| Title |
Variation in the use of cues to guide visual working memory
|
|---|---|
| Published in |
Attention, Perception, & Psychophysics, May 2017
|
| DOI | 10.3758/s13414-017-1335-4 |
| Pubmed ID | |
| Authors |
Matthew K. Robison, Nash Unsworth |
| Abstract |
Across two experiments we examined individual differences in the use of precues and retrocues to guide the selective encoding and maintenance of information in visual working memory (WM). In Experiment 1, we used spatial cues to indicate which item would be tested either before or after the presentation of a memory array. Regression analyses allowed us to separate variance due to visual WM capacity and attention control differences. In Experiment 2, we used categorical cues to indicate from which subset of items the tested item would be drawn, and we measured attention control with two independent tasks. Collectively, the results supported the idea that an element of individual differences in WM is the ability to flexibly allocate attention to encode only relevant information and subsequently select relevant information during maintenance stages. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 75% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 33 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 5 | 15% |
| Student > Master | 4 | 12% |
| Professor > Associate Professor | 4 | 12% |
| Student > Ph. D. Student | 4 | 12% |
| Researcher | 4 | 12% |
| Other | 3 | 9% |
| Unknown | 9 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 15 | 45% |
| Neuroscience | 3 | 9% |
| Unspecified | 1 | 3% |
| Economics, Econometrics and Finance | 1 | 3% |
| Nursing and Health Professions | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 10 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 18 June 2017.
All research outputs
#13,409,618
of 24,003,070 outputs
Outputs from Attention, Perception, & Psychophysics
#461
of 1,773 outputs
Outputs of similar age
#147,912
of 316,878 outputs
Outputs of similar age from Attention, Perception, & Psychophysics
#10
of 42 outputs
Altmetric has tracked 24,003,070 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,773 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has gotten more attention than average, scoring higher than 73% 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 316,878 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 53% 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 gotten more attention than average, scoring higher than 73% of its contemporaries.