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A model of microsaccade-related neural responses induced by short-term depression in thalamocortical synapses

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2013
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Title
A model of microsaccade-related neural responses induced by short-term depression in thalamocortical synapses
Published in
Frontiers in Computational Neuroscience, January 2013
DOI 10.3389/fncom.2013.00047
Pubmed ID
Authors

Wu-Jie Yuan, Olaf Dimigen, Werner Sommer, Changsong Zhou

Abstract

Microsaccades during fixation have been suggested to counteract visual fading. Recent experiments have also observed microsaccade-related neural responses from cellular record, scalp electroencephalogram (EEG), and functional magnetic resonance imaging (fMRI). The underlying mechanism, however, is not yet understood and highly debated. It has been proposed that the neural activity of primary visual cortex (V1) is a crucial component for counteracting visual adaptation. In this paper, we use computational modeling to investigate how short-term depression (STD) in thalamocortical synapses might affect the neural responses of V1 in the presence of microsaccades. Our model not only gives a possible synaptic explanation for microsaccades in counteracting visual fading, but also reproduces several features in experimental findings. These modeling results suggest that STD in thalamocortical synapses plays an important role in microsaccade-related neural responses and the model may be useful for further investigation of behavioral properties and functional roles of microsaccades.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Unknown 30 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 19%
Student > Bachelor 4 13%
Student > Master 4 13%
Student > Ph. D. Student 3 10%
Student > Postgraduate 3 10%
Other 3 10%
Unknown 8 26%
Readers by discipline Count As %
Psychology 7 23%
Neuroscience 7 23%
Agricultural and Biological Sciences 3 10%
Engineering 2 6%
Medicine and Dentistry 2 6%
Other 3 10%
Unknown 7 23%
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 23 April 2013.
All research outputs
#20,191,579
of 22,708,120 outputs
Outputs from Frontiers in Computational Neuroscience
#1,157
of 1,336 outputs
Outputs of similar age
#248,737
of 280,717 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#105
of 131 outputs
Altmetric has tracked 22,708,120 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 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 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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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 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.