Properties of artificial neurons that report lightness based on accumulated experience with luminance

• Main Authors: Yaniv eMorgenstern, Dhara Venkata Rukmini, Brian B Monson, Dale ePurves
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2014-11-01
• Series: Frontiers in Computational Neuroscience
• Subjects: Vision; image statistics; efficient coding; inverse problem; gain control; Lightness perception
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00134/full

The responses of visual neurons in experimental animals have been extensively characterized. To ask whether these responses are consistent with a wholly empirical concept of visual perception, we optimized simple neural networks that respond according to the cumulative frequency of occurrence of local luminance patterns in retinal images. Based on this estimation of accumulated experience, the neuron responses showed classical center-surround receptive fields, luminance gain control and contrast gain control, the key properties of early level visual neurons determined in animal experiments. These results imply that a major purpose of pre-cortical neuronal circuitry is to contend with the inherently uncertain significance of luminance values in natural stimuli.