Environmental color statistics shape the anisotropic geometry of human color discrimination

Hue is a powerful cue for object discrimination, but human color discrimination is anisotropic: hue thresholds are lower than chroma thresholds for orangish colors, but nearly equal for purplish colors. Here we show that this asymmetry reflects environmental color statistics rather than being a fixed consequence of cone-opponent architecture. Across fifteen image and reflectance databases, orangish hues accounted for 62.5% of chromatic samples, compared with 5.3% for purplish hues. We replicated the hue–chroma asymmetry psychophysically in 44 participants. Magnetoencephalography revealed a corresponding neural asymmetry, with superior decoding of orangish hue differences emerging around 250 ms after stimulus onset. Deep neural networks trained on naturalistic image datasets reproduced the human-like asymmetry without explicit color supervision. Critically, training on hue-inverted images reversed the asymmetry, producing greater hue sensitivity for purplish than for orangish colors. These results suggest that the geometry of color discrimination is shaped by ecological chromatic structure.