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Consolidated learning can be susceptible to gradually-developing interference in prolonged motor learning

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2013
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Title
Consolidated learning can be susceptible to gradually-developing interference in prolonged motor learning
Published in
Frontiers in Computational Neuroscience, January 2013
DOI 10.3389/fncom.2013.00069
Pubmed ID
Authors

Yuko Yotsumoto, Takeo Watanabe, Li-Hung Chang, Yuka Sasaki

Abstract

When multiple items are learned in sequential order, learning for one item tends to be disrupted by subsequently learned items. Such retrograde interference has been studied with paradigms conducted over a relatively short term. Resistance to interference is generally believed to be a measure of learning or consolidation. Here, we used a finger-tapping motor sequence paradigm to examine interference in prolonged motor learning. Three groups of nine subjects participated in training sessions for 16 days, and practiced three different sequences in different orders and combinations. We found that a well-trained motor sequence was subject to a gradual interference when the subsequent learning was paired in a particular order. The results suggest that a well-learned motor memory is still susceptible to interference, and that resistance to interference in one condition does not necessarily imply full, permanent consolidation.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Netherlands 1 2%
Unknown 51 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 23%
Researcher 9 17%
Student > Master 8 15%
Student > Bachelor 7 13%
Professor 2 4%
Other 8 15%
Unknown 7 13%
Readers by discipline Count As %
Psychology 16 30%
Neuroscience 10 19%
Agricultural and Biological Sciences 3 6%
Sports and Recreations 3 6%
Social Sciences 3 6%
Other 7 13%
Unknown 11 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 28 May 2013.
All research outputs
#15,222,208
of 22,711,242 outputs
Outputs from Frontiers in Computational Neuroscience
#850
of 1,336 outputs
Outputs of similar age
#180,871
of 280,736 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#71
of 131 outputs
Altmetric has tracked 22,711,242 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,336 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 35th percentile – i.e., 35% 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 280,736 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 131 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.