↓ Skip to main content

Characteristics of Eye-Position Gain Field Populations Determine Geometry of Visual Space

Overview of attention for article published in Frontiers in Integrative Neuroscience, January 2016
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
37 Mendeley
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
Characteristics of Eye-Position Gain Field Populations Determine Geometry of Visual Space
Published in
Frontiers in Integrative Neuroscience, January 2016
DOI 10.3389/fnint.2015.00072
Pubmed ID
Authors

Sidney R. Lehky, Margaret E. Sereno, Anne B. Sereno

Abstract

We have previously demonstrated differences in eye-position spatial maps for anterior inferotemporal cortex (AIT) in the ventral stream and lateral intraparietal cortex (LIP) in the dorsal stream, based on population decoding of gaze angle modulations of neural visual responses (i.e., eye-position gain fields). Here we explore the basis of such spatial encoding differences through modeling of gain field characteristics. We created a population of model neurons, each having a different eye-position gain field. This population was used to reconstruct eye-position visual space using multidimensional scaling. As gain field shapes have never been well-established experimentally, we examined different functions, including planar, sigmoidal, elliptical, hyperbolic, and mixtures of those functions. All functions successfully recovered positions, indicating weak constraints on allowable gain field shapes. We then used a genetic algorithm to modify the characteristics of model gain field populations until the recovered spatial maps closely matched those derived from monkey neurophysiological data in AIT and LIP. The primary differences found between model AIT and LIP gain fields were that AIT gain fields were more foveally dominated. That is, gain fields in AIT operated on smaller spatial scales and smaller dispersions than in LIP. Thus, we show that the geometry of eye-position visual space depends on the population characteristics of gain fields, and that differences in gain field characteristics for different cortical areas may underlie differences in the representation of space.

X Demographics

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 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 3%
France 1 3%
Unknown 35 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 30%
Researcher 6 16%
Student > Doctoral Student 5 14%
Student > Bachelor 4 11%
Professor 3 8%
Other 4 11%
Unknown 4 11%
Readers by discipline Count As %
Neuroscience 14 38%
Agricultural and Biological Sciences 6 16%
Psychology 5 14%
Computer Science 2 5%
Medicine and Dentistry 2 5%
Other 2 5%
Unknown 6 16%
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 20 January 2016.
All research outputs
#20,302,535
of 22,840,638 outputs
Outputs from Frontiers in Integrative Neuroscience
#757
of 856 outputs
Outputs of similar age
#331,714
of 394,766 outputs
Outputs of similar age from Frontiers in Integrative Neuroscience
#23
of 26 outputs
Altmetric has tracked 22,840,638 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 856 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one is in the 1st percentile – i.e., 1% 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 394,766 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 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.