Reset filters

Search publications


By keyword
By department

No publications found.

 

Spatial summation of broadband contrast.

Authors: Richard BHansen BCJohnson APShafto P


Affiliations

1 Department of Mathematics and Computer Science, Rutgers University, Newark, NJ, USA.
2 Department of Psychological and Brain Sciences, Neuroscience Program, Colgate University, Hamilton, NY, USA.
3 Department of Psychology, Concordia University, Montreal, Quebec, Canada.

Description

Spatial summation of broadband contrast.

J Vis. 2019 May 01;19(5):16

Authors: Richard B, Hansen BC, Johnson AP, Shafto P

Abstract

Spatial summation of luminance contrast signals has historically been psychophysically measured with stimuli isolated in spatial frequency (i.e., narrowband). Here, we revisit the study of spatial summation with noise patterns that contain the naturalistic 1/fa distribution of contrast across spatial frequency. We measured amplitude spectrum slope (a) discrimination thresholds and verified if sensitivity to a improved according to stimulus size. Discrimination thresholds did decrease with an increase in stimulus size. These data were modeled with a summation model originally designed for narrowband stimuli (i.e., single detecting channel; Baker & Meese, 2011; Meese & Baker, 2011) that we modified to include summation across multiple-differently tuned-spatial frequency channels. To fit our data, contrast gain control weights had to be inversely related to spatial frequency (1/f); thus low spatial frequencies received significantly more divisive inhibition than higher spatial frequencies, which is a similar finding to previous models of broadband contrast perception (Haun & Essock, 2010; Haun & Peli, 2013). We found summation across spatial frequency channels to occur prior to summation across space, channel summation was near linear and summation across space was nonlinear. Our analysis demonstrates that classical psychophysical models can be adapted to computationally define visual mechanisms under broadband visual input, with the adapted models offering novel insight on the integration of signals across channels and space.

PMID: 31100132 [PubMed - in process]


Links

PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31100132?dopt=Abstract