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Understanding Consolidation through the Architecture of Memories

Overview of attention for article published in The Neuroscientist, June 2016
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1 Facebook page

Citations

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56 Dimensions

Readers on

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153 Mendeley
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1 CiteULike
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1 Connotea
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Title
Understanding Consolidation through the Architecture of Memories
Published in
The Neuroscientist, June 2016
DOI 10.1177/1073858406287935
Pubmed ID
Authors

Edwin M Robertson, Daniel A Cohen

Abstract

Following its encoding, a memory undergoes consolidation. It may be possible to deepen our understanding of the mechanisms supporting consolidation by considering the complex architecture of a memory. Any behavior can be split into multiple components. For example, when learning a new skill we simultaneously learn the movement and the goal of that movement. Each of these components has a distinct representation within a memory. The "off-line" processing of each component may follow different rules, providing an explanation for the variety of performance changes supported by consolidation. By viewing a memory as a representation with multiple components, it is possible to bridge the gap between the behavioral changes, which define consolidation, and the biological mechanisms that support those changes. This is partly because different memory components can be mapped onto different neural circuits. With an increased understanding of consolidation, it may become possible to modulate these off-line processes to improve psychiatric and neurological rehabilitation.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 2%
United Kingdom 3 2%
United States 3 2%
Canada 3 2%
Switzerland 1 <1%
Brazil 1 <1%
Argentina 1 <1%
Iran, Islamic Republic of 1 <1%
Unknown 137 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 37 24%
Student > Ph. D. Student 30 20%
Student > Master 18 12%
Student > Bachelor 11 7%
Professor 10 7%
Other 29 19%
Unknown 18 12%
Readers by discipline Count As %
Psychology 44 29%
Neuroscience 22 14%
Medicine and Dentistry 17 11%
Agricultural and Biological Sciences 15 10%
Engineering 10 7%
Other 18 12%
Unknown 27 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 29 September 2014.
All research outputs
#20,237,640
of 22,764,165 outputs
Outputs from The Neuroscientist
#684
of 720 outputs
Outputs of similar age
#304,665
of 351,751 outputs
Outputs of similar age from The Neuroscientist
#210
of 216 outputs
Altmetric has tracked 22,764,165 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 720 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 351,751 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 216 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.