Previous studies on emotional effects of color often failed to control all the three perceptual dimensions of color: hue, saturation, and brightness. Here, we presented a three-dimensional space of chromatic colors by independently varying hue (blue, green, red), saturation (low, medium, high), and brightness (dark, medium, bright) in a factorial design. The 27 chromatic colors, plus 3 brightness-matched achromatic colors, were presented via an LED display. Participants (N = 62) viewed each color for 30 s and then rated their current emotional state (valence and arousal). Skin conductance and heart rate were measured continuously. The emotion ratings showed that saturated and bright colors were associated with higher arousal. The hue also had a significant effect on arousal, which increased from blue and green to red. The ratings of valence were the highest for saturated and bright colors, and also depended on the hue. Several interaction effects of the three color dimensions were observed for both arousal and valence. For instance, the valence ratings were higher for blue than for the remaining hues, but only for highly saturated colors. Saturated and bright colors caused significantly stronger skin conductance responses. Achromatic colors resulted in a short-term deceleration in the heart rate, while chromatic colors caused an acceleration. The results confirm that color stimuli have effects on the emotional state of the observer. These effects are not only determined by the hue of a color, as is often assumed, but by all the three color dimensions as well as their interactions.

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Many of us “see red,” “feel blue,” or “turn green with envy.” Are such color-emotion associations fundamental to our shared cognitive architecture, or are they cultural creations learned through our languages and traditions? To answer these questions, we tested emotional associations of colors in 4,598 participants from 30 nations speaking 22 native languages. Participants associated 20 emotion concepts with 12 color terms. Pattern-similarity analyses revealed universal color-emotion associations (average similarity coefficient r = .88). However, local differences were also apparent. A machine-learning algorithm revealed that nation predicted color-emotion associations above and beyond those observed universally. Similarity was greater when nations were linguistically or geographically close. This study highlights robust universal color-emotion associations, further modulated by linguistic and geographic factors. These results pose further theoretical and empirical questions about the affective properties of color and may inform practice in applied domains, such as well-being and design.

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