| Title |
Frequency variation analysis in neuronal cultures for stimulus response characterization
|
|---|---|
| Published in |
Neural Computing and Applications, January 2019
|
| DOI | 10.1007/s00521-018-3942-y |
| Authors |
Mikel Val-Calvo, José Ramón Álvarez-Sánchez, Javier Alegre-Cortés, Félix de la Paz-López, José Manuel Ferrández-Vicente, Eduardo Fernández-Jover, Inhar Val-Calvo |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 4 | 57% |
| Japan | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
| Scientists | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 15% |
| Student > Master | 3 | 12% |
| Researcher | 2 | 8% |
| Student > Ph. D. Student | 2 | 8% |
| Student > Doctoral Student | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 12 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 4 | 15% |
| Physics and Astronomy | 3 | 12% |
| Engineering | 3 | 12% |
| Computer Science | 2 | 8% |
| Medicine and Dentistry | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 10 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 30 January 2019.
All research outputs
#5,727,444
of 23,839,820 outputs
Outputs from Neural Computing and Applications
#102
of 2,407 outputs
Outputs of similar age
#113,198
of 442,128 outputs
Outputs of similar age from Neural Computing and Applications
#5
of 20 outputs
Altmetric has tracked 23,839,820 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,407 research outputs from this source. They receive a mean Attention Score of 1.3. This one has done particularly well, scoring higher than 95% 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 442,128 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.