Is there a general trait of susceptibility to simultaneous contrast?

Individuals differ in their susceptibility to simultaneous contrast. Are the underlying differences in neural machinery conserved across different stimulus dimensions? We measured the extent to which 101 subjects perceived simultaneous contrast on the dimensions of luminance, colour, luminance contrast, colour contrast, orientation, spatial frequency, motion and numerosity. Individual differences showed re-test reliability for each dimension (0.32ICC(c,1)0.78, p0.05), but susceptibility to simultaneous contrast, with a few exceptions, was not correlated across dimensions. Either susceptibility to contrast arises empirically from an individual's interactions with the environment, or it is genetically determined but independently for different dimensions

No difference in variability of unique hue selections and binary hue selections

If unique hues have special status in phenomenological experience as perceptually pure, it seems reasonable to assume that they are represented more precisely by the visual system than are other colors. Following the method of Malkoc et al. (J. Opt. Soc. Am. A22, 2154 [2005]), we gathered unique and binary hue selections from 50 subjects. For these subjects we repeated the measurements in two separate sessions, allowing us to measure test-retest reliabilities (0.52≤ρ≤0.78; p≪0.01). We quantified the within-individual variability for selections of each hue. Adjusting for the differences in variability intrinsic to different regions of chromaticity space, we compared the within-individual variability for unique hues to that for binary hues. Surprisingly, we found that selections of unique hues did not show consistently lower variability than selections of binary hues. We repeated hue measurements in a single session for an independent sample of 58 subjects, using a different relative scaling of the cardinal axes of MacLeod-Boynton chromaticity space. Again, we found no consistent difference in adjusted within-individual variability for selections of unique and binary hues. Our finding does not depend on the particular scaling chosen for the Y axis of MacLeod-Boynton chromaticity space

An online version of the Mooney Face Test: phenotypic and genetic associations.

The Mooney Face Test is a widely used test of face perception, but was originally designed to be administered by personal interview. We have developed a three-alternative forced-choice version for online testing. We tested 397 healthy adults between the ages of 18 and 42 (M=24 years). There was a wide range of performance (64-100% correct; M=89.6%). We observed a significant sex difference favoring males (.31 standard deviation; p =.004). In addition, independently of sex, higher 2D:4D digit ratios were significantly associated with higher scores (ρ=.14, p=.006). A genome-wide association study (GWAS) for a subset of 370 participants identified an association between Mooney performance and a polymorphism in the RAPGEF5 gene (rs1522280; p=9.68×10(-8)). This association survives a permutation test (p=.031).This is the author's accepted manuscript. The final version of this paper is published by Elsevier in Neuropsychologia here: http://www.sciencedirect.com/science/article/pii/S0028393214002747

The Oxytocin Receptor Gene ( OXTR) and Face Recognition.

A recent study has linked individual differences in face recognition to rs237887, a single-nucleotide polymorphism (SNP) of the oxytocin receptor gene ( OXTR; Skuse et al., 2014). In that study, participants were assessed using the Warrington Recognition Memory Test for Faces, but performance on Warrington's test has been shown not to rely purely on face recognition processes. We administered the widely used Cambridge Face Memory Test-a purer test of face recognition-to 370 participants. Performance was not significantly associated with rs237887, with 16 other SNPs of OXTR that we genotyped, or with a further 75 imputed SNPs. We also administered three other tests of face processing (the Mooney Face Test, the Glasgow Face Matching Test, and the Composite Face Test), but performance was never significantly associated with rs237887 or with any of the other genotyped or imputed SNPs, after corrections for multiple testing. In addition, we found no associations between OXTR and Autism-Spectrum Quotient scores.This work was supported by Gatsby Charitable Foundation Grant GAT2903

The oxytocin receptor gene OXTR is not associated with face recognition

A recent study has linked individual differences in face recognition to rs237887, a single-nucleotide polymorphism (SNP) of the oxytocin receptor gene (OXTR; Skuse et al., 2014). In that study, participants were assessed using the Warrington Recognition Memory Test for Faces, but performance on Warrington’s test has been shown not to rely purely on face recognition processes. We administered the widely used Cambridge Face Memory Test—a purer test of face recognition—to 370 participants. Performance was not significantly associated with rs237887, with 16 other SNPs of OXTR that we genotyped, or with a further 75 imputed SNPs. We also administered three other tests of face processing (the Mooney Face Test, the Glasgow Face Matching Test, and the Composite Face Test), but performance was never significantly associated with rs237887 or with any of the other genotyped or imputed SNPs, after corrections for multiple testing. In addition, we found no associations between OXTR and Autism-Spectrum Quotient scores

General and specific factors in the processing of faces.

The ability to recognize faces varies considerably between individuals, but does performance co-vary for tests of different aspects of face processing? For 397 participants (of whom the majority were university students) we obtained scores on the Mooney Face Test, Glasgow Face Matching Test (GFMT), Cambridge Face Memory Test (CFMT) and Composite Face Test. Overall performance was significantly correlated for each pair of tests, and we suggest the term f for the factor underlying this pattern of positive correlations. However, there were large variations in the amount of variance shared by individual tests: The GFMT and CFMT are strongly related, whereas the GFMT and the Mooney test tap largely independent abilities. We do not replicate a frequently reported relationship between holistic processing (from the Composite test) and face recognition (from the CFMT)-indeed, holistic processing does not correlate with any of our tests. We report associations of performance with digit ratio and autism-spectrum quotient (AQ), and from our genome-wide association study we include a list of suggestive genetic associations with performance on the four face tests, as well as with f.Gatsby Charitable Foundation (Grant ID: GAT2903

Empirical evidence for unique hues?

Red, green, blue, yellow, and white have been distinguished from other hues as unique. We present results from two experiments that undermine existing behavioral evidence to separate the unique hues from other colors. In Experiment 1 we used hue scaling, which has often been used to support the existence of unique hues, but has never been attempted with a set of non-unique primaries. Subjects were assigned to one of two experimental conditions. In the "unique" condition, they rated the proportions of red, yellow, blue, and green that they perceived in each of a series of test stimuli. In the "intermediate" condition, they rated the proportions of teal, purple, orange, and lime. We found, surprisingly, that results from the two conditions were largely equivalent. In Experiment 2, we investigated the effect of instruction on subjects' settings of unique hues. We found that altering the color terms given in the instructions to include intermediate hues led to significant shifts in the hue that subjects identified as unique. The results of both experiments question subjects' abilities to identify certain hues as unique

A neural signature of the unique hues

Since at least the 17th century there has been the idea that there are four simple and perceptually pure “unique” hues: red, yellow, green, and blue, and that all other hues are perceived as mixtures of these four hues. However, sustained scientific investigation has not yet provided solid evidence for a neural representation that separates the unique hues from other colors. We measured event-related potentials elicited from unique hues and the ‘intermediate’ hues in between them. We find a neural signature of the unique hues 230 ms after stimulus onset at a post-perceptual stage of visual processing. Specifically, the posterior P2 component over the parieto-occipital lobe peaked significantly earlier for the unique than for the intermediate hues (Z = -2.9, p = .004). Having identified a neural marker for unique hues, fundamental questions about the contribution of neural hardwiring, language and environment to the unique hues can now be addressed

Compensation for red-green contrast loss in anomalous trichromats

For anomalous trichromats, threshold contrasts for color differences captured by the L and M cones and their anomalous analogs are much higher than for normal trichromats. The greater spectral overlap of the cone sensitivities reduces chromatic contrast both at and above threshold. But above threshold, adaptively nonlinear processing might compensate for the chromatically impoverished photoreceptor inputs. Ratios of sensitivity for threshold variations and for color appearance along the two cardinal axes of MacLeod-Boynton chromaticity space were calculated for three groups: normals (N = 15), deuteranomals (N = 9), and protanomals (N = 5). Using a four-alternative forced choice (4AFC) task, threshold sensitivity was measured in four color-directions along the two cardinal axes. For the same participants, we reconstructed perceptual color spaces for the positions of 25 hues using multidimensional scaling (MDS). From the reconstructed color spaces we extracted "color difference ratios," defined as ratios for the size of perceived color differences along the L/(L + M) axis relative to those along the S/(L + M) axis, analogous to "sensitivity ratios" extracted from the 4AFC task. In the 4AFC task, sensitivity ratios were 38% of normal for deuteranomals and 19% of normal for protanomals. Yet, in the MDS results, color difference ratios were 86% of normal for deuteranomals and 67% of normal for protanomals. Thus, the contraction along the L/(L + M) axis shown in the perceptual color spaces of anomalous trichromats is far smaller than predicted by their reduced sensitivity, suggesting that an adaptive adjustment of postreceptoral gain may magnify the cone signals of anomalous trichromats to exploit the range of available postreceptoral neural signals

What is white?

To shed light on the perceptual basis of the color white, we measured settings of unique white in a dark surround. We find that settings reliably show more variability in an oblique (blue-yellow) direction in color space than along the cardinal axes of the cone-opponent mechanisms. This is against the idea that white perception arises at the null point of the cone-opponent mechanisms, but one alternative possibility is that it occurs through calibration to the visual environment. We found that the locus of maximum variability in settings lies close to the locus of natural daylights, suggesting that variability may result from uncertainty about the color of the illuminant. We tested this by manipulating uncertainty. First, we altered the extent to which the task was absolute (requiring knowledge of the illumination), or relative. We found no clear effect of this factor on the reduction in sensitivity in the blue-yellow direction. Second, we provided a white surround as a cue to the illumination, or left the surround dark. Sensitivity was selectively worse in the blue-yellow direction when the surround was black than when it was white. Our results can be functionally related to the statistics of natural images, where a greater blue-yellow dispersion is characteristic of both reflectances (where anisotropy is weak) and illuminants (where it is very pronounced). Mechanistically, the results could suggest a neural signal responsive to deviations from the blue-yellow locus, or an adaptively matched range of contrast response functions for signals that encode different directions in color space