The data shown below were collected from the profiles of 24 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, January 2017
|
| DOI | 10.3389/fncom.2017.00004 |
| Pubmed ID | |
| Authors |
Tomoyasu Horikawa, Yukiyasu Kamitani |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 17% |
| Singapore | 1 | 4% |
| Egypt | 1 | 4% |
| Japan | 1 | 4% |
| Unknown | 17 | 71% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 15 | 63% |
| Scientists | 7 | 29% |
| Practitioners (doctors, other healthcare professionals) | 2 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 191 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| Malaysia | 1 | <1% |
| Netherlands | 1 | <1% |
| United Kingdom | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 186 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 37 | 19% |
| Student > Bachelor | 25 | 13% |
| Student > Master | 23 | 12% |
| Researcher | 22 | 12% |
| Student > Doctoral Student | 7 | 4% |
| Other | 25 | 13% |
| Unknown | 52 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 47 | 25% |
| Psychology | 24 | 13% |
| Computer Science | 20 | 10% |
| Engineering | 17 | 9% |
| Agricultural and Biological Sciences | 8 | 4% |
| Other | 16 | 8% |
| Unknown | 59 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 34. 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 May 2024.
All research outputs
#1,257,409
of 26,430,863 outputs
Outputs from Frontiers in Computational Neuroscience
#45
of 1,495 outputs
Outputs of similar age
#25,667
of 430,266 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#1
of 31 outputs
Altmetric has tracked 26,430,863 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,495 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done particularly well, scoring higher than 96% 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 430,266 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 94% of its contemporaries.
We're also able to compare this research output to 31 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.