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Full Access Nonlinear integration of multispectral information: Human colour vision analogues to sensory integration in rattlesnake

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Nonlinear integration of multispectral information: Human colour vision analogues to sensory integration in rattlesnake

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Information integration occurs at every sensory scale and although distinctions are made for integration between and within senses, integration at intermediate scales may exploit familiar mechanisms. Here, we explore this idea by applying a sensory integration mechanism to some poorly understood multispectral integration problems in human colour vision. Billock and Tsou (IMRF, 2011) used a binding-like neural synchronization mechanism to model intensity-dependent (inverse) enhancement of visual responses by auditory stimulation in cat. The same model also applies to mutual enhancement of visual and infrared responses in rattlesnake, suggesting that a similar mechanism could model integration of spectral information in human colour vision. For example, chromatic brightness is thought to be a vector-like nonlinear combination of luminance and chromatic channels; its neural correlate is unknown. We model its spectral sensitivity by pairwise excitatory synchronization between luminance (broadband) neurons and cortically rectified L+M- and S+M-L- LGN neurons. Similarly, the yellow lobe of the yellow-blue opponent channel is known to be a nonlinearly enhanced combination of long- and medium-wavelength-sensitive inputs, but no sensible neural model for this interaction has been advanced. We model the spectral sensitivity of ‘yellowness’ using excitatory synchronization between cortically rectified L+M+S- and M+L- LGN units. The inputs for both simulations were macaque neural firing rate data (DeValois et al., 1966). Fascinatingly, in both cases, multispectral integration in human colour vision was well modeled using the rattlesnake/cat neural synchronization equations without any use of fitting parameters. This is the first application of sensory integration concepts to human colour vision transformations.

Affiliations: 1: 1National Research Council at the U.S. Air Force Research Laboratory, US; 2: 2U.S. Air Force Research Laboratory, US

Information integration occurs at every sensory scale and although distinctions are made for integration between and within senses, integration at intermediate scales may exploit familiar mechanisms. Here, we explore this idea by applying a sensory integration mechanism to some poorly understood multispectral integration problems in human colour vision. Billock and Tsou (IMRF, 2011) used a binding-like neural synchronization mechanism to model intensity-dependent (inverse) enhancement of visual responses by auditory stimulation in cat. The same model also applies to mutual enhancement of visual and infrared responses in rattlesnake, suggesting that a similar mechanism could model integration of spectral information in human colour vision. For example, chromatic brightness is thought to be a vector-like nonlinear combination of luminance and chromatic channels; its neural correlate is unknown. We model its spectral sensitivity by pairwise excitatory synchronization between luminance (broadband) neurons and cortically rectified L+M- and S+M-L- LGN neurons. Similarly, the yellow lobe of the yellow-blue opponent channel is known to be a nonlinearly enhanced combination of long- and medium-wavelength-sensitive inputs, but no sensible neural model for this interaction has been advanced. We model the spectral sensitivity of ‘yellowness’ using excitatory synchronization between cortically rectified L+M+S- and M+L- LGN units. The inputs for both simulations were macaque neural firing rate data (DeValois et al., 1966). Fascinatingly, in both cases, multispectral integration in human colour vision was well modeled using the rattlesnake/cat neural synchronization equations without any use of fitting parameters. This is the first application of sensory integration concepts to human colour vision transformations.

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1. Billock V. A. , Tsou B. H. ( 2011). "Oscillatory synchronization can predict intensity-dependent enhancement: A bridge between sensory binding theory and multisensory integration". MultiSense 2011, the annual meeting of the International Multisensory Research Forum, Fukuoka, Japan, I-Perception Vol 2( 8), 888.
2. De Valois R. L. , Abramov I. , Jacobs G. H. ( 1966). "Analysis of response patterns of LGN cells", Journal of the Optical Society of America Vol 56, 966977. http://dx.doi.org/10.1364/JOSA.56.000966
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/content/journals/10.1163/187847612x648099
2012-01-01
2016-12-08

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