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Attention Score in Context
| Title |
ToolConnect: A Functional Connectivity Toolbox for In vitro Networks
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, March 2016
|
| DOI | 10.3389/fninf.2016.00013 |
| Pubmed ID | |
| Authors |
Vito Paolo Pastore, Daniele Poli, Aleksandar Godjoski, Sergio Martinoia, Paolo Massobrio |
| Abstract |
Nowadays, the use of in vitro reduced models of neuronal networks to investigate the interplay between structural-functional connectivity and the emerging collective dynamics is a widely accepted approach. In this respect, a relevant advance for this kind of studies has been given by the recent introduction of high-density large-scale Micro-Electrode Arrays (MEAs) which have favored the mapping of functional connections and the recordings of the neuronal electrical activity. Although, several toolboxes have been implemented to characterize network dynamics and derive functional links, no specifically dedicated software for the management of huge amount of data and direct estimation of functional connectivity maps has been developed. toolconnect offers the implementation of up to date algorithms and a user-friendly Graphical User Interface (GUI) to analyze recorded data from large scale networks. It has been specifically conceived as a computationally efficient open-source software tailored to infer functional connectivity by analyzing the spike trains acquired from in vitro networks coupled to MEAs. In the current version, toolconnect implements correlation- (cross-correlation, partial-correlation) and information theory (joint entropy, transfer entropy) based core algorithms, as well as useful and practical add-ons to visualize functional connectivity graphs and extract some topological features. In this work, we present the software, its main features and capabilities together with some demonstrative applications on hippocampal recordings. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 1% |
| Unknown | 80 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 21% |
| Researcher | 11 | 14% |
| Student > Master | 10 | 12% |
| Student > Bachelor | 8 | 10% |
| Professor | 6 | 7% |
| Other | 10 | 12% |
| Unknown | 19 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 22 | 27% |
| Engineering | 14 | 17% |
| Agricultural and Biological Sciences | 10 | 12% |
| Biochemistry, Genetics and Molecular Biology | 5 | 6% |
| Computer Science | 4 | 5% |
| Other | 4 | 5% |
| Unknown | 22 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 30 March 2016.
All research outputs
#20,317,110
of 22,858,915 outputs
Outputs from Frontiers in Neuroinformatics
#679
of 750 outputs
Outputs of similar age
#254,730
of 300,631 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#11
of 12 outputs
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So far Altmetric has tracked 750 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 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.