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X Demographics
Mendeley readers
Attention Score in Context
| Title |
End-to-End Deep Image Reconstruction From Human Brain Activity
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, April 2019
|
| DOI | 10.3389/fncom.2019.00021 |
| Pubmed ID | |
| Authors |
Guohua Shen, Kshitij Dwivedi, Kei Majima, Tomoyasu Horikawa, Yukiyasu Kamitani |
X Demographics
The data shown below were collected from the profiles of 176 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 | 22 | 13% |
| France | 16 | 9% |
| United Kingdom | 5 | 3% |
| Spain | 4 | 2% |
| Belgium | 4 | 2% |
| Japan | 3 | 2% |
| Canada | 3 | 2% |
| Korea, Republic of | 2 | 1% |
| Finland | 2 | 1% |
| Other | 14 | 8% |
| Unknown | 101 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 153 | 87% |
| Scientists | 20 | 11% |
| Practitioners (doctors, other healthcare professionals) | 2 | 1% |
| Science communicators (journalists, bloggers, editors) | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 410 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 410 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 69 | 17% |
| Student > Master | 67 | 16% |
| Student > Bachelor | 45 | 11% |
| Researcher | 43 | 10% |
| Student > Doctoral Student | 20 | 5% |
| Other | 64 | 16% |
| Unknown | 102 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 74 | 18% |
| Computer Science | 70 | 17% |
| Engineering | 41 | 10% |
| Psychology | 33 | 8% |
| Agricultural and Biological Sciences | 10 | 2% |
| Other | 58 | 14% |
| Unknown | 124 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 179. 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 December 2023.
All research outputs
#229,297
of 25,818,700 outputs
Outputs from Frontiers in Computational Neuroscience
#11
of 1,475 outputs
Outputs of similar age
#4,743
of 367,421 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#1
of 25 outputs
Altmetric has tracked 25,818,700 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,475 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has done particularly well, scoring higher than 99% 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 367,421 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 98% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.