Literature DB >> 15707920

Opponent-motion mechanisms are self-normalizing.

Stéphane J M Rainville1, Walter L Makous, Nicholas E Scott-Samuel.   

Abstract

In the ultimate stage of the Adelson-Bergen motion energy model [Adelson, E. H., & Bergen, J. (1985). Spatiotemporal energy models for the perception of motion. Journal of the Optical Society of America, 2, 284-299], motion is derived from the difference between directionally opponent energies E(L) and E(R). However, Georgeson and Scott-Samuel [Georgeson, M. A., & Scott-Samuel, N. E. (1999). Motion contrast: A new metric for direction discrimination. Vision Research, 39, 4393-4402] demonstrated that motion contrast-a metric that normalizes opponent motion energy (E(L)-E(R)) by flicker energy (E(L)+E(R))-is a better descriptor of human direction discrimination. In a previous study [Rainville, S. J. M., Makous, W. L., & Scott-Samuel, N. E. (2002). The spatial properties of opponent-motion normalization. Vision Research, 42, 1727-1738], we used a lateral masking paradigm to show that opponent-motion normalization is selective for flicker position, orientation, and spatial-frequency. In the present study, we used a superposition masking paradigm and compared results to lateral masking data, as the two masking types activate local and remote normalization mechanisms differentially. Although selectivity for flicker orientation and spatial frequency varied across observers, bandwidths were similar across lateral and superimposed masking conditions. Additional experiments demonstrated that normalization signals are pooled over a spatial region whose aspect ratio and size are consistent with those of local motion detectors. Together, results show no evidence of remote normalization signals predicted by broadband inhibitory models [(e.g.) Heeger, D. J. (1992). Normalization of cell responses in cat striate cortex. Visual Neuroscience, 9, 181-197; Foley, J. M. (1994). Human luminance pattern-vision mechanisms: Masking experiments require a new model. Journal of the Optical Society of America A-Optics and Image Science, 11, 1710-1719] but support a local normalization process whose spatial properties are inherited from low-level motion detectors.

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Year:  2004        PMID: 15707920     DOI: 10.1016/j.visres.2004.10.018

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  3 in total

1.  Modelling fast forms of visual neural plasticity using a modified second-order motion energy model.

Authors:  Andrea Pavan; Adriano Contillo; George Mather
Journal:  J Comput Neurosci       Date:  2014-07-31       Impact factor: 1.621

2.  Binocular function during unequal monocular input.

Authors:  Taekjun Kim; Ralph D Freeman
Journal:  Eur J Neurosci       Date:  2017-01-25       Impact factor: 3.386

3.  Modelling adaptation to directional motion using the Adelson-Bergen energy sensor.

Authors:  Andrea Pavan; Adriano Contillo; George Mather
Journal:  PLoS One       Date:  2013-03-15       Impact factor: 3.240

  3 in total

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