The data shown below were collected from the profiles of 18 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 |
A mechanistic model of ADHD as resulting from dopamine phasic/tonic imbalance during reinforcement learning
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, July 2022
|
| DOI | 10.3389/fncom.2022.849323 |
| Pubmed ID | |
| Authors |
Florence Véronneau-Veilleux, Philippe Robaey, Mauro Ursino, Fahima Nekka |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 6% |
| United States | 1 | 6% |
| India | 1 | 6% |
| Unknown | 15 | 83% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 15 | 83% |
| Practitioners (doctors, other healthcare professionals) | 3 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 10% |
| Student > Master | 4 | 8% |
| Researcher | 4 | 8% |
| Student > Bachelor | 4 | 8% |
| Other | 3 | 6% |
| Other | 3 | 6% |
| Unknown | 25 | 52% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 5 | 10% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Neuroscience | 3 | 6% |
| Computer Science | 2 | 4% |
| Medicine and Dentistry | 2 | 4% |
| Other | 6 | 13% |
| Unknown | 27 | 56% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 14 August 2024.
All research outputs
#1,570,223
of 26,588,565 outputs
Outputs from Frontiers in Computational Neuroscience
#55
of 1,501 outputs
Outputs of similar age
#33,914
of 441,389 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#2
of 42 outputs
Altmetric has tracked 26,588,565 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,501 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 441,389 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 42 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 95% of its contemporaries.