Many studies have provided evidence for the existence of universal constraints on color categorization or naming in various languages, but the biological basis of these constraints is unknown. A recent study of the pattern of color categorization across numerous languages has suggested that these patterns tend to avoid straddling a region in color space at or near the border between the English composite categories of “warm” and “cool”. This fault line in color space represents a fundamental constraint on color naming. Here we report that the two-way categorization along the fault line is correlated with the sign of the L- versus M-cone contrast of a stimulus color. Moreover, we found that the sign of the L-M cone contrast also accounted for the two-way clustering of the spatially distributed neural responses in small regions of the macaque primary visual cortex, visualized with optical imaging. These small regions correspond to the hue maps, where our previous study found a spatially organized representation of stimulus hue. Altogether, these results establish a direct link between a universal constraint on color naming and the cone-specific information that is represented in the primate early visual system.

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Introduction Heritability estimates of nicotine dependence (ND) range from 40-70%, but discovery GWAS of ND are underpowered and have limited predictive utility. In this work, we leverage genetically correlated traits and diseases to increase the accuracy of polygenic risk prediction. Methods We employed a multi-trait model using summary statistic-based best linear unbiased predictors (SBLUP) of genetic correlates of DSM-IV diagnosis of ND in 6,394 individuals of European Ancestry (prevalence = 45.3%, %female = 46.8%, µage = 40.08 [s.d. = 10.43]) and 3,061 individuals from a nationally-representative sample with Fagerström Test for Nicotine Dependence symptom count (FTND; 51.32% female, mean age = 28.9 [s.d. = 1.70]). Polygenic predictors were derived from GWASs known to be phenotypically and genetically correlated with ND (i.e., Cigarettes per Day (CPD), the Alcohol Use Disorders Identification Test (AUDIT-Consumption and AUDIT-Problems), Neuroticism, Depression, Schizophrenia, Educational Attainment, Body Mass Index (BMI), and Self-Perceived Risk-Taking); including Height as a negative control. Analyses controlled for age, gender, study site, and the first 10 ancestral principal components. Results The multi-trait model accounted for 3.6% of the total trait variance in DSM-IV ND. Educational Attainment (β=-0.125; 95% confidence interval (CI): [-0.149,-0.101]), CPD (0.071 [0.047,0.095]), and Self-Perceived Risk-Taking (0.051 [0.026,0.075]) were the most robust predictors. PGS effects on FTND were limited. Conclusions Risk for ND is not only polygenic, but also pleiotropic. Polygenic effects on ND that are accessible by these traits are limited in size and act additively to explain risk.

Cigarette cravings, especially those in response to environmental stressors and other smoking-related triggers (e.g., passing by a favorite smoking spot), are important contributors to smoking behavior and relapse. Previous studies have demonstrated significant individual differences in such cravings. This study explores the possibility that attitudes about smoking can influence the experience of cigarette craving. Consistent with classical theories of the links between cognition and motivation, we predicted that smokers who exhibit more favorable attitudes towards smoking would have greater cravings. Daily smokers (n=103, mean age=41.8years, 33% female) were instructed to imagine smoking, stress, and neutral scenarios. Cravings were measured prior to and after each exposure. Participants also completed an abridged version of the Smoking Consequence Questionnaire (SCQ) that had them rate the: 1) desirability and 2) likelihood, for eighteen separate negative smoking consequences (e.g., "The more I smoke, the more I risk my health", "People will think less of me if they see me smoking"). Findings revealed that favorable attitudes about the consequences of smoking, as measured by the SCQ-desirability index, significantly predicted cigarette cravings. Findings suggest that individual attitudes toward smoking may play an important role in better understanding cigarette cravings, which may ultimately help identify targets for more efficient and effective cognitive/attitude-based interventions for smoking cessation.