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Optimal Control of Saccades by Spatial-Temporal Activity Patterns in the Monkey Superior Colliculus

Overview of attention for article published in PLoS Computational Biology, May 2012
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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 (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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blogs
1 blog
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2 X users

Citations

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64 Dimensions

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91 Mendeley
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1 CiteULike
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Title
Optimal Control of Saccades by Spatial-Temporal Activity Patterns in the Monkey Superior Colliculus
Published in
PLoS Computational Biology, May 2012
DOI 10.1371/journal.pcbi.1002508
Pubmed ID
Authors

H H L M Goossens, A J van Opstal

Abstract

A major challenge in computational neurobiology is to understand how populations of noisy, broadly-tuned neurons produce accurate goal-directed actions such as saccades. Saccades are high-velocity eye movements that have stereotyped, nonlinear kinematics; their duration increases with amplitude, while peak eye-velocity saturates for large saccades. Recent theories suggest that these characteristics reflect a deliberate strategy that optimizes a speed-accuracy tradeoff in the presence of signal-dependent noise in the neural control signals. Here we argue that the midbrain superior colliculus (SC), a key sensorimotor interface that contains a topographically-organized map of saccade vectors, is in an ideal position to implement such an optimization principle. Most models attribute the nonlinear saccade kinematics to saturation in the brainstem pulse generator downstream from the SC. However, there is little data to support this assumption. We now present new neurophysiological evidence for an alternative scheme, which proposes that these properties reside in the spatial-temporal dynamics of SC activity. As predicted by this scheme, we found a remarkably systematic organization in the burst properties of saccade-related neurons along the rostral-to-caudal (i.e., amplitude-coding) dimension of the SC motor map: peak firing-rates systematically decrease for cells encoding larger saccades, while burst durations and skewness increase, suggesting that this spatial gradient underlies the increase in duration and skewness of the eye velocity profiles with amplitude. We also show that all neurons in the recruited population synchronize their burst profiles, indicating that the burst-timing of each cell is determined by the planned saccade vector in which it participates, rather than by its anatomical location. Together with the observation that saccade-related SC cells indeed show signal-dependent noise, this precisely tuned organization of SC burst activity strongly supports the notion of an optimal motor-control principle embedded in the SC motor map as it fully accounts for the straight trajectories and kinematic nonlinearity of saccades.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 3%
Netherlands 2 2%
United States 1 1%
United Kingdom 1 1%
Unknown 84 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 23%
Researcher 16 18%
Student > Master 14 15%
Professor 11 12%
Student > Bachelor 4 4%
Other 11 12%
Unknown 14 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 22%
Neuroscience 19 21%
Psychology 10 11%
Medicine and Dentistry 9 10%
Engineering 5 5%
Other 11 12%
Unknown 17 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 10 May 2016.
All research outputs
#4,216,382
of 25,371,288 outputs
Outputs from PLoS Computational Biology
#3,465
of 8,958 outputs
Outputs of similar age
#27,478
of 176,742 outputs
Outputs of similar age from PLoS Computational Biology
#25
of 108 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,958 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 gotten more attention than average, scoring higher than 61% 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 176,742 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 108 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.