Spectral sensitivities of the human cones

Stockman, Andrew; MacLeod, Donald I. A.; Johnson, Nancy E.

doi:10.1364/josaa.10.002491

Cited by 354 publications

(250 citation statements)

References 73 publications

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“…This confirms the conclusions using high-color backgrounds (Conway, 2001). High-color backgrounds may provide more reliable estimates of the cone inputs because "transient chromatic adaptation produced by an abrupt change of background color permits an easier and closer approach to cone isolation than does steadystate adaptation" (Stockman et al, 1993). In any event, the receptive-field structure of single double-opponent cells remains relatively stable using both methods (Conway, 2006) and predicts that the neurons will respond optimally to adjacent patches of oppositely colored light (e.g., red next to green).…”

supporting

confidence: 80%

Spatial and Temporal Properties of Cone Signals in Alert Macaque Primary Visual Cortex

Conway¹,

Livingstone²

2006

J. Neurosci.

140

185

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7°) than spatial-opponent cell centers (ϳ1°). We found that red-green cells received S-cone input, which aligned with M input, and, unlike blue-yellow cells, red-green cells gave push-pull responses: receptivefield centers of red-ON cells were excited by both L increments (bright red) and M decrements (dark red) and were suppressed by both L decrements (dark green) and M increments (bright green). Excitatory responses to decrements were slightly larger than to increments, which may account for the lower detection and discrimination thresholds of decrements shown psychophysically. By virtue of their specialized receptive fields, the neurons described here spatially transform the cone signals and represent the first stage in the visual system at which spatially opponent color calculations are made.

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supporting

confidence: 80%

Spatial and Temporal Properties of Cone Signals in Alert Macaque Primary Visual Cortex

Conway¹,

Livingstone²

2006

J. Neurosci.

140

185

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“…Spectral and gamma curves were measured at 4 nm intervals in the 380 -770 nm range using a photospectrometer (PR-650; Photoresearch, Chatsworth, CA). Stimulus cone contrasts were calculated using the 2°Stockman fundamentals (Stockman et al, 1993), which incorporate the macular pigment absorption effects. Because our stimuli were within 3°eccentricities, no correction for macular pigment was necessary.…”

Section: Visual Displaymentioning

confidence: 99%

Specializations for Chromatic and Temporal Signals in Human Visual Cortex

Liu¹,

Wandell²

2005

J. Neurosci.

110

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Neurological case studies and qualitative measurements suggest that regions within human extrastriate cortex are specialized for different perceptual functions, including color. However, there are few quantitative measurements of human extrastriate color specializations. We studied the chromatic and temporal responses in several different clusters of human visual field maps using functional magnetic resonance imaging. Contrast response functions were measured for luminance [(L ϩ M)-cone], red-green [(L Ϫ M)-cone] and blueyellow (S-cone) modulations at various temporal frequencies. In primary visual cortex (V1), temporal responsivities to luminance and red-green modulations are approximately constant up to 10 Hz, but responsivities to blue-yellow modulations decrease significantly. In ventral occipital cortex (VO), all colors elicit strong responses, and, for each color, low temporal frequency modulations are more effective than high temporal frequency modulations. Hence, VO represents the full range of color information but does not respond well to rapid modulations. Conversely, in human motion-selective cortex (MTϩ) and V3A, blue-yellow modulations elicit very weak responses, whereas luminance and red-green high temporal frequency modulations are equally or more effective than low temporal frequency modulations. Hence, these dorsal occipital regions respond well to rapid modulations, but not all color information is represented. Similar to human motion perception, MTϩ and V3A respond powerfully to all temporal frequencies but only to some colors. Similar to human color perception, VO responds powerfully to all colors but only to relatively low temporal frequencies.

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“…One may compute cone coordinates or XYZ tristimulus coordinates from the spectral power distributions measured by spectroradiometers. If one wishes to use a description of color vision that differs from that specified by the CIE system (e.g., 24,25,27,42,62,63), then it is necessary to characterize the display by using a spectroradiometer. However, spectroradiometers are expensive (thousands of dollars), whereas colorimeters often cost less than a thousand dollars and the XYZ measurements they provide are sufficient for many applications.…”

Section: Instrumental Considerationsmentioning

confidence: 99%

Display Characterization

Brainard¹,

Pelli²,

Robson³

2002

Encyclopedia of Imaging Science and Technology

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This article describes the characterization and use of computer‐controlled displays. Most imaging devices are now computer controlled, and this makes it possible for the computer to take into account the properties of the imaging device to achieve the intended image. CRT (cathode ray tube) monitors is emphasizes the article begins with the standard model of CRT imaging. How this model may be used to render the desired visual image accurately from its numerical representation is shown. The domain of validity of the standard CRT model is discussed. The model makes several assumptions about monitor performance that are usually valid but can fail for certain images and CRTs. How to detect such failures and how to cope with them are explained. Primarily users who will be doing accurate imaging on a CRT are addressed. CRTs are very well suited for accurate rendering. Treatment of LCDs (liquid crystal displays) is brief, in part because this technology is changing very rapidly and in part because the strong dependence of emitted light on viewing angle in current LCD displays is a great obstacle to accurate rendering. Plasma displays seem more promising in this regard. All the steps of a basic characterization are presented. The treatment emphasizes accuracy both in color and in space. The display characteristics that need to be taken into account to present an arbitrary spatiotemporal image accurately, that is, luminance and chromaticity as a function of space and time are reviewed. A number of topics of interest to the vision scientist who requires precise control of a displayed stimulus are treated. This article explains the standard CRT model (and necessary basic colorimetry) and describes simple visual tests (available online) that establish the model's validity for a monitor. How to use the standard model to characterize your display for accurate rendering is shown. Finally, the discussion briefly presents several more advanced topics, including characterization of non‐CRT displays.

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Spectral sensitivities of the human cones

Cited by 354 publications

References 73 publications

Spatial and Temporal Properties of Cone Signals in Alert Macaque Primary Visual Cortex

Spatial and Temporal Properties of Cone Signals in Alert Macaque Primary Visual Cortex

Specializations for Chromatic and Temporal Signals in Human Visual Cortex

Display Characterization

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