scholarly journals MEA Viewer: a High-performance Interactive Application for Visualizing Electrophysiological Data

2017 ◽  
Author(s):  
Daniel C. Bridges ◽  
Kenneth R. Tovar ◽  
Bian Wu ◽  
Paul K. Hansma ◽  
Kenneth S. Kosik
Keyword(s):  
Action Potentials ◽  
High Performance ◽  
Detection Threshold ◽  
Electrode Arrays ◽  
Electrophysiological Data ◽  
Signal Average ◽  
Research Areas ◽  
Raster Plot ◽  
Data Files ◽  
Interactive Application

AbstractMulti-electrode arrays (MEAs) have been used for many years to measure electrical activity in ensembles of many hundreds of neurons, and are used in research areas as diverse as neuronal connectivity and drug discovery. A high sampling frequency is required to adequately capture action potentials, also known as spikes, the primary electrical event associated with neuronal activity, and the resulting raw data files are large and difficult to visualize with traditional plotting tools. Many common approaches to deal with this issue, such as extracting spikes times and solely performing spike train analysis, significantly reduce data dimensionality. Unbiased data exploration benefits from the use of tools that minimize data transforms and such tools enable the development of heuristic perspective from data prior to any subsequent processing. Here we introduce MEA Viewer, a high-performance interactive application for the direct visualization of multi-channel electrophysiological data. MEA Viewer provides many high-performance visualizations of electrophysiological data, including an easily navigable overview of all recorded extracellular signals overlaid with spike timestamp data and an interactive raster plot. Beyond the fundamental data displays, MEA Viewer can signal average and spatially overlay the extent of action potential propagation within single neurons. This view extracts information below the spike detection threshold to directly visualize the propagation of action potentials across the plane of the MEA. This entirely new method of using MEAs opens up new and novel research applications for medium density arrays. MEA Viewer is licensed under the General Public License version 3, GPLv3, and is available at http://github.com/dbridges/mea-tools.

scholarly journals MEA Viewer: A high-performance interactive application for visualizing electrophysiological data

PLoS ONE ◽  
2018 ◽  
Vol 13 (2) ◽  
pp. e0192477 ◽  
Author(s):  
Daniel C. Bridges ◽  
Kenneth R. Tovar ◽  
Bian Wu ◽  
Paul K. Hansma ◽  
Kenneth S. Kosik
Keyword(s):  
High Performance ◽  
Electrophysiological Data ◽  
Interactive Application

A Study of the Cloud Computing Adoption Issues and Challenges

2020 ◽  
Vol 13 (3) ◽  
pp. 313-318 ◽  
Author(s):  
Dhanapal Angamuthu ◽  
Nithyanandam Pandian
Keyword(s):  
Cloud Computing ◽  
High Performance ◽  
Cloud Service ◽  
Ease Of Use ◽  
Modern Trend ◽  
Security Issues ◽  
Research Areas ◽  
Data Location ◽  
Broad Classification

<P>Background: The cloud computing is the modern trend in high-performance computing. Cloud computing becomes very popular due to its characteristic of available anywhere, elasticity, ease of use, cost-effectiveness, etc. Though the cloud grants various benefits, it has associated issues and challenges to prevent the organizations to adopt the cloud. </P><P> Objective: The objective of this paper is to cover the several perspectives of Cloud Computing. This includes a basic definition of cloud, classification of the cloud based on Delivery and Deployment Model. The broad classification of the issues and challenges faced by the organization to adopt the cloud computing model are explored. Examples for the broad classification are Data Related issues in the cloud, Service availability related issues in cloud, etc. The detailed sub-classifications of each of the issues and challenges discussed. The example sub-classification of the Data Related issues in cloud shall be further classified into Data Security issues, Data Integrity issue, Data location issue, Multitenancy issues, etc. This paper also covers the typical problem of vendor lock-in issue. This article analyzed and described the various possible unique insider attacks in the cloud environment. </P><P> Results: The guideline and recommendations for the different issues and challenges are discussed. The most importantly the potential research areas in the cloud domain are explored. </P><P> Conclusion: This paper discussed the details on cloud computing, classifications and the several issues and challenges faced in adopting the cloud. The guideline and recommendations for issues and challenges are covered. The potential research areas in the cloud domain are captured. This helps the researchers, academicians and industries to focus and address the current challenges faced by the customers.</P>

The long-term development of Russian biotech sector

foresight ◽  
2017 ◽  
Vol 19 (5) ◽  
pp. 491-500 ◽  
Author(s):  
Anna Grebenyuk ◽  
Nikolai Ravin
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Technological Development ◽  
Science And Technology ◽  
Plant Biotechnology ◽  
High Tech ◽  
Content Type ◽  
Research Areas ◽  
Research Activities ◽  
The Usa

Purpose To define strategic directions for the Russia’s social, economic, scientific and technological development in 2011-2013, a large-scale foresight study including the deep analysis of prospects of biotechnology development there was undertaken (Russia 2030: Science and Technology Foresight). This paper aims to present results of this research. Design/methodology/approach The study was based on a combination of technology-push and market-pull approaches that aimed not only to identify most promising science and technology (S&T) areas but also to understand how they can be realized in practice. Representatives from federal authorities, science and business were involved in the project to create future visions of technological directions; analyze grand challenges, weak signals and wild cards; and set research and development (R&D) priorities. Findings According to results of the study, Russia has a potential for biotech sector development, although the level of R&D in the majority of areas is lagging behind that in the USA and leading EU countries. However, there are several advanced applied research areas where efforts can be focused. Among them are high-performance genomics and post-genomics research platforms, systems and structural biology, microbial metabolic engineering, plant biotechnology and microbial strains and consortia for development of symbiotic plant–microbial communities. Originality/value Concentration of available resources of government and business on biotechnological sector development can help to find answers for challenges that Russia faces today or will face tomorrow. It will help to pick up on the current level of research activities, improve the quality of personnel training, make this area the engine of the economy and carry out the so-called new industrialization of the country, building a new, high-tech device industry.

Editing trains of action potentials from multi-electrode arrays

2004 ◽  
Vol 134 (1) ◽  
pp. 91-100 ◽  
Author(s):  
Richard B. Stein ◽  
Douglas J. Weber
Keyword(s):  
Action Potentials ◽  
Electrode Arrays

Two-Photon Excitation of Potentiometric Probes Enables Optical Recording of Action Potentials From Mammalian Nerve Terminals In Situ

2008 ◽  
Vol 99 (3) ◽  
pp. 1545-1553 ◽  
Author(s):  
Jonathan A. N. Fisher ◽  
Jonathan R. Barchi ◽  
Cristin G. Welle ◽  
Gi-Ho Kim ◽  
Paul Kosterin ◽  
...  
Keyword(s):  
Action Potentials ◽  
Optical Recording ◽  
Photon Absorption ◽  
Nerve Terminals ◽  
Electrode Arrays ◽  
Two Photon ◽  
Photon Excitation ◽  
Mammalian Nerve ◽  
Two Photon Excitation

We report the first optical recordings of action potentials, in single trials, from one or a few (∼1–2 μm) mammalian nerve terminals in an intact in vitro preparation, the mouse neurohypophysis. The measurements used two-photon excitation along the “blue” edge of the two-photon absorption spectrum of di-3-ANEPPDHQ (a fluorescent voltage-sensitive naphthyl styryl-pyridinium dye), and epifluorescence detection, a configuration that is critical for noninvasive recording of electrical activity from intact brains. Single-trial recordings of action potentials exhibited signal-to-noise ratios of ∼5:1 and fractional fluorescence changes of up to ∼10%. This method, by virtue of its optical sectioning capability, deep tissue penetration, and efficient epifluorescence detection, offers clear advantages over linear, as well as other nonlinear optical techniques used to monitor voltage changes in localized neuronal regions, and provides an alternative to invasive electrode arrays for studying neuronal systems in vivo.

scholarly journals Performance Evaluation of Modularity Based Community Detection Algorithms in Large Scale Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Vinícius da Fonseca Vieira ◽  
Carolina Ribeiro Xavier ◽  
Nelson Francisco Favilla Ebecken ◽  
Alexandre Gonçalves Evsukoff
Keyword(s):  
Spectral Method ◽  
Community Detection ◽  
High Performance ◽  
Large Scale ◽  
Fine Tuning ◽  
Detection Algorithms ◽  
Research Areas ◽  
Structure Detection ◽  
Wide Range ◽  
Large Scale Networks

Community structure detection is one of the major research areas of network science and it is particularly useful for large real networks applications. This work presents a deep study of the most discussed algorithms for community detection based on modularity measure: Newman’s spectral method using a fine-tuning stage and the method of Clauset, Newman, and Moore (CNM) with its variants. The computational complexity of the algorithms is analysed for the development of a high performance code to accelerate the execution of these algorithms without compromising the quality of the results, according to the modularity measure. The implemented code allows the generation of partitions with modularity values consistent with the literature and it overcomes 1 million nodes with Newman’s spectral method. The code was applied to a wide range of real networks and the performances of the algorithms are evaluated.

scholarly journals Electrical Stimulus Artifact Cancellation and Neural Spike Detection on Large Multi-Electrode Arrays

2016 ◽  
Author(s):  
Gonzalo E. Mena ◽  
Lauren E. Grosberg ◽  
Sasidhar Madugula ◽  
Paweł Hottowy ◽  
Alan Litke ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
High Resolution ◽  
Action Potentials ◽  
Process Model ◽  
Error Rates ◽  
Neural Interfaces ◽  
Spike Sorting ◽  
Electrode Arrays ◽  
Retinal Prostheses ◽  
Sorting Process

AbstractSimultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible.Author SummarySimultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these recordings is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is largely stymied by electrical stimulation artifacts across the array, which are typically larger than the signals of interest. We develop a novel computational framework to estimate and subtract away this contaminating artifact, enabling the large-scale analysis of responses of possibly hundreds of cells to tailored stimulation. Importantly, we suggest that this technology may also be helpful for the development of future high-resolution neural prosthetic devices (e.g., retinal prostheses).

scholarly journals Diagnostic effectiveness of spatial indices of computed vectorcardiography for evaluation of left ventricular hypertrophy

2003 ◽  
Vol 9 (4) ◽  
pp. 142-144
Author(s):  
S. A. Boitsov ◽  
S. L. Gizhayev ◽  
I. G. Lastochkin ◽  
A. N. Pinegin
Keyword(s):  
Left Ventricular Hypertrophy ◽  
High Performance ◽  
Ventricular Hypertrophy ◽  
Left Ventricular ◽  
Spatial Indices ◽  
Signal Average

The paper shows how the spatial indices of a cardiac signal obtained from recording high-performance signal-average EGG may be useful in diagnosing left ventricular hypertrophy.

scholarly journals An automated method for precise axon reconstruction from recordings of high-density micro-electrode arrays

2021 ◽  
Author(s):  
Alessio Paolo Buccino ◽  
Xinyue Yuan ◽  
Vishalini Emmenegger ◽  
Xiaohan Xue ◽  
Tobias Gaenswein ◽  
...  
Keyword(s):  
Action Potential ◽  
Action Potentials ◽  
Electrical Potential ◽  
Simulated Data ◽  
Signal Propagation ◽  
High Density ◽  
Electrode Arrays ◽  
Action Potential Propagation ◽  
Automated Method ◽  
Propagation Velocities

Neurons communicate with each other by sending action potentials through their axons. The velocity of axonal signal propagation describes how fast electrical action potentials can travel, and can be affected in a human brain by several pathologies, including multiple sclerosis, traumatic brain injury and channelopathies. High-density microelectrode arrays (HD-MEAs) provide unprecedented spatio-temporal resolution to extracellularly record neural electrical activity. The high density of the recording electrodes enables to image the activity of individual neurons down to subcellular resolution, which includes the propagation of axonal signals. However, axon reconstruction, to date, mainly relies on a manual approach to select the electrodes and channels that seemingly record the signals along a specific axon, while an automated approach to track multiple axonal branches in extracellular action-potential recordings is still missing. In this article, we propose a fully automated approach to reconstruct axons from extracellular electrical-potential landscapes, so-called "electrical footprints" of neurons. After an initial electrode and channel selection, the proposed method first constructs a graph, based on the voltage signal amplitudes and latencies. Then, the graph is interrogated to extract possible axonal branches. Finally, the axonal branches are pruned and axonal action-potential propagation velocities are computed. We first validate our method using simulated data from detailed reconstructions of neurons, showing that our approach is capable of accurately reconstructing axonal branches. We then apply the reconstruction algorithm to experimental recordings of HD-MEAs and show that it can be used to determine axonal morphologies and signal-propagation velocities at high throughput. We introduce a fully automated method to reconstruct axonal branches and estimate axonal action-potential propagation velocities using HD-MEA recordings. Our method yields highly reliable and reproducible velocity estimations, which constitute an important electrophysiological feature of neuronal preparations.

scholarly journals Visualizing systems and software performance - Report on the GI-Dagstuhl seminar for young researchers, July 9-13, 2018

2018 ◽  
Author(s):  
Fabian Beck ◽  
Alexandre Bergel ◽  
Cor-Paul Bezemer ◽  
Katherine E. Isaacs
Keyword(s):  
High Performance ◽  
Community Collaboration ◽  
Software Performance ◽  
Data Systems ◽  
Related Data ◽  
Performance Engineering ◽  
Research Areas ◽  
Performance Report ◽  
Big Data Systems ◽  
Young Researchers

This GI-Dagstuhl seminar addressed the problem of visualizing performance-related data of systems and the software that they run. Due to the scale of performance-related data and the open-ended nature of analyzing it, visualization is often the only feasible way to comprehend, improve, and debug the performance behaviour of systems. The rise of cloud and big data systems, and the rapidly growing scale of the performance-related data that they generate, have led to an increased need for visualization of such data. However, the research communities behind data visualization, performance engineering, and high-performance computing are largely disjunct. The goal of this seminar was to bring together young researchers from these research areas to identify cross-community collaboration and to set the path for long-lasting collaborations towards rich and effective visualizations of performance-related data.

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