August 2012
Volume 12, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2012
Luminance range mapping in lightness computation: a novel role for attentional modulation
Author Affiliations
  • Michael E. Rudd
    Howard Hughes Medical Institute\nDepartment of Physiology and Biophysics, University of Washington
Journal of Vision August 2012, Vol.12, 1207. doi:10.1167/12.9.1207
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      Michael E. Rudd; Luminance range mapping in lightness computation: a novel role for attentional modulation. Journal of Vision 2012;12(9):1207. doi: 10.1167/12.9.1207.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Our visual system is capable of operating over an enormous range of light intensities, from an absolute threshold of a few photons to light environments twelve orders of magnitude greater in average intensity. By comparison, the noise-limited operating range of a spiking neuron is about three orders of magnitude. Significant signal compression is therefore required to map the range of environmental luminances into a neural rate code. Here I consider the problem of range mapping—also known as ‘scaling’ (Gilchrist et al., 1999)—in the context of lightness computation when scene luminances are interpreted as surface reflectances (e.g. Gelb staircase). I argue that range mapping is influenced by a combination of neural adaptation mechanisms functioning at different levels of the visual hierarchy and on different spatial scales, working in concert to avoid saturating higher-level neural mechanisms that represent surface reflectance. An example of a local adaptation mechanism is luminance ratio encoding, which is known to occur early in visual processing. Psychophysical data suggests the existence of a second local process that converts ratios to logarithms in order to avoid saturation at a subsequent processing stage, where local contrasts are perceptually integrated across space. At a somewhat larger spatial scale, contrast gain control functions to further avoid saturation in the mechanisms that spatially integrate contrast. Finally, I consider the question of where attention fits into this scheme. Several recent studies (Arend & Spehar, 1993; Rudd, 2010; Economou, ECVP 2011) demonstrate that lightness percepts can be influenced by instructions (attention). I argue from the experimental data that attentional selection influences perceived lightness at a processing stage prior to the stage at which contrast gain control operates and that this positioning in the sequence of lightness computations makes sense in that it protects the neurons representing reflectance from being saturated by unattended image content.

Meeting abstract presented at VSS 2012

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