Wednesday, September 28, 2016

Extreme color naming experiment finds locus for luma–chroma transformation

From time to time, a new physiological experimentation technique or a significant new instrument is developed, leading to breakthrough discoveries. In the case of color vision, this usually entails a doctoral student and their significant other—and maybe some additional dedicated colleagues or the professor—to undergo the cruel ordeal of having their pupils dilated (mydriasis) and their ciliary muscle paralyzed to avoid accommodation (cycloplegia), then get strapped to a headrest while biting a dental impression mount, to make observations in repeated interminable sessions for months on end, all in the name of science.

In their recent paper The elementary representation of spatial and color vision in the human retina, Ramkumar Sabesan et al. report on a seminal study to locate where in the human visual system (HVS), the luma-chroma encoding occurs in the parvocellular pathway (midget ganglion cells).

This study by Ramkumar Sabesan et al. represents the first time cone photoreceptors of known spectral type have been individually targeted and activated with light in the living human retina.

I cannot believe, it has been thirty years since I drew this diagram:

cognitive model

Although the above diagram looks like a model for the HVS, it was more a plan for my implementation of a color workbench. To keep the head cool and prevent it from overheating, our brain evolved to minimize the usage of energy. This is accomplished by having pipelines where at each stage the information gets recoded to make it more complex but more compact. This is at the cost of speed: while a two-photon catch the shift in electron density takes less than a femtosecond, the entire photo-cycle lasts a picosecond and at the end of the pipeline, adaptation can take seconds and color naming minutes.

An important feature were the bidirectional arrows: we have a feedback loop with control moving down and information moving up. Because of the sequence of recoding and the feedback, the receptors in the retina are not like pixels in a CCD sensor

  • Receptive field: area of visual field that activates a retinal ganglion (H.K. Hartline, 1938)
  • Center-surround fields allow for adaptive coding (transmit contrast instead of absolute values)
  • Horizontal cells presumed to inhibit either its bipolar cell or the receptors: opponent response in red–green and yellow–blue potentials (G. Svaetichin, 1956)
  • Retinal ganglion can be tonic or phasic: pathway may also be organized by information density or bandwidth

The last item comes from a table of the parvocellular and magnocellular pathways Lucia Rositani-Ronchi compiled for me at the 1993 AIC meeting in Budapest:

Originating retinal ganglion cells
Temporal resolution
Slow (sustained responses, low conduction velocity)
Fast (mostly transient responses, some sustained, high conduction velocity)
Modulation dominance
Adaptation occurs at high frequencies
Adaptation occurs at all frequencies
Receives mostly opponent type input from cones sensitive to short and long wavelengths
Receives mostly combined (broadband) input from M and L cones, both from the center and from the surround of receptive fields
Contrast sensitivity
Low (threshold > 10%)
High (threshold < 2%)
LGN cell saturation
Linear up to about 64% contrast
At 10%
Spatial resolution
High (small cells)
Low (large cells)
Spatio-temporal resolution
When fixation is strictly foveal, extraction of high spatial frequency information (test gratings), reflecting small color receptive fields
Responds to flicker
Long integration time
Short integration time
Relation to channels
Could be a site for both a lightness channel as for opponent-color channels. The role depends on the spatio-temporal content of the target used in the experiment
Might be a site for achromatic channels because the spectral sensitivity is similar to Vλ, it is more sensitive to flicker, and has only a weak opponent color component
Possible main role in the visual system
Sustain the perception of color, texture, shape, and fine stereopsis
Sustain the detection of movement, depth, and flicker; reading of text

We have four retinal pigments (erythrolabe, chlorolabe, cyanolabe, rhodopsin) attached by a lysine to a protein backbone. These four pigments are sensitized to photons at 4 energy levels (wavelengths): L, M, S, and rods. The energy levels are not numbers but distributions, namely the probabilities for a photon catch with that chromatophore.

A 3-dimensional signal with L, M, S is not efficient because we need a high spatial resolution but the chromatic information can be at a lower resolution. This is reflected in the modulations transfer functions for the HVS and is exploited for example in image encoding, where we transform an RGB signal into a color opponent signal and then down-sample the chroma images:

CIELAB separations

In 1993, it was not known where this transformation occurs in the HVS. In fact, there is quite a bit of processing in the retina, and many details are still unknown.


In their recent paper The elementary representation of spatial and color vision in the human retina, Ramkumar Sabesan et al. report on a seminal study to locate where in the HVS, the luma-chroma encoding occurs in the parvocellular pathway.

Using an adaptive optics scanning laser ophthalmoscope (AO-SLO), the authors studied 174 L-cone, 99 M-cone, and 12 S-cone samples by stimulating them individually with a 543 nm, 500 ms pulse and asking two subjects to report the perceived color name. The names were restricted to red, green, blue, yellow, white, and not seen.

The subjects reported achromatic sensations 61.8% of the time. When red was reported (22.5% of seen trials), it was more likely to be driven by L- than M-cones, whereas green (15.7%) was more likely to come from the excitation of M-cones. Thus, L-cones tended to signal both white and red, whereas M-cones tended to signal both white and green. The observation that these color percepts roughly align with the predictions of large-field cone-isolating stimuli suggests that the same opponent neuronal circuits may be implicated in both paradigms. This finding also supports the idea that the visual system can learn the spectral identity of individual cones.

The apparent segregation of color categories into distinct populations of cells is suggestive of a parallel representation of color and achromatic sensations. Moreover, these results imply that, for a large number of cones, their individual activation is not sufficient to produce a color. (Remember that in this experiment single cones are excited; in free vision, most cones are activated and the eye saccades, presenting a point in the visual field to several cones.)

The authors found that the cones most likely to generate strong spectral opponency in a parvocellular neuron, that is, those surrounded by cones of opposing type, were not more likely to generate red or green percepts. Rather, all these examples, when stimulated in isolation, drove achromatic percepts on a majority of the trials.

There is little doubt that the long-duration supra-threshold stimulation of individual cones here influences the firing of a number of different ganglion cell types. In particular, a multi-electrode study demonstrated that the activation of a single cone simultaneously evoked responses in both midget (parvocellular) and parasol (magnocellular) ganglion cells. The results may be particularly informative in differentiating proposals about the role of parvocellular neurons in achromatic spatial and color vision.

The study confirms the old result that the red-green system samples the visual world at a lower resolution than the achromatic system. The new results from the studies reported in the present paper are consistent with the idea that the HVS represents these two pieces of information with separate pathways that emerge as early as the photoreceptor synapse: one chiefly concerned with high-resolution achromatic vision and a second, lower-resolution color system.

The luma-chroma transformation with chroma subsampling is very important in image processing. In your opinion, does this new result allow the design of better imaging pipelines? Does this allow us to design better retinex algorithms? Join the conversation in the Trellis group.

Citation: R. Sabesan, B. P. Schmidt, W. S. Tuten, A. Roorda, The elementary representation of spatial and color vision in the human retina. Sci. Adv. 2, e1600797 (2016).

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