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Frontiers in Neuroinformatics

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https://www.readbyqxmd.com/read/28620293/a-manual-segmentation-tool-for-three-dimensional-neuron-datasets
#1
Chiara Magliaro, Alejandro L Callara, Nicola Vanello, Arti Ahluwalia
To date, automated or semi-automated software and algorithms for segmentation of neurons from three-dimensional imaging datasets have had limited success. The gold standard for neural segmentation is considered to be the manual isolation performed by an expert. To facilitate the manual isolation of complex objects from image stacks, such as neurons in their native arrangement within the brain, a new Manual Segmentation Tool (ManSegTool) has been developed. ManSegTool allows user to load an image stack, scroll down the images and to manually draw the structures of interest stack-by-stack...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28616008/corrigendum-toolconnect-a-functional-connectivity-toolbox-for-in-vitro-networks
#2
Vito P Pastore, Daniele Poli, Aleksandar Godjoski, Sergio Martinoia, Paolo Massobrio
[This corrects the article on p. 13 in vol. 10, PMID: 27065841.].
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28611620/atpp-a-pipeline-for-automatic-tractography-based-brain-parcellation
#3
Hai Li, Lingzhong Fan, Junjie Zhuo, Jiaojian Wang, Yu Zhang, Zhengyi Yang, Tianzi Jiang
There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resonance imaging in the past two decades. The Brainnetome Atlas published recently is such an atlas that follows the framework of connectivity-based parcellation. However, in the construction of the atlas, the deluge of high resolution multimodal MRI data and time-consuming computation poses challenges and there is still short of publically available tools dedicated to parcellation...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28596730/integration-of-continuous-time-dynamics-in-a-spiking-neural-network-simulator
#4
Jan Hahne, David Dahmen, Jannis Schuecker, Andreas Frommer, Matthias Bolten, Moritz Helias, Markus Diesmann
Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28559808/constructing-neuronal-network-models-in-massively-parallel-environments
#5
Tammo Ippen, Jochen M Eppler, Hans E Plesser, Markus Diesmann
Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28522970/automatic-optimization-of-the-computation-graph-in-the-nengo-neural-network-simulator
#6
Jan Gosmann, Chris Eliasmith
One critical factor limiting the size of neural cognitive models is the time required to simulate such models. To reduce simulation time, specialized hardware is often used. However, such hardware can be costly, not readily available, or require specialized software implementations that are difficult to maintain. Here, we present an algorithm that optimizes the computational graph of the Nengo neural network simulator, allowing simulations to run more quickly on commodity hardware. This is achieved by merging identical operations into single operations and restructuring the accessed data in larger blocks of sequential memory...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28507515/reusable-client-side-javascript-modules-for-immersive-web-based-real-time-collaborative-neuroimage-visualization
#7
Jorge L Bernal-Rusiel, Nicolas Rannou, Randy L Gollub, Steve Pieper, Shawn Murphy, Richard Robertson, Patricia E Grant, Rudolph Pienaar
In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28496407/unsupervised-idealization-of-ion-channel-recordings-by-minimum-description-length-application-to-human-piezo1-channels
#8
Radhakrishnan Gnanasambandam, Morten S Nielsen, Christopher Nicolai, Frederick Sachs, Johannes P Hofgaard, Jakob K Dreyer
Researchers can investigate the mechanistic and molecular basis of many physiological phenomena in cells by analyzing the fundamental properties of single ion channels. These analyses entail recording single channel currents and measuring current amplitudes and transition rates between conductance states. Since most electrophysiological recordings contain noise, the data analysis can proceed by idealizing the recordings to isolate the true currents from the noise. This de-noising can be accomplished with threshold crossing algorithms and Hidden Markov Models, but such procedures generally depend on inputs and supervision by the user, thus requiring some prior knowledge of underlying processes...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28496406/neural-correlates-of-phrase-rhythm-an-eeg-study-of-bipartite-vs-rondo-sonata-form
#9
Arturo Martínez-Rodrigo, Alicia Fernández-Sotos, José Miguel Latorre, José Moncho-Bogani, Antonio Fernández-Caballero
This paper introduces the neural correlates of phrase rhythm. In short, phrase rhythm is the rhythmic aspect of phrase construction and the relationships between phrases. For the sake of establishing the neural correlates, a musical experiment has been designed to induce music-evoked stimuli related to phrase rhythm. Brain activity is monitored through electroencephalography (EEG) by using a brain-computer interface. The power spectral value of each EEG channel is estimated to obtain how power variance distributes as a function of frequency...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28491032/topological-filtering-of-dynamic-functional-brain-networks-unfolds-informative-chronnectomics-a-novel-data-driven-thresholding-scheme-based-on-orthogonal-minimal-spanning-trees-omsts
#10
Stavros I Dimitriadis, Christos Salis, Ioannis Tarnanas, David E Linden
The human brain is a large-scale system of functionally connected brain regions. This system can be modeled as a network, or graph, by dividing the brain into a set of regions, or "nodes," and quantifying the strength of the connections between nodes, or "edges," as the temporal correlation in their patterns of activity. Network analysis, a part of graph theory, provides a set of summary statistics that can be used to describe complex brain networks in a meaningful way. The large-scale organization of the brain has features of complex networks that can be quantified using network measures from graph theory...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28469570/a-framework-for-collaborative-curation-of-neuroscientific-literature
#11
Christian O'Reilly, Elisabetta Iavarone, Sean L Hill
Large models of complex neuronal circuits require specifying numerous parameters, with values that often need to be extracted from the literature, a tedious and error-prone process. To help establishing shareable curated corpora of annotations, we have developed a literature curation framework comprising an annotation format, a Python API (NeuroAnnotation Toolbox; NAT), and a user-friendly graphical interface (NeuroCurator). This framework allows the systematic annotation of relevant statements and model parameters...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28443014/the-topographical-mapping-in-drosophila-central-complex-network-and-its-signal-routing
#12
Po-Yen Chang, Ta-Shun Su, Chi-Tin Shih, Chung-Chuan Lo
Neural networks regulate brain functions by routing signals. Therefore, investigating the detailed organization of a neural circuit at the cellular levels is a crucial step toward understanding the neural mechanisms of brain functions. To study how a complicated neural circuit is organized, we analyzed recently published data on the neural circuit of the Drosophila central complex, a brain structure associated with a variety of functions including sensory integration and coordination of locomotion. We discovered that, except for a small number of "atypical" neuron types, the network structure formed by the identified 194 neuron types can be described by only a few simple mathematical rules...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28443013/pypes-workflows-for-processing-multimodal-neuroimaging-data
#13
Alexandre M Savio, Michael Schutte, Manuel Graña, Igor Yakushev
No abstract text is available yet for this article.
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28428750/applying-an-archetype-based-approach-to-electroencephalography-event-related-potential-experiments-in-the-eegbase-resource
#14
Václav Papež, Roman Mouček
PURPOSE: The purpose of this study is to investigate the feasibility of applying openEHR (an archetype-based approach for electronic health records representation) to modeling data stored in EEGBase, a portal for experimental electroencephalography/event-related potential (EEG/ERP) data management. The study evaluates re-usage of existing openEHR archetypes and proposes a set of new archetypes together with the openEHR templates covering the domain. The main goals of the study are to (i) link existing EEGBase data/metadata and openEHR archetype structures and (ii) propose a new openEHR archetype set describing the EEG/ERP domain since this set of archetypes currently does not exist in public repositories...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28424607/multivariate-analysis-of-18-f-dmfp-pet-data-to-assist-the-diagnosis-of-parkinsonism
#15
Fermín Segovia, Juan M Górriz, Javier Ramírez, Francisco J Martínez-Murcia, Johannes Levin, Madeleine Schuberth, Matthias Brendel, Axel Rominger, Kai Bötzel, Gaëtan Garraux, Christophe Phillips
An early and differential diagnosis of parkinsonian syndromes still remains a challenge mainly due to the similarity of their symptoms during the onset of the disease. Recently, (18)F-Desmethoxyfallypride (DMFP) has been suggested to increase the diagnostic precision as it is an effective radioligand that allows us to analyze post-synaptic dopamine D2/3 receptors. Nevertheless, the analysis of these data is still poorly covered and its use limited. In order to address this challenge, this paper shows a novel model to automatically distinguish idiopathic parkinsonism from non-idiopathic variants using DMFP data...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28408879/comparison-of-in-vivo-and-ex-vivo-mri-for-the-detection-of-structural-abnormalities-in-a-mouse-model-of-tauopathy
#16
Holly E Holmes, Nick M Powell, Da Ma, Ozama Ismail, Ian F Harrison, Jack A Wells, Niall Colgan, James M O'Callaghan, Ross A Johnson, Tracey K Murray, Zeshan Ahmed, Morten Heggenes, Alice Fisher, M Jorge Cardoso, Marc Modat, Michael J O'Neill, Emily C Collins, Elizabeth M C Fisher, Sébastien Ourselin, Mark F Lythgoe
With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28396633/the-open-anatomy-browser-a-collaborative-web-based-viewer-for-interoperable-anatomy-atlases
#17
Michael Halle, Valentin Demeusy, Ron Kikinis
The Open Anatomy Browser (OABrowser) is an open source, web-based, zero-installation anatomy atlas viewer based on current web browser technologies and evolving anatomy atlas interoperability standards. OABrowser displays three-dimensional anatomical models, image cross-sections of labeled structures and source radiological imaging, and a text-based hierarchy of structures. The viewer includes novel collaborative tools: users can save bookmarks of atlas views for later access and exchange those bookmarks with other users, and dynamic shared views allow groups of users can participate in a collaborative interactive atlas viewing session...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28381997/reproducible-large-scale-neuroimaging-studies-with-the-openmole-workflow-management-system
#18
Jonathan Passerat-Palmbach, Romain Reuillon, Mathieu Leclaire, Antonios Makropoulos, Emma C Robinson, Sarah Parisot, Daniel Rueckert
OpenMOLE is a scientific workflow engine with a strong emphasis on workload distribution. Workflows are designed using a high level Domain Specific Language (DSL) built on top of Scala. It exposes natural parallelism constructs to easily delegate the workload resulting from a workflow to a wide range of distributed computing environments. OpenMOLE hides the complexity of designing complex experiments thanks to its DSL. Users can embed their own applications and scale their pipelines from a small prototype running on their desktop computer to a large-scale study harnessing distributed computing infrastructures, simply by changing a single line in the pipeline definition...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28360851/neuroimaging-genetics-and-clinical-data-sharing-in-python-using-the-cubicweb-framework
#19
Antoine Grigis, David Goyard, Robin Cherbonnier, Thomas Gareau, Dimitri Papadopoulos Orfanos, Nicolas Chauvat, Adrien Di Mascio, Gunter Schumann, Will Spooren, Declan Murphy, Vincent Frouin
In neurosciences or psychiatry, the emergence of large multi-center population imaging studies raises numerous technological challenges. From distributed data collection, across different institutions and countries, to final data publication service, one must handle the massive, heterogeneous, and complex data from genetics, imaging, demographics, or clinical scores. These data must be both efficiently obtained and downloadable. We present a Python solution, based on the CubicWeb open-source semantic framework, aimed at building population imaging study repositories...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28344551/construction-and-analysis-of-weighted-brain-networks-from-sice-for-the-study-of-alzheimer-s-disease
#20
Jorge Munilla, Andrés Ortiz, Juan M Górriz, Javier Ramírez
Alzheimer's Disease (AD) is the most common neurodegenerative disease in elderly people, and current drugs, unfortunately, do not represent yet a cure but only slow down its progression. This is explained, at least in part, because the understanding of the neurodegenerative process is still incomplete, being sometimes mistaken, particularly at the first steps of the illness, with the natural aging process. A better identification of how the functional activity deteriorates is thus crucial to develop new and more effective treatments...
2017: Frontiers in Neuroinformatics
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