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Neuroinformatics

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https://www.readbyqxmd.com/read/28447297/generating-neuron-geometries-for-detailed-three-dimensional-simulations-using-anamorph
#1
Konstantin Mörschel, Markus Breit, Gillian Queisser
Generating realistic and complex computational domains for numerical simulations is often a challenging task. In neuroscientific research, more and more one-dimensional morphology data is becoming publicly available through databases. This data, however, only contains point and diameter information not suitable for detailed three-dimensional simulations. In this paper, we present a novel framework, AnaMorph, that automatically generates water-tight surface meshes from one-dimensional point-diameter files. These surface triangulations can be used to simulate the electrical and biochemical behavior of the underlying cell...
April 26, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/28417316/a-web-resource-for-levodopa-induced-dyskinesia-genetics-in-parkinson-s-disease
#2
Hagen Blankenburg, Marika Falla, Christine Schwienbacher, Giovanni Fabbrini, Alfredo Berardelli, Peter P Pramstaller, Francisco S Domingues
No abstract text is available yet for this article.
April 17, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/28378263/improved-automatic-segmentation-of-white-matter-hyperintensities-in-mri-based-on-multilevel-lesion-features
#3
M Rincón, E Díaz-López, P Selnes, K Vegge, M Altmann, T Fladby, A Bjørnerud
Brain white matter hyperintensities (WMHs) are linked to increased risk of cerebrovascular and neurodegenerative diseases among the elderly. Consequently, detection and characterization of WMHs are of significant clinical importance. We propose a novel approach for WMH segmentation from multi-contrast MRI where both voxel-based and lesion-based information are used to improve overall performance in both volume-oriented and object-oriented metrics. Our segmentation method (AMOS-2D) consists of four stages following a "generate-and-test" approach: pre-processing, Gaussian white matter (WM) modelling, hierarchical multi-threshold WMH segmentation and object-based WMH filtering using support vector machines...
April 4, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/28316055/a-comparison-of-accelerated-and-non-accelerated-mri-scans-for-brain-volume-and-boundary-shift-integral-measures-of-volume-change-evidence-from-the-adni-dataset
#4
Emily N Manning, Kelvin K Leung, Jennifer M Nicholas, Ian B Malone, M Jorge Cardoso, Jonathan M Schott, Nick C Fox, Josephine Barnes
The aim of this study was to assess whether the use of accelerated MRI scans in place of non-accelerated scans influenced brain volume and atrophy rate measures in controls and subjects with mild cognitive impairment and Alzheimer's disease. We used data from 861 subjects at baseline, 573 subjects at 6 months and 384 subjects at 12 months from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We calculated whole-brain, ventricular and hippocampal atrophy rates using the k-means boundary shift integral (BSI)...
March 18, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/28210983/multi-view-ensemble-classification-of-brain-connectivity-images-for-neurodegeneration-type-discrimination
#5
Michele Fratello, Giuseppina Caiazzo, Francesca Trojsi, Antonio Russo, Gioacchino Tedeschi, Roberto Tagliaferri, Fabrizio Esposito
Brain connectivity analyses using voxels as features are not robust enough for single-patient classification because of the inter-subject anatomical and functional variability. To construct more robust features, voxels can be aggregated into clusters that are maximally coherent across subjects. Moreover, combining multi-modal neuroimaging and multi-view data integration techniques allows generating multiple independent connectivity features for the same patient. Structural and functional connectivity features were extracted from multi-modal MRI images with a clustering technique, and used for the multi-view classification of different phenotypes of neurodegeneration by an ensemble learning method (random forest)...
February 16, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/28185058/ensemble-neuron-tracer-for-3d-neuron-reconstruction
#6
Ching-Wei Wang, Yu-Ching Lee, Hilmil Pradana, Zhi Zhou, Hanchuan Peng
Tracing of neuron paths is important in neuroscience. Recent studies have shown that it is possible to segment and reconstruct three-dimensional morphology of axons and dendrites using fully automatic neuron tracing methods. A specific tracer may be better than others for a specific dataset, but another tracer could perform better for some other datasets. Ensemble of learners is an effective way to improve learning accuracy in machine learning. We developed automatic ensemble neuron tracers, which consistently perform well on 57 datasets of 5 species collected from 7 laboratories worldwide...
February 9, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/28132187/combining-a-patch-based-approach-with-a-non-rigid-registration-based-label-fusion-method-for-the-hippocampal-segmentation-in-alzheimer-s-disease
#7
Carlos Platero, M Carmen Tobar
We provide and evaluate an open-source software solution for automatically hippocampal segmentation from T1-weighted (T1w) magnetic resonance imaging (MRI). The method is applied for measuring the hippocampal volume, which allows discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and elderly controls (NC). The method is based on a fast patch-based label fusion method, whose selected patches and their weights are calculated from a combination of similarity measures between patches using intensity-based distances and labeling-based distances...
January 28, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/28063108/validation-of-18-f-fdg-pet-single-subject-optimized-spm-procedure-with-different-pet-scanners
#8
Luca Presotto, Tommaso Ballarini, Silvia Paola Caminiti, Valentino Bettinardi, Luigi Gianolli, Daniela Perani
(18)F-fluoro-deoxy-glucose Positron Emission Tomography (FDG-PET) allows early identification of neurodegeneration in dementia. The use of an optimized method based on the SPM software package highly improves diagnostic accuracy. However, the impact of different scanners for data acquisition on the SPM results and the effects of different pools of healthy subjects on the statistical comparison have not been investigated yet. Images from 144 AD patients acquired using six different PET scanners were analysed with an optimized single-subject SPM procedure to identify the typical AD hypometabolism pattern at single subject level...
January 6, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/28058618/time-to-bring-single-neuron-modeling-into-3d
#9
EDITORIAL
Weiliang Chen, Erik De Schutter
No abstract text is available yet for this article.
January 5, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/27873151/a-stereotactic-probabilistic-atlas-for-the-major-cerebral-arteries
#10
Tora Dunås, Anders Wåhlin, Khalid Ambarki, Laleh Zarrinkoob, Jan Malm, Anders Eklund
Improved whole brain angiographic and velocity-sensitive MRI is pushing the boundaries of noninvasively obtained cerebral vascular flow information. The complexity of the information contained in such datasets calls for automated algorithms and pipelines, thus reducing the need of manual analyses by trained radiologists. The objective of this work was to lay the foundation for such automated pipelining by constructing and evaluating a probabilistic atlas describing the shape and location of the major cerebral arteries...
January 2017: Neuroinformatics
https://www.readbyqxmd.com/read/27837401/collection-of-simulated-data-from-a-thalamocortical-network-model
#11
Helena Głąbska, Chaitanya Chintaluri, Daniel K Wójcik
A major challenge in experimental data analysis is the validation of analytical methods in a fully controlled scenario where the justification of the interpretation can be made directly and not just by plausibility. In some sciences, this could be a mathematical proof, yet biological systems usually do not satisfy assumptions of mathematical theorems. One solution is to use simulations of realistic models to generate ground truth data. In neuroscience, creating such data requires plausible models of neural activity, access to high performance computers, expertise and time to prepare and run the simulations, and to process the output...
January 2017: Neuroinformatics
https://www.readbyqxmd.com/read/27722821/fast-automatic-segmentation-of-white-matter-streamlines-based-on-a-multi-subject-bundle-atlas
#12
Nicole Labra, Pamela Guevara, Delphine Duclap, Josselin Houenou, Cyril Poupon, Jean-François Mangin, Miguel Figueroa
This paper presents an algorithm for fast segmentation of white matter bundles from massive dMRI tractography datasets using a multisubject atlas. We use a distance metric to compare streamlines in a subject dataset to labeled centroids in the atlas, and label them using a per-bundle configurable threshold. In order to reduce segmentation time, the algorithm first preprocesses the data using a simplified distance metric to rapidly discard candidate streamlines in multiple stages, while guaranteeing that no false negatives are produced...
January 2017: Neuroinformatics
https://www.readbyqxmd.com/read/27655341/automating-neuron-simulation-deployment-in-cloud-resources
#13
David B Stockton, Fidel Santamaria
Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, cloud computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and cloud resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three clouds: Chameleon Cloud, a hybrid private academic cloud for cloud technology research based on the OpenStack software; Rackspace, a public commercial cloud, also based on OpenStack; and Amazon Elastic Cloud Computing, based on Amazon's proprietary software...
January 2017: Neuroinformatics
https://www.readbyqxmd.com/read/27638650/metric-learning-for-multi-atlas-based-segmentation-of-hippocampus
#14
Hancan Zhu, Hewei Cheng, Xuesong Yang, Yong Fan
Automatic and reliable segmentation of hippocampus from MR brain images is of great importance in studies of neurological diseases, such as epilepsy and Alzheimer's disease. In this paper, we proposed a novel metric learning method to fuse segmentation labels in multi-atlas based image segmentation. Different from current label fusion methods that typically adopt a predefined distance metric model to compute a similarity measure between image patches of atlas images and the image to be segmented, we learn a distance metric model from the atlases to keep image patches of the same structure close to each other while those of different structures are separated...
January 2017: Neuroinformatics
https://www.readbyqxmd.com/read/27628934/spinecreator-a-graphical-user-interface-for-the-creation-of-layered-neural-models
#15
A J Cope, P Richmond, S S James, K Gurney, D J Allerton
There is a growing requirement in computational neuroscience for tools that permit collaborative model building, model sharing, combining existing models into a larger system (multi-scale model integration), and are able to simulate models using a variety of simulation engines and hardware platforms. Layered XML model specification formats solve many of these problems, however they are difficult to write and visualise without tools. Here we describe a new graphical software tool, SpineCreator, which facilitates the creation and visualisation of layered models of point spiking neurons or rate coded neurons without requiring the need for programming...
January 2017: Neuroinformatics
https://www.readbyqxmd.com/read/27585914/classification-of-normal-and-pathological-gait-in-young-children-based-on-foot-pressure-data
#16
Guodong Guo, Keegan Guffey, Wenbin Chen, Paola Pergami
Human gait recognition, an active research topic in computer vision, is generally based on data obtained from images/videos. We applied computer vision technology to classify pathology-related changes in gait in young children using a foot-pressure database collected using the GAITRite walkway system. As foot positioning changes with children's development, we also investigated the possibility of age estimation based on this data. Our results demonstrate that the data collected by the GAITRite system can be used for normal/pathological gait classification...
January 2017: Neuroinformatics
https://www.readbyqxmd.com/read/27585913/erratum-to-multi-atlas-library-for-eliminating-normalization-failures-in-non-human-primates
#17
Joseph A Maldjian, Carol A Shively, Michael A Nader, David P Friedman, Christopher T Whitlow
No abstract text is available yet for this article.
January 2017: Neuroinformatics
https://www.readbyqxmd.com/read/27412029/n3dfix-an-algorithm-for-automatic-removal-of-swelling-artifacts-in-neuronal-reconstructions
#18
Eduardo Conde-Sousa, Peter Szücs, Hanchuan Peng, Paulo Aguiar
It is well established that not only electrophysiology but also morphology plays an important role in shaping the functional properties of neurons. In order to properly quantify morphological features it is first necessary to translate observational histological data into 3-dimensional geometric reconstructions of the neuronal structures. This reconstruction process, independently of being manual or (semi-)automatic, requires several preparation steps (e.g. histological processing) before data acquisition using specialized software...
January 2017: Neuroinformatics
https://www.readbyqxmd.com/read/27928657/multi-domain-transfer-learning-for-early-diagnosis-of-alzheimer-s-disease
#19
Bo Cheng, Mingxia Liu, Dinggang Shen, Zuoyong Li, Daoqiang Zhang
Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer's Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD...
December 7, 2016: Neuroinformatics
https://www.readbyqxmd.com/read/27928656/sparsetracer-the-reconstruction-of-discontinuous-neuronal-morphology-in-noisy-images
#20
Shiwei Li, Hang Zhou, Tingwei Quan, Jing Li, Yuxin Li, Anan Li, Qingming Luo, Hui Gong, Shaoqun Zeng
Digital reconstruction of a single neuron occupies an important position in computational neuroscience. Although many novel methods have been proposed, recent advances in molecular labeling and imaging systems allow for the production of large and complicated neuronal datasets, which pose many challenges for neuron reconstruction, especially when discontinuous neuronal morphology appears in a strong noise environment. Here, we develop a new pipeline to address this challenge. Our pipeline is based on two methods, one is the region-to-region connection (RRC) method for detecting the initial part of a neurite, which can effectively gather local cues, i...
December 7, 2016: Neuroinformatics
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