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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The neural decoding toolbox
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, January 2013
|
| DOI | 10.3389/fninf.2013.00008 |
| Pubmed ID | |
| Authors |
Ethan M. Meyers |
| Abstract |
Population decoding is a powerful way to analyze neural data, however, currently only a small percentage of systems neuroscience researchers use this method. In order to increase the use of population decoding, we have created the Neural Decoding Toolbox (NDT) which is a Matlab package that makes it easy to apply population decoding analyses to neural activity. The design of the toolbox revolves around four abstract object classes which enables users to interchange particular modules in order to try different analyses while keeping the rest of the processing stream intact. The toolbox is capable of analyzing data from many different types of recording modalities, and we give examples of how it can be used to decode basic visual information from neural spiking activity and how it can be used to examine how invariant the activity of a neural population is to stimulus transformations. Overall this toolbox will make it much easier for neuroscientists to apply population decoding analyses to their data, which should help increase the pace of discovery in neuroscience. |
X Demographics
The data shown below were collected from the profiles of 20 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 20% |
| United Kingdom | 3 | 15% |
| Mexico | 2 | 10% |
| Japan | 2 | 10% |
| Switzerland | 2 | 10% |
| Italy | 1 | 5% |
| Canada | 1 | 5% |
| Turkey | 1 | 5% |
| Uruguay | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 3 | 15% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 17 | 85% |
| Scientists | 2 | 10% |
| Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 254 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | <1% |
| Germany | 1 | <1% |
| Hong Kong | 1 | <1% |
| Canada | 1 | <1% |
| Australia | 1 | <1% |
| Japan | 1 | <1% |
| Belgium | 1 | <1% |
| Unknown | 246 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 63 | 25% |
| Researcher | 54 | 21% |
| Student > Master | 20 | 8% |
| Student > Bachelor | 19 | 7% |
| Professor | 13 | 5% |
| Other | 41 | 16% |
| Unknown | 44 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 82 | 32% |
| Agricultural and Biological Sciences | 37 | 15% |
| Psychology | 29 | 11% |
| Engineering | 20 | 8% |
| Computer Science | 12 | 5% |
| Other | 22 | 9% |
| Unknown | 52 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 04 August 2019.
All research outputs
#2,301,108
of 24,143,470 outputs
Outputs from Frontiers in Neuroinformatics
#85
of 790 outputs
Outputs of similar age
#22,908
of 288,617 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#8
of 36 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 790 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 89% of its peers.
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 288,617 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.