↓ Skip to main content

A Computational Analysis of the Function of Three Inhibitory Cell Types in Contextual Visual Processing

Overview of attention for article published in Frontiers in Computational Neuroscience, April 2017
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

twitter
8 X users

Citations

dimensions_citation
35 Dimensions

Readers on

mendeley
105 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A Computational Analysis of the Function of Three Inhibitory Cell Types in Contextual Visual Processing
Published in
Frontiers in Computational Neuroscience, April 2017
DOI 10.3389/fncom.2017.00028
Pubmed ID
Authors

Jung H. Lee, Christof Koch, Stefan Mihalas

Abstract

Most cortical inhibitory cell types exclusively express one of three genes, parvalbumin, somatostatin and 5HT3a. We conjecture that these three inhibitory neuron types possess distinct roles in visual contextual processing based on two observations. First, they have distinctive synaptic sources and targets over different spatial extents and from different areas. Second, the visual responses of cortical neurons are affected not only by local cues, but also by visual context. We use modeling to relate structural information to function in primary visual cortex (V1) of the mouse, and investigate their role in contextual visual processing. Our findings are three-fold. First, the inhibition mediated by parvalbumin positive (PV) cells mediates local processing and could underlie their role in boundary detection. Second, the inhibition mediated by somatostatin-positive (SST) cells facilitates longer range spatial competition among receptive fields. Third, non-specific top-down modulation to interneurons expressing vasoactive intestinal polypeptide (VIP), a subclass of 5HT3a neurons, can selectively enhance V1 responses.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Israel 1 <1%
Netherlands 1 <1%
United States 1 <1%
Unknown 102 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 32%
Researcher 26 25%
Student > Master 11 10%
Student > Bachelor 6 6%
Student > Doctoral Student 6 6%
Other 9 9%
Unknown 13 12%
Readers by discipline Count As %
Neuroscience 39 37%
Agricultural and Biological Sciences 20 19%
Physics and Astronomy 8 8%
Psychology 4 4%
Medicine and Dentistry 3 3%
Other 11 10%
Unknown 20 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 June 2017.
All research outputs
#6,981,149
of 22,888,307 outputs
Outputs from Frontiers in Computational Neuroscience
#372
of 1,347 outputs
Outputs of similar age
#110,304
of 309,253 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#11
of 37 outputs
Altmetric has tracked 22,888,307 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 1,347 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has gotten more attention than average, scoring higher than 71% 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 309,253 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% 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 gotten more attention than average, scoring higher than 64% of its contemporaries.