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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Development and Analysis of Integrated Neuroscience Data
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, February 2016
|
| DOI | 10.3389/fncom.2016.00011 |
| Pubmed ID | |
| Authors |
Joshua I. Glaser, Konrad P. Kording |
| Abstract |
There is a strong emphasis on developing novel neuroscience technologies, in particular on recording from more neurons. There has thus been increasing discussion about how to analyze the resulting big datasets. What has received less attention is that over the last 30 years, papers in neuroscience have progressively integrated more approaches, such as electrophysiology, anatomy, and genetics. As such, there has been little discussion on how to combine and analyze this multimodal data. Here, we describe the growth of multimodal approaches, and discuss the needed analysis advancements to make sense of this data. |
X Demographics
The data shown below were collected from the profiles of 12 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 | 3 | 25% |
| Germany | 1 | 8% |
| Australia | 1 | 8% |
| Netherlands | 1 | 8% |
| Switzerland | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 75% |
| Scientists | 3 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 4% |
| Unknown | 49 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 25% |
| Researcher | 12 | 24% |
| Student > Doctoral Student | 5 | 10% |
| Student > Master | 5 | 10% |
| Other | 3 | 6% |
| Other | 8 | 16% |
| Unknown | 5 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 15 | 29% |
| Agricultural and Biological Sciences | 11 | 22% |
| Computer Science | 5 | 10% |
| Engineering | 5 | 10% |
| Medicine and Dentistry | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 7 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 08 March 2016.
All research outputs
#4,172,215
of 22,844,985 outputs
Outputs from Frontiers in Computational Neuroscience
#189
of 1,343 outputs
Outputs of similar age
#75,055
of 400,575 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#3
of 27 outputs
Altmetric has tracked 22,844,985 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,343 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done well, scoring higher than 86% 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 400,575 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.