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Updated: Aug 9, 2026

Simultaneous Whole-cell Recordings from Photoreceptors and Second-order Neurons in an Amphibian Retinal Slice Preparation
Published on: June 1, 2013
[Computation of responses to color and brightness differences of neurons in the rabbit lateral geniculate nucleus]
Abstract:
Changes in activity of 51 neurons in the rabbit lateral geniculate nucleus evoked by the replacement of eight color and eight achromatic stimuli in pairs were analyzed. It was found that neurons displayed the earliest phasic (within 50-90 ms after the replacement) and tonic response components. The earliest component strongly correlated with differences between stimuli, whereas the tonic component depended on stimuli intensity. Analysis of phasic component revealed two neuronal populations: the first group of cells was specialized for stimuli differentiation only by their intensities, and, and the second group could measure differences in colors and intensities. Neuronal perceptual spaces were reconstructed using the average of the earliest response component as a measure of differences between stimuli. Spaces of 44 neurons (86%) were two-dimensional with brightness and darkness axes. Such neurons had the same structures of space for color and achromatic stimuli. Spaces of 7 neurons (14%) were four-dimensional with two chromatic and two achromatic axes. The structures of perceptual space reconstructed from neurons in the lateral geniculate nucleus were identical to the spaces calculated from the neurons in the primary visual cortex. The structure of the perceptual space reconstructed from neuronal spikes was also similar to space calculated from the N85 visual evoked potential component recorded under similar conditions and to another space reconstructed on the basis of rabbit's instrumental learning. This fact confirmed the general principle of vector coding in the visual system. The tonic component of the most of neurons in the lateral geniculate nucleus showed a linear correlation with changes in intensities, thereby these neurons could be characterized as pre-detectors for cortical selective detectors.
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