acquired subsequently to fMRI sessions involving pain stimuli. The resting-state fMRI brain connectivity was investigated using 159 seed regions located in cardinal pain processing brain regions. Additional principal component based multivariate pattern analysis of the whole brain connectivity pattern was carried out in a data driven analysis to localize group differences in functional connectivity. Results: When RA patients were compared to controls, we observed significantly lower pain resilience for pressure on the affected finger joints (i.e., P50-joint) and an overall heightened level of perceived global pain in RA patients. Relative to controls, RA patients displayed increased brain connectivity predominately for the supplementary motor areas, mid-cingulate cortex, and the primary sensorimotor cortex. Additionally, we observed an increase in brain connectivity between the insula and prefrontal cortex as well as between anterior cingulate cortex and occipital areas for RA patients. None of the group differences in brain connectivity were significantly correlated with behavioral parameters. Conclusion: Our study provides experimental evidence of increased connectivity between frontal midline regions that are implicated in affective pain processing and bilateral sensorimotor regions in RA patients. PMID:27014038

Brain activity changes in cognitive networks in relapsing-remitting multiple sclerosis - insights from a longitudinal FMRI study.

PubMed

Loitfelder, Marisa; Fazekas, Franz; Koschutnig, Karl; Fuchs, Siegrid; Petrovic, Katja; Ropele, Stefan; Pichler, Alexander; Jehna, Margit; Langkammer, Christian; Schmidt, Reinhold; Neuper, Christa; Enzinger, Christian

2014-01-01

Extrapolations from previous cross-sectional fMRI studies suggest cerebral functional changes with progression of Multiple Sclerosis (MS), but longitudinal studies are scarce. We assessed brain activation changes over time in MS patients using a cognitive fMRI paradigm and examined correlations with clinical and cognitive status and brain morphology. 13 MS patients and 15 healthy controls (HC) underwent MRI including fMRI (go/no-go task), neurological and neuropsychological exams at baseline (BL) and follow-up (FU; minimum 12, median 20 months). We assessed estimates of and changes in fMRI activation, total brain and subcortical grey matter volumes, cortical thickness, and T2-lesion load. Bland-Altman (BA) plots served to assess fMRI signal variability. Cognitive and disability levels remained largely stable in the patients. With the fMRI task, both at BL and FU, patients compared to HC showed increased activation in the insular cortex, precuneus, cerebellum, posterior cingulate cortex, and occipital cortex. At BL, patients vs. HC also had lower caudate nucleus, thalamus and putamen volumes. Over time, patients (but not HC) demonstrated fMRI activity increments in the left inferior parietal lobule. These correlated with worse single-digit-modality test (SDMT) performance. BA-plots attested to reproducibility of the fMRI task. In the patients, the right caudate nucleus decreased in volume which again correlated with worsening SDMT performance. Given preserved cognitive performance, the increased activation at BL in the patients may be viewed as largely adaptive. In contrast, the negative correlation with SDMT performance suggests increasing parietal activation over time to be maladaptive. Several areas with purported relevance for cognition showed decreased volumes at BL and right caudate nucleus volume decline correlated with decreasing SDMT performance. This highlights the dynamics of functional changes and the strategic importance of specific brain areas for cognitive processes in MS.

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics

PubMed Central

Deutsch, Eric W.; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L.

2015-01-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include mass spectrometry to define protein sequence, protein:protein interactions, and protein post-translational modifications. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative mass spectrometry proteomics. It supports all major operating systems and instrument vendors via open data formats. Here we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of tandem mass spectrometry datasets, as well as some major upcoming features. PMID:25631240

Leak detection in gas pipeline by acoustic and signal processing - A review

NASA Astrophysics Data System (ADS)

Adnan, N. F.; Ghazali, M. F.; Amin, M. M.; Hamat, A. M. A.

2015-12-01

The pipeline system is the most important part in media transport in order to deliver fluid to another station. The weak maintenance and poor safety will contribute to financial losses in term of fluid waste and environmental impacts. There are many classifications of techniques to make it easier to show their specific method and application. This paper's discussion about gas leak detection in pipeline system using acoustic method will be presented in this paper. The wave propagation in the pipeline is a key parameter in acoustic method when the leak occurs and the pressure balance of the pipe will generated by the friction between wall in the pipe. The signal processing is used to decompose the raw signal and show in time- frequency. Findings based on the acoustic method can be used for comparative study in the future. Acoustic signal and HHT is the best method to detect leak in gas pipelines. More experiments and simulation need to be carried out to get the fast result of leaking and estimation of their location.

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics.

PubMed

Deutsch, Eric W; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L

2015-08-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include MS to define protein sequence, protein:protein interactions, and protein PTMs. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative MS proteomics. It supports all major operating systems and instrument vendors via open data formats. Here, we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of MS/MS datasets, as well as some major upcoming features. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Pipeline for 3D Digital Optical Phenotyping Plant Root System Architecture

NASA Astrophysics Data System (ADS)

Davis, T. W.; Shaw, N. M.; Schneider, D. J.; Shaff, J. E.; Larson, B. G.; Craft, E. J.; Liu, Z.; Kochian, L. V.; Piñeros, M. A.

2017-12-01

This work presents a new pipeline for digital optical phenotyping the root system architecture of agricultural crops. The pipeline begins with a 3D root-system imaging apparatus for hydroponically grown crop lines of interest. The apparatus acts as a self-containing dark room, which includes an imaging tank, motorized rotating bearing and digital camera. The pipeline continues with the Plant Root Imaging and Data Acquisition (PRIDA) software, which is responsible for image capturing and storage. Once root images have been captured, image post-processing is performed using the Plant Root Imaging Analysis (PRIA) command-line tool, which extracts root pixels from color images. Following the pre-processing binarization of digital root images, 3D trait characterization is performed using the next-generation RootReader3D software. RootReader3D measures global root system architecture traits, such as total root system volume and length, total number of roots, and maximum rooting depth and width. While designed to work together, the four stages of the phenotyping pipeline are modular and stand-alone, which provides flexibility and adaptability for various research endeavors.

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

PubMed

Kim, Jiwoong; Kim, Min Soo; Koh, Andrew Y; Xie, Yang; Zhan, Xiaowei

2016-10-10

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets. Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines. FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

CFHT data processing and calibration ESPaDOnS pipeline: Upena and OPERA (optical spectropolarimetry)

NASA Astrophysics Data System (ADS)

Martioli, Eder; Teeple, D.; Manset, Nadine

2011-03-01

CFHT is ESPaDOnS responsible for processing raw images, removing instrument related artifacts, and delivering science-ready data to the PIs. Here we describe the Upena pipeline, which is the software used to reduce the echelle spectro-polarimetric data obtained with the ESPaDOnS instrument. Upena is an automated pipeline that performs calibration and reduction of raw images. Upena has the capability of both performing real-time image-by-image basis reduction and a post observing night complete reduction. Upena produces polarization and intensity spectra in FITS format. The pipeline is designed to perform parallel computing for improved speed, which assures that the final products are delivered to the PIs before noon HST after each night of observations. We also present the OPERA project, which is an open-source pipeline to reduce ESPaDOnS data that will be developed as a collaborative work between CFHT and the scientific community. OPERA will match the core capabilities of Upena and in addition will be open-source, flexible and extensible.

Physical and numerical modeling of hydrophysical proceses on the site of underwater pipelines

NASA Astrophysics Data System (ADS)

Garmakova, M. E.; Degtyarev, V. V.; Fedorova, N. N.; Shlychkov, V. A.

2018-03-01

The paper outlines issues related to ensuring the exploitation safety of underwater pipelines that are at risk of accidents. The performed research is based on physical and mathematical modeling of local bottom erosion in the area of pipeline location. The experimental studies were performed on the basis of the Hydraulics Laboratory of the Department of Hydraulic Engineering Construction, Safety and Ecology of NSUACE (Sibstrin). In the course of physical experiments it was revealed that the intensity of the bottom soil reforming depends on the deepening of the pipeline. The ANSYS software has been used for numerical modeling. The process of erosion of the sandy bottom was modeled under the pipeline. Comparison of computational results at various mass flow rates was made.

Status of the TESS Science Processing Operations Center

NASA Technical Reports Server (NTRS)

Jenkins, Jon M.; Twicken, Joseph D.; Campbell, Jennifer; Tenebaum, Peter; Sanderfer, Dwight; Davies, Misty D.; Smith, Jeffrey C.; Morris, Rob; Mansouri-Samani, Masoud; Girouardi, Forrest;

Kepler Planet Detection Metrics: Pixel-Level Transit Injection Tests of Pipeline Detection Efficiency for Data Release 25

NASA Technical Reports Server (NTRS)

Christiansen, Jessie L.

2017-01-01

This document describes the results of the fourth pixel-level transit injection experiment, which was designed to measure the detection efficiency of both the Kepler pipeline (Jenkins 2002, 2010; Jenkins et al. 2017) and the Robovetter (Coughlin 2017). Previous transit injection experiments are described in Christiansen et al. (2013, 2015a,b, 2016).In order to calculate planet occurrence rates using a given Kepler planet catalogue, produced with a given version of the Kepler pipeline, we need to know the detection efficiency of that pipeline. This can be empirically determined by injecting a suite of simulated transit signals into the Kepler data, processing the data through the pipeline, and examining the distribution of successfully recovered transits. This document describes the results for the pixel-level transit injection experiment performed to accompany the final Q1-Q17 Data Release 25 (DR25) catalogue (Thompson et al. 2017)of the Kepler Objects of Interest. The catalogue was generated using the SOC pipeline version 9.3 and the DR25 Robovetter acting on the uniformly processed Q1-Q17 DR25 light curves (Thompson et al. 2016a) and assuming the Q1-Q17 DR25 Kepler stellar properties (Mathur et al. 2017).

A Comparison between the Decimated Padé Approximant and Decimated Signal Diagonalization Methods for Leak Detection in Pipelines Equipped with Pressure Sensors.

PubMed

Lay-Ekuakille, Aimé; Fabbiano, Laura; Vacca, Gaetano; Kitoko, Joël Kidiamboko; Kulapa, Patrice Bibala; Telesca, Vito

2018-06-04

Pipelines conveying fluids are considered strategic infrastructures to be protected and maintained. They generally serve for transportation of important fluids such as drinkable water, waste water, oil, gas, chemicals, etc. Monitoring and continuous testing, especially on-line, are necessary to assess the condition of pipelines. The paper presents findings related to a comparison between two spectral response algorithms based on the decimated signal diagonalization (DSD) and decimated Padé approximant (DPA) techniques that allow to one to process signals delivered by pressure sensors mounted on an experimental pipeline.

Intermediate Palomar Transient Factory: Realtime Image Subtraction Pipeline

DOE PAGES

Cao, Yi; Nugent, Peter E.; Kasliwal, Mansi M.

2016-09-28

A fast-turnaround pipeline for realtime data reduction plays an essential role in discovering and permitting followup observations to young supernovae and fast-evolving transients in modern time-domain surveys. In this paper, we present the realtime image subtraction pipeline in the intermediate Palomar Transient Factory. By using highperformance computing, efficient databases, and machine-learning algorithms, this pipeline manages to reliably deliver transient candidates within 10 minutes of images being taken. Our experience in using high-performance computing resources to process big data in astronomy serves as a trailblazer to dealing with data from large-scale time-domain facilities in the near future.

Intermediate Palomar Transient Factory: Realtime Image Subtraction Pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, Yi; Nugent, Peter E.; Kasliwal, Mansi M.

A fast-turnaround pipeline for realtime data reduction plays an essential role in discovering and permitting followup observations to young supernovae and fast-evolving transients in modern time-domain surveys. In this paper, we present the realtime image subtraction pipeline in the intermediate Palomar Transient Factory. By using highperformance computing, efficient databases, and machine-learning algorithms, this pipeline manages to reliably deliver transient candidates within 10 minutes of images being taken. Our experience in using high-performance computing resources to process big data in astronomy serves as a trailblazer to dealing with data from large-scale time-domain facilities in the near future.

VPipe: Virtual Pipelining for Scheduling of DAG Stream Query Plans

NASA Astrophysics Data System (ADS)

Wang, Song; Gupta, Chetan; Mehta, Abhay

There are data streams all around us that can be harnessed for tremendous business and personal advantage. For an enterprise-level stream processing system such as CHAOS [1] (Continuous, Heterogeneous Analytic Over Streams), handling of complex query plans with resource constraints is challenging. While several scheduling strategies exist for stream processing, efficient scheduling of complex DAG query plans is still largely unsolved. In this paper, we propose a novel execution scheme for scheduling complex directed acyclic graph (DAG) query plans with meta-data enriched stream tuples. Our solution, called Virtual Pipelined Chain (or VPipe Chain for short), effectively extends the "Chain" pipelining scheduling approach to complex DAG query plans.

DPPP: Default Pre-Processing Pipeline

NASA Astrophysics Data System (ADS)

van Diepen, Ger; Dijkema, Tammo Jan

2018-04-01

DPPP (Default Pre-Processing Pipeline, also referred to as NDPPP) reads and writes radio-interferometric data in the form of Measurement Sets, mainly those that are created by the LOFAR telescope. It goes through visibilities in time order and contains standard operations like averaging, phase-shifting and flagging bad stations. Between the steps in a pipeline, the data is not written to disk, making this tool suitable for operations where I/O dominates. More advanced procedures such as gain calibration are also included. Other computing steps can be provided by loading a shared library; currently supported external steps are the AOFlagger (ascl:1010.017) and a bridge that enables loading python steps.

The visual and radiological inspection of a pipeline using a teleoperated pipe crawler

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fogle, R.F.; Kuelske, K.; Kellner, R.A.

1996-07-01

In the 1950s the Savannah River Site built an open, unlined retention basin for temporary storage of potentially radionuclide-contaminated cooling water form a chemical separations process and storm water drainage from a nearby waste management facility which stored large quantities of nuclear fission by-products in carbon steel tanks. An underground process pipeline lead to the basin. Once the closure of the basin in 1972, further assessment has been required. A visual and radiological inspection of the pipeline was necessary to aid in the decision about further remediation. This article describes the inspection using a teleoperated pipe crawler. 5 figs.

Hardware and software facilities for the J-PAS and J-PLUS surveys archiving, processing and data publication

NASA Astrophysics Data System (ADS)

Cristóbal-Hornillos, D.; Varela, J.; Ederoclite, A.; Vázquez Ramió, H.; López-Sainz, A.; Hernández-Fuertes, J.; Civera, T.; Muniesa, D.; Moles, M.; Cenarro, A. J.; Marín-Franch, A.; Yanes-Díaz, A.

2015-05-01

The Observatorio Astrofísico de Javalambre consists of two main telescopes: JST/T250, a 2.5 m telescope with a FoV of 3 deg, and JAST/T80, a 83 cm with a 2 deg FoV. JST/T250 will be devoted to complete the Javalambre-PAU Astronomical Survey (J-PAS). It is a photometric survey with a system of 54 narrow-band plus 3 broad-band filters covering an area of 8500°^2. The JAST/T80 will perform the J-PLUS survey, covering the same area in a system of 12 filters. This contribution presents the software and hardware architecture designed to store and process the data. The processing pipeline runs daily and it is devoted to correct instrumental signature on the science images, to perform astrometric and photometric calibration, and the computation of individual image catalogs. In a second stage, the pipeline performs the combination of the tile mosaics and the computation of final catalogs. The catalogs are ingested in as Scientific database to be provided to the community. The processing software is connected with a management database to store persistent information about the pipeline operations done on each frame. The processing pipeline is executed in a computing cluster under a batch queuing system. Regarding the storage system, it will combine disk and tape technologies. The disk storage system will have capacity to store the data that is accessed by the pipeline. The tape library will store and archive the raw data and earlier data releases with lower access frequency.

Virtual Instrumentation Corrosion Controller for Natural Gas Pipelines

NASA Astrophysics Data System (ADS)

Gopalakrishnan, J.; Agnihotri, G.; Deshpande, D. M.

2012-12-01

Corrosion is an electrochemical process. Corrosion in natural gas (methane) pipelines leads to leakages. Corrosion occurs when anode and cathode are connected through electrolyte. Rate of corrosion in metallic pipeline can be controlled by impressing current to it and thereby making it to act as cathode of corrosion cell. Technologically advanced and energy efficient corrosion controller is required to protect natural gas pipelines. Proposed virtual instrumentation (VI) based corrosion controller precisely controls the external corrosion in underground metallic pipelines, enhances its life and ensures safety. Designing and development of proportional-integral-differential (PID) corrosion controller using VI (LabVIEW) is carried out. When the designed controller is deployed at field, it maintains the pipe to soil potential (PSP) within safe operating limit and not entering into over/under protection zone. Horizontal deployment of this technique can be done to protect all metallic structure, oil pipelines, which need corrosion protection.

Weld Design, Testing, and Assessment Procedures for High Strength Pipelines

DOT National Transportation Integrated Search

2011-12-20

Long-distance high-strength pipelines are increasingly being constructed for the efficient transportation of energy products. While the high-strength linepipe steels and high productivity welding processes are being applied, the procedures employed f...

ORAC-DR -- SCUBA-2 Pipeline Data Reduction

NASA Astrophysics Data System (ADS)

Gibb, Andrew G.; Jenness, Tim

The ORAC-DR data reduction pipeline is designed to reduce data from many different instruments. This document describes how to use ORAC-DR to process data taken with the SCUBA-2 instrument on the James Clerk Maxwell Telescope.

NGSANE: a lightweight production informatics framework for high-throughput data analysis.

PubMed

Buske, Fabian A; French, Hugh J; Smith, Martin A; Clark, Susan J; Bauer, Denis C

2014-05-15

The initial steps in the analysis of next-generation sequencing data can be automated by way of software 'pipelines'. However, individual components depreciate rapidly because of the evolving technology and analysis methods, often rendering entire versions of production informatics pipelines obsolete. Constructing pipelines from Linux bash commands enables the use of hot swappable modular components as opposed to the more rigid program call wrapping by higher level languages, as implemented in comparable published pipelining systems. Here we present Next Generation Sequencing ANalysis for Enterprises (NGSANE), a Linux-based, high-performance-computing-enabled framework that minimizes overhead for set up and processing of new projects, yet maintains full flexibility of custom scripting when processing raw sequence data. Ngsane is implemented in bash and publicly available under BSD (3-Clause) licence via GitHub at https://github.com/BauerLab/ngsane. Denis.Bauer@csiro.au Supplementary data are available at Bioinformatics online.

Study on Failure of Third-Party Damage for Urban Gas Pipeline Based on Fuzzy Comprehensive Evaluation.

PubMed

Li, Jun; Zhang, Hong; Han, Yinshan; Wang, Baodong

2016-01-01

Focusing on the diversity, complexity and uncertainty of the third-party damage accident, the failure probability of third-party damage to urban gas pipeline was evaluated on the theory of analytic hierarchy process and fuzzy mathematics. The fault tree of third-party damage containing 56 basic events was built by hazard identification of third-party damage. The fuzzy evaluation of basic event probabilities were conducted by the expert judgment method and using membership function of fuzzy set. The determination of the weight of each expert and the modification of the evaluation opinions were accomplished using the improved analytic hierarchy process, and the failure possibility of the third-party to urban gas pipeline was calculated. Taking gas pipelines of a certain large provincial capital city as an example, the risk assessment structure of the method was proved to conform to the actual situation, which provides the basis for the safety risk prevention.

A Model for Oil-Gas Pipelines Cost Prediction Based on a Data Mining Process

NASA Astrophysics Data System (ADS)

Batzias, Fragiskos A.; Spanidis, Phillip-Mark P.

2009-08-01

This paper addresses the problems associated with the cost estimation of oil/gas pipelines during the elaboration of feasibility assessments. Techno-economic parameters, i.e., cost, length and diameter, are critical for such studies at the preliminary design stage. A methodology for the development of a cost prediction model based on Data Mining (DM) process is proposed. The design and implementation of a Knowledge Base (KB), maintaining data collected from various disciplines of the pipeline industry, are presented. The formulation of a cost prediction equation is demonstrated by applying multiple regression analysis using data sets extracted from the KB. Following the methodology proposed, a learning context is inductively developed as background pipeline data are acquired, grouped and stored in the KB, and through a linear regression model provide statistically substantial results, useful for project managers or decision makers.

Applying the vantage PDMS to jack-up drilling ships

NASA Astrophysics Data System (ADS)

Yin, Peng; Chen, Yuan-Ming; Cui, Tong-Kai; Wang, Zi-Shen; Gong, Li-Jiang; Yu, Xiang-Fen

2009-09-01

The plant design management system (PDMS) is an integrated application which includes a database and is useful when designing complex 3-D industrial projects. It could be used to simplify the most difficult part of a subsea oil extraction project—detailed pipeline design. It could also be used to integrate the design of equipment, structures, HVAC, E-ways as well as the detailed designs of other specialists. This article mainly examines the applicability of the Vantage PDMS database to pipeline projects involving jack-up drilling ships. It discusses the catalogue (CATA) of the pipeline, the spec-world (SPWL) of the pipeline, the bolt tables (BLTA) and so on. This article explains the main methods for CATA construction as well as problem in the process of construction. In this article, the authors point out matters needing attention when using the Vantage PDMS database in the design process and discuss partial solutions to these questions.

The application of Mike Urban model in drainage and waterlogging in Lincheng county, China

NASA Astrophysics Data System (ADS)

Luan, Qinghua; Zhang, Kun; Liu, Jiahong; Wang, Dong; Ma, Jun

2018-06-01

Recently, the water disaster in cities especially in Chinese mountainous cities is more serious, due to the coupling influences of waterlogging and regional floods. It is necessary to study the surface runoff process of mountainous cities and examine the regional drainage pipeline network. In this study, the runoff processes of Lincheng county (located in Hebei province, China) in different scenarios were simulated through Mike Urban model. The results show that all of the runoff process of the old town and the new residential area with larger slope, is significant and full flow of these above zones exists in the part of the drainage pipeline network; and the overflow exists in part of the drainage pipeline network when the return period is ten years or twenty years, which illuminates that the waterlogging risk in this zone of Lincheng is higher. Therefore, remodeling drainage pipeline network in the old town of Lincheng and adding water storage ponds in the new residential areas were suggested. This research provides both technical support and decision-making reference to local storm flood management, also give the experiences for the study on the runoff process of similar cities.

Linear Discriminant Analysis Achieves High Classification Accuracy for the BOLD fMRI Response to Naturalistic Movie Stimuli

PubMed Central

Mandelkow, Hendrik; de Zwart, Jacco A.; Duyn, Jeff H.

2016-01-01

Naturalistic stimuli like movies evoke complex perceptual processes, which are of great interest in the study of human cognition by functional MRI (fMRI). However, conventional fMRI analysis based on statistical parametric mapping (SPM) and the general linear model (GLM) is hampered by a lack of accurate parametric models of the BOLD response to complex stimuli. In this situation, statistical machine-learning methods, a.k.a. multivariate pattern analysis (MVPA), have received growing attention for their ability to generate stimulus response models in a data-driven fashion. However, machine-learning methods typically require large amounts of training data as well as computational resources. In the past, this has largely limited their application to fMRI experiments involving small sets of stimulus categories and small regions of interest in the brain. By contrast, the present study compares several classification algorithms known as Nearest Neighbor (NN), Gaussian Naïve Bayes (GNB), and (regularized) Linear Discriminant Analysis (LDA) in terms of their classification accuracy in discriminating the global fMRI response patterns evoked by a large number of naturalistic visual stimuli presented as a movie. Results show that LDA regularized by principal component analysis (PCA) achieved high classification accuracies, above 90% on average for single fMRI volumes acquired 2 s apart during a 300 s movie (chance level 0.7% = 2 s/300 s). The largest source of classification errors were autocorrelations in the BOLD signal compounded by the similarity of consecutive stimuli. All classifiers performed best when given input features from a large region of interest comprising around 25% of the voxels that responded significantly to the visual stimulus. Consistent with this, the most informative principal components represented widespread distributions of co-activated brain regions that were similar between subjects and may represent functional networks. In light of these results, the combination of naturalistic movie stimuli and classification analysis in fMRI experiments may prove to be a sensitive tool for the assessment of changes in natural cognitive processes under experimental manipulation. PMID:27065832

Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research.

PubMed

Milchenko, Mikhail; Snyder, Abraham Z; LaMontagne, Pamela; Shimony, Joshua S; Benzinger, Tammie L; Fouke, Sarah Jost; Marcus, Daniel S

2016-07-01

Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis. Given this heterogeneity, conventional processing workflows developed for research purposes are not optimal for clinical data. In this work, we describe an approach called Heterogeneous Optimization Framework (HOF) for developing image analysis pipelines that can handle the high degree of clinical data non-uniformity. HOF provides a set of guidelines for configuration, algorithm development, deployment, interpretation of results and quality control for such pipelines. At each step, we illustrate the HOF approach using the implementation of an automated pipeline for Multimodal Glioma Analysis (MGA) as an example. The MGA pipeline computes tissue diffusion characteristics of diffusion tensor imaging (DTI) acquisitions, hemodynamic characteristics using a perfusion model of susceptibility contrast (DSC) MRI, and spatial cross-modal co-registration of available anatomical, physiological and derived patient images. Developing MGA within HOF enabled the processing of neuro-oncology MR imaging studies to be fully automated. MGA has been successfully used to analyze over 160 clinical tumor studies to date within several research projects. Introduction of the MGA pipeline improved image processing throughput and, most importantly, effectively produced co-registered datasets that were suitable for advanced analysis despite high heterogeneity in acquisition protocols.

Visual analysis of variance: a tool for quantitative assessment of fMRI data processing and analysis.

PubMed

McNamee, R L; Eddy, W F

2001-12-01

Analysis of variance (ANOVA) is widely used for the study of experimental data. Here, the reach of this tool is extended to cover the preprocessing of functional magnetic resonance imaging (fMRI) data. This technique, termed visual ANOVA (VANOVA), provides both numerical and pictorial information to aid the user in understanding the effects of various parts of the data analysis. Unlike a formal ANOVA, this method does not depend on the mathematics of orthogonal projections or strictly additive decompositions. An illustrative example is presented and the application of the method to a large number of fMRI experiments is discussed. Copyright 2001 Wiley-Liss, Inc.

Designing Image Analysis Pipelines in Light Microscopy: A Rational Approach.

PubMed

Arganda-Carreras, Ignacio; Andrey, Philippe

2017-01-01

With the progress of microscopy techniques and the rapidly growing amounts of acquired imaging data, there is an increased need for automated image processing and analysis solutions in biological studies. Each new application requires the design of a specific image analysis pipeline, by assembling a series of image processing operations. Many commercial or free bioimage analysis software are now available and several textbooks and reviews have presented the mathematical and computational fundamentals of image processing and analysis. Tens, if not hundreds, of algorithms and methods have been developed and integrated into image analysis software, resulting in a combinatorial explosion of possible image processing sequences. This paper presents a general guideline methodology to rationally address the design of image processing and analysis pipelines. The originality of the proposed approach is to follow an iterative, backwards procedure from the target objectives of analysis. The proposed goal-oriented strategy should help biologists to better apprehend image analysis in the context of their research and should allow them to efficiently interact with image processing specialists.

Comparison of fMRI data from passive listening and active-response story processing tasks in children

PubMed Central

Vannest, Jennifer J.; Karunanayaka, Prasanna R.; Altaye, Mekibib; Schmithorst, Vincent J.; Plante, Elena M.; Eaton, Kenneth J.; Rasmussen, Jerod M.; Holland, Scott K.

2009-01-01

Purpose To use functional MRI methods to visualize a network of auditory and language-processing brain regions associated with processing an aurally-presented story. We compare a passive listening (PL) story paradigm to an active-response (AR) version including on-line performance monitoring and a sparse acquisition technique. Materials/Methods Twenty children (ages 11−13) completed PL and AR story processing tasks. The PL version presented alternating 30-second blocks of stories and tones; the AR version presented story segments, comprehension questions, and 5s tone sequences, with fMRI acquisitions between stimuli. fMRI data was analyzed using a general linear model approach and paired t-test identifying significant group activation. Results Both tasks activated in primary auditory cortex, superior temporal gyrus bilaterally, left inferior frontal gyrus. The AR task demonstrated more extensive activation, including dorsolateral prefrontal cortex and anterior/posterior cingulate cortex. Comparison of effect size in each paradigm showed a larger effect for the AR paradigm in a left inferior frontal ROI. Conclusion Activation patterns for story processing in children are similar in passive listening and active-response tasks. Increases in extent and magnitude of activation in the AR task are likely associated with memory and attention resources engaged across acquisition intervals. PMID:19306445

Update on the SDSS-III MARVELS data pipeline development

NASA Astrophysics Data System (ADS)

Li, Rui; Ge, J.; Thomas, N. B.; Petersen, E.; Wang, J.; Ma, B.; Sithajan, S.; Shi, J.; Ouyang, Y.; Chen, Y.

2014-01-01

MARVELS (Multi-object APO Radial Velocity Exoplanet Large-area Survey), as one of the four surveys in the SDSS-III program, has monitored over 3,300 stars during 2008-2012, with each being visited an average of 26 times over a 2-year window. Although the early data pipeline was able to detect over 20 brown dwarf candidates and several hundreds of binaries, no giant planet candidates have been reliably identified due to its large systematic errors. Learning from past data pipeline lessons, we re-designed the entire pipeline to handle various types of systematic effects caused by the instrument (such as trace, slant, distortion, drifts and dispersion) and observation condition changes (such as illumination profile and continuum). We also introduced several advanced methods to precisely extract the RV signals. To date, we have achieved a long term RMS RV measurement error of 14 m/s for HIP-14810 (one of our reference stars) after removal of the known planet signal based on previous HIRES RV measurement. This new 1-D data pipeline has been used to robustly identify four giant planet candidates within the small fraction of the survey data that has been processed (Thomas et al. this meeting). The team is currently working hard to optimize the pipeline, especially the 2-D interference-fringe RV extraction, where early results show a 1.5 times improvement over the 1-D data pipeline. We are quickly approaching the survey baseline performance requirement of 10-35 m/s RMS for 8-12 solar type stars. With this fine-tuned pipeline and the soon to be processed plates of data, we expect to discover many more giant planet candidates and make a large statistical impact to the exoplanet study.

Image processing pipeline for synchrotron-radiation-based tomographic microscopy.

PubMed

Hintermüller, C; Marone, F; Isenegger, A; Stampanoni, M

2010-07-01

With synchrotron-radiation-based tomographic microscopy, three-dimensional structures down to the micrometer level can be visualized. Tomographic data sets typically consist of 1000 to 1500 projections of 1024 x 1024 to 2048 x 2048 pixels and are acquired in 5-15 min. A processing pipeline has been developed to handle this large amount of data efficiently and to reconstruct the tomographic volume within a few minutes after the end of a scan. Just a few seconds after the raw data have been acquired, a selection of reconstructed slices is accessible through a web interface for preview and to fine tune the reconstruction parameters. The same interface allows initiation and control of the reconstruction process on the computer cluster. By integrating all programs and tools, required for tomographic reconstruction into the pipeline, the necessary user interaction is reduced to a minimum. The modularity of the pipeline allows functionality for new scan protocols to be added, such as an extended field of view, or new physical signals such as phase-contrast or dark-field imaging etc.

The Role of Age of Acquisition on Past Tense Generation in Spanish-English Bilinguals: An fMRI Study

ERIC Educational Resources Information Center

Waldron, Eric J.; Hernandez, Arturo E.

2013-01-01

At its most basic sense, the sensorimotor/emergentist (S/E) model suggests that early second language (L2) learning is preferentially reliant upon sensory and motor processes, while later L2 learning is accomplished by greater reliance on executive abilities. To investigate the S/E model using fMRI, neural correlates of L2 age of acquisition were…

Reward circuitry in resilience to severe trauma: An fMRI investigation of resilient special forces soldiers

PubMed Central

Vythilingam, Meena; Nelson, Eric E.; Scaramozza, Matthew; Waldeck, Tracy; Hazlett, Gary; Southwick, Steven M.; Pine, Daniel S.; Drevets, Wayne; Charney, Dennis S.; Ernst, Monique

2008-01-01

Enhanced brain reward function could contribute to resilience to trauma. Reward circuitry in active duty, resilient special forces (SF) soldiers was evaluated using fMRI during a monetary incentive delay task. Findings in this group of resilient individuals revealed unique patterns of activation during expectation of reward in the subgenual prefrontal cortex and nucleus accumbens area; regions pivotal to reward processes. PMID:19243926

Supply Support of Air Force 463L Equipment: An Analysis of the 463L equipment Spare Parts Pipeline

DTIC Science & Technology

1989-09-01

service; and 4) the order processing system created inherent delays in the pipeline because of outdated and indirect information systems and technology. Keywords: Materials handling equipment, Theses. (AW)

Extraction of UMLS® Concepts Using Apache cTAKES™ for German Language.

PubMed

Becker, Matthias; Böckmann, Britta

2016-01-01

Automatic information extraction of medical concepts and classification with semantic standards from medical reports is useful for standardization and for clinical research. This paper presents an approach for an UMLS concept extraction with a customized natural language processing pipeline for German clinical notes using Apache cTAKES. The objectives are, to test the natural language processing tool for German language if it is suitable to identify UMLS concepts and map these with SNOMED-CT. The German UMLS database and German OpenNLP models extended the natural language processing pipeline, so the pipeline can normalize to domain ontologies such as SNOMED-CT using the German concepts. For testing, the ShARe/CLEF eHealth 2013 training dataset translated into German was used. The implemented algorithms are tested with a set of 199 German reports, obtaining a result of average 0.36 F1 measure without German stemming, pre- and post-processing of the reports.

Kepler: A Search for Terrestrial Planets - SOC 9.3 DR25 Pipeline Parameter Configuration Reports

NASA Technical Reports Server (NTRS)

Campbell, Jennifer R.

2017-01-01

This document describes the manner in which the pipeline and algorithm parameters for the Kepler Science Operations Center (SOC) science data processing pipeline were managed. This document is intended for scientists and software developers who wish to better understand the software design for the final Kepler codebase (SOC 9.3) and the effect of the software parameters on the Data Release (DR) 25 archival products.

Pipeline transport and simultaneous saccharification of corn stover.

PubMed

Kumar, Amit; Cameron, Jay B; Flynn, Peter C

2005-05-01

Pipeline transport of corn stover delivered by truck from the field is evaluated against a range of truck transport costs. Corn stover transported by pipeline at 20% solids concentration (wet basis) or higher could directly enter an ethanol fermentation plant, and hence the investment in the pipeline inlet end processing facilities displaces comparable investment in the plant. At 20% solids, pipeline transport of corn stover costs less than trucking at capacities in excess of 1.4 M drytonnes/yr when compared to a mid range of truck transport cost (excluding any credit for economies of scale achieved in the ethanol fermentation plant from larger scale due to multiple pipelines). Pipelining of corn stover gives the opportunity to conduct simultaneous transport and saccharification (STS). If current enzymes are used, this would require elevated temperature. Heating of the slurry for STS, which in a fermentation plant is achieved from waste heat, is a significant cost element (more than 5 cents/l of ethanol) if done at the pipeline inlet unless waste heat is available, for example from an electric power plant located adjacent to the pipeline inlet. Heat loss in a 1.26 m pipeline carrying 2 M drytonnes/yr is about 5 degrees C at a distance of 400 km in typical prairie clay soils, and would not likely require insulation; smaller pipelines or different soil conditions might require insulation for STS. Saccharification in the pipeline would reduce the need for investment in the fermentation plant, saving about 0.2 cents/l of ethanol. Transport of corn stover in multiple pipelines offers the opportunity to develop a large ethanol fermentation plant, avoiding some of the diseconomies of scale that arise from smaller plants whose capacities are limited by issues of truck congestion.

High density event-related potential data acquisition in cognitive neuroscience.

PubMed

Slotnick, Scott D

2010-04-16

Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.

Nonlinear Complexity Analysis of Brain fMRI Signals in Schizophrenia

PubMed Central

Sokunbi, Moses O.; Gradin, Victoria B.; Waiter, Gordon D.; Cameron, George G.; Ahearn, Trevor S.; Murray, Alison D.; Steele, Douglas J.; Staff, Roger T.

2014-01-01

We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H). 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems. PMID:24824731

49 CFR 192.937 - What is a continual process of evaluation and assessment to maintain a pipeline's integrity?

Code of Federal Regulations, 2012 CFR

2012-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.937 What is a..., or stress corrosion cracking. An operator must conduct the direct assessment in accordance with the...

49 CFR 192.937 - What is a continual process of evaluation and assessment to maintain a pipeline's integrity?

Code of Federal Regulations, 2011 CFR

2011-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.937 What is a..., or stress corrosion cracking. An operator must conduct the direct assessment in accordance with the...

49 CFR 192.937 - What is a continual process of evaluation and assessment to maintain a pipeline's integrity?

Code of Federal Regulations, 2013 CFR

2013-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.937 What is a..., or stress corrosion cracking. An operator must conduct the direct assessment in accordance with the...

49 CFR 192.937 - What is a continual process of evaluation and assessment to maintain a pipeline's integrity?

Code of Federal Regulations, 2014 CFR

2014-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.937 What is a..., or stress corrosion cracking. An operator must conduct the direct assessment in accordance with the...

Providing Situational Awareness for Pipeline Control Operations

NASA Astrophysics Data System (ADS)

Butts, Jonathan; Kleinhans, Hugo; Chandia, Rodrigo; Papa, Mauricio; Shenoi, Sujeet

A SCADA system for a single 3,000-mile-long strand of oil or gas pipeline may employ several thousand field devices to measure process parameters and operate equipment. Because of the vital tasks performed by these sensors and actuators, pipeline operators need accurate and timely information about their status and integrity. This paper describes a realtime scanner that provides situational awareness about SCADA devices and control operations. The scanner, with the assistance of lightweight, distributed sensors, analyzes SCADA network traffic, verifies the operational status and integrity of field devices, and identifies anomalous activity. Experimental results obtained using real pipeline control traffic demonstrate the utility of the scanner in industrial settings.

fMRI responses to pictures of mutilation and contamination.

PubMed

Schienle, Anne; Schäfer, Axel; Hermann, Andrea; Walter, Bertram; Stark, Rudolf; Vaitl, Dieter

2006-01-30

Findings from several functional magnetic resonance imaging (fMRI) studies implicate the existence of a distinct neural disgust substrate, whereas others support the idea of distributed and integrative brain systems involved in emotional processing. In the present fMRI experiment 12 healthy females viewed pictures from four emotion categories. Two categories were disgust-relevant and depicted contamination or mutilation. The other scenes showed attacks (fear) or were affectively neutral. The two types of disgust elicitors received comparable ratings for disgust, fear and arousal. Both were associated with activation of the occipitotemporal cortex, the amygdala, and the orbitofrontal cortex; insula activity was nonsignificant in the two disgust conditions. Mutilation scenes induced greater inferior parietal activity than contamination scenes, which might mirror their greater capacity to capture attention. Our results are in disagreement with the idea of selective disgust processing at the insula. They point to a network of brain regions involved in the decoding of stimulus salience and the regulation of attention.

A method to classify schizophrenia using inter-task spatial correlations of functional brain images.

PubMed

Michael, Andrew M; Calhoun, Vince D; Andreasen, Nancy C; Baum, Stefi A

2008-01-01

The clinical heterogeneity of schizophrenia (scz) and the overlap of self reported and observed symptoms with other mental disorders makes its diagnosis a difficult task. At present no laboratory-based or image-based diagnostic tool for scz exists and such tools are desired to support existing methods for more precise diagnosis. Functional magnetic resonance imaging (fMRI) is currently employed to identify and correlate cognitive processes related to scz and its symptoms. Fusion of multiple fMRI tasks that probe different cognitive processes may help to better understand hidden networks of this complex disorder. In this paper we utilize three different fMRI tasks and introduce an approach to classify subjects based on inter-task spatial correlations of brain activation. The technique was applied to groups of patients and controls and its validity was checked with the leave-one-out method. We show that the classification rate increases when information from multiple tasks are combined.

Decoupling function and anatomy in atlases of functional connectivity patterns: language mapping in tumor patients.

PubMed

Langs, Georg; Sweet, Andrew; Lashkari, Danial; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J; Golland, Polina

2014-12-01

In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors. Copyright © 2014. Published by Elsevier Inc.

From sequencer to supercomputer: an automatic pipeline for managing and processing next generation sequencing data.

PubMed

Camerlengo, Terry; Ozer, Hatice Gulcin; Onti-Srinivasan, Raghuram; Yan, Pearlly; Huang, Tim; Parvin, Jeffrey; Huang, Kun

2012-01-01

Next Generation Sequencing is highly resource intensive. NGS Tasks related to data processing, management and analysis require high-end computing servers or even clusters. Additionally, processing NGS experiments requires suitable storage space and significant manual interaction. At The Ohio State University's Biomedical Informatics Shared Resource, we designed and implemented a scalable architecture to address the challenges associated with the resource intensive nature of NGS secondary analysis built around Illumina Genome Analyzer II sequencers and Illumina's Gerald data processing pipeline. The software infrastructure includes a distributed computing platform consisting of a LIMS called QUEST (http://bisr.osumc.edu), an Automation Server, a computer cluster for processing NGS pipelines, and a network attached storage device expandable up to 40TB. The system has been architected to scale to multiple sequencers without requiring additional computing or labor resources. This platform provides demonstrates how to manage and automate NGS experiments in an institutional or core facility setting.

DKIST visible broadband imager data processing pipeline

NASA Astrophysics Data System (ADS)

Beard, Andrew; Cowan, Bruce; Ferayorni, Andrew

2014-07-01

The Daniel K. Inouye Solar Telescope (DKIST) Data Handling System (DHS) provides the technical framework and building blocks for developing on-summit instrument quality assurance and data reduction pipelines. The DKIST Visible Broadband Imager (VBI) is a first light instrument that alone will create two data streams with a bandwidth of 960 MB/s each. The high data rate and data volume of the VBI require near-real time processing capability for quality assurance and data reduction, and will be performed on-summit using Graphics Processing Unit (GPU) technology. The VBI data processing pipeline (DPP) is the first designed and developed using the DKIST DHS components, and therefore provides insight into the strengths and weaknesses of the framework. In this paper we lay out the design of the VBI DPP, examine how the underlying DKIST DHS components are utilized, and discuss how integration of the DHS framework with GPUs was accomplished. We present our results of the VBI DPP alpha release implementation of the calibration, frame selection reduction, and quality assurance display processing nodes.

Tumor image signatures and habitats: a processing pipeline of multimodality metabolic and physiological images.

PubMed

You, Daekeun; Kim, Michelle M; Aryal, Madhava P; Parmar, Hemant; Piert, Morand; Lawrence, Theodore S; Cao, Yue

2018-01-01

To create tumor "habitats" from the "signatures" discovered from multimodality metabolic and physiological images, we developed a framework of a processing pipeline. The processing pipeline consists of six major steps: (1) creating superpixels as a spatial unit in a tumor volume; (2) forming a data matrix [Formula: see text] containing all multimodality image parameters at superpixels; (3) forming and clustering a covariance or correlation matrix [Formula: see text] of the image parameters to discover major image "signatures;" (4) clustering the superpixels and organizing the parameter order of the [Formula: see text] matrix according to the one found in step 3; (5) creating "habitats" in the image space from the superpixels associated with the "signatures;" and (6) pooling and clustering a matrix consisting of correlation coefficients of each pair of image parameters from all patients to discover subgroup patterns of the tumors. The pipeline was applied to a dataset of multimodality images in glioblastoma (GBM) first, which consisted of 10 image parameters. Three major image "signatures" were identified. The three major "habitats" plus their overlaps were created. To test generalizability of the processing pipeline, a second image dataset from GBM, acquired on the scanners different from the first one, was processed. Also, to demonstrate the clinical association of image-defined "signatures" and "habitats," the patterns of recurrence of the patients were analyzed together with image parameters acquired prechemoradiation therapy. An association of the recurrence patterns with image-defined "signatures" and "habitats" was revealed. These image-defined "signatures" and "habitats" can be used to guide stereotactic tissue biopsy for genetic and mutation status analysis and to analyze for prediction of treatment outcomes, e.g., patterns of failure.

Predicting decisions in human social interactions using real-time fMRI and pattern classification.

PubMed

Hollmann, Maurice; Rieger, Jochem W; Baecke, Sebastian; Lützkendorf, Ralf; Müller, Charles; Adolf, Daniela; Bernarding, Johannes

2011-01-01

Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.

Interpersonal touch suppresses visual processing of aversive stimuli

PubMed Central

Kawamichi, Hiroaki; Kitada, Ryo; Yoshihara, Kazufumi; Takahashi, Haruka K.; Sadato, Norihiro

2015-01-01

Social contact is essential for survival in human society. A previous study demonstrated that interpersonal contact alleviates pain-related distress by suppressing the activity of its underlying neural network. One explanation for this is that attention is shifted from the cause of distress to interpersonal contact. To test this hypothesis, we conducted a functional MRI (fMRI) study wherein eight pairs of close female friends rated the aversiveness of aversive and non-aversive visual stimuli under two conditions: joining hands either with a rubber model (rubber-hand condition) or with a close friend (human-hand condition). Subsequently, participants rated the overall comfortableness of each condition. The rating result after fMRI indicated that participants experienced greater comfortableness during the human-hand compared to the rubber-hand condition, whereas aversiveness ratings during fMRI were comparable across conditions. The fMRI results showed that the two conditions commonly produced aversive-related activation in both sides of the visual cortex (including V1, V2, and V5). An interaction between aversiveness and hand type showed rubber-hand-specific activation for (aversive > non-aversive) in other visual areas (including V1, V2, V3, and V4v). The effect of interpersonal contact on the processing of aversive stimuli was negatively correlated with the increment of attentional focus to aversiveness measured by a pain-catastrophizing scale. These results suggest that interpersonal touch suppresses the processing of aversive visual stimuli in the occipital cortex. This effect covaried with aversiveness-insensitivity, such that aversive-insensitive individuals might require a lesser degree of attentional capture to aversive-stimulus processing. As joining hands did not influence the subjective ratings of aversiveness, interpersonal touch may operate by redirecting excessive attention away from aversive characteristics of the stimuli. PMID:25904856

Selective attention modulates neural substrates of repetition priming and "implicit" visual memory: suppressions and enhancements revealed by FMRI.

PubMed

Vuilleumier, Patrik; Schwartz, Sophie; Duhoux, Stéphanie; Dolan, Raymond J; Driver, Jon

2005-08-01

Attention can enhance processing for relevant information and suppress this for ignored stimuli. However, some residual processing may still arise without attention. Here we presented overlapping outline objects at study, with subjects attending to those in one color but not the other. Attended objects were subsequently recognized on a surprise memory test, whereas there was complete amnesia for ignored items on such direct explicit testing; yet reliable behavioral priming effects were found on indirect testing. Event-related fMRI examined neural responses to previously attended or ignored objects, now shown alone in the same or mirror-reversed orientation as before, intermixed with new items. Repetition-related decreases in fMRI responses for objects previously attended and repeated in the same orientation were found in the right posterior fusiform, lateral occipital, and left inferior frontal cortex. More anterior fusiform regions also showed some repetition decreases for ignored objects, irrespective of orientation. View-specific repetition decreases were found in the striate cortex, particularly for previously attended items. In addition, previously ignored objects produced some fMRI response increases in the bilateral lingual gyri, relative to new objects. Selective attention at exposure can thus produce several distinct long-term effects on processing of stimuli repeated later, with neural response suppression stronger for previously attended objects, and some response enhancement for previously ignored objects, with these effects arising in different brain areas. Although repetition decreases may relate to positive priming phenomena, the repetition increases for ignored objects shown here for the first time might relate to processes that can produce "negative priming" in some behavioral studies. These results reveal quantitative and qualitative differences between neural substrates of long-term repetition effects for attended versus unattended objects.

The neural correlates of self-referential memory encoding and retrieval in schizophrenia.

PubMed

Jimenez, Amy M; Lee, Junghee; Wynn, Jonathan K; Green, Michael F

2018-01-31

Enhanced memory for self-oriented information is known as the self-referential memory (SRM) effect. fMRI studies of the SRM effect have focused almost exclusively on encoding, revealing selective engagement of the medial prefrontal cortex (mPFC) during "self" relative to other processing conditions. Other critical areas for self-processing include ventrolateral prefrontal cortex (vlPFC), temporo-parietal junction (TPJ) and posterior cingulate/precuneus (PCC/PC). Previous behavioral studies show that individuals with schizophrenia fail to benefit from this memory boost. However, the neural correlates of this deficit, at either encoding or retrieval, are unknown. Twenty individuals with schizophrenia and 16 healthy controls completed an event-related fMRI SRM paradigm. During encoding, trait adjectives were judged in terms of structural features ("case" condition), social desirability ("other" condition), or as self-referential ("self" condition). Participants then completed an unexpected recognition test (retrieval phase). We examined BOLD activation during both encoding and retrieval within mPFC, vlPFC, TPJ, and PCC/PC regions-of-interest (ROIs). During encoding, fMRI data indicated both groups had greater activation during the "self" relative to the "other" condition across ROIs. Controls showed this primarily in mPFC whereas patients showed this in PCC/PC. During retrieval, fMRI data indicated controls showed differentiation across ROIs between "self" and "other" conditions, but patients did not. Results suggest regional differences in the neural processing of self-referential information in individuals with schizophrenia, perhaps because representation of the self is not as well established in patients relative to controls. The current study presents novel findings that add to the literature implicating impaired self-oriented processing in schizophrenia. Published by Elsevier Ltd.

Quantifying rapid changes in cardiovascular state with a moving ensemble average.

PubMed

Cieslak, Matthew; Ryan, William S; Babenko, Viktoriya; Erro, Hannah; Rathbun, Zoe M; Meiring, Wendy; Kelsey, Robert M; Blascovich, Jim; Grafton, Scott T

2018-04-01

MEAP, the moving ensemble analysis pipeline, is a new open-source tool designed to perform multisubject preprocessing and analysis of cardiovascular data, including electrocardiogram (ECG), impedance cardiogram (ICG), and continuous blood pressure (BP). In addition to traditional ensemble averaging, MEAP implements a moving ensemble averaging method that allows for the continuous estimation of indices related to cardiovascular state, including cardiac output, preejection period, heart rate variability, and total peripheral resistance, among others. Here, we define the moving ensemble technique mathematically, highlighting its differences from fixed-window ensemble averaging. We describe MEAP's interface and features for signal processing, artifact correction, and cardiovascular-based fMRI analysis. We demonstrate the accuracy of MEAP's novel B point detection algorithm on a large collection of hand-labeled ICG waveforms. As a proof of concept, two subjects completed a series of four physical and cognitive tasks (cold pressor, Valsalva maneuver, video game, random dot kinetogram) on 3 separate days while ECG, ICG, and BP were recorded. Critically, the moving ensemble method reliably captures the rapid cyclical cardiovascular changes related to the baroreflex during the Valsalva maneuver and the classic cold pressor response. Cardiovascular measures were seen to vary considerably within repetitions of the same cognitive task for each individual, suggesting that a carefully designed paradigm could be used to capture fast-acting event-related changes in cardiovascular state. © 2017 Society for Psychophysiological Research.

Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767

Susceptibility-weighted imaging using inter-echo-variance channel combination for improved contrast at 7 tesla.

PubMed

Hosseini, Zahra; Liu, Junmin; Solovey, Igor; Menon, Ravi S; Drangova, Maria

2017-04-01

To implement and optimize a new approach for susceptibility-weighted image (SWI) generation from multi-echo multi-channel image data and compare its performance against optimized traditional SWI pipelines. Five healthy volunteers were imaged at 7 Tesla. The inter-echo-variance (IEV) channel combination, which uses the variance of the local frequency shift at multiple echo times as a weighting factor during channel combination, was used to calculate multi-echo local phase shift maps. Linear phase masks were combined with the magnitude to generate IEV-SWI. The performance of the IEV-SWI pipeline was compared with that of two accepted SWI pipelines-channel combination followed by (i) Homodyne filtering (HPH-SWI) and (ii) unwrapping and high-pass filtering (SVD-SWI). The filtering steps of each pipeline were optimized. Contrast-to-noise ratio was used as the comparison metric. Qualitative assessment of artifact and vessel conspicuity was performed and processing time of pipelines was evaluated. The optimized IEV-SWI pipeline (σ = 7 mm) resulted in continuous vessel visibility throughout the brain. IEV-SWI had significantly higher contrast compared with HPH-SWI and SVD-SWI (P < 0.001, Friedman nonparametric test). Residual background fields and phase wraps in HPH-SWI and SVD-SWI corrupted the vessel signal and/or generated vessel-mimicking artifact. Optimized implementation of the IEV-SWI pipeline processed a six-echo 16-channel dataset in under 10 min. IEV-SWI benefits from channel-by-channel processing of phase data and results in high contrast images with an optimal balance between contrast and background noise removal, thereby presenting evidence of importance of the order in which postprocessing techniques are applied for multi-channel SWI generation. 2 J. Magn. Reson. Imaging 2017;45:1113-1124. © 2016 International Society for Magnetic Resonance in Medicine.

Emotion Processing by ERP Combined with Development and Plasticity.

PubMed

Ding, Rui; Li, Ping; Wang, Wei; Luo, Wenbo

2017-01-01

Emotions important for survival and social interaction have received wide and deep investigations. The application of the fMRI technique into emotion processing has obtained overwhelming achievements with respect to the localization of emotion processes. The ERP method, which possesses highly temporal resolution compared to fMRI, can be employed to investigate the time course of emotion processing. The emotional modulation of the ERP component has been verified across numerous researches. Emotions, described as dynamically developing along with the growing age, have the possibility to be enhanced through learning (or training) or to be damaged due to disturbances in growth, which is underlain by the neural plasticity of emotion-relevant nervous systems. And mood disorders with typical symptoms of emotion discordance probably have been caused by the dysfunctional neural plasticity.

Emotion Processing by ERP Combined with Development and Plasticity

PubMed Central

2017-01-01

Emotions important for survival and social interaction have received wide and deep investigations. The application of the fMRI technique into emotion processing has obtained overwhelming achievements with respect to the localization of emotion processes. The ERP method, which possesses highly temporal resolution compared to fMRI, can be employed to investigate the time course of emotion processing. The emotional modulation of the ERP component has been verified across numerous researches. Emotions, described as dynamically developing along with the growing age, have the possibility to be enhanced through learning (or training) or to be damaged due to disturbances in growth, which is underlain by the neural plasticity of emotion-relevant nervous systems. And mood disorders with typical symptoms of emotion discordance probably have been caused by the dysfunctional neural plasticity. PMID:28831313

Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline*

PubMed Central

Slagel, Joseph; Mendoza, Luis; Shteynberg, David; Deutsch, Eric W.; Moritz, Robert L.

2015-01-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. PMID:25418363

Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.

PubMed

Slagel, Joseph; Mendoza, Luis; Shteynberg, David; Deutsch, Eric W; Moritz, Robert L

2015-02-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Image Registration to Compensate for EPI Distortion in Patients with Brain Tumors: An Evaluation of Tract-Specific Effects.

PubMed

Albi, Angela; Meola, Antonio; Zhang, Fan; Kahali, Pegah; Rigolo, Laura; Tax, Chantal M W; Ciris, Pelin Aksit; Essayed, Walid I; Unadkat, Prashin; Norton, Isaiah; Rathi, Yogesh; Olubiyi, Olutayo; Golby, Alexandra J; O'Donnell, Lauren J

2018-03-01

Diffusion magnetic resonance imaging (dMRI) provides preoperative maps of neurosurgical patients' white matter tracts, but these maps suffer from echo-planar imaging (EPI) distortions caused by magnetic field inhomogeneities. In clinical neurosurgical planning, these distortions are generally not corrected and thus contribute to the uncertainty of fiber tracking. Multiple image processing pipelines have been proposed for image-registration-based EPI distortion correction in healthy subjects. In this article, we perform the first comparison of such pipelines in neurosurgical patient data. Five pipelines were tested in a retrospective clinical dMRI dataset of 9 patients with brain tumors. Pipelines differed in the choice of fixed and moving images and the similarity metric for image registration. Distortions were measured in two important tracts for neurosurgery, the arcuate fasciculus and corticospinal tracts. Significant differences in distortion estimates were found across processing pipelines. The most successful pipeline used dMRI baseline and T2-weighted images as inputs for distortion correction. This pipeline gave the most consistent distortion estimates across image resolutions and brain hemispheres. Quantitative results of mean tract distortions on the order of 1-2 mm are in line with other recent studies, supporting the potential need for distortion correction in neurosurgical planning. Novel results include significantly higher distortion estimates in the tumor hemisphere and greater effect of image resolution choice on results in the tumor hemisphere. Overall, this study demonstrates possible pitfalls and indicates that care should be taken when implementing EPI distortion correction in clinical settings. Copyright © 2018 by the American Society of Neuroimaging.

Determine new design and construction techniques for transportation of ethanol and ethanol/gasoline blends in new pipelines.

DOT National Transportation Integrated Search

2013-02-15

The technical tasks in this study included activities to characterize the impact of selected : metallurgical processing and fabrication variables on ethanol stress corrosion cracking (ethanol : SCC) of new pipeline steels, develop a better understand...

Guidelines for Constructing Natural Gas and Liquid Hydrocarbon Pipelines Through Areas Prone to Landslide and Subsidence Hazards

DOT National Transportation Integrated Search

2009-01-01

These guidelines provide recommendations for the assessment of new and existing natural gas and liquid hydrocarbon pipelines subjected to potential ground displacements resulting from landslides and subsidence. The process of defining landslide and s...

Bio-Docklets: virtualization containers for single-step execution of NGS pipelines.

PubMed

Kim, Baekdoo; Ali, Thahmina; Lijeron, Carlos; Afgan, Enis; Krampis, Konstantinos

2017-08-01

Processing of next-generation sequencing (NGS) data requires significant technical skills, involving installation, configuration, and execution of bioinformatics data pipelines, in addition to specialized postanalysis visualization and data mining software. In order to address some of these challenges, developers have leveraged virtualization containers toward seamless deployment of preconfigured bioinformatics software and pipelines on any computational platform. We present an approach for abstracting the complex data operations of multistep, bioinformatics pipelines for NGS data analysis. As examples, we have deployed 2 pipelines for RNA sequencing and chromatin immunoprecipitation sequencing, preconfigured within Docker virtualization containers we call Bio-Docklets. Each Bio-Docklet exposes a single data input and output endpoint and from a user perspective, running the pipelines as simply as running a single bioinformatics tool. This is achieved using a "meta-script" that automatically starts the Bio-Docklets and controls the pipeline execution through the BioBlend software library and the Galaxy Application Programming Interface. The pipeline output is postprocessed by integration with the Visual Omics Explorer framework, providing interactive data visualizations that users can access through a web browser. Our goal is to enable easy access to NGS data analysis pipelines for nonbioinformatics experts on any computing environment, whether a laboratory workstation, university computer cluster, or a cloud service provider. Beyond end users, the Bio-Docklets also enables developers to programmatically deploy and run a large number of pipeline instances for concurrent analysis of multiple datasets. © The Authors 2017. Published by Oxford University Press.

Bio-Docklets: virtualization containers for single-step execution of NGS pipelines

PubMed Central

Kim, Baekdoo; Ali, Thahmina; Lijeron, Carlos; Afgan, Enis

2017-01-01

Abstract Processing of next-generation sequencing (NGS) data requires significant technical skills, involving installation, configuration, and execution of bioinformatics data pipelines, in addition to specialized postanalysis visualization and data mining software. In order to address some of these challenges, developers have leveraged virtualization containers toward seamless deployment of preconfigured bioinformatics software and pipelines on any computational platform. We present an approach for abstracting the complex data operations of multistep, bioinformatics pipelines for NGS data analysis. As examples, we have deployed 2 pipelines for RNA sequencing and chromatin immunoprecipitation sequencing, preconfigured within Docker virtualization containers we call Bio-Docklets. Each Bio-Docklet exposes a single data input and output endpoint and from a user perspective, running the pipelines as simply as running a single bioinformatics tool. This is achieved using a “meta-script” that automatically starts the Bio-Docklets and controls the pipeline execution through the BioBlend software library and the Galaxy Application Programming Interface. The pipeline output is postprocessed by integration with the Visual Omics Explorer framework, providing interactive data visualizations that users can access through a web browser. Our goal is to enable easy access to NGS data analysis pipelines for nonbioinformatics experts on any computing environment, whether a laboratory workstation, university computer cluster, or a cloud service provider. Beyond end users, the Bio-Docklets also enables developers to programmatically deploy and run a large number of pipeline instances for concurrent analysis of multiple datasets. PMID:28854616

PyEmir: Data Reduction Pipeline for EMIR, the GTC Near-IR Multi-Object Spectrograph

NASA Astrophysics Data System (ADS)

Pascual, S.; Gallego, J.; Cardiel, N.; Eliche-Moral, M. C.

2010-12-01

EMIR is the near-infrared wide-field camera and multi-slit spectrograph being built for Gran Telescopio Canarias. We present here the work being done on its data processing pipeline. PyEmir is based on Python and it will process automatically data taken in both imaging and spectroscopy mode. PyEmir is begin developed by the UCM Group of Extragalactic Astrophysics and Astronomical Instrumentation.

High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms

PubMed Central

Teodoro, George; Pan, Tony; Kurc, Tahsin M.; Kong, Jun; Cooper, Lee A. D.; Podhorszki, Norbert; Klasky, Scott; Saltz, Joel H.

2014-01-01

Analysis of large pathology image datasets offers significant opportunities for the investigation of disease morphology, but the resource requirements of analysis pipelines limit the scale of such studies. Motivated by a brain cancer study, we propose and evaluate a parallel image analysis application pipeline for high throughput computation of large datasets of high resolution pathology tissue images on distributed CPU-GPU platforms. To achieve efficient execution on these hybrid systems, we have built runtime support that allows us to express the cancer image analysis application as a hierarchical data processing pipeline. The application is implemented as a coarse-grain pipeline of stages, where each stage may be further partitioned into another pipeline of fine-grain operations. The fine-grain operations are efficiently managed and scheduled for computation on CPUs and GPUs using performance aware scheduling techniques along with several optimizations, including architecture aware process placement, data locality conscious task assignment, data prefetching, and asynchronous data copy. These optimizations are employed to maximize the utilization of the aggregate computing power of CPUs and GPUs and minimize data copy overheads. Our experimental evaluation shows that the cooperative use of CPUs and GPUs achieves significant improvements on top of GPU-only versions (up to 1.6×) and that the execution of the application as a set of fine-grain operations provides more opportunities for runtime optimizations and attains better performance than coarser-grain, monolithic implementations used in other works. An implementation of the cancer image analysis pipeline using the runtime support was able to process an image dataset consisting of 36,848 4Kx4K-pixel image tiles (about 1.8TB uncompressed) in less than 4 minutes (150 tiles/second) on 100 nodes of a state-of-the-art hybrid cluster system. PMID:25419546

MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.

PubMed

Franceschi, Pietro; Mylonas, Roman; Shahaf, Nir; Scholz, Matthias; Arapitsas, Panagiotis; Masuero, Domenico; Weingart, Georg; Carlin, Silvia; Vrhovsek, Urska; Mattivi, Fulvio; Wehrens, Ron

2014-01-01

Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework.

Failure modes for pipelines in landslide areas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruschi, R.; Spinazze, M.; Tomassini, D.

1995-12-31

In recent years a number of incidences of pipelines affected by slow soil movements have been reported in the relevant literature. Further related issues such as soil-pipe interaction have been studied both theoretically and through experimental surveys, along with the environmental conditions which are responsible for hazard to the pipeline integrity. A suitable design criteria under these circumstances has been discussed by several authors, in particular in relation to a limit state approach and hence a strain based criteria. The scope of this paper is to describe the failure mechanisms which may affect the pipeline in the presence of slowmore » soil movements impacting on the pipeline, both in the longitudinal and transverse direction. Particular attention is paid to environmental, geometric and structural parameters which steer the process towards one or other failure mechanism. Criteria for deciding upon remedial measures required to guarantee the structural integrity of the pipeline, both in the short and in the long term, are discussed.« less

Framework for the Integration of Multi-Instrument Pipelines in the BepiColombo Science Operations Control System

NASA Astrophysics Data System (ADS)

Pérez-López, F.; Vallejo, J. C.; Martínez, S.; Ortiz, I.; Macfarlane, A.; Osuna, P.; Gill, R.; Casale, M.

2015-09-01

BepiColombo is an interdisciplinary ESA mission to explore the planet Mercury in cooperation with JAXA. The mission consists of two separate orbiters: ESA's Mercury Planetary Orbiter (MPO) and JAXA's Mercury Magnetospheric Orbiter (MMO), which are dedicated to the detailed study of the planet and its magnetosphere. The MPO scientific payload comprises eleven instruments packages covering different disciplines developed by several European teams. This paper describes the design and development approach of the framework required to support the operation of the distributed BepiColombo MPO instruments pipelines, developed and operated from different locations, but designed as a single entity. An architecture based on primary-redundant configuration, fully integrated into the BepiColombo Science Operations Control System (BSCS), has been selected, where some instrument pipelines will be operated from the instrument team's data processing centres, having a pipeline replica that can be run from the Science Ground Segment (SGS), while others will be executed as primary pipelines from the SGS, adopting the SGS the pipeline orchestration role.

Effects of propofol anesthesia on the processing of noxious stimuli in the spinal cord and the brain.

PubMed

Lichtner, Gregor; Auksztulewicz, Ryszard; Kirilina, Evgeniya; Velten, Helena; Mavrodis, Dionysios; Scheel, Michael; Blankenburg, Felix; von Dincklage, Falk

2018-05-15

Drug-induced unconsciousness is an essential component of general anesthesia, commonly attributed to attenuation of higher-order processing of external stimuli and a resulting loss of information integration capabilities of the brain. In this study, we investigated how the hypnotic drug propofol at doses comparable to those in clinical practice influences the processing of somatosensory stimuli in the spinal cord and in primary and higher-order cortices. Using nociceptive reflexes, somatosensory evoked potentials and functional magnet resonance imaging (fMRI), we found that propofol abolishes the processing of innocuous and moderate noxious stimuli at low to medium concentration levels, but that intense noxious stimuli evoked spinal and cerebral responses even during deep propofol anesthesia that caused profound electroencephalogram (EEG) burst suppression. While nociceptive reflexes and somatosensory potentials were affected only in a minor way by further increasing doses of propofol after the loss of consciousness, fMRI showed that increasing propofol concentration abolished processing of intense noxious stimuli in the insula and secondary somatosensory cortex and vastly increased processing in the frontal cortex. As the fMRI functional connectivity showed congruent changes with increasing doses of propofol - namely the temporal brain areas decreasing their connectivity with the bilateral pre-/postcentral gyri and the supplementary motor area, while connectivity of the latter with frontal areas is increased - we conclude that the changes in processing of noxious stimuli during propofol anesthesia might be related to changes in functional connectivity. Copyright © 2018 Elsevier Inc. All rights reserved.

Hemispheric differences in processing the literal interpretation of idioms: converging evidence from behavioral and fMRI studies.

PubMed

Mashal, Nira; Faust, Miriam; Hendler, Talma; Jung-Beeman, Mark

2008-01-01

The present study examined the role of the left (LH) and right (RH) cerebral hemispheres in processing alternative meanings of idiomatic sentences. We conducted two experiments using ambiguous idioms with plausible literal interpretations as stimuli. In the first experiment we tested hemispheric differences in accessing either the literal or the idiomatic meaning of idioms for targets presented to either the left or the right visual field. In the second experiment, we used functional magnetic resonance imaging (fMRI) to define regional brain activation patterns in healthy adults processing either the idiomatic meaning of idioms or the literal meanings of either idioms or literal sentences. According to the Graded Salience Hypothesis (GSH, Giora, 2003), a selective RH involvement in the processing of nonsalient meanings, such as literal interpretations of idiomatic expressions, was expected. Results of the two experiments were consistent with the GSH predictions and show that literal interpretations of idioms are accessed faster than their idiomatic meanings in the RH. The fMRI data showed that processing the idiomatic interpretation of idioms and the literal interpretations of literal sentences involved LH regions whereas processing the literal interpretation of idioms was associated with increased activity in right brain regions including the right precuneus, right middle frontal gyrus (MFG), right posterior middle temporal gyrus (MTG), and right anterior superior temporal gyrus (STG). We suggest that these RH areas are involved in semantic ambiguity resolution and in processing nonsalient meanings of conventional idiomatic expressions.

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection.

PubMed

Power, Jonathan D; Plitt, Mark; Kundu, Prantik; Bandettini, Peter A; Martin, Alex

2017-01-01

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10-50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion).

Amygdala abnormalities in first-degree relatives of individuals with schizophrenia unmasked by benzodiazepine challenge

PubMed Central

Wolf, Daniel H.; Satterthwaite, Theodore D.; Loughead, James; Pinkham, Amy; Overton, Eve; Elliott, Mark A.; Dent, Gersham W.; Smith, Mark A.; Gur, Ruben C.; Gur, Raquel E.

2014-01-01

Rationale Impaired emotion processing in schizophrenia predicts broader social dysfunction and has been related to negative symptom severity and amygdala dysfunction. Pharmacological modulation of emotion-processing deficits and related neural abnormalities may provide useful phenotypes for pathophysiological investigation. Objectives We used an acute benzodiazepine challenge to identify and modulate potential emotion-processing abnormalities in 20 unaffected first-degree relatives of individuals with schizophrenia, compared to 25 control subjects without a family history of psychosis. Methods An oral 1mg dose of the short-acting anxiolytic benzodiazepine alprazolam was administered in a balanced crossover placebo-controlled double-blind design, preceding identical 3T fMRI sessions approximately 1 week apart. Primary outcomes included fMRI activity in amygdala and related regions during two facial emotion-processing tasks: emotion identification and emotion memory. Results Family members exhibited abnormally strong alprazolam-induced reduction in amygdala and hippocampus activation during emotion identification, compared to equal reduction in both groups for the emotion memory task. Conclusions GABAergic modulation with alprazolam produced differential responses in family members vs. controls, perhaps by unmasking underlying amygdalar and/or GABAergic abnormalities. Such pharmacological fMRI paradigms could prove useful for developing drugs targeting specific neural circuits to treat or prevent schizophrenia. PMID:21603892

Direction of Amygdala-Neocortex Interaction During Dynamic Facial Expression Processing.

PubMed

Sato, Wataru; Kochiyama, Takanori; Uono, Shota; Yoshikawa, Sakiko; Toichi, Motomi

2017-03-01

Dynamic facial expressions of emotion strongly elicit multifaceted emotional, perceptual, cognitive, and motor responses. Neuroimaging studies revealed that some subcortical (e.g., amygdala) and neocortical (e.g., superior temporal sulcus and inferior frontal gyrus) brain regions and their functional interaction were involved in processing dynamic facial expressions. However, the direction of the functional interaction between the amygdala and the neocortex remains unknown. To investigate this issue, we re-analyzed functional magnetic resonance imaging (fMRI) data from 2 studies and magnetoencephalography (MEG) data from 1 study. First, a psychophysiological interaction analysis of the fMRI data confirmed the functional interaction between the amygdala and neocortical regions. Then, dynamic causal modeling analysis was used to compare models with forward, backward, or bidirectional effective connectivity between the amygdala and neocortical networks in the fMRI and MEG data. The results consistently supported the model of effective connectivity from the amygdala to the neocortex. Further increasing time-window analysis of the MEG demonstrated that this model was valid after 200 ms from the stimulus onset. These data suggest that emotional processing in the amygdala rapidly modulates some neocortical processing, such as perception, recognition, and motor mimicry, when observing dynamic facial expressions of emotion. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection

PubMed Central

Plitt, Mark; Kundu, Prantik; Bandettini, Peter A.; Martin, Alex

2017-01-01

Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10–50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion). PMID:28880888

Differentiating maturational and training influences on fMRI activation during music processing.

PubMed

Ellis, Robert J; Norton, Andrea C; Overy, Katie; Winner, Ellen; Alsop, David C; Schlaug, Gottfried

2012-04-15

Two major influences on how the brain processes music are maturational development and active musical training. Previous functional neuroimaging studies investigating music processing have typically focused on either categorical differences between "musicians versus nonmusicians" or "children versus adults." In the present study, we explored a cross-sectional data set (n=84) using multiple linear regression to isolate the performance-independent effects of age (5 to 33 years) and cumulative duration of musical training (0 to 21,000 practice hours) on fMRI activation similarities and differences between melodic discrimination (MD) and rhythmic discrimination (RD). Age-related effects common to MD and RD were present in three left hemisphere regions: temporofrontal junction, ventral premotor cortex, and the inferior part of the intraparietal sulcus, regions involved in active attending to auditory rhythms, sensorimotor integration, and working memory transformations of pitch and rhythmic patterns. By contrast, training-related effects common to MD and RD were localized to the posterior portion of the left superior temporal gyrus/planum temporale, an area implicated in spectrotemporal pattern matching and auditory-motor coordinate transformations. A single cluster in right superior temporal gyrus showed significantly greater activation during MD than RD. This is the first fMRI which has distinguished maturational from training effects during music processing. Copyright © 2012 Elsevier Inc. All rights reserved.

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Electrodermal Recording and fMRI to Inform Sensorimotor Recovery in Stroke Patients

PubMed Central

MacIntosh, Bradley J.; McIlroy, William E.; Mraz, Richard; Staines, W. Richard; Black, Sandra E.; Graham, Simon J.

2016-01-01

Background Functional magnetic resonance imaging (fMRI) appears to be useful for investigating motor recovery after stroke. Some of the potential confounders of brain activation studies, however, could be mitigated through complementary physiological monitoring. Objective To investigate a sensorimotor fMRI battery that included simultaneous measurement of electrodermal activity in subjects with hemiparetic stroke to provide a measure related to the sense of effort during motor performance. Methods Bilateral hand and ankle tasks were performed by 6 patients with stroke (2 subacute, 4 chronic) during imaging with blood oxygen level-dependent (BOLD) fMRI using an event-related design. BOLD percent changes, peak activation, and laterality index values were calculated in the sensorimotor cortex. Electrodermal recordings were made concurrently and used as a regressor. Results Sensorimotor BOLD time series and percent change values provided evidence of an intact motor network in each of these well-recovered patients. During tasks involving the hemiparetic limb, electrodermal activity changes were variable in amplitude, and electrodermal activity time-series data showed significant correlations with fMRI in 3 of 6 patients. No such correlations were observed for control tasks involving the unaffected lower limb. Conclusions Electrodermal activity activation maps implicated the contralesional over the ipsilesional hemisphere, supporting the notion that stroke patients may require higher order motor processing to perform simple tasks. Electrodermal activity recordings may be useful as a physiological marker of differences in effort required during movements of a subject’s hemiparetic compared with the unaffected limb during fMRI studies. PMID:18784267

Tensorial extensions of independent component analysis for multisubject FMRI analysis.

PubMed

Beckmann, C F; Smith, S M

2005-03-01

We discuss model-free analysis of multisubject or multisession FMRI data by extending the single-session probabilistic independent component analysis model (PICA; Beckmann and Smith, 2004. IEEE Trans. on Medical Imaging, 23 (2) 137-152) to higher dimensions. This results in a three-way decomposition that represents the different signals and artefacts present in the data in terms of their temporal, spatial, and subject-dependent variations. The technique is derived from and compared with parallel factor analysis (PARAFAC; Harshman and Lundy, 1984. In Research methods for multimode data analysis, chapter 5, pages 122-215. Praeger, New York). Using simulated data as well as data from multisession and multisubject FMRI studies we demonstrate that the tensor PICA approach is able to efficiently and accurately extract signals of interest in the spatial, temporal, and subject/session domain. The final decompositions improve upon PARAFAC results in terms of greater accuracy, reduced interference between the different estimated sources (reduced cross-talk), robustness (against deviations of the data from modeling assumptions and against overfitting), and computational speed. On real FMRI 'activation' data, the tensor PICA approach is able to extract plausible activation maps, time courses, and session/subject modes as well as provide a rich description of additional processes of interest such as image artefacts or secondary activation patterns. The resulting data decomposition gives simple and useful representations of multisubject/multisession FMRI data that can aid the interpretation and optimization of group FMRI studies beyond what can be achieved using model-based analysis techniques.

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks

PubMed Central

Jang, Hojin; Plis, Sergey M.; Calhoun, Vince D.; Lee, Jong-Hwan

2016-01-01

Feedforward deep neural networks (DNN), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean ± standard deviation; %) of 6.9 (± 3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4 ± 4.6) and the two-layer network (7.4 ± 4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the extraction of hidden representations of fMRI volumes associated with tasks across multiple hidden layers. Our study may be beneficial to the automatic classification/diagnosis of neuropsychiatric and neurological diseases and prediction of disease severity and recovery in (pre-) clinical settings using fMRI volumes without requiring an estimation of activation patterns or ad hoc statistical evaluation. PMID:27079534

How restful is it with all that noise? Comparison of Interleaved silent steady state (ISSS) and conventional imaging in resting-state fMRI.

PubMed

Andoh, J; Ferreira, M; Leppert, I R; Matsushita, R; Pike, B; Zatorre, R J

2017-02-15

Resting-state fMRI studies have become very important in cognitive neuroscience because they are able to identify BOLD fluctuations in brain circuits involved in motor, cognitive, or perceptual processes without the use of an explicit task. Such approaches have been fruitful when applied to various disordered populations, or to children or the elderly. However, insufficient attention has been paid to the consequences of the loud acoustic scanner noise associated with conventional fMRI acquisition, which could be an important confounding factor affecting auditory and/or cognitive networks in resting-state fMRI. Several approaches have been developed to mitigate the effects of acoustic noise on fMRI signals, including sparse sampling protocols and interleaved silent steady state (ISSS) acquisition methods, the latter being used only for task-based fMRI. Here, we developed an ISSS protocol for resting-state fMRI (rs-ISSS) consisting of rapid acquisition of a set of echo planar imaging volumes following each silent period, during which the steady state longitudinal magnetization was maintained with a train of relatively silent slice-selective excitation pulses. We evaluated the test-retest reliability of intensity and spatial extent of connectivity networks of fMRI BOLD signal across three different days for rs-ISSS and compared it with a standard resting-state fMRI (rs-STD). We also compared the strength and distribution of connectivity networks between rs-ISSS and rs-STD. We found that both rs-ISSS and rs-STD showed high reproducibility of fMRI signal across days. In addition, rs-ISSS showed a more robust pattern of functional connectivity within the somatosensory and motor networks, as well as an auditory network compared with rs-STD. An increased connectivity between the default mode network and the language network and with the anterior cingulate cortex (ACC) network was also found for rs-ISSS compared with rs-STD. Finally, region of interest analysis showed higher interhemispheric connectivity in Heschl's gyri in rs-ISSS compared with rs-STD, with lower variability across days. The present findings suggest that rs-ISSS may be advantageous for detecting network connectivity in a less noisy environment, and that resting-state studies carried out with standard scanning protocols should consider the potential effects of loud noise on the measured networks. Copyright © 2017 Elsevier Inc. All rights reserved.

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.

PubMed

Jang, Hojin; Plis, Sergey M; Calhoun, Vince D; Lee, Jong-Hwan

2017-01-15

Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean±standard deviation; %) of 6.9 (±3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4±4.6) and the two-layer network (7.4±4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the extraction of hidden representations of fMRI volumes associated with tasks across multiple hidden layers. Our study may be beneficial to the automatic classification/diagnosis of neuropsychiatric and neurological diseases and prediction of disease severity and recovery in (pre-) clinical settings using fMRI volumes without requiring an estimation of activation patterns or ad hoc statistical evaluation. Copyright © 2016 Elsevier Inc. All rights reserved.

A Role of DLPFC in the Learning Process of Human Mate Copying

PubMed Central

Zhuang, Jin-Ying; Xie, Jiajia; Hu, Die; Fan, Mingxia; Zheng, Li

2016-01-01

In the current study, we conducted a behavioral experiment to test the mate coping effect and a functional magnetic resonance imaging (fMRI) experiment to test the neural basis involved in the social learning process of mate copying. In the behavioral experiment, participants were asked to rate the attractiveness of isolated opposite-sex (potential mates) facial photographs, then shown the targets associating with a neutral-faced model with textual cues indicating the models’ attitude (interested vs. not-interested) toward the potential mates, and then asked to re-evaluate the potential mates’ attractiveness. Using a similar procedure as the behavioral experiment, participants were scanned while observing the compound images in the fMRI experiment. The mate copying effect was confirmed in the behavioral experiment –greater increase in attractiveness ratings was observed for opposite-sex photographs in the interested than in the not-interested condition. The fMRI results showed that the dorsolateral prefrontal gyrus (DLPFC) was significantly active in the comparison of interested > not-interested condition, suggesting that a cognitive integration and selection function may be involved when participants process information from conditions related to mate copying. PMID:27148151

The supplementary motor area in motor and perceptual time processing: fMRI studies.

PubMed

Macar, Françoise; Coull, Jennifer; Vidal, Franck

2006-06-01

The neural bases of timing mechanisms in the second-to-minute range are currently investigated using multidisciplinary approaches. This paper documents the involvement of the supplementary motor area (SMA) in the encoding of target durations by reporting convergent fMRI data from motor and perceptual timing tasks. Event-related fMRI was used in two temporal procedures, involving (1) the production of an accurate interval as compared to an accurate force, and (2) a dual-task of time and colour discrimination with parametric manipulation of the level of attention attributed to each parameter. The first study revealed greater activation of the SMA proper in skilful control of time compared to force. The second showed that increasing attentional allocation to time increased activity in a cortico-striatal network including the pre-SMA (in contrast with the occipital cortex for increasing attention to colour). Further, the SMA proper was sensitive to the attentional modulation cued prior to the time processing period. Taken together, these data and related literature suggest that the SMA plays a key role in time processing as part of the striato-cortical pathway previously identified by animal studies, human neuropsychology and neuroimaging.

Demonstrating the Effects of Shop Flow Process Variability on the Air Force Depot Level Reparable Item Pipeline

DTIC Science & Technology

1992-09-01

Crawford found that pipeline contents are extremely variable about their mean (10:24) and Kettner and Wheatley said that "a statistical analysis of data...write the results from this replication "* to the ANOVA files for later analysis . The first set outputs points "* for overall pipeline contents . The...families and friends for their unselfishness and support. Marvin A. Arostegui and Jon A. Larvick ii Table of Contents Page Preface

Study on Failure of Third-Party Damage for Urban Gas Pipeline Based on Fuzzy Comprehensive Evaluation

PubMed Central

Li, Jun; Zhang, Hong; Han, Yinshan; Wang, Baodong

2016-01-01

Focusing on the diversity, complexity and uncertainty of the third-party damage accident, the failure probability of third-party damage to urban gas pipeline was evaluated on the theory of analytic hierarchy process and fuzzy mathematics. The fault tree of third-party damage containing 56 basic events was built by hazard identification of third-party damage. The fuzzy evaluation of basic event probabilities were conducted by the expert judgment method and using membership function of fuzzy set. The determination of the weight of each expert and the modification of the evaluation opinions were accomplished using the improved analytic hierarchy process, and the failure possibility of the third-party to urban gas pipeline was calculated. Taking gas pipelines of a certain large provincial capital city as an example, the risk assessment structure of the method was proved to conform to the actual situation, which provides the basis for the safety risk prevention. PMID:27875545

On application of kernel PCA for generating stimulus features for fMRI during continuous music listening.

PubMed

Tsatsishvili, Valeri; Burunat, Iballa; Cong, Fengyu; Toiviainen, Petri; Alluri, Vinoo; Ristaniemi, Tapani

2018-06-01

There has been growing interest towards naturalistic neuroimaging experiments, which deepen our understanding of how human brain processes and integrates incoming streams of multifaceted sensory information, as commonly occurs in real world. Music is a good example of such complex continuous phenomenon. In a few recent fMRI studies examining neural correlates of music in continuous listening settings, multiple perceptual attributes of music stimulus were represented by a set of high-level features, produced as the linear combination of the acoustic descriptors computationally extracted from the stimulus audio. NEW METHOD: fMRI data from naturalistic music listening experiment were employed here. Kernel principal component analysis (KPCA) was applied to acoustic descriptors extracted from the stimulus audio to generate a set of nonlinear stimulus features. Subsequently, perceptual and neural correlates of the generated high-level features were examined. The generated features captured musical percepts that were hidden from the linear PCA features, namely Rhythmic Complexity and Event Synchronicity. Neural correlates of the new features revealed activations associated to processing of complex rhythms, including auditory, motor, and frontal areas. Results were compared with the findings in the previously published study, which analyzed the same fMRI data but applied linear PCA for generating stimulus features. To enable comparison of the results, methodology for finding stimulus-driven functional maps was adopted from the previous study. Exploiting nonlinear relationships among acoustic descriptors can lead to the novel high-level stimulus features, which can in turn reveal new brain structures involved in music processing. Copyright © 2018 Elsevier B.V. All rights reserved.

Aging affects the interaction between attentional control and source memory: an fMRI study.

PubMed

Dulas, Michael R; Duarte, Audrey

2014-12-01

Age-related source memory impairments may be due, at least in part, to deficits in executive processes mediated by the PFC at both study and test. Behavioral work suggests that providing environmental support at encoding, such as directing attention toward item-source associations, may improve source memory and reduce age-related deficits in the recruitment of these executive processes. The present fMRI study investigated the effects of directed attention and aging on source memory encoding and retrieval. At study, participants were shown pictures of objects. They were either asked to attend to the objects and their color (source) or to their size. At test, participants determined if objects were seen before, and if so, whether they were the same color as previously. Behavioral results showed that direction of attention improved source memory for both groups; however, age-related deficits persisted. fMRI results revealed that, across groups, direction of attention facilitated medial temporal lobe-mediated contextual binding processes during study and attenuated right PFC postretrieval monitoring effects at test. However, persistent age-related source memory deficits may be related to increased recruitment of medial anterior PFC during encoding, indicative of self-referential processing, as well as underrecruitment of lateral anterior PFC-mediated relational processes. Taken together, this study suggests that, even when supported, older adults may fail to selectively encode goal-relevant contextual details supporting source memory performance.

High-caloric and chocolate stimuli processing in healthy humans: an integration of functional imaging and electrophysiological findings.

PubMed

Asmaro, Deyar; Liotti, Mario

2014-01-10

There has been a great deal of interest in understanding how the human brain processes appetitive food cues, and knowing how such cues elicit craving responses is particularly relevant when current eating behavior trends within Westernized societies are considered. One substance that holds a special place with regard to food preference is chocolate, and studies that used functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) have identified neural regions and electrical signatures that are elicited by chocolate cue presentations. This review will examine fMRI and ERP findings from studies that used high-caloric food and chocolate cues as stimuli, with a focus on responses observed in samples of healthy participants, as opposed to those with eating-related pathology. The utility of using high-caloric and chocolate stimuli as a means of understanding the human reward system will also be highlighted, as these findings may be particularly important for understanding processes related to pathological overeating and addiction to illicit substances. Finally, research from our own lab that focused on chocolate stimulus processing in chocolate cravers and non-cravers will be discussed, as the approach used may help bridge fMRI and ERP findings so that a more complete understanding of appetitive stimulus processing in the temporal and spatial domains may be established.

Processing emotional words in two languages with one brain: ERP and fMRI evidence from Chinese-English bilinguals.

PubMed

Chen, Peiyao; Lin, Jie; Chen, Bingle; Lu, Chunming; Guo, Taomei

2015-10-01

Emotional words in a bilingual's second language (L2) seem to have less emotional impact compared to emotional words in the first language (L1). The present study examined the neural mechanisms of emotional word processing in Chinese-English bilinguals' two languages by using both event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI). Behavioral results show a robust positive word processing advantage in L1 such that responses to positive words were faster and more accurate compared to responses to neutral words and negative words. In L2, emotional words only received higher accuracies than neutral words. In ERPs, positive words elicited a larger early posterior negativity and a smaller late positive component than neutral words in L1, while a trend of reduced N400 component was found for positive words compared to neutral words in L2. In fMRI, reduced activation was found for L1 emotional words in both the left middle occipital gyrus and the left cerebellum whereas increased activation in the left cerebellum was found for L2 emotional words. Altogether, these results suggest that emotional word processing advantage in L1 relies on rapid and automatic attention capture while facilitated semantic retrieval might help processing emotional words in L2. Copyright © 2015 Elsevier Ltd. All rights reserved.

High-Caloric and Chocolate Stimuli Processing in Healthy Humans: An Integration of Functional Imaging and Electrophysiological Findings

PubMed Central

Asmaro, Deyar; Liotti, Mario

2014-01-01

There has been a great deal of interest in understanding how the human brain processes appetitive food cues, and knowing how such cues elicit craving responses is particularly relevant when current eating behavior trends within Westernized societies are considered. One substance that holds a special place with regard to food preference is chocolate, and studies that used functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) have identified neural regions and electrical signatures that are elicited by chocolate cue presentations. This review will examine fMRI and ERP findings from studies that used high-caloric food and chocolate cues as stimuli, with a focus on responses observed in samples of healthy participants, as opposed to those with eating-related pathology. The utility of using high-caloric and chocolate stimuli as a means of understanding the human reward system will also be highlighted, as these findings may be particularly important for understanding processes related to pathological overeating and addiction to illicit substances. Finally, research from our own lab that focused on chocolate stimulus processing in chocolate cravers and non-cravers will be discussed, as the approach used may help bridge fMRI and ERP findings so that a more complete understanding of appetitive stimulus processing in the temporal and spatial domains may be established. PMID:24434747

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

PubMed

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

Incidental Memory Encoding Assessed with Signal Detection Theory and Functional Magnetic Resonance Imaging (fMRI).

PubMed

Clemens, Benjamin; Regenbogen, Christina; Koch, Kathrin; Backes, Volker; Romanczuk-Seiferth, Nina; Pauly, Katharina; Shah, N Jon; Schneider, Frank; Habel, Ute; Kellermann, Thilo

2015-01-01

In functional magnetic resonance imaging (fMRI) studies that apply a "subsequent memory" approach, successful encoding is indicated by increased fMRI activity during the encoding phase for hits vs. misses, in areas underlying memory encoding such as the hippocampal formation. Signal-detection theory (SDT) can be used to analyze memory-related fMRI activity as a function of the participant's memory trace strength (d(')). The goal of the present study was to use SDT to examine the relationship between fMRI activity during incidental encoding and participants' recognition performance. To implement a new approach, post-experimental group assignment into High- or Low Performers (HP or LP) was based on 29 healthy participants' recognition performance, assessed with SDT. The analyses focused on the interaction between the factors group (HP vs. LP) and recognition performance (hits vs. misses). A whole-brain analysis revealed increased activation for HP vs. LP during incidental encoding for remembered vs. forgotten items (hits > misses) in the insula/temporo-parietal junction (TPJ) and the fusiform gyrus (FFG). Parameter estimates in these regions exhibited a significant positive correlation with d('). As these brain regions are highly relevant for salience detection (insula), stimulus-driven attention (TPJ), and content-specific processing of mnemonic stimuli (FFG), we suggest that HPs' elevated memory performance was associated with enhanced attentional and content-specific sensory processing during the encoding phase. We provide first correlative evidence that encoding-related activity in content-specific sensory areas and content-independent attention and salience detection areas influences memory performance in a task with incidental encoding of facial stimuli. Based on our findings, we discuss whether the aforementioned group differences in brain activity during incidental encoding might constitute the basis of general differences in memory performance between HP and LP.

Task-Related Edge Density (TED)—A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain

PubMed Central

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach “Task-related Edge Density” (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function. PMID:27341204

Task-Related Edge Density (TED)-A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain.

PubMed

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.

Naproxen effects on brain response to painful pressure stimulation in patients with knee osteoarthritis: a double-blind, randomized, placebo-controlled, single-dose study.

PubMed

Giménez, Mónica; Pujol, Jesús; Ali, Zahid; López-Solà, Marina; Contreras-Rodríguez, Oren; Deus, Joan; Ortiz, Héctor; Soriano-Mas, Carles; Llorente-Onaindia, Jone; Monfort, Jordi

2014-11-01

The aim of our study was to investigate the effects of naproxen, an antiinflammatory analgesic drug, on brain response to painful stimulation on the affected knee in chronic osteoarthritis (OA) using functional magnetic resonance imaging (fMRI) in a double-blind, placebo-controlled study. A sample of 25 patients with knee OA received naproxen (500 mg), placebo, or no treatment in 3 separate sessions in a randomized manner. Pressure stimulation was applied to the medial articular interline of the knee during the fMRI pain sequence. We evaluated subjective pain ratings at every session and their association with brain responses to pain. An fMRI control paradigm was included to discard global brain vascular effects of naproxen. We found brain activation reductions under naproxen compared to no treatment in different cortical and subcortical core pain processing regions (p≤0.001). Compared to placebo, naproxen triggered an attenuation of amygdala activation (p=0.001). Placebo extended its attenuation effects beyond the classical pain processing network (p≤0.001). Subjective pain scores during the fMRI painful task differed between naproxen and no treatment (p=0.037). Activation attenuation under naproxen in different regions (i.e., ventral brain, cingulate gyrus) was accompanied by an improvement in the subjective pain complaints (p≤0.002). Naproxen effectively reduces pain-related brain responses involving different regions and the attenuation is related to subjective pain changes. Our current work yields further support to the utility of fMRI to objectify the acute analgesic effects of a single naproxen dose in patients affected by knee OA. The trial was registered at the EuropeanClinicalTrials Database, "EudraCT Number 2008-004501-33".

Theory and Application of Magnetic Flux Leakage Pipeline Detection.

PubMed

Shi, Yan; Zhang, Chao; Li, Rui; Cai, Maolin; Jia, Guanwei

2015-12-10

Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted.

Theory and Application of Magnetic Flux Leakage Pipeline Detection

PubMed Central

Shi, Yan; Zhang, Chao; Li, Rui; Cai, Maolin; Jia, Guanwei

2015-01-01

Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted. PMID:26690435

Simulation of pipeline in the area of the underwater crossing

NASA Astrophysics Data System (ADS)

Burkov, P.; Chernyavskiy, D.; Burkova, S.; Konan, E. C.

2014-08-01

The article studies stress-strain behavior of the main oil-pipeline section Alexandrovskoye-Anzhero-Sudzhensk using software system Ansys. This method of examination and assessment of technical conditions of objects of pipeline transport studies the objects and the processes that affect the technical condition of these facilities, including the research on the basis of computer simulation. Such approach allows to develop the theory, methods of calculations and designing of objects of pipeline transport, units and parts of machines, regardless of their industry and destination with a view to improve the existing constructions and create new structures, machines of high performance, durability and reliability, maintainability, low material capacity and cost, which have competitiveness on the world market.

CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.

PubMed

Soysal, Ergin; Wang, Jingqi; Jiang, Min; Wu, Yonghui; Pakhomov, Serguei; Liu, Hongfang; Xu, Hua

2017-11-24

Existing general clinical natural language processing (NLP) systems such as MetaMap and Clinical Text Analysis and Knowledge Extraction System have been successfully applied to information extraction from clinical text. However, end users often have to customize existing systems for their individual tasks, which can require substantial NLP skills. Here we present CLAMP (Clinical Language Annotation, Modeling, and Processing), a newly developed clinical NLP toolkit that provides not only state-of-the-art NLP components, but also a user-friendly graphic user interface that can help users quickly build customized NLP pipelines for their individual applications. Our evaluation shows that the CLAMP default pipeline achieved good performance on named entity recognition and concept encoding. We also demonstrate the efficiency of the CLAMP graphic user interface in building customized, high-performance NLP pipelines with 2 use cases, extracting smoking status and lab test values. CLAMP is publicly available for research use, and we believe it is a unique asset for the clinical NLP community. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

How task demands shape brain responses to visual food cues.

PubMed

Pohl, Tanja Maria; Tempelmann, Claus; Noesselt, Toemme

2017-06-01

Several previous imaging studies have aimed at identifying the neural basis of visual food cue processing in humans. However, there is little consistency of the functional magnetic resonance imaging (fMRI) results across studies. Here, we tested the hypothesis that this variability across studies might - at least in part - be caused by the different tasks employed. In particular, we assessed directly the influence of task set on brain responses to food stimuli with fMRI using two tasks (colour vs. edibility judgement, between-subjects design). When participants judged colour, the left insula, the left inferior parietal lobule, occipital areas, the left orbitofrontal cortex and other frontal areas expressed enhanced fMRI responses to food relative to non-food pictures. However, when judging edibility, enhanced fMRI responses to food pictures were observed in the superior and middle frontal gyrus and in medial frontal areas including the pregenual anterior cingulate cortex and ventromedial prefrontal cortex. This pattern of results indicates that task sets can significantly alter the neural underpinnings of food cue processing. We propose that judging low-level visual stimulus characteristics - such as colour - triggers stimulus-related representations in the visual and even in gustatory cortex (insula), whereas discriminating abstract stimulus categories activates higher order representations in both the anterior cingulate and prefrontal cortex. Hum Brain Mapp 38:2897-2912, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A new concept of a unified parameter management, experiment control, and data analysis in fMRI: application to real-time fMRI at 3T and 7T.

PubMed

Hollmann, M; Mönch, T; Mulla-Osman, S; Tempelmann, C; Stadler, J; Bernarding, J

2008-10-30

In functional MRI (fMRI) complex experiments and applications require increasingly complex parameter handling as the experimental setup usually consists of separated soft- and hardware systems. Advanced real-time applications such as neurofeedback-based training or brain computer interfaces (BCIs) may even require adaptive changes of the paradigms and experimental setup during the measurement. This would be facilitated by an automated management of the overall workflow and a control of the communication between all experimental components. We realized a concept based on an XML software framework called Experiment Description Language (EDL). All parameters relevant for real-time data acquisition, real-time fMRI (rtfMRI) statistical data analysis, stimulus presentation, and activation processing are stored in one central EDL file, and processed during the experiment. A usability study comparing the central EDL parameter management with traditional approaches showed an improvement of the complete experimental handling. Based on this concept, a feasibility study realizing a dynamic rtfMRI-based brain computer interface showed that the developed system in combination with EDL was able to reliably detect and evaluate activation patterns in real-time. The implementation of a centrally controlled communication between the subsystems involved in the rtfMRI experiments reduced potential inconsistencies, and will open new applications for adaptive BCIs.

Modulation of brain response to emotional conflict as a function of current mood in bipolar disorder: preliminary findings from a follow-up state-based fMRI study.

PubMed

Rey, Gwladys; Desseilles, Martin; Favre, Sophie; Dayer, Alexandre; Piguet, Camille; Aubry, Jean-Michel; Vuilleumier, Patrik

2014-08-30

We used functional magnetic resonance imaging (fMRI) to examine affective control longitudinally in a group of patients with bipolar disorder (BD). Participants comprised 12 BD patients who underwent repeated fMRI scans in euthymic (n=11), depressed (n=9), or hypomanic (n=9) states, and were compared with 12 age-matched healthy controls. During fMRI, participants performed an emotional face-word interference task with either low or high attentional demands. Relative to healthy controls, patients showed decreased activation of the cognitive control network normally associated with conflict processing, more severely during hypomania than during depression, but regardless of level of task demand in both cases. During euthymia, a decreased response to conflict was observed only during the high load condition. Additionally, unlike healthy participants, patients exhibited deactivation in several key areas in response to emotion-conflict trials - including the rostral anterior cingulate cortex during euthymia, the hippocampus during depression, and the posterior cingulate cortex during hypomania. Our results indicate that the ability of BD patients to recruit control networks when processing affective conflict, and the abnormal suppression of activity in distinct components of the default mode network, may depend on their current clinical state and attentional demand. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Object representations in ventral and dorsal visual streams: fMRI repetition effects depend on attention and part–whole configuration

PubMed Central

Thoma, Volker; Henson, Richard N.

2011-01-01

The effects of attention and object configuration on the neural responses to short-lag visual image repetition were investigated with fMRI. Attention to one of two object images in a prime display was cued spatially. The images were either intact or split vertically; a manipulation that negates the influence of view-based representations. A subsequent single intact probe image was named covertly. Behavioural priming observed as faster button presses was found for attended primes in both intact and split configurations, but only for uncued primes in the intact configuration. In a voxel-wise analysis, fMRI repetition suppression (RS) was observed in a left mid-fusiform region for attended primes, both intact and split, whilst a right intraparietal region showed repetition enhancement (RE) for intact primes, regardless of attention. In a factorial analysis across regions of interest (ROIs) defined from independent localiser contrasts, RS for attended objects in the ventral stream was significantly left-lateralised, whilst repetition effects in ventral and dorsal ROIs correlated with the amount of priming in specific conditions. These fMRI results extend hybrid theories of object recognition, implicating left ventral stream regions in analytic processing (requiring attention), consistent with prior hypotheses about hemispheric specialisation, and implicating dorsal stream regions in holistic processing (independent of attention). PMID:21554967

Investigating the neural basis for functional and effective connectivity. Application to fMRI

PubMed Central

Horwitz, Barry; Warner, Brent; Fitzer, Julie; Tagamets, M.-A; Husain, Fatima T; Long, Theresa W

2005-01-01

Viewing cognitive functions as mediated by networks has begun to play a central role in interpreting neuroscientific data, and studies evaluating interregional functional and effective connectivity have become staples of the neuroimaging literature. The neurobiological substrates of functional and effective connectivity are, however, uncertain. We have constructed neurobiologically realistic models for visual and auditory object processing with multiple interconnected brain regions that perform delayed match-to-sample (DMS) tasks. We used these models to investigate how neurobiological parameters affect the interregional functional connectivity between functional magnetic resonance imaging (fMRI) time-series. Variability is included in the models as subject-to-subject differences in the strengths of anatomical connections, scan-to-scan changes in the level of attention, and trial-to-trial interactions with non-specific neurons processing noise stimuli. We find that time-series correlations between integrated synaptic activities between the anterior temporal and the prefrontal cortex were larger during the DMS task than during a control task. These results were less clear when the integrated synaptic activity was haemodynamically convolved to generate simulated fMRI activity. As the strength of the model anatomical connectivity between temporal and frontal cortex was weakened, so too was the strength of the corresponding functional connectivity. These results provide a partial validation for using fMRI functional connectivity to assess brain interregional relations. PMID:16087450

Impacts of simultaneous multislice acquisition on sensitivity and specificity in fMRI.

PubMed

Risk, Benjamin B; Kociuba, Mary C; Rowe, Daniel B

2018-05-15

Simultaneous multislice (SMS) imaging can be used to decrease the time between acquisition of fMRI volumes, which can increase sensitivity by facilitating the removal of higher-frequency artifacts and boosting effective sample size. The technique requires an additional processing step in which the slices are separated, or unaliased, to recover the whole brain volume. However, this may result in signal "leakage" between aliased locations, i.e., slice "leakage," and lead to spurious activation (decreased specificity). SMS can also lead to noise amplification, which can reduce the benefits of decreased repetition time. In this study, we evaluate the original slice-GRAPPA (no leak block) reconstruction algorithm and acceleration factor (AF = 8) used in the fMRI data in the young adult Human Connectome Project (HCP). We also evaluate split slice-GRAPPA (leak block), which can reduce slice leakage. We use simulations to disentangle higher test statistics into true positives (sensitivity) and false positives (decreased specificity). Slice leakage was greatly decreased by split slice-GRAPPA. Noise amplification was decreased by using moderate acceleration factors (AF = 4). We examined slice leakage in unprocessed fMRI motor task data from the HCP. When data were smoothed, we found evidence of slice leakage in some, but not all, subjects. We also found evidence of SMS noise amplification in unprocessed task and processed resting-state HCP data. Copyright © 2018 Elsevier Inc. All rights reserved.

Subtle In-Scanner Motion Biases Automated Measurement of Brain Anatomy From In Vivo MRI

PubMed Central

Alexander-Bloch, Aaron; Clasen, Liv; Stockman, Michael; Ronan, Lisa; Lalonde, Francois; Giedd, Jay; Raznahan, Armin

2016-01-01

While the potential for small amounts of motion in functional magnetic resonance imaging (fMRI) scans to bias the results of functional neuroimaging studies is well appreciated, the impact of in-scanner motion on morphological analysis of structural MRI is relatively under-studied. Even among “good quality” structural scans, there may be systematic effects of motion on measures of brain morphometry. In the present study, the subjects’ tendency to move during fMRI scans, acquired in the same scanning sessions as their structural scans, yielded a reliable, continuous estimate of in-scanner motion. Using this approach within a sample of 127 children, adolescents, and young adults, significant relationships were found between this measure and estimates of cortical gray matter volume and mean curvature, as well as trend-level relationships with cortical thickness. Specifically, cortical volume and thickness decreased with greater motion, and mean curvature increased. These effects of subtle motion were anatomically heterogeneous, were present across different automated imaging pipelines, showed convergent validity with effects of frank motion assessed in a separate sample of 274 scans, and could be demonstrated in both pediatric and adult populations. Thus, using different motion assays in two large non-overlapping sets of structural MRI scans, convergent evidence showed that in-scanner motion—even at levels which do not manifest in visible motion artifact—can lead to systematic and regionally specific biases in anatomical estimation. These findings have special relevance to structural neuroimaging in developmental and clinical datasets, and inform ongoing efforts to optimize neuroanatomical analysis of existing and future structural MRI datasets in non-sedated humans. PMID:27004471

The representation of order information in auditory-verbal short-term memory.

PubMed

Kalm, Kristjan; Norris, Dennis

2014-05-14

Here we investigate how order information is represented in auditory-verbal short-term memory (STM). We used fMRI and a serial recall task to dissociate neural activity patterns representing the phonological properties of the items stored in STM from the patterns representing their order. For this purpose, we analyzed fMRI activity patterns elicited by different item sets and different orderings of those items. These fMRI activity patterns were compared with the predictions made by positional and chaining models of serial order. The positional models encode associations between items and their positions in a sequence, whereas the chaining models encode associations between successive items and retain no position information. We show that a set of brain areas in the postero-dorsal stream of auditory processing store associations between items and order as predicted by a positional model. The chaining model of order representation generates a different pattern similarity prediction, which was shown to be inconsistent with the fMRI data. Our results thus favor a neural model of order representation that stores item codes, position codes, and the mapping between them. This study provides the first fMRI evidence for a specific model of order representation in the human brain. Copyright © 2014 the authors 0270-6474/14/346879-08$15.00/0.

Parallel processing considerations for image recognition tasks

NASA Astrophysics Data System (ADS)

Simske, Steven J.

2011-01-01

Many image recognition tasks are well-suited to parallel processing. The most obvious example is that many imaging tasks require the analysis of multiple images. From this standpoint, then, parallel processing need be no more complicated than assigning individual images to individual processors. However, there are three less trivial categories of parallel processing that will be considered in this paper: parallel processing (1) by task; (2) by image region; and (3) by meta-algorithm. Parallel processing by task allows the assignment of multiple workflows-as diverse as optical character recognition [OCR], document classification and barcode reading-to parallel pipelines. This can substantially decrease time to completion for the document tasks. For this approach, each parallel pipeline is generally performing a different task. Parallel processing by image region allows a larger imaging task to be sub-divided into a set of parallel pipelines, each performing the same task but on a different data set. This type of image analysis is readily addressed by a map-reduce approach. Examples include document skew detection and multiple face detection and tracking. Finally, parallel processing by meta-algorithm allows different algorithms to be deployed on the same image simultaneously. This approach may result in improved accuracy.

Scaling-up NLP Pipelines to Process Large Corpora of Clinical Notes.

PubMed

Divita, G; Carter, M; Redd, A; Zeng, Q; Gupta, K; Trautner, B; Samore, M; Gundlapalli, A

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". This paper describes the scale-up efforts at the VA Salt Lake City Health Care System to address processing large corpora of clinical notes through a natural language processing (NLP) pipeline. The use case described is a current project focused on detecting the presence of an indwelling urinary catheter in hospitalized patients and subsequent catheter-associated urinary tract infections. An NLP algorithm using v3NLP was developed to detect the presence of an indwelling urinary catheter in hospitalized patients. The algorithm was tested on a small corpus of notes on patients for whom the presence or absence of a catheter was already known (reference standard). In planning for a scale-up, we estimated that the original algorithm would have taken 2.4 days to run on a larger corpus of notes for this project (550,000 notes), and 27 days for a corpus of 6 million records representative of a national sample of notes. We approached scaling-up NLP pipelines through three techniques: pipeline replication via multi-threading, intra-annotator threading for tasks that can be further decomposed, and remote annotator services which enable annotator scale-out. The scale-up resulted in reducing the average time to process a record from 206 milliseconds to 17 milliseconds or a 12- fold increase in performance when applied to a corpus of 550,000 notes. Purposely simplistic in nature, these scale-up efforts are the straight forward evolution from small scale NLP processing to larger scale extraction without incurring associated complexities that are inherited by the use of the underlying UIMA framework. These efforts represent generalizable and widely applicable techniques that will aid other computationally complex NLP pipelines that are of need to be scaled out for processing and analyzing big data.

49 CFR 192.243 - Nondestructive testing.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 3 2010-10-01 2010-10-01 false Nondestructive testing. 192.243 Section 192.243... BY PIPELINE: MINIMUM FEDERAL SAFETY STANDARDS Welding of Steel in Pipelines § 192.243 Nondestructive testing. (a) Nondestructive testing of welds must be performed by any process, other than trepanning, that...

State Regulators Promote Consumer Choice in Retail Gas Markets

EIA Publications

1996-01-01

Restructuring of interstate pipeline companies has created new choices and challenges for local distribution companies (LDCs), their regulators, and their customers. The process of separating interstate pipeline gas sales from transportation service has been completed and has resulted in greater gas procurement options for LDCs.

DALiuGE: A graph execution framework for harnessing the astronomical data deluge

NASA Astrophysics Data System (ADS)

Wu, C.; Tobar, R.; Vinsen, K.; Wicenec, A.; Pallot, D.; Lao, B.; Wang, R.; An, T.; Boulton, M.; Cooper, I.; Dodson, R.; Dolensky, M.; Mei, Y.; Wang, F.

2017-07-01

The Data Activated Liu Graph Engine - DALiuGE- is an execution framework for processing large astronomical datasets at a scale required by the Square Kilometre Array Phase 1 (SKA1). It includes an interface for expressing complex data reduction pipelines consisting of both datasets and algorithmic components and an implementation run-time to execute such pipelines on distributed resources. By mapping the logical view of a pipeline to its physical realisation, DALiuGE separates the concerns of multiple stakeholders, allowing them to collectively optimise large-scale data processing solutions in a coherent manner. The execution in DALiuGE is data-activated, where each individual data item autonomously triggers the processing on itself. Such decentralisation also makes the execution framework very scalable and flexible, supporting pipeline sizes ranging from less than ten tasks running on a laptop to tens of millions of concurrent tasks on the second fastest supercomputer in the world. DALiuGE has been used in production for reducing interferometry datasets from the Karl E. Jansky Very Large Array and the Mingantu Ultrawide Spectral Radioheliograph; and is being developed as the execution framework prototype for the Science Data Processor (SDP) consortium of the Square Kilometre Array (SKA) telescope. This paper presents a technical overview of DALiuGE and discusses case studies from the CHILES and MUSER projects that use DALiuGE to execute production pipelines. In a companion paper, we provide in-depth analysis of DALiuGE's scalability to very large numbers of tasks on two supercomputing facilities.

Bifrost: a Modular Python/C++ Framework for Development of High-Throughput Data Analysis Pipelines

NASA Astrophysics Data System (ADS)

Cranmer, Miles; Barsdell, Benjamin R.; Price, Danny C.; Garsden, Hugh; Taylor, Gregory B.; Dowell, Jayce; Schinzel, Frank; Costa, Timothy; Greenhill, Lincoln J.

2017-01-01

Large radio interferometers have data rates that render long-term storage of raw correlator data infeasible, thus motivating development of real-time processing software. For high-throughput applications, processing pipelines are challenging to design and implement. Motivated by science efforts with the Long Wavelength Array, we have developed Bifrost, a novel Python/C++ framework that eases the development of high-throughput data analysis software by packaging algorithms as black box processes in a directed graph. This strategy to modularize code allows astronomers to create parallelism without code adjustment. Bifrost uses CPU/GPU ’circular memory’ data buffers that enable ready introduction of arbitrary functions into the processing path for ’streams’ of data, and allow pipelines to automatically reconfigure in response to astrophysical transient detection or input of new observing settings. We have deployed and tested Bifrost at the latest Long Wavelength Array station, in Sevilleta National Wildlife Refuge, NM, where it handles throughput exceeding 10 Gbps per CPU core.

Gathering pipeline methane emissions in Fayetteville shale pipelines and scoping guidelines for future pipeline measurement campaigns

DOE PAGES

Zimmerle, Daniel J.; Pickering, Cody K.; Bell, Clay S.; ...

2017-11-24

Gathering pipelines, which transport gas from well pads to downstream processing, are a sector of the natural gas supply chain for which little measured methane emissions data are available. This study performed leak detection and measurement on 96 km of gathering pipeline and the associated 56 pigging facilities and 39 block valves. The study found one underground leak accounting for 83% (4.0 kg CH 4/hr) of total measured emissions. Methane emissions for the 4684 km of gathering pipeline in the study area were estimated at 402 kg CH 4/hr [95 to 1065 kg CH 4/hr, 95% CI], or 1% [0.2%more » to 2.6%] of all methane emissions measured during a prior aircraft study of the same area. Emissions estimated by this study fall within the uncertainty range of emissions estimated using emission factors from EPA's 2015 Greenhouse Inventory and study activity estimates. While EPA's current inventory is based upon emission factors from distribution mains measured in the 1990s, this study indicates that using emission factors from more recent distribution studies could significantly underestimate emissions from gathering pipelines. To guide broader studies of pipeline emissions, we also estimate the fraction of the pipeline length within a basin that must be measured to constrain uncertainty of pipeline emissions estimates to within 1% of total basin emissions. The study provides both substantial insight into the mix of emission sources and guidance for future gathering pipeline studies, but since measurements were made in a single basin, the results are not sufficiently representative to provide methane emission factors at the regional or national level.« less

Gathering pipeline methane emissions in Fayetteville shale pipelines and scoping guidelines for future pipeline measurement campaigns

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zimmerle, Daniel J.; Pickering, Cody K.; Bell, Clay S.

Gathering pipelines, which transport gas from well pads to downstream processing, are a sector of the natural gas supply chain for which little measured methane emissions data are available. This study performed leak detection and measurement on 96 km of gathering pipeline and the associated 56 pigging facilities and 39 block valves. The study found one underground leak accounting for 83% (4.0 kg CH 4/hr) of total measured emissions. Methane emissions for the 4684 km of gathering pipeline in the study area were estimated at 402 kg CH 4/hr [95 to 1065 kg CH 4/hr, 95% CI], or 1% [0.2%more » to 2.6%] of all methane emissions measured during a prior aircraft study of the same area. Emissions estimated by this study fall within the uncertainty range of emissions estimated using emission factors from EPA's 2015 Greenhouse Inventory and study activity estimates. While EPA's current inventory is based upon emission factors from distribution mains measured in the 1990s, this study indicates that using emission factors from more recent distribution studies could significantly underestimate emissions from gathering pipelines. To guide broader studies of pipeline emissions, we also estimate the fraction of the pipeline length within a basin that must be measured to constrain uncertainty of pipeline emissions estimates to within 1% of total basin emissions. The study provides both substantial insight into the mix of emission sources and guidance for future gathering pipeline studies, but since measurements were made in a single basin, the results are not sufficiently representative to provide methane emission factors at the regional or national level.« less

A method for simulating the release of natural gas from the rupture of high-pressure pipelines in any terrain.

PubMed

Deng, Yajun; Hu, Hongbing; Yu, Bo; Sun, Dongliang; Hou, Lei; Liang, Yongtu

2018-01-15

The rupture of a high-pressure natural gas pipeline can pose a serious threat to human life and environment. In this research, a method has been proposed to simulate the release of natural gas from the rupture of high-pressure pipelines in any terrain. The process of gas releases from the rupture of a high-pressure pipeline is divided into three stages, namely the discharge, jet, and dispersion stages. Firstly, a discharge model is established to calculate the release rate of the orifice. Secondly, an improved jet model is proposed to obtain the parameters of the pseudo source. Thirdly, a fast-modeling method applicable to any terrain is introduced. Finally, based upon these three steps, a dispersion model, which can take any terrain into account, is established. Then, the dispersion scenarios of released gas in four different terrains are studied. Moreover, the effects of pipeline pressure, pipeline diameter, wind speed and concentration of hydrogen sulfide on the dispersion scenario in real terrain are systematically analyzed. The results provide significant guidance for risk assessment and contingency planning of a ruptured natural gas pipeline. Copyright © 2017. Published by Elsevier B.V.

Serotonergic neurotransmission in emotional processing: New evidence from long-term recreational poly-drug ecstasy use.

PubMed

Laursen, Helle Ruff; Henningsson, Susanne; Macoveanu, Julian; Jernigan, Terry L; Siebner, Hartwig R; Holst, Klaus K; Skimminge, Arnold; Knudsen, Gitte M; Ramsoy, Thomas Z; Erritzoe, David

2016-12-01

The brain's serotonergic system plays a crucial role in the processing of emotional stimuli, and several studies have shown that a reduced serotonergic neurotransmission is associated with an increase in amygdala activity during emotional face processing. Prolonged recreational use of ecstasy (3,4-methylene-dioxymethamphetamine [MDMA]) induces alterations in serotonergic neurotransmission that are comparable to those observed in a depleted state. In this functional magnetic resonance imaging (fMRI) study, we investigated the responsiveness of the amygdala to emotional face stimuli in recreational ecstasy users as a model of long-term serotonin depletion. Fourteen ecstasy users and 12 non-using controls underwent fMRI to measure the regional neural activity elicited in the amygdala by male or female faces expressing anger, disgust, fear, sadness, or no emotion. During fMRI, participants made a sex judgement on each face stimulus. Positron emission tomography with 11 C-DASB was additionally performed to assess serotonin transporter (SERT) binding in the brain. In the ecstasy users, SERT binding correlated negatively with amygdala activity, and accumulated lifetime intake of ecstasy tablets was associated with an increase in amygdala activity during angry face processing. Conversely, time since the last ecstasy intake was associated with a trend toward a decrease in amygdala activity during angry and sad face processing. These results indicate that the effects of long-term serotonin depletion resulting from ecstasy use are dose-dependent, affecting the functional neural basis of emotional face processing. © The Author(s) 2016.

Natural gas and CO2 price variation: impact on the relative cost-efficiency of LNG and pipelines.

PubMed

Ulvestad, Marte; Overland, Indra

2012-06-01

THIS ARTICLE DEVELOPS A FORMAL MODEL FOR COMPARING THE COST STRUCTURE OF THE TWO MAIN TRANSPORT OPTIONS FOR NATURAL GAS: liquefied natural gas (LNG) and pipelines. In particular, it evaluates how variations in the prices of natural gas and greenhouse gas emissions affect the relative cost-efficiency of these two options. Natural gas is often promoted as the most environmentally friendly of all fossil fuels, and LNG as a modern and efficient way of transporting it. Some research has been carried out into the local environmental impact of LNG facilities, but almost none into aspects related to climate change. This paper concludes that at current price levels for natural gas and CO 2 emissions the distance from field to consumer and the volume of natural gas transported are the main determinants of transport costs. The pricing of natural gas and greenhouse emissions influence the relative cost-efficiency of LNG and pipeline transport, but only to a limited degree at current price levels. Because more energy is required for the LNG process (especially for fuelling the liquefaction process) than for pipelines at distances below 9100 km, LNG is more exposed to variability in the price of natural gas and greenhouse gas emissions up to this distance. If the prices of natural gas and/or greenhouse gas emission rise dramatically in the future, this will affect the choice between pipelines and LNG. Such a price increase will be favourable for pipelines relative to LNG.

Natural gas and CO2 price variation: impact on the relative cost-efficiency of LNG and pipelines

PubMed Central

Ulvestad, Marte; Overland, Indra

2012-01-01

This article develops a formal model for comparing the cost structure of the two main transport options for natural gas: liquefied natural gas (LNG) and pipelines. In particular, it evaluates how variations in the prices of natural gas and greenhouse gas emissions affect the relative cost-efficiency of these two options. Natural gas is often promoted as the most environmentally friendly of all fossil fuels, and LNG as a modern and efficient way of transporting it. Some research has been carried out into the local environmental impact of LNG facilities, but almost none into aspects related to climate change. This paper concludes that at current price levels for natural gas and CO2 emissions the distance from field to consumer and the volume of natural gas transported are the main determinants of transport costs. The pricing of natural gas and greenhouse emissions influence the relative cost-efficiency of LNG and pipeline transport, but only to a limited degree at current price levels. Because more energy is required for the LNG process (especially for fuelling the liquefaction process) than for pipelines at distances below 9100 km, LNG is more exposed to variability in the price of natural gas and greenhouse gas emissions up to this distance. If the prices of natural gas and/or greenhouse gas emission rise dramatically in the future, this will affect the choice between pipelines and LNG. Such a price increase will be favourable for pipelines relative to LNG. PMID:24683269

A novel joint-processing adaptive nonlinear equalizer using a modular recurrent neural network for chaotic communication systems.

PubMed

Zhao, Haiquan; Zeng, Xiangping; Zhang, Jiashu; Liu, Yangguang; Wang, Xiaomin; Li, Tianrui

2011-01-01

To eliminate nonlinear channel distortion in chaotic communication systems, a novel joint-processing adaptive nonlinear equalizer based on a pipelined recurrent neural network (JPRNN) is proposed, using a modified real-time recurrent learning (RTRL) algorithm. Furthermore, an adaptive amplitude RTRL algorithm is adopted to overcome the deteriorating effect introduced by the nesting process. Computer simulations illustrate that the proposed equalizer outperforms the pipelined recurrent neural network (PRNN) and recurrent neural network (RNN) equalizers. Copyright © 2010 Elsevier Ltd. All rights reserved.

Probing the brain with molecular fMRI.

PubMed

Ghosh, Souparno; Harvey, Peter; Simon, Jacob C; Jasanoff, Alan

2018-06-01

One of the greatest challenges of modern neuroscience is to incorporate our growing knowledge of molecular and cellular-scale physiology into integrated, organismic-scale models of brain function in behavior and cognition. Molecular-level functional magnetic resonance imaging (molecular fMRI) is a new technology that can help bridge these scales by mapping defined microscopic phenomena over large, optically inaccessible regions of the living brain. In this review, we explain how MRI-detectable imaging probes can be used to sensitize noninvasive imaging to mechanistically significant components of neural processing. We discuss how a combination of innovative probe design, advanced imaging methods, and strategies for brain delivery can make molecular fMRI an increasingly successful approach for spatiotemporally resolved studies of diverse neural phenomena, perhaps eventually in people. Copyright © 2018 Elsevier Ltd. All rights reserved.

Autogenic training alters cerebral activation patterns in fMRI.

PubMed

Schlamann, Marc; Naglatzki, Ryan; de Greiff, Armin; Forsting, Michael; Gizewski, Elke R

2010-10-01

Cerebral activation patterns during the first three auto-suggestive phases of autogenic training (AT) were investigated in relation to perceived experiences. Nineteen volunteers trained in AT and 19 controls were studied with fMRI during the first steps of autogenic training. FMRI revealed activation of the left postcentral areas during AT in those with experience in AT, which also correlated with the level of AT experience. Activation of prefrontal and insular cortex was significantly higher in the group with experience in AT while insular activation was correlated with number years of simple relaxation exercises. Specific activation in subjects experienced in AT may represent a training effect. Furthermore, the correlation of insular activation suggests that these subjects are different from untrained subjects in emotional processing or self-awareness.

A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines

PubMed Central

2011-01-01

Background Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP) paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts. Results To enable the flexible creation and execution of bioinformatics dataflows, we have written a modular framework for parallel pipelines in Python ('PaPy'). A PaPy workflow is created from re-usable components connected by data-pipes into a directed acyclic graph, which together define nested higher-order map functions. The successive functional transformations of input data are evaluated on flexibly pooled compute resources, either local or remote. Input items are processed in batches of adjustable size, all flowing one to tune the trade-off between parallelism and lazy-evaluation (memory consumption). An add-on module ('NuBio') facilitates the creation of bioinformatics workflows by providing domain specific data-containers (e.g., for biomolecular sequences, alignments, structures) and functionality (e.g., to parse/write standard file formats). Conclusions PaPy offers a modular framework for the creation and deployment of parallel and distributed data-processing workflows. Pipelines derive their functionality from user-written, data-coupled components, so PaPy also can be viewed as a lightweight toolkit for extensible, flow-based bioinformatics data-processing. The simplicity and flexibility of distributed PaPy pipelines may help users bridge the gap between traditional desktop/workstation and grid computing. PaPy is freely distributed as open-source Python code at http://muralab.org/PaPy, and includes extensive documentation and annotated usage examples. PMID:21352538

A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines.

PubMed

Cieślik, Marcin; Mura, Cameron

2011-02-25

Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP) paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts. To enable the flexible creation and execution of bioinformatics dataflows, we have written a modular framework for parallel pipelines in Python ('PaPy'). A PaPy workflow is created from re-usable components connected by data-pipes into a directed acyclic graph, which together define nested higher-order map functions. The successive functional transformations of input data are evaluated on flexibly pooled compute resources, either local or remote. Input items are processed in batches of adjustable size, all flowing one to tune the trade-off between parallelism and lazy-evaluation (memory consumption). An add-on module ('NuBio') facilitates the creation of bioinformatics workflows by providing domain specific data-containers (e.g., for biomolecular sequences, alignments, structures) and functionality (e.g., to parse/write standard file formats). PaPy offers a modular framework for the creation and deployment of parallel and distributed data-processing workflows. Pipelines derive their functionality from user-written, data-coupled components, so PaPy also can be viewed as a lightweight toolkit for extensible, flow-based bioinformatics data-processing. The simplicity and flexibility of distributed PaPy pipelines may help users bridge the gap between traditional desktop/workstation and grid computing. PaPy is freely distributed as open-source Python code at http://muralab.org/PaPy, and includes extensive documentation and annotated usage examples.

27 CFR 20.94 - Statement of process.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 5150.19 shall also contain the following information: (i) Flow diagrams shall be submitted with the... connecting pipelines and valves. All major equipment shall be identified as to its use. The direction of flow through the pipelines shall be indicated in the flow diagram. The flow diagram, shall be accompanied by a...

27 CFR 20.94 - Statement of process.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 5150.19 shall also contain the following information: (i) Flow diagrams shall be submitted with the... connecting pipelines and valves. All major equipment shall be identified as to its use. The direction of flow through the pipelines shall be indicated in the flow diagram. The flow diagram, shall be accompanied by a...

27 CFR 20.94 - Statement of process.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 5150.19 shall also contain the following information: (i) Flow diagrams shall be submitted with the... connecting pipelines and valves. All major equipment shall be identified as to its use. The direction of flow through the pipelines shall be indicated in the flow diagram. The flow diagram, shall be accompanied by a...

27 CFR 20.94 - Statement of process.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 5150.19 shall also contain the following information: (i) Flow diagrams shall be submitted with the... connecting pipelines and valves. All major equipment shall be identified as to its use. The direction of flow through the pipelines shall be indicated in the flow diagram. The flow diagram, shall be accompanied by a...

27 CFR 20.94 - Statement of process.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 5150.19 shall also contain the following information: (i) Flow diagrams shall be submitted with the... connecting pipelines and valves. All major equipment shall be identified as to its use. The direction of flow through the pipelines shall be indicated in the flow diagram. The flow diagram, shall be accompanied by a...

The Application of PVDF in Converter Cooling Pipeline

NASA Astrophysics Data System (ADS)

Geng, Man; Lu, Zhimin

2017-11-01

The structure, mechanical property, thermodynamics property, electrical aspects, radiation property and chemical property were introduced, and PVDF could satisfy the requirement of converter cooling pipe. PVDF department and pipe of distribution pipeline of converter cooling system in Debao HVDC project are used to introduce the molding process of PVDF.

Basic overview towards the assessment of landslide and subsidence risks along a geothermal pipeline network

NASA Astrophysics Data System (ADS)

Astisiasari; Van Westen, Cees; Jetten, Victor; van der Meer, Freek; Rahmawati Hizbaron, Dyah

2017-12-01

An operating geothermal power plant consists of installation units that work systematically in a network. The pipeline network connects various engineering structures, e.g. well pads, separator, scrubber, and power station, in the process of transferring geothermal fluids to generate electricity. Besides, a pipeline infrastructure also delivers the brine back to earth, through the injection well-pads. Despite of its important functions, a geothermal pipeline may bear a threat to its vicinity through a pipeline failure. The pipeline can be impacted by perilous events like landslides, earthquakes, and subsidence. The pipeline failure itself may relate to physical deterioration over time, e.g. due to corrosion and fatigue. The geothermal reservoirs are usually located in mountainous areas that are associated with steep slopes, complex geology, and weathered soil. Geothermal areas record a noteworthy number of disasters, especially due to landslide and subsidence. Therefore, a proper multi-risk assessment along the geothermal pipeline is required, particularly for these two types of hazard. This is also to mention that the impact on human fatality and injury is not presently discussed here. This paper aims to give a basic overview on the existing approaches for the assessment of multi-risk assessment along geothermal pipelines. It delivers basic principles on the analysis of risks and its contributing variables, in order to model the loss consequences. By considering the loss consequences, as well as the alternatives for mitigation measures, the environmental safety in geothermal working area could be enforced.

First Retrieval of Surface Lambert Albedos From Mars Reconnaissance Orbiter CRISM Data

NASA Astrophysics Data System (ADS)

McGuire, P. C.; Arvidson, R. E.; Murchie, S. L.; Wolff, M. J.; Smith, M. D.; Martin, T. Z.; Milliken, R. E.; Mustard, J. F.; Pelkey, S. M.; Lichtenberg, K. A.; Cavender, P. J.; Humm, D. C.; Titus, T. N.; Malaret, E. R.

2006-12-01

We have developed a pipeline-processing software system to convert radiance-on-sensor for each of 72 out of 544 CRISM spectral bands used in global mapping to the corresponding surface Lambert albedo, accounting for atmospheric, thermal, and photoclinometric effects. We will present and interpret first results from this software system for the retrieval of Lambert albedos from CRISM data. For the multispectral mapping modes, these pipeline-processed 72 spectral bands constitute all of the available bands, for wavelengths from 0.362-3.920 μm, at 100-200 m/pixel spatial resolution, and ~ 0.006\\spaceμm spectral resolution. For the hyperspectral targeted modes, these pipeline-processed 72 spectral bands are only a selection of all of the 544 spectral bands, but at a resolution of 15-38 m/pixel. The pipeline processing for both types of observing modes (multispectral and hyperspectral) will use climatology, based on data from MGS/TES, in order to estimate ice- and dust-aerosol optical depths, prior to the atmospheric correction with lookup tables based upon radiative-transport calculations via DISORT. There is one DISORT atmospheric-correction lookup table for converting radiance-on-sensor to Lambert albedo for each of the 72 spectral bands. The measurements of the Emission Phase Function (EPF) during targeting will not be employed in this pipeline processing system. We are developing a separate system for extracting more accurate aerosol optical depths and surface scattering properties. This separate system will use direct calls (instead of lookup tables) to the DISORT code for all 544 bands, and it will use the EPF data directly, bootstrapping from the climatology data for the aerosol optical depths. The pipeline processing will thermally correct the albedos for the spectral bands above ~ 2.6 μm, by a choice between 4 different techniques for determining surface temperature: 1) climatology, 2) empirical estimation of the albedo at 3.9 μm from the measured albedo at 2.5 μm, 3) a physical thermal model (PTM) based upon maps of thermal inertia from TES and coarse-resolution surface slopes (SS) from MOLA, and 4) a photoclinometric extension to the PTM that uses CRISM albedos at 0.41 μm to compute the SS at CRISM spatial resolution. For the thermal correction, we expect that each of these 4 different techniques will be valuable for some fraction of the observations.

Smart Sound Processing for Defect Sizing in Pipelines Using EMAT Actuator Based Multi-Frequency Lamb Waves

PubMed Central

García-Gómez, Joaquín; Rosa-Zurera, Manuel; Romero-Camacho, Antonio; Jiménez-Garrido, Jesús Antonio; García-Benavides, Víctor

2018-01-01

Pipeline inspection is a topic of particular interest to the companies. Especially important is the defect sizing, which allows them to avoid subsequent costly repairs in their equipment. A solution for this issue is using ultrasonic waves sensed through Electro-Magnetic Acoustic Transducer (EMAT) actuators. The main advantage of this technology is the absence of the need to have direct contact with the surface of the material under investigation, which must be a conductive one. Specifically interesting is the meander-line-coil based Lamb wave generation, since the directivity of the waves allows a study based in the circumferential wrap-around received signal. However, the variety of defect sizes changes the behavior of the signal when it passes through the pipeline. Because of that, it is necessary to apply advanced techniques based on Smart Sound Processing (SSP). These methods involve extracting useful information from the signals sensed with EMAT at different frequencies to obtain nonlinear estimations of the depth of the defect, and to select the features that better estimate the profile of the pipeline. The proposed technique has been tested using both simulated and real signals in steel pipelines, obtaining good results in terms of Root Mean Square Error (RMSE). PMID:29518927

A homology-based pipeline for global prediction of post-translational modification sites

NASA Astrophysics Data System (ADS)

Chen, Xiang; Shi, Shao-Ping; Xu, Hao-Dong; Suo, Sheng-Bao; Qiu, Jian-Ding

2016-05-01

The pathways of protein post-translational modifications (PTMs) have been shown to play particularly important roles for almost any biological process. Identification of PTM substrates along with information on the exact sites is fundamental for fully understanding or controlling biological processes. Alternative computational strategies would help to annotate PTMs in a high-throughput manner. Traditional algorithms are suited for identifying the common organisms and tissues that have a complete PTM atlas or extensive experimental data. While annotation of rare PTMs in most organisms is a clear challenge. In this work, to this end we have developed a novel homology-based pipeline named PTMProber that allows identification of potential modification sites for most of the proteomes lacking PTMs data. Cross-promotion E-value (CPE) as stringent benchmark has been used in our pipeline to evaluate homology to known modification sites. Independent-validation tests show that PTMProber achieves over 58.8% recall with high precision by CPE benchmark. Comparisons with other machine-learning tools show that PTMProber pipeline performs better on general predictions. In addition, we developed a web-based tool to integrate this pipeline at http://bioinfo.ncu.edu.cn/PTMProber/index.aspx. In addition to pre-constructed prediction models of PTM, the website provides an extensional functionality to allow users to customize models.

The distributed neural system for top-down letter processing: an fMRI study

NASA Astrophysics Data System (ADS)

Liu, Jiangang; Feng, Lu; Li, Ling; Tian, Jie

2011-03-01

This fMRI study used Psychophysiological interaction (PPI) to investigate top-down letter processing with an illusory letter detection task. After an initial training that became increasingly difficult, participant was instructed to detect a letter from pure noise images where there was actually no letter. Such experimental paradigm allowed for isolating top-down components of letter processing and minimizing the influence of bottom-up perceptual input. A distributed cortical network of top-down letter processing was identified by analyzing the functional connectivity patterns of letter-preferential area (LA) within the left fusiform gyrus. Such network extends from the visual cortex to high level cognitive cortexes, including the left middle frontal gyrus, left medial frontal gyrus, left superior parietal gyrus, bilateral precuneus, and left inferior occipital gyrus. These findings suggest that top-down letter processing contains not only regions for processing of letter phonology and appearance, but also those involved in internal information generation and maintenance, and attention and memory processing.

Generation of Custom DSP Transform IP Cores: Case Study Walsh-Hadamard Transform

DTIC Science & Technology

2002-09-01

mathematics and hardware design What I know: Finite state machine Pipelining Systolic array … What I know: Linear algebra Digital signal processing...state machine Pipelining Systolic array … What I know: Linear algebra Digital signal processing Adaptive filter theory … A math guy A hardware engineer...Synthesis Technology Libary Bit-width (8) HF factor (1,2,3,6) VF factor (1,2,4, ... 32) Xilinx FPGA Place&Route Xilinx FPGA Place&Route Performance

Adjudicating between face-coding models with individual-face fMRI responses

PubMed Central

Kriegeskorte, Nikolaus

2017-01-01

The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging. PMID:28746335

Age-Dependent Mesial Temporal Lobe Lateralization in Language FMRI

PubMed Central

Sepeta, Leigh N.; Berl, Madison M.; Wilke, Marko; You, Xiaozhen; Mehta, Meera; Xu, Benjamin; Inati, Sara; Dustin, Irene; Khan, Omar; Austermuehle, Alison; Theodore, William H.; Gaillard, William D.

2015-01-01

Objective FMRI activation of the mesial temporal lobe (MTL) may be important for epilepsy surgical planning. We examined MTL activation and lateralization during language fMRI in children and adults with focal epilepsy. Methods 142 controls and patients with left hemisphere focal epilepsy (Pediatric: epilepsy, n = 17, mean age = 9.9 ± 2.0; controls, n = 48; mean age = 9.1 ± 2.6; Adult: epilepsy, n = 20, mean age = 26.7 ± 5.8; controls, n = 57, mean age = 26.2 ± 7.5) underwent 3T fMRI using a language task (auditory description decision task). Image processing and analyses were conducted in SPM8; ROIs included MTL, Broca’s area, and Wernicke’s area. We assessed group and individual MTL activation, and examined degree of lateralization. Results Patients and controls (pediatric and adult) demonstrated group and individual MTL activation during language fMRI. MTL activation was left lateralized for adults but less so in children (p’s < 0.005). Patients did not differ from controls in either age group. Stronger left-lateralized MTL activation was related to older age (p = 0.02). Language lateralization (Broca’s and Wernicke’s) predicted 19% of the variance in MTL lateralization for adults (p = 0.001), but not children. Significance Language fMRI may be used to elicit group and individual MTL activation. The developmental difference in MTL lateralization and its association with language lateralization suggests a developmental shift in lateralization of MTL function, with increased left lateralization across the age span. This shift may help explain why children have better memory outcomes following resection compared to adults. PMID:26696589

Development of an apparatus and methodology for conducting functional magnetic resonance imaging (fMRI) with pharmacological stimuli in conscious rhesus monkeys.

PubMed

Murnane, Kevin Sean; Howell, Leonard Lee

2010-08-15

Functional magnetic resonance imaging (fMRI) is a technique with significant potential to advance our understanding of multiple brain systems. However, when human subjects undergo fMRI studies they are typically conscious whereas pre-clinical fMRI studies typically utilize anesthesia, which complicates comparisons across studies. Therefore, we have developed an apparatus suitable for imaging conscious rhesus monkeys. In order to minimize subject stress and spatial motion, each subject was acclimated to the necessary procedures over several months. The effectiveness of this process was then evaluated, in fully trained subjects, by quantifying objective physiological measures. These physiological metrics were stable both within and across sessions and did not differ from when these same subjects were immobilized using standard primate handling procedures. Subject motion and blood oxygenation level dependent (BOLD) fMRI measurements were then evaluated by scanning subjects under three different conditions: the absence of stimulation, presentation of a visual stimulus, or administration of intravenous (i.v.) cocaine (0.3mg/kg). Spatial motion differed neither by condition nor along the three principal axes. In addition, maximum translational and rotational motion never exceeded one half of the voxel size (0.75 mm) or 1.5 degrees, respectively. Furthermore, the localization of changes in blood oxygenation closely matched those reported in previous studies using similar stimuli. These findings document the feasibility of fMRI data collection in conscious rhesus monkeys using these procedures and allow for the further study of the neural effects of psychoactive drugs. (c) 2010 Elsevier B.V. All rights reserved.

Fast fMRI can detect oscillatory neural activity in humans.

PubMed

Lewis, Laura D; Setsompop, Kawin; Rosen, Bruce R; Polimeni, Jonathan R

2016-10-25

Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG-fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain.

Optimal Energy Consumption Analysis of Natural Gas Pipeline

PubMed Central

Liu, Enbin; Li, Changjun; Yang, Yi

2014-01-01

There are many compressor stations along long-distance natural gas pipelines. Natural gas can be transported using different boot programs and import pressures, combined with temperature control parameters. Moreover, different transport methods have correspondingly different energy consumptions. At present, the operating parameters of many pipelines are determined empirically by dispatchers, resulting in high energy consumption. This practice does not abide by energy reduction policies. Therefore, based on a full understanding of the actual needs of pipeline companies, we introduce production unit consumption indicators to establish an objective function for achieving the goal of lowering energy consumption. By using a dynamic programming method for solving the model and preparing calculation software, we can ensure that the solution process is quick and efficient. Using established optimization methods, we analyzed the energy savings for the XQ gas pipeline. By optimizing the boot program, the import station pressure, and the temperature parameters, we achieved the optimal energy consumption. By comparison with the measured energy consumption, the pipeline now has the potential to reduce energy consumption by 11 to 16 percent. PMID:24955410

Risk analysis of urban gas pipeline network based on improved bow-tie model

NASA Astrophysics Data System (ADS)

Hao, M. J.; You, Q. J.; Yue, Z.

2017-11-01

Gas pipeline network is a major hazard source in urban areas. In the event of an accident, there could be grave consequences. In order to understand more clearly the causes and consequences of gas pipeline network accidents, and to develop prevention and mitigation measures, the author puts forward the application of improved bow-tie model to analyze risks of urban gas pipeline network. The improved bow-tie model analyzes accident causes from four aspects: human, materials, environment and management; it also analyzes the consequences from four aspects: casualty, property loss, environment and society. Then it quantifies the causes and consequences. Risk identification, risk analysis, risk assessment, risk control, and risk management will be clearly shown in the model figures. Then it can suggest prevention and mitigation measures accordingly to help reduce accident rate of gas pipeline network. The results show that the whole process of an accident can be visually investigated using the bow-tie model. It can also provide reasons for and predict consequences of an unfortunate event. It is of great significance in order to analyze leakage failure of gas pipeline network.

Time-Distance Helioseismology Data-Analysis Pipeline for Helioseismic and Magnetic Imager Onboard Solar Dynamics Observatory (SDO-HMI) and Its Initial Results

NASA Technical Reports Server (NTRS)

Zhao, J.; Couvidat, S.; Bogart, R. S.; Parchevsky, K. V.; Birch, A. C.; Duvall, Thomas L., Jr.; Beck, J. G.; Kosovichev, A. G.; Scherrer, P. H.

2011-01-01

The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) provides continuous full-disk observations of solar oscillations. We develop a data-analysis pipeline based on the time-distance helioseismology method to measure acoustic travel times using HMI Doppler-shift observations, and infer solar interior properties by inverting these measurements. The pipeline is used for routine production of near-real-time full-disk maps of subsurface wave-speed perturbations and horizontal flow velocities for depths ranging from 0 to 20 Mm, every eight hours. In addition, Carrington synoptic maps for the subsurface properties are made from these full-disk maps. The pipeline can also be used for selected target areas and time periods. We explain details of the pipeline organization and procedures, including processing of the HMI Doppler observations, measurements of the travel times, inversions, and constructions of the full-disk and synoptic maps. Some initial results from the pipeline, including full-disk flow maps, sunspot subsurface flow fields, and the interior rotation and meridional flow speeds, are presented.

Research on Submarine Pipeline Steel with High Performance

NASA Astrophysics Data System (ADS)

Ren, Yi; Liu, Wenyue; Zhang, Shuai; Wang, Shuang; Gao, Hong

Submarine pipeline steel has largely uniform elongation, low yield ratio and good balance between high strength and high plasticity because of the microstructure with dual phase. In this work, the microstructure and properties of the submarine pipeline steel are studied. The results show that the matrix structure is consisted of ferrite, bainite and martensite -austenite islands. The structure has a tight relationship with the thermal-mechanical controlled process. Fine dual phase shows good plasticity and low yield ratio, which can support the good balance between high strength and high plasticity.

A conditional Granger causality model approach for group analysis in functional MRI

PubMed Central

Zhou, Zhenyu; Wang, Xunheng; Klahr, Nelson J.; Liu, Wei; Arias, Diana; Liu, Hongzhi; von Deneen, Karen M.; Wen, Ying; Lu, Zuhong; Xu, Dongrong; Liu, Yijun

2011-01-01

Granger causality model (GCM) derived from multivariate vector autoregressive models of data has been employed for identifying effective connectivity in the human brain with functional MR imaging (fMRI) and to reveal complex temporal and spatial dynamics underlying a variety of cognitive processes. In the most recent fMRI effective connectivity measures, pairwise GCM has commonly been applied based on single voxel values or average values from special brain areas at the group level. Although a few novel conditional GCM methods have been proposed to quantify the connections between brain areas, our study is the first to propose a viable standardized approach for group analysis of an fMRI data with GCM. To compare the effectiveness of our approach with traditional pairwise GCM models, we applied a well-established conditional GCM to pre-selected time series of brain regions resulting from general linear model (GLM) and group spatial kernel independent component analysis (ICA) of an fMRI dataset in the temporal domain. Datasets consisting of one task-related and one resting-state fMRI were used to investigate connections among brain areas with the conditional GCM method. With the GLM detected brain activation regions in the emotion related cortex during the block design paradigm, the conditional GCM method was proposed to study the causality of the habituation between the left amygdala and pregenual cingulate cortex during emotion processing. For the resting-state dataset, it is possible to calculate not only the effective connectivity between networks but also the heterogeneity within a single network. Our results have further shown a particular interacting pattern of default mode network (DMN) that can be characterized as both afferent and efferent influences on the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC). These results suggest that the conditional GCM approach based on a linear multivariate vector autoregressive (MVAR) model can achieve greater accuracy in detecting network connectivity than the widely used pairwise GCM, and this group analysis methodology can be quite useful to extend the information obtainable in fMRI. PMID:21232892

Alterations of decision making and underlying neural correlates after resection of a mediofrontal cortical dysplasia: A single case study.

PubMed

Labudda, Kirsten; Brand, Matthias; Mertens, Markus; Ebner, Alois; Markowitsch, Hans J; Woermann, Friedrich G

2010-02-01

We investigated the impact of a congenital prefrontal lesion and its resection on decision making under risk and under ambiguity in a patient with right mediofrontal cortical dysplasia. Both kinds of decision making are normally associated with the medial prefrontal cortex. We additionally studied pre- and postsurgical fMRI activations when processing information relevant for risky decision making. Results indicate selective impairments of ambiguous decision making pre- and postsurgically. Decision making under risk was intact. In contrast to healthy subjects the patient exhibited no activation within the dysplastic anterior cingulate cortex but left-sided orbitofrontal activation on the fMRI task suggesting early reorganization processes.

Vector processing efficiency of plasma MHD codes by use of the FACOM 230-75 APU

NASA Astrophysics Data System (ADS)

Matsuura, T.; Tanaka, Y.; Naraoka, K.; Takizuka, T.; Tsunematsu, T.; Tokuda, S.; Azumi, M.; Kurita, G.; Takeda, T.

1982-06-01

In the framework of pipelined vector architecture, the efficiency of vector processing is assessed with respect to plasma MHD codes in nuclear fusion research. By using a vector processor, the FACOM 230-75 APU, the limit of the enhancement factor due to parallelism of current vector machines is examined for three numerical codes based on a fluid model. Reasonable speed-up factors of approximately 6,6 and 4 times faster than the highly optimized scalar version are obtained for ERATO (linear stability code), AEOLUS-R1 (nonlinear stability code) and APOLLO (1-1/2D transport code), respectively. Problems of the pipelined vector processors are discussed from the viewpoint of restructuring, optimization and choice of algorithms. In conclusion, the important concept of "concurrency within pipelined parallelism" is emphasized.

Effect of Cooling Mode on Microstructure and Mechanical Properties of Pipeline Steel for Strain Based Design and Research on its Deformation Mechanism

NASA Astrophysics Data System (ADS)

Hesong, Zhang; Yonglin, Kang

With the rapid development of oil and gas industry long distance pipelines inevitably pass through regions with complex geological activities. In order to avoid large deformation the pipelines must be designed based on strain criteria. In this paper the alloy system of X80 high deformability pipeline steel was designed which was 0.25%Mo-0.05%C-1.75%Mn. The effect of controlled cooling process on microstructure and mechanical properties of X80 high deformability pipeline steel were systematically investigated. Through the two-stage controlled cooling process the microstructure of the X80 high deformability pipeline steel were ferrite, bainite and M/A island. There were two kinds of ferrite which were polygonal ferrite (PF) and quasi-polygonal ferrite (QF). The bainite was granular bainite ferrite (GF). Along with the decrease of the start cooling temperature, the volume fraction of ferrite and M/A both increased, the yield ratio (Y/T) decreased, the uniform elongation (uEl) increased firstly with the content of ferrite increased but then decreased with the content and size of M/A increased. When the finish cooling temperature decreasing, the size of M/A became finer. As the start cooling temperature was 690 °C and the finish cooling temperature was 450 °C the volume fraction of ferrite was 23%, the size of ferrite grain was 5μm, the size of M/A island was below 1μm and the structure uniformity was the best. The deformation mechanism of X80 high deformability pipeline steel was analyzed. The best way to improve the work hardening rate was reducing the size of M/A islands on the premise of a certain volume fraction. The decreasing path of instantaneous strain hardening index (n*-value) showed three stages in the deformation process. The n*-value kept stable in the second stage, the reason was that the retained austenite transformed into martensite and the phase transition improved the strain hardening ability of the microstructure. This phenomenon was called transformation induced plasticity effect (TRIP).

Effects of Achievement Goals on Challenge Seeking and Feedback Processing: Behavioral and fMRI Evidence

PubMed Central

Lee, Woogul; Kim, Sung-il

2014-01-01

We conducted behavioral and functional magnetic resonance imaging (fMRI) research to investigate the effects of two types of achievement goals—mastery goals and performance-approach goals— on challenge seeking and feedback processing. The results of the behavioral experiment indicated that mastery goals were associated with a tendency to seek challenge, both before and after experiencing difficulty during task performance, whereas performance-approach goals were related to a tendency to avoid challenge after encountering difficulty during task performance. The fMRI experiment uncovered a significant decrease in ventral striatal activity when participants received negative feedback for any task type and both forms of achievement goals. During the processing of negative feedback for the rule-finding task, performance-approach-oriented participants showed a substantial reduction in activity in the dorsolateral prefrontal cortex (DLPFC) and the frontopolar cortex, whereas mastery-oriented participants showed little change. These results suggest that performance-approach-oriented participants are less likely to either recruit control processes in response to negative feedback or focus on task-relevant information provided alongside the negative feedback. In contrast, mastery-oriented participants are more likely to modulate aversive valuations to negative feedback and focus on the constructive elements of feedback in order to attain their task goals. We conclude that performance-approach goals lead to a reluctant stance towards difficulty, while mastery goals encourage a proactive stance. PMID:25251396

Towards a neural circuit model of verbal humor processing: an fMRI study of the neural substrates of incongruity detection and resolution.

PubMed

Chan, Yu-Chen; Chou, Tai-Li; Chen, Hsueh-Chih; Yeh, Yu-Chu; Lavallee, Joseph P; Liang, Keng-Chen; Chang, Kuo-En

2013-02-01

The present study builds on our previous study within the framework of Wyer and Collin's comprehension-elaboration theory of humor processing. In this study, an attempt is made to segregate the neural substrates of incongruity detection and incongruity resolution during the comprehension of verbal jokes. Although a number of fMRI studies have investigated the incongruity-resolution process, the differential neurological substrates of comprehension are still not fully understood. The present study utilized an event-related fMRI design incorporating three conditions (unfunny, nonsensical and funny) to examine distinct brain regions associated with the detection and resolution of incongruities. Stimuli in the unfunny condition contained no incongruities; stimuli in the nonsensical condition contained irresolvable incongruities; and stimuli in the funny condition contained resolvable incongruities. The results showed that the detection of incongruities was associated with greater activation in the right middle temporal gyrus and right medial frontal gyrus, and the resolution of incongruities with greater activation in the left superior frontal gyrus and left inferior parietal lobule. Further analysis based on participants' rating scores provided converging results. Our findings suggest a three-stage neural circuit model of verbal humor processing: incongruity detection and incongruity resolution during humor comprehension and inducement of the feeling of amusement during humor elaboration. Copyright © 2012 Elsevier Inc. All rights reserved.

Categorical speech processing in Broca's area: an fMRI study using multivariate pattern-based analysis.

PubMed

Lee, Yune-Sang; Turkeltaub, Peter; Granger, Richard; Raizada, Rajeev D S

2012-03-14

Although much effort has been directed toward understanding the neural basis of speech processing, the neural processes involved in the categorical perception of speech have been relatively less studied, and many questions remain open. In this functional magnetic resonance imaging (fMRI) study, we probed the cortical regions mediating categorical speech perception using an advanced brain-mapping technique, whole-brain multivariate pattern-based analysis (MVPA). Normal healthy human subjects (native English speakers) were scanned while they listened to 10 consonant-vowel syllables along the /ba/-/da/ continuum. Outside of the scanner, individuals' own category boundaries were measured to divide the fMRI data into /ba/ and /da/ conditions per subject. The whole-brain MVPA revealed that Broca's area and the left pre-supplementary motor area evoked distinct neural activity patterns between the two perceptual categories (/ba/ vs /da/). Broca's area was also found when the same analysis was applied to another dataset (Raizada and Poldrack, 2007), which previously yielded the supramarginal gyrus using a univariate adaptation-fMRI paradigm. The consistent MVPA findings from two independent datasets strongly indicate that Broca's area participates in categorical speech perception, with a possible role of translating speech signals into articulatory codes. The difference in results between univariate and multivariate pattern-based analyses of the same data suggest that processes in different cortical areas along the dorsal speech perception stream are distributed on different spatial scales.

Prolonged fasting impairs neural reactivity to visual stimulation.

PubMed

Kohn, N; Wassenberg, A; Toygar, T; Kellermann, T; Weidenfeld, C; Berthold-Losleben, M; Chechko, N; Orfanos, S; Vocke, S; Laoutidis, Z G; Schneider, F; Karges, W; Habel, U

2016-01-01

Previous literature has shown that hypoglycemia influences the intensity of the BOLD signal. A similar but smaller effect may also be elicited by low normal blood glucose levels in healthy individuals. This may not only confound the BOLD signal measured in fMRI, but also more generally interact with cognitive processing, and thus indirectly influence fMRI results. Here we show in a placebo-controlled, crossover, double-blind study on 40 healthy subjects, that overnight fasting and low normal levels of glucose contrasted to an activated, elevated glucose condition have an impact on brain activation during basal visual stimulation. Additionally, functional connectivity of the visual cortex shows a strengthened association with higher-order attention-related brain areas in an elevated blood glucose condition compared to the fasting condition. In a fasting state visual brain areas show stronger coupling to the inferior temporal gyrus. Results demonstrate that prolonged overnight fasting leads to a diminished BOLD signal in higher-order occipital processing areas when compared to an elevated blood glucose condition. Additionally, functional connectivity patterns underscore the modulatory influence of fasting on visual brain networks. Patterns of brain activation and functional connectivity associated with a broad range of attentional processes are affected by maturation and aging and associated with psychiatric disease and intoxication. Thus, we conclude that prolonged fasting may decrease fMRI design sensitivity in any task involving attentional processes when fasting status or blood glucose is not controlled.

Naturalistic FMRI mapping reveals superior temporal sulcus as the hub for the distributed brain network for social perception.

PubMed

Lahnakoski, Juha M; Glerean, Enrico; Salmi, Juha; Jääskeläinen, Iiro P; Sams, Mikko; Hari, Riitta; Nummenmaa, Lauri

2012-01-01

Despite the abundant data on brain networks processing static social signals, such as pictures of faces, the neural systems supporting social perception in naturalistic conditions are still poorly understood. Here we delineated brain networks subserving social perception under naturalistic conditions in 19 healthy humans who watched, during 3-T functional magnetic resonance imaging (fMRI), a set of 137 short (approximately 16 s each, total 27 min) audiovisual movie clips depicting pre-selected social signals. Two independent raters estimated how well each clip represented eight social features (faces, human bodies, biological motion, goal-oriented actions, emotion, social interaction, pain, and speech) and six filler features (places, objects, rigid motion, people not in social interaction, non-goal-oriented action, and non-human sounds) lacking social content. These ratings were used as predictors in the fMRI analysis. The posterior superior temporal sulcus (STS) responded to all social features but not to any non-social features, and the anterior STS responded to all social features except bodies and biological motion. We also found four partially segregated, extended networks for processing of specific social signals: (1) a fronto-temporal network responding to multiple social categories, (2) a fronto-parietal network preferentially activated to bodies, motion, and pain, (3) a temporo-amygdalar network responding to faces, social interaction, and speech, and (4) a fronto-insular network responding to pain, emotions, social interactions, and speech. Our results highlight the role of the pSTS in processing multiple aspects of social information, as well as the feasibility and efficiency of fMRI mapping under conditions that resemble the complexity of real life.

High Field fMRI Reveals Thalamocortical Integration of Segregated Cognitive and Emotional Processing in Mediodorsal and Intralaminar Thalamic Nuclei

PubMed Central

Metzger, C. D.; Eckert, U.; Steiner, J.; Sartorius, A.; Buchmann, J. E.; Stadler, J.; Tempelmann, C.; Speck, O.; Bogerts, B.; Abler, B.; Walter, M.

2010-01-01

Thalamocortical loops, connecting functionally segregated, higher order cortical regions, and basal ganglia, have been proposed not only for well described motor and sensory regions, but also for limbic and prefrontal areas relevant for affective and cognitive processes. These functions are, however, more specific to humans, rendering most invasive neuroanatomical approaches impossible and interspecies translations difficult. In contrast, non-invasive imaging of functional neuroanatomy using fMRI allows for the development of elaborate task paradigms capable of testing the specific functionalities proposed for these circuits. Until recently, spatial resolution largely limited the anatomical definition of functional clusters at the level of distinct thalamic nuclei. Since their anatomical distinction seems crucial not only for the segregation of cognitive and limbic loops but also for the detection of their functional interaction during cognitive–emotional integration, we applied high resolution fMRI on 7 Tesla. Using an event-related design, we could isolate thalamic effects for preceding attention as well as experience of erotic stimuli. We could demonstrate specific thalamic effects of general emotional arousal in mediodorsal nucleus and effects specific to preceding attention and expectancy in intralaminar centromedian/parafascicular complex. These thalamic effects were paralleled by specific coactivations in the head of caudate nucleus as well as segregated portions of rostral or caudal cingulate cortex and anterior insula supporting distinct thalamo–striato–cortical loops. In addition to predescribed effects of sexual arousal in hypothalamus and ventral striatum, high resolution fMRI could extent this network to paraventricular thalamus encompassing laterodorsal and parataenial nuclei. We could lend evidence to segregated subcortical loops which integrate cognitive and emotional aspects of basic human behavior such as sexual processing. PMID:21088699

Patterns of frontoparietal activation as a marker for unsuccessful visuospatial processing in healthy aging.

PubMed

Drag, Lauren L; Light, Sharee N; Langenecker, Scott A; Hazlett, Kathleen E; Wilde, Elisabeth A; Welsh, Robert; Steinberg, Brett A; Bieliauskas, Linas A

2016-09-01

Visuospatial abilities are sensitive to age-related decline, although the neural basis for this decline (and its everyday behavioral correlates) is as yet poorly understood. fMRI was employed to examine age-related differences in patterns of functional activation that underlie changes in visuospatial processing. All participants completed a brief neuropsychological battery and also a figure ground task (FGT) assessing visuospatial processing while fMRI was recorded. Participants included 16 healthy older adults (OA; aged 69-82 years) and 16 healthy younger adults (YA; aged 20-35 years). We examined age-related differences in behavioral performance on the FGT in relation to patterns of fMRI activation. OA demonstrated reduced performance on the FGT task and showed increased activation of supramarginal parietal cortex as well as increased activation of frontal and temporal regions compared to their younger counterparts. Performance on the FGT related to increased supramarginal gyrus activity and increased medial prefrontal activity in OAs, but not YAs. Our results are consistent with an anterior-posterior compensation model. Successful FGT performance requires the perception and integration of multiple stimuli and thus it is plausible that healthy aging may be accompanied by changes in visuospatial processing that mimic a subtle form of dorsal simultanagnosia. Overall, decreased visuospatial processing in OA relates to an altered frontoparietal neurobiological signature that may contribute to the general phenomenon of increasingly fragmented execution of behavior associated with normal aging.

Brain activation in response to randomized visual stimulation as obtained from conjunction and differential analysis: an fMRI study

NASA Astrophysics Data System (ADS)

Nasaruddin, N. H.; Yusoff, A. N.; Kaur, S.

2014-11-01

The objective of this multiple-subjects functional magnetic resonance imaging (fMRI) study was to identify the common brain areas that are activated when viewing black-and-white checkerboard pattern stimuli of various shapes, pattern and size and to investigate specific brain areas that are involved in processing static and moving visual stimuli. Sixteen participants viewed the moving (expanding ring, rotating wedge, flipping hour glass and bowtie and arc quadrant) and static (full checkerboard) stimuli during an fMRI scan. All stimuli have black-and-white checkerboard pattern. Statistical parametric mapping (SPM) was used in generating brain activation. Differential analyses were implemented to separately search for areas involved in processing static and moving stimuli. In general, the stimuli of various shapes, pattern and size activated multiple brain areas mostly in the left hemisphere. The activation in the right middle temporal gyrus (MTG) was found to be significantly higher in processing moving visual stimuli as compared to static stimulus. In contrast, the activation in the left calcarine sulcus and left lingual gyrus were significantly higher for static stimulus as compared to moving stimuli. Visual stimulation of various shapes, pattern and size used in this study indicated left lateralization of activation. The involvement of the right MTG in processing moving visual information was evident from differential analysis, while the left calcarine sulcus and left lingual gyrus are the areas that are involved in the processing of static visual stimulus.

Spatiotemporal Dynamics of Argument Retrieval and Reordering: An fMRI and EEG Study on Sentence Processing

PubMed Central

Meyer, Lars; Obleser, Jonas; Kiebel, Stefan J.; Friederici, Angela D.

2012-01-01

In sentence processing, it is still unclear how the neural language network successfully establishes argument–verb dependencies in its spatiotemporal neuronal dynamics. Previous work has suggested that the establishment of subject–verb and object–verb dependencies requires argument retrieval from working memory, and that dependency establishment in object-first sentences additionally necessitates argument reordering. We examine the spatiotemporal neuronal dynamics of the brain regions that subserve these sub-processes by crossing an argument reordering factor (i.e., subject-first versus object-first sentences) with an argument retrieval factor (i.e., short versus long argument–verb dependencies) in German. Using functional magnetic resonance imaging (fMRI), we found that reordering demands focally activate the left pars opercularis (Broca’s area), while storage and retrieval demands activated left temporo-parietal (TP) regions. In addition, when analyzing the time course of fMRI-informed equivalent current dipole sources in the EEG at the subcategorizing verb, we found that activity in the TP-region occurs relatively early (40–180 ms), followed by activity in Broca’s area (300–500 ms). These findings were matched by topographical correlation analyses of fMRI activations in EEG sensor space, showing that, in the scalp potential, TP-region activity surfaces as an early positivity and IFG activity as a later positivity in the scalp potential. These results provide fine-grained evidence for spatiotemporally separable sub-processes of argument retrieval and reordering in sentence processing. PMID:23248607

Abnormal processing of deontological guilt in obsessive-compulsive disorder.

PubMed

Basile, Barbara; Mancini, Francesco; Macaluso, Emiliano; Caltagirone, Carlo; Bozzali, Marco

2014-07-01

Guilt plays a significant role in the occurrence and maintenance of obsessive-compulsive disorder (OCD). Two major types of guilt have been identified: one deriving from the transgression of a moral rule (deontological guilt DG), another (altruistic guilt AG), relying on the assumption of having compromised a personal altruistic goal. Clinical evidence suggests that OCD patients are particularly sensitive to DG, but not AG. In this functional magnetic resonance imaging (fMRI) study, we investigated brain response of OCD patients while processing DG and AG stimuli. A previously validated fMRI paradigm was used to selectively evoke DG and AG, and anger and sadness, as control emotions in 13 OCD patients and 19 healthy controls. Patients' behavioral results showed a prominent attitude to experience guilt, compared to controls, while accomplishing task. fMRI results revealed that patients have reduced activation in the anterior cingulate (ACC) and frontal gyrus when experiencing guilt, regardless of its specific type (DG or AG). When separately considering each type of guilt (against each of its control), patients showed decreased activation in the ACC, the insula and the precuneus, for DG. No significant differences were observed between groups when processing AG, anger or sad stimuli. This study provides evidence for an abnormal processing of guilt, and specifically DG, in OCD patients. We suggest that decreased activation may reflect patients' cerebral efficiency, which derives from their frequent exposure to guilty feelings ("neural efficiency hypothesis"). In conclusion, our study confirms a selective abnormal processing of guilt, and specifically DG, in OCD.

[Dynamics of functional MRI and speech function in patients after resection of frontal and temporal lobe tumors].

PubMed

Buklina, S B; Batalov, A I; Smirnov, A S; Poddubskaya, A A; Pitskhelauri, D I; Kobyakov, G L; Zhukov, V Yu; Goryaynov, S A; Kulikov, A S; Ogurtsova, A A; Golanov, A V; Varyukhina, M D; Pronin, I N

There are no studies on application of functional MRI (fMRI) for long-term monitoring of the condition of patients after resection of frontal and temporal lobe tumors. The study purpose was to correlate, using fMRI, reorganization of the speech system and dynamics of speech disorders in patients with left hemisphere gliomas before surgery and in the early and late postoperative periods. A total of 20 patients with left hemisphere gliomas were dynamically monitored using fMRI and comprehensive neuropsychological testing. The tumor was located in the frontal lobe in 12 patients and in the temporal lobe in 8 patients. Fifteen patients underwent primary surgery; 5 patients had repeated surgery. Sixteen patients had WHO Grade II and Grade III gliomas; the others had WHO Grade IV gliomas. Nineteen patients were examined preoperatively; 20 patients were examined at different times after surgery. Speech functions were assessed by a Luria's test; the dominant hand was determined using the Annette questionnaire; a family history of left-handedness was investigated. Functional MRI was performed on an HDtx 3.0 T scanner using BrainWavePA 2.0, Z software for fMRI data processing program for all calculations >7, p<0.001. In patients with extensive tumors and recurrent tumors, activation of right-sided homologues of the speech areas cold be detected even before surgery; but in most patients, the activation was detected 3 months or more after surgery. Therefore, reorganization of the speech system took time. Activation of right-sided homologues of the speech areas remained in all patients for up to a year. Simultaneous activation of right-sided homologues of both speech areas, the Broca's and Wernicke's areas, was detected more often in patients with frontal lobe tumors than in those with temporal lobe tumors. No additional activation foci in the left hemisphere were found at the thresholds used to process fMRI data. Recovery of the speech function, to a certain degree, occurred in all patients, but no clear correlation with fMRI data was found. Complex fMRI and neuropsychological studies in 20 patients after resection of frontal and temporal lobe tumors revealed individual features of speech system reorganization within one year follow-up. Probably, activation of right-sided homologues of the speech areas in the presence of left hemisphere tumors depends not only on the severity of speech disorder but also reflects individual involvement of the right hemisphere in enabling speech function. This is confirmed by right-sided activation, according to the fMRI data, in right-sided patients without aphasia and, conversely, the lack of activation of right-sided homologues of the speech areas in several patients with severe postoperative speech disorders during the entire follow-up period.

Full image-processing pipeline in field-programmable gate array for a small endoscopic camera

NASA Astrophysics Data System (ADS)

Mostafa, Sheikh Shanawaz; Sousa, L. Natércia; Ferreira, Nuno Fábio; Sousa, Ricardo M.; Santos, Joao; Wäny, Martin; Morgado-Dias, F.

2017-01-01

Endoscopy is an imaging procedure used for diagnosis as well as for some surgical purposes. The camera used for the endoscopy should be small and able to produce a good quality image or video, to reduce discomfort of the patients, and to increase the efficiency of the medical team. To achieve these fundamental goals, a small endoscopy camera with a footprint of 1 mm×1 mm×1.65 mm is used. Due to the physical properties of the sensors and human vision system limitations, different image-processing algorithms, such as noise reduction, demosaicking, and gamma correction, among others, are needed to faithfully reproduce the image or video. A full image-processing pipeline is implemented using a field-programmable gate array (FPGA) to accomplish a high frame rate of 60 fps with minimum processing delay. Along with this, a viewer has also been developed to display and control the image-processing pipeline. The control and data transfer are done by a USB 3.0 end point in the computer. The full developed system achieves real-time processing of the image and fits in a Xilinx Spartan-6LX150 FPGA.

78 FR 35658 - Spectra Energy Corp., Application for a New or Amended Presidential Permit

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-13

... transactions. Spectra Energy owns and operates a large diversified portfolio of natural gas-related energy assets in the areas of gathering and processing, transmission, and distribution. Its natural gas pipeline..., to Caster, Wyoming and includes five pump stations. The Express Pipeline has been in operation since...

49 CFR 192.227 - Qualification of welders.

Code of Federal Regulations, 2010 CFR

2010-10-01

... BY PIPELINE: MINIMUM FEDERAL SAFETY STANDARDS Welding of Steel in Pipelines § 192.227 Qualification... earlier edition. (b) A welder may qualify to perform welding on pipe to be operated at a pressure that... process to be used, under the test set forth in section I of Appendix C of this part. Each welder who is...

Disrupting the Pipeline: The Role of School Leadership in Mitigating Exclusion and Criminalization of Students

ERIC Educational Resources Information Center

Wilson, Michael G.

2013-01-01

Recently, the effects of school exclusion and criminalization of youth misbehavior has garnered much attention from the research community. The process associated with school exclusion and criminalization has been described popularly as a school to prison pipeline (STPP). Studies of school exclusion and criminalization repeatedly report evidence…

Improved Photometry for the DASCH Pipeline

NASA Astrophysics Data System (ADS)

Tang, Sumin; Grindlay, Jonathan; Los, Edward; Servillat, Mathieu

2013-07-01

The Digital Access to a Sky Century@Harvard (DASCH) project is digitizing the ˜500,000 glass plate images obtained (full sky) by the Harvard College Observatory from 1885 to 1992. Astrometry and photometry for each resolved object are derived with photometric rms values of ˜0.15 mag for the initial photometry analysis pipeline. Here we describe new developments for DASCH photometry, applied to the Kepler field, that have yielded further improvements, including better identification of image blends and plate defects by measuring image profiles and astrometric deviations. A local calibration procedure using nearby stars in a similar magnitude range as the program star (similar to what has been done for visual photometry from the plates) yields additional improvement for a net photometric rms of ˜0.1 mag. We also describe statistical measures of light curves that are now used in the DASCH pipeline processing to identify new variables autonomously. The DASCH photometry methods described here are used in the pipeline processing for the data releases of DASCH data,5 as well as for a forthcoming paper on the long-term variables discovered by DASCH in the Kepler field.

Accelerating root system phenotyping of seedlings through a computer-assisted processing pipeline.

PubMed

Dupuy, Lionel X; Wright, Gladys; Thompson, Jacqueline A; Taylor, Anna; Dekeyser, Sebastien; White, Christopher P; Thomas, William T B; Nightingale, Mark; Hammond, John P; Graham, Neil S; Thomas, Catherine L; Broadley, Martin R; White, Philip J

2017-01-01

There are numerous systems and techniques to measure the growth of plant roots. However, phenotyping large numbers of plant roots for breeding and genetic analyses remains challenging. One major difficulty is to achieve high throughput and resolution at a reasonable cost per plant sample. Here we describe a cost-effective root phenotyping pipeline, on which we perform time and accuracy benchmarking to identify bottlenecks in such pipelines and strategies for their acceleration. Our root phenotyping pipeline was assembled with custom software and low cost material and equipment. Results show that sample preparation and handling of samples during screening are the most time consuming task in root phenotyping. Algorithms can be used to speed up the extraction of root traits from image data, but when applied to large numbers of images, there is a trade-off between time of processing the data and errors contained in the database. Scaling-up root phenotyping to large numbers of genotypes will require not only automation of sample preparation and sample handling, but also efficient algorithms for error detection for more reliable replacement of manual interventions.

Dynamic 2D self-phase-map Nyquist ghost correction for simultaneous multi-slice echo planar imaging.

PubMed

Yarach, Uten; Tung, Yi-Hang; Setsompop, Kawin; In, Myung-Ho; Chatnuntawech, Itthi; Yakupov, Renat; Godenschweger, Frank; Speck, Oliver

2018-02-09

To develop a reconstruction pipeline that intrinsically accounts for both simultaneous multislice echo planar imaging (SMS-EPI) reconstruction and dynamic slice-specific Nyquist ghosting correction in time-series data. After 1D slice-group average phase correction, the separate polarity (i.e., even and odd echoes) SMS-EPI data were unaliased by slice GeneRalized Autocalibrating Partial Parallel Acquisition. Both the slice-unaliased even and odd echoes were jointly reconstructed using a model-based framework, extended for SMS-EPI reconstruction that estimates a 2D self-phase map, corrects dynamic slice-specific phase errors, and combines data from all coils and echoes to obtain the final images. The percentage ghost-to-signal ratios (%GSRs) and its temporal variations for MB3R y 2 with a field of view/4 shift in a human brain obtained by the proposed dynamic 2D and standard 1D phase corrections were 1.37 ± 0.11 and 2.66 ± 0.16, respectively. Even with a large regularization parameter λ applied in the proposed reconstruction, the smoothing effect in fMRI activation maps was comparable to a very small Gaussian kernel size 1 × 1 × 1 mm 3 . The proposed reconstruction pipeline reduced slice-specific phase errors in SMS-EPI, resulting in reduction of GSR. It is applicable for functional MRI studies because the smoothing effect caused by the regularization parameter selection can be minimal in a blood-oxygen-level-dependent activation map. © 2018 International Society for Magnetic Resonance in Medicine.

Grid Computing Application for Brain Magnetic Resonance Image Processing

NASA Astrophysics Data System (ADS)

Valdivia, F.; Crépeault, B.; Duchesne, S.

2012-02-01

This work emphasizes the use of grid computing and web technology for automatic post-processing of brain magnetic resonance images (MRI) in the context of neuropsychiatric (Alzheimer's disease) research. Post-acquisition image processing is achieved through the interconnection of several individual processes into pipelines. Each process has input and output data ports, options and execution parameters, and performs single tasks such as: a) extracting individual image attributes (e.g. dimensions, orientation, center of mass), b) performing image transformations (e.g. scaling, rotation, skewing, intensity standardization, linear and non-linear registration), c) performing image statistical analyses, and d) producing the necessary quality control images and/or files for user review. The pipelines are built to perform specific sequences of tasks on the alphanumeric data and MRIs contained in our database. The web application is coded in PHP and allows the creation of scripts to create, store and execute pipelines and their instances either on our local cluster or on high-performance computing platforms. To run an instance on an external cluster, the web application opens a communication tunnel through which it copies the necessary files, submits the execution commands and collects the results. We present result on system tests for the processing of a set of 821 brain MRIs from the Alzheimer's Disease Neuroimaging Initiative study via a nonlinear registration pipeline composed of 10 processes. Our results show successful execution on both local and external clusters, and a 4-fold increase in performance if using the external cluster. However, the latter's performance does not scale linearly as queue waiting times and execution overhead increase with the number of tasks to be executed.

The Chandra Source Catalog: Processing and Infrastructure

NASA Astrophysics Data System (ADS)

Evans, Janet; Evans, Ian N.; Glotfelty, Kenny J.; Hain, Roger; Hall, Diane M.; Miller, Joseph B.; Plummer, David A.; Zografou, Panagoula; Primini, Francis A.; Anderson, Craig S.; Bonaventura, Nina R.; Chen, Judy C.; Davis, John E.; Doe, Stephen M.; Fabbiano, Giuseppina; Galle, Elizabeth C.; Gibbs, Danny G., II; Grier, John D.; Harbo, Peter N.; He, Xiang Qun (Helen); Houck, John C.; Karovska, Margarita; Kashyap, Vinay L.; Lauer, Jennifer; McCollough, Michael L.; McDowell, Jonathan C.; Mitschang, Arik W.; Morgan, Douglas L.; Mossman, Amy E.; Nichols, Joy S.; Nowak, Michael A.; Refsdal, Brian L.; Rots, Arnold H.; Siemiginowska, Aneta L.; Sundheim, Beth A.; Tibbetts, Michael S.; van Stone, David W.; Winkelman, Sherry L.

2009-09-01

Chandra Source Catalog processing recalibrates each observation using the latest available calibration data, and employs a wavelet-based source detection algorithm to identify all the X-ray sources in the field of view. Source properties are then extracted from each detected source that is a candidate for inclusion in the catalog. Catalog processing is completed by matching sources across multiple observations, merging common detections, and applying quality assurance checks. The Chandra Source Catalog processing system shares a common processing infrastructure and utilizes much of the functionality that is built into the Standard Data Processing (SDP) pipeline system that provides calibrated Chandra data to end-users. Other key components of the catalog processing system have been assembled from the portable CIAO data analysis package. Minimal new software tool development has been required to support the science algorithms needed for catalog production. Since processing pipelines must be instantiated for each detected source, the number of pipelines that are run during catalog construction is a factor of order 100 times larger than for SDP. The increased computational load, and inherent parallel nature of the processing, is handled by distributing the workload across a multi-node Beowulf cluster. Modifications to the SDP automated processing application to support catalog processing, and extensions to Chandra Data Archive software to ingest and retrieve catalog products, complete the upgrades to the infrastructure to support catalog processing.

Processing of subliminal facial expressions of emotion: a behavioral and fMRI study.

PubMed

Prochnow, D; Kossack, H; Brunheim, S; Müller, K; Wittsack, H-J; Markowitsch, H-J; Seitz, R J

2013-01-01

The recognition of emotional facial expressions is an important means to adjust behavior in social interactions. As facial expressions widely differ in their duration and degree of expressiveness, they often manifest with short and transient expressions below the level of awareness. In this combined behavioral and fMRI study, we aimed at examining whether or not consciously accessible (subliminal) emotional facial expressions influence empathic judgments and which brain activations are related to it. We hypothesized that subliminal facial expressions of emotions masked with neutral expressions of the same faces induce an empathic processing similar to consciously accessible (supraliminal) facial expressions. Our behavioral data in 23 healthy subjects showed that subliminal emotional facial expressions of 40 ms duration affect the judgments of the subsequent neutral facial expressions. In the fMRI study in 12 healthy subjects it was found that both, supra- and subliminal emotional facial expressions shared a widespread network of brain areas including the fusiform gyrus, the temporo-parietal junction, and the inferior, dorsolateral, and medial frontal cortex. Compared with subliminal facial expressions, supraliminal facial expressions led to a greater activation of left occipital and fusiform face areas. We conclude that masked subliminal emotional information is suited to trigger processing in brain areas which have been implicated in empathy and, thereby in social encounters.

Exposure to subliminal arousing stimuli induces robust activation in the amygdala, hippocampus, anterior cingulate, insular cortex and primary visual cortex: a systematic meta-analysis of fMRI studies.

PubMed

Brooks, S J; Savov, V; Allzén, E; Benedict, C; Fredriksson, R; Schiöth, H B

2012-02-01

Functional Magnetic Resonance Imaging (fMRI) demonstrates that the subliminal presentation of arousing stimuli can activate subcortical brain regions independently of consciousness-generating top-down cortical modulation loops. Delineating these processes may elucidate mechanisms for arousal, aberration in which may underlie some psychiatric conditions. Here we are the first to review and discuss four Activation Likelihood Estimation (ALE) meta-analyses of fMRI studies using subliminal paradigms. We find a maximum of 9 out of 12 studies using subliminal presentation of faces contributing to activation of the amygdala, and also a significantly high number of studies reporting activation in the bilateral anterior cingulate, bilateral insular cortex, hippocampus and primary visual cortex. Subliminal faces are the strongest modality, whereas lexical stimuli are the weakest. Meta-analyses independent of studies using Regions of Interest (ROI) revealed no biasing effect. Core neuronal arousal in the brain, which may be at first independent of conscious processing, potentially involves a network incorporating primary visual areas, somatosensory, implicit memory and conflict monitoring regions. These data could provide candidate brain regions for the study of psychiatric disorders associated with aberrant automatic emotional processing. Copyright © 2011 Elsevier Inc. All rights reserved.

Patterns of cerebral activation during lexical and phonological reading in Portuguese.

PubMed

Senaha, M L H; Martin, M G M; Amaro, E; Campi, C; Caramelli, P

2005-12-01

According to the concepts of cognitive neuropsychology, there are two principal routes of reading processing: a lexical route, in which global reading of words occurs and a phonological route, responsible for the conversion of the graphemes into their respective phonemes. In the present study, functional magnetic resonance imaging (fMRI) was used to investigate the patterns of cerebral activation in lexical and phonological reading by 13 healthy women with a formal educational level greater than 11 years. Participants were submitted to a silent reading task containing three types of stimuli: real words (irregular and foreign words), nonwords and illegitimate graphic stimuli. An increased number of activated voxels were identified by fMRI in the word reading (lexical processing) than in the nonword reading (phonological processing) task. In word reading, activation was greater than for nonwords in the following areas: superior, middle and inferior frontal gyri, and bilateral superior temporal gyrus, right cerebellum and the left precentral gyrus, as indicated by fMRI. In the reading of nonwords, the activation was predominant in the right cerebellum and in the left superior temporal gyrus. The results of the present study suggest the existence of differences in the patterns of cerebral activation during lexical and phonological reading, with greater involvement of the right hemisphere in reading words than nonwords.

Have we been asking the right questions when assessing response inhibition in go/no-go tasks with fMRI? A meta-analysis and critical review.

PubMed

Criaud, Marion; Boulinguez, Philippe

2013-01-01

The popular go/no-go paradigm is supposed to ensure a reliable probing of response inhibition mechanisms. Functional magnetic resonance imaging (fMRI) studies have repeatedly found a large number of structures, usually including a right lateralized parieto-frontal network and the pre-supplementary motor area (pre-SMA). However, it is unlikely that all these regions are directly related to the mechanism that actively suppresses the motor command. Since most go/no-go designs involve complex stimulus identification/detection processes, these activations may rather reflect the engagement of different cognitive processes that are intrinsically related and quite difficult to disentangle. The current critical review is based on repeated meta-analyses of 30 go/no-go fMRI experiments using the Activation Likelihood Estimate method to contrast studies using simple vs. complex stimuli. The results show that most of the activity typically elicited by no-go signals, including pre-SMA hemodynamic response, is actually driven by the engagement of high attentional or working memory resources, not by inhibitory processes per se. Implications for current methods and theories of inhibitory control are discussed, and new lines of inquiry are proposed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Characterization of functional brain activity and connectivity using EEG and fMRI in patients with sickle cell disease.

PubMed

Case, Michelle; Zhang, Huishi; Mundahl, John; Datta, Yvonne; Nelson, Stephen; Gupta, Kalpna; He, Bin

2017-01-01

Sickle cell disease (SCD) is a red blood cell disorder that causes many complications including life-long pain. Treatment of pain remains challenging due to a poor understanding of the mechanisms and limitations to characterize and quantify pain. In the present study, we examined simultaneously recording functional MRI (fMRI) and electroencephalogram (EEG) to better understand neural connectivity as a consequence of chronic pain in SCD patients. We performed independent component analysis and seed-based connectivity on fMRI data. Spontaneous power and microstate analysis was performed on EEG-fMRI data. ICA analysis showed that patients lacked activity in the default mode network (DMN) and executive control network compared to controls. EEG-fMRI data revealed that the insula cortex's role in salience increases with age in patients. EEG microstate analysis showed patients had increased activity in pain processing regions. The cerebellum in patients showed a stronger connection to the periaqueductal gray matter (involved in pain inhibition), and negative connections to pain processing areas. These results suggest that patients have reduced activity of DMN and increased activity in pain processing regions during rest. The present findings suggest resting state connectivity differences between patients and controls can be used as novel biomarkers of SCD pain.

Residual fMRI sensitivity for identity changes in acquired prosopagnosia.

PubMed

Fox, Christopher J; Iaria, Giuseppe; Duchaine, Bradley C; Barton, Jason J S

2013-01-01

While a network of cortical regions contribute to face processing, the lesions in acquired prosopagnosia are highly variable, and likely result in different combinations of spared and affected regions of this network. To assess the residual functional sensitivities of spared regions in prosopagnosia, we designed a rapid event-related functional magnetic resonance imaging (fMRI) experiment that included pairs of faces with same or different identities and same or different expressions. By measuring the release from adaptation to these facial changes we determined the residual sensitivity of face-selective regions-of-interest. We tested three patients with acquired prosopagnosia, and all three of these patients demonstrated residual sensitivity for facial identity changes in surviving fusiform and occipital face areas of either the right or left hemisphere, but not in the right posterior superior temporal sulcus. The patients also showed some residual capabilities for facial discrimination with normal performance on the Benton Facial Recognition Test, but impaired performance on more complex tasks of facial discrimination. We conclude that fMRI can demonstrate residual processing of facial identity in acquired prosopagnosia, that this adaptation can occur in the same structures that show similar processing in healthy subjects, and further, that this adaptation may be related to behavioral indices of face perception.

Cross-classification of musical and vocal emotions in the auditory cortex.

PubMed

Paquette, Sébastien; Takerkart, Sylvain; Saget, Shinji; Peretz, Isabelle; Belin, Pascal

2018-05-09

Whether emotions carried by voice and music are processed by the brain using similar mechanisms has long been investigated. Yet neuroimaging studies do not provide a clear picture, mainly due to lack of control over stimuli. Here, we report a functional magnetic resonance imaging (fMRI) study using comparable stimulus material in the voice and music domains-the Montreal Affective Voices and the Musical Emotional Bursts-which include nonverbal short bursts of happiness, fear, sadness, and neutral expressions. We use a multivariate emotion-classification fMRI analysis involving cross-timbre classification as a means of comparing the neural mechanisms involved in processing emotional information in the two domains. We find, for affective stimuli in the violin, clarinet, or voice timbres, that local fMRI patterns in the bilateral auditory cortex and upper premotor regions support above-chance emotion classification when training and testing sets are performed within the same timbre category. More importantly, classifier performance generalized well across timbre in cross-classifying schemes, albeit with a slight accuracy drop when crossing the voice-music boundary, providing evidence for a shared neural code for processing musical and vocal emotions, with possibly a cost for the voice due to its evolutionary significance. © 2018 New York Academy of Sciences.

Residual fMRI sensitivity for identity changes in acquired prosopagnosia

PubMed Central

Fox, Christopher J.; Iaria, Giuseppe; Duchaine, Bradley C.; Barton, Jason J. S.

2013-01-01

While a network of cortical regions contribute to face processing, the lesions in acquired prosopagnosia are highly variable, and likely result in different combinations of spared and affected regions of this network. To assess the residual functional sensitivities of spared regions in prosopagnosia, we designed a rapid event-related functional magnetic resonance imaging (fMRI) experiment that included pairs of faces with same or different identities and same or different expressions. By measuring the release from adaptation to these facial changes we determined the residual sensitivity of face-selective regions-of-interest. We tested three patients with acquired prosopagnosia, and all three of these patients demonstrated residual sensitivity for facial identity changes in surviving fusiform and occipital face areas of either the right or left hemisphere, but not in the right posterior superior temporal sulcus. The patients also showed some residual capabilities for facial discrimination with normal performance on the Benton Facial Recognition Test, but impaired performance on more complex tasks of facial discrimination. We conclude that fMRI can demonstrate residual processing of facial identity in acquired prosopagnosia, that this adaptation can occur in the same structures that show similar processing in healthy subjects, and further, that this adaptation may be related to behavioral indices of face perception. PMID:24151479

Neuroimaging studies of practice-related change: fMRI and meta-analytic evidence of a domain-general control network for learning.

PubMed

Chein, Jason M; Schneider, Walter

2005-12-01

Functional magnetic resonance imaging and a meta-analysis of prior neuroimaging studies were used to characterize cortical changes resulting from extensive practice and to evaluate a dual-processing account of the neural mechanisms underlying human learning. Three core predictions of the dual processing theory are evaluated: 1) that practice elicits generalized reductions in regional activity by reducing the load on the cognitive control mechanisms that scaffold early learning; 2) that these control mechanisms are domain-general; and 3) that no separate processing pathway emerges as skill develops. To evaluate these predictions, a meta-analysis of prior neuroimaging studies and a within-subjects fMRI experiment contrasting unpracticed to practiced performance in a paired-associate task were conducted. The principal effect of practice was found to be a reduction in the extent and magnitude of activity in a cortical network spanning bilateral dorsal prefrontal, left ventral prefrontal, medial frontal (anterior cingulate), left insular, bilateral parietal, and occipito-temporal (fusiform) areas. These activity reductions are shown to occur in common regions across prior neuroimaging studies and for both verbal and nonverbal paired-associate learning in the present fMRI experiment. The implicated network of brain regions is interpreted as a domain-general system engaged specifically to support novice, but not practiced, performance.

Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification.

PubMed

Lee, Dongha; Jang, Changwon; Park, Hae-Jeong

2015-03-01

Signal drift in functional magnetic resonance imaging (fMRI) is an unavoidable artifact that limits classification performance in multi-voxel pattern analysis of fMRI. As conventional methods to reduce signal drift, global demeaning or proportional scaling disregards regional variations of drift, whereas voxel-wise univariate detrending is too sensitive to noisy fluctuations. To overcome these drawbacks, we propose a multivariate real-time detrending method for multiclass classification that involves spatial demeaning at each scan and the recursive detrending of drifts in the classifier outputs driven by a multiclass linear support vector machine. Experiments using binary and multiclass data showed that the linear trend estimation of the classifier output drift for each class (a weighted sum of drifts in the class-specific voxels) was more robust against voxel-wise artifacts that lead to inconsistent spatial patterns and the effect of online processing than voxel-wise detrending. The classification performance of the proposed method was significantly better, especially for multiclass data, than that of voxel-wise linear detrending, global demeaning, and classifier output detrending without demeaning. We concluded that the multivariate approach using classifier output detrending of fMRI signals with spatial demeaning preserves spatial patterns, is less sensitive than conventional methods to sample size, and increases classification performance, which is a useful feature for real-time fMRI classification. Copyright © 2014 Elsevier Inc. All rights reserved.

Resting-State fMRI Activity Predicts Unsupervised Learning and Memory in an Immersive Virtual Reality Environment

PubMed Central

Wong, Chi Wah; Olafsson, Valur; Plank, Markus; Snider, Joseph; Halgren, Eric; Poizner, Howard; Liu, Thomas T.

2014-01-01

In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment. PMID:25286145

Brain activity underlying auditory perceptual learning during short period training: simultaneous fMRI and EEG recording

PubMed Central

2013-01-01

Background There is an accumulating body of evidence indicating that neuronal functional specificity to basic sensory stimulation is mutable and subject to experience. Although fMRI experiments have investigated changes in brain activity after relative to before perceptual learning, brain activity during perceptual learning has not been explored. This work investigated brain activity related to auditory frequency discrimination learning using a variational Bayesian approach for source localization, during simultaneous EEG and fMRI recording. We investigated whether the practice effects are determined solely by activity in stimulus-driven mechanisms or whether high-level attentional mechanisms, which are linked to the perceptual task, control the learning process. Results The results of fMRI analyses revealed significant attention and learning related activity in left and right superior temporal gyrus STG as well as the left inferior frontal gyrus IFG. Current source localization of simultaneously recorded EEG data was estimated using a variational Bayesian method. Analysis of current localized to the left inferior frontal gyrus and the right superior temporal gyrus revealed gamma band activity correlated with behavioral performance. Conclusions Rapid improvement in task performance is accompanied by plastic changes in the sensory cortex as well as superior areas gated by selective attention. Together the fMRI and EEG results suggest that gamma band activity in the right STG and left IFG plays an important role during perceptual learning. PMID:23316957

Functional brain activation differences in stuttering identified with a rapid fMRI sequence

PubMed Central

Kraft, Shelly Jo; Choo, Ai Leen; Sharma, Harish; Ambrose, Nicoline G.

2011-01-01

The purpose of this study was to investigate whether brain activity related to the presence of stuttering can be identified with rapid functional MRI (fMRI) sequences that involved overt and covert speech processing tasks. The long-term goal is to develop sensitive fMRI approaches with developmentally appropriate tasks to identify deviant speech motor and auditory brain activity in children who stutter closer to the age at which recovery from stuttering is documented. Rapid sequences may be preferred for individuals or populations who do not tolerate long scanning sessions. In this report, we document the application of a picture naming and phoneme monitoring task in three minute fMRI sequences with adults who stutter (AWS). If relevant brain differences are found in AWS with these approaches that conform to previous reports, then these approaches can be extended to younger populations. Pairwise contrasts of brain BOLD activity between AWS and normally fluent adults indicated the AWS showed higher BOLD activity in the right inferior frontal gyrus (IFG), right temporal lobe and sensorimotor cortices during picture naming and and higher activity in the right IFG during phoneme monitoring. The right lateralized pattern of BOLD activity together with higher activity in sensorimotor cortices is consistent with previous reports, which indicates rapid fMRI sequences can be considered for investigating stuttering in younger participants. PMID:22133409

Distortion correction for diffusion-weighted MRI tractography and fMRI in the temporal lobes.

PubMed

Embleton, Karl V; Haroon, Hamied A; Morris, David M; Ralph, Matthew A Lambon; Parker, Geoff J M

2010-10-01

Single shot echo-planar imaging (EPI) sequences are currently the most commonly used sequences for diffusion-weighted imaging (DWI) and functional magnetic resonance imaging (fMRI) as they allow relatively high signal to noise with rapid acquisition time. A major drawback of EPI is the substantial geometric distortion and signal loss that can occur due to magnetic field inhomogeneities close to air-tissue boundaries. If DWI-based tractography and fMRI are to be applied to these regions, then the distortions must be accurately corrected to achieve meaningful results. We describe robust acquisition and processing methods for correcting such distortions in spin echo (SE) EPI using a variant of the reversed direction k space traversal method with a number of novel additions. We demonstrate that dual direction k space traversal with maintained diffusion-encoding gradient strength and direction results in correction of the great majority of eddy current-associated distortions in DWI, in addition to those created by variations in magnetic susceptibility. We also provide examples to demonstrate that the presence of severe distortions cannot be ignored if meaningful tractography results are desired. The distortion correction routine was applied to SE-EPI fMRI acquisitions and allowed detection of activation in the temporal lobe that had been previously found using PET but not conventional fMRI. © 2010 Wiley-Liss, Inc.

Use of Preoperative Functional MRI to Predict Verbal Memory Decline After Temporal Lobe Epilepsy Surgery

PubMed Central

Binder, Jeffrey R.; Sabsevitz, David S.; Swanson, Sara J.; Hammeke, Thomas A.; Raghavan, Manoj; Mueller, Wade M.

2010-01-01

Purpose Verbal memory decline is a frequent complication of left anterior temporal lobectomy (L-ATL). The goal of this study was to determine whether preoperative language mapping using functional magnetic resonance imaging (fMRI) is useful for predicting which patients are likely to experience verbal memory decline after L-ATL. Methods Sixty L-ATL patients underwent preoperative language mapping with fMRI, preoperative intracarotid amobarbital (Wada) testing for language and memory lateralization, and pre- and postoperative neuropsychological testing. Demographic, historical, neuropsychological, and imaging variables were examined for their ability to predict pre- to postoperative memory change. Results Verbal memory decline occurred in over 30% of patients. Good preoperative performance, late age at onset of epilepsy, left dominance on fMRI, and left dominance on the Wada test were each predictive of memory decline. Preoperative performance and age at onset together accounted for roughly 50% of the variance in memory outcome (p < .001), and fMRI explained an additional 10% of this variance (p ≤ .003). Neither Wada memory asymmetry nor Wada language asymmetry added additional predictive power beyond these noninvasive measures. Discussion Preoperative fMRI is useful for identifying patients at high risk for verbal memory decline prior to L-ATL surgery. Lateralization of language is correlated with lateralization of verbal memory, whereas Wada memory testing is either insufficiently reliable or insufficiently material-specific to accurately localize verbal memory processes. PMID:18435753

BOLD fMRI and DTI in strabismic amblyopes following occlusion therapy.

PubMed

Gupta, Shikha; Kumaran, Senthil S; Saxena, Rohit; Gudwani, Sunita; Menon, Vimala; Sharma, Pradeep

2016-08-01

Evaluation of brain cluster activation using the functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) was sought in strabismic amblyopes. In this hospital-based case-control cross-sectional study, fMRI and DTI were conducted in strabismic amblyopes before initiation of any therapy and after visual recovery following the administration of occlusion therapy. FMRI was performed in 10 strabismic amblyopic subjects (baseline group) and in 5 left strabismic amblyopic children post-occlusion therapy after two-line visual improvement. Ten age-matched healthy children with right ocular dominance formed control group. Structural and functional MRI was carried out on 1.5T MR scanner. The visual task consisted of 8 Hz flickering checkerboard with red dot and occasional green dot. Blood-oxygen-level-dependent (BOLD) fMRI was analyzed using statistical parametric mapping and DTI on NordicIce (NordicNeuroLab) softwares. Reduced occipital activation was elicited when viewing with the amblyopic eye in amblyopes. An 'ipsilateral to viewing eye' pattern of calcarine BOLD activation was observed in controls and left amblyopes. Activation of cortical areas associated with visual processing differed in relation to the viewing eye. Following visual recovery on occlusion therapy, enhanced activity in bilateral hemispheres in striate as well as extrastriate regions when viewing with either eye was seen. Improvement in visual acuity following occlusion therapy correlates with hemodynamic activity in amblyopes.

Comparative coal transportation costs: an economic and engineering analysis of truck, belt, rail, barge and coal slurry and pneumatic pipelines. Volume 3. Coal slurry pipelines. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rieber, M.; Soo, S.L.

1977-08-01

A coal slurry pipeline system requires that the coal go through a number of processing stages before it is used by the power plant. Once mined, the coal is delivered to a preparation plant where it is pulverized to sizes between 18 and 325 mesh and then suspended in about an equal weight of water. This 50-50 slurry mixture has a consistency approximating toothpaste. It is pushed through the pipeline via electric pumping stations 70 to 100 miles apart. Flow velocity through the line must be maintained within a narrow range. For example, if a 3.5 mph design is usedmore » at 5 mph, the system must be able to withstand double the horsepower, peak pressure, and wear. Minimum flowrate must be maintained to avoid particle settling and plugging. However, in general, once a pipeline system has been designed, because of economic considerations on the one hand and design limits on the other, flowrate is rather inflexible. Pipelines that have a slowly moving throughput and a water carrier may be subject to freezing in northern areas during periods of severe cold. One of the problems associated with slurry pipeline analyses is the lack of operating experience.« less

ToTem: a tool for variant calling pipeline optimization.

PubMed

Tom, Nikola; Tom, Ondrej; Malcikova, Jitka; Pavlova, Sarka; Kubesova, Blanka; Rausch, Tobias; Kolarik, Miroslav; Benes, Vladimir; Bystry, Vojtech; Pospisilova, Sarka

2018-06-26

High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user's priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data. ToTem is a tool for automated pipeline optimization which is freely available as a web application at  https://totem.software .

Ultrasonic wave based pressure measurement in small diameter pipeline.

PubMed

Wang, Dan; Song, Zhengxiang; Wu, Yuan; Jiang, Yuan

2015-12-01

An effective non-intrusive method of ultrasound-based technique that allows monitoring liquid pressure in small diameter pipeline (less than 10mm) is presented in this paper. Ultrasonic wave could penetrate medium, through the acquisition of representative information from the echoes, properties of medium can be reflected. This pressure measurement is difficult due to that echoes' information is not easy to obtain in small diameter pipeline. The proposed method is a study on pipeline with Kneser liquid and is based on the principle that the transmission speed of ultrasonic wave in pipeline liquid correlates with liquid pressure and transmission speed of ultrasonic wave in pipeline liquid is reflected through ultrasonic propagation time providing that acoustic distance is fixed. Therefore, variation of ultrasonic propagation time can reflect variation of pressure in pipeline. Ultrasonic propagation time is obtained by electric processing approach and is accurately measured to nanosecond through high resolution time measurement module. We used ultrasonic propagation time difference to reflect actual pressure in this paper to reduce the environmental influences. The corresponding pressure values are finally obtained by acquiring the relationship between variation of ultrasonic propagation time difference and pressure with the use of neural network analysis method, the results show that this method is accurate and can be used in practice. Copyright © 2015 Elsevier B.V. All rights reserved.

Nanosurveyor: a framework for real-time data processing

DOE PAGES

Daurer, Benedikt J.; Krishnan, Hari; Perciano, Talita; ...

2017-01-31

Background: The ever improving brightness of accelerator based sources is enabling novel observations and discoveries with faster frame rates, larger fields of view, higher resolution, and higher dimensionality. Results: Here we present an integrated software/algorithmic framework designed to capitalize on high-throughput experiments through efficient kernels, load-balanced workflows, which are scalable in design. We describe the streamlined processing pipeline of ptychography data analysis. Conclusions: The pipeline provides throughput, compression, and resolution as well as rapid feedback to the microscope operators.

Workflows for microarray data processing in the Kepler environment.

PubMed

Stropp, Thomas; McPhillips, Timothy; Ludäscher, Bertram; Bieda, Mark

2012-05-17

Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or R/BioConductor scripting approaches to pipeline design. Finally, we suggest that microarray data processing task workflows may provide a basis for future example-based comparison of different workflow systems. We provide a set of tools and complete workflows for microarray data analysis in the Kepler environment, which has the advantages of offering graphical, clear display of conceptual steps and parameters and the ability to easily integrate other resources such as remote data and web services.