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Software and hardware infrastructure for research in electrophysiology

Overview of attention for article published in Frontiers in Neuroinformatics, March 2014
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)

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2 X users
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1 peer review site

Citations

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42 Mendeley
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Title
Software and hardware infrastructure for research in electrophysiology
Published in
Frontiers in Neuroinformatics, March 2014
DOI 10.3389/fninf.2014.00020
Pubmed ID
Authors

Roman Mouček, Petr Ježek, Lukáš Vařeka, Tomáš Řondík, Petr Brůha, Václav Papež, Pavel Mautner, Jiří Novotný, Tomáš Prokop, Jan Štěbeták

Abstract

As in other areas of experimental science, operation of electrophysiological laboratory, design and performance of electrophysiological experiments, collection, storage and sharing of experimental data and metadata, analysis and interpretation of these data, and publication of results are time consuming activities. If these activities are well organized and supported by a suitable infrastructure, work efficiency of researchers increases significantly. This article deals with the main concepts, design, and development of software and hardware infrastructure for research in electrophysiology. The described infrastructure has been primarily developed for the needs of neuroinformatics laboratory at the University of West Bohemia, the Czech Republic. However, from the beginning it has been also designed and developed to be open and applicable in laboratories that do similar research. After introducing the laboratory and the whole architectural concept the individual parts of the infrastructure are described. The central element of the software infrastructure is a web-based portal that enables community researchers to store, share, download and search data and metadata from electrophysiological experiments. The data model, domain ontology and usage of semantic web languages and technologies are described. Current data publication policy used in the portal is briefly introduced. The registration of the portal within Neuroscience Information Framework is described. Then the methods used for processing of electrophysiological signals are presented. The specific modifications of these methods introduced by laboratory researches are summarized; the methods are organized into a laboratory workflow. Other parts of the software infrastructure include mobile and offline solutions for data/metadata storing and a hardware stimulator communicating with an EEG amplifier and recording software.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Serbia 1 2%
Germany 1 2%
Australia 1 2%
Unknown 39 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 29%
Student > Ph. D. Student 8 19%
Student > Bachelor 4 10%
Professor 3 7%
Professor > Associate Professor 3 7%
Other 6 14%
Unknown 6 14%
Readers by discipline Count As %
Engineering 8 19%
Neuroscience 8 19%
Computer Science 6 14%
Agricultural and Biological Sciences 4 10%
Psychology 3 7%
Other 4 10%
Unknown 9 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 March 2014.
All research outputs
#13,056,194
of 22,747,498 outputs
Outputs from Frontiers in Neuroinformatics
#413
of 743 outputs
Outputs of similar age
#106,125
of 221,149 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#11
of 15 outputs
Altmetric has tracked 22,747,498 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 743 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 221,149 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.