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Cerebellar Motor Learning: When Is Cortical Plasticity Not Enough?

Overview of attention for article published in PLoS Computational Biology, October 2007
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

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1 blog
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19 X users

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130 Mendeley
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Title
Cerebellar Motor Learning: When Is Cortical Plasticity Not Enough?
Published in
PLoS Computational Biology, October 2007
DOI 10.1371/journal.pcbi.0030197
Pubmed ID
Authors

John Porrill, Paul Dean

Abstract

Classical Marr-Albus theories of cerebellar learning employ only cortical sites of plasticity. However, tests of these theories using adaptive calibration of the vestibulo-ocular reflex (VOR) have indicated plasticity in both cerebellar cortex and the brainstem. To resolve this long-standing conflict, we attempted to identify the computational role of the brainstem site, by using an adaptive filter version of the cerebellar microcircuit to model VOR calibration for changes in the oculomotor plant. With only cortical plasticity, introducing a realistic delay in the retinal-slip error signal of 100 ms prevented learning at frequencies higher than 2.5 Hz, although the VOR itself is accurate up to at least 25 Hz. However, the introduction of an additional brainstem site of plasticity, driven by the correlation between cerebellar and vestibular inputs, overcame the 2.5 Hz limitation and allowed learning of accurate high-frequency gains. This "cortex-first" learning mechanism is consistent with a wide variety of evidence concerning the role of the flocculus in VOR calibration, and complements rather than replaces the previously proposed "brainstem-first" mechanism that operates when ocular tracking mechanisms are effective. These results (i) describe a process whereby information originally learnt in one area of the brain (cerebellar cortex) can be transferred and expressed in another (brainstem), and (ii) indicate for the first time why a brainstem site of plasticity is actually required by Marr-Albus type models when high-frequency gains must be learned in the presence of error delay.

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 4 3%
United Kingdom 4 3%
United States 4 3%
Brazil 1 <1%
India 1 <1%
Belgium 1 <1%
Switzerland 1 <1%
Spain 1 <1%
Poland 1 <1%
Other 0 0%
Unknown 112 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 25%
Researcher 33 25%
Student > Master 12 9%
Professor 10 8%
Professor > Associate Professor 9 7%
Other 26 20%
Unknown 7 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 26%
Neuroscience 22 17%
Engineering 16 12%
Psychology 15 12%
Medicine and Dentistry 14 11%
Other 19 15%
Unknown 10 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 22 March 2017.
All research outputs
#2,002,214
of 25,576,801 outputs
Outputs from PLoS Computational Biology
#1,773
of 9,003 outputs
Outputs of similar age
#4,378
of 89,527 outputs
Outputs of similar age from PLoS Computational Biology
#4
of 37 outputs
Altmetric has tracked 25,576,801 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,003 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done well, scoring higher than 80% 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 89,527 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 95% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.