English and Russian color terms divide the color spectrum differently. Unlike English, Russian makes an obligatory distinction between lighter blues (''goluboy'') and darker blues (''siniy''). We investigated whether this linguistic difference leads to differences in color discrimination. We tested English and Russian speakers in a speeded color discrimination task using blue stimuli that spanned the siniy/goluboy border. We found that Russian speakers were faster to discriminate two colors when they fell into different linguistic categories in Russian (one siniy and the other goluboy) than when they were from the same linguistic category (both siniy or both goluboy). Moreover, this category advantage was eliminated by a verbal, but not a spatial, dual task. These effects were stronger for difficult discriminations (i.e., when the colors were perceptually close) than for easy discriminations (i.e., when the colors were further apart). English speakers tested on the identical stimuli did not show a category advantage in any of the conditions. These results demonstrate that (i) categories in language affect performance on simple perceptual color tasks and (ii) the effect of language is online (and can be disrupted by verbal interference).categorization ͉ cross-linguistic ͉ Whorf

Human visual cortex is organized into distinct visual field maps whose locations and properties provide important information about visual computations. There are two conflicting models of the organization and computational role of ventral occipital visual field maps. We report new functional MRI measurements that test these models. We also present the first coordinated measurements of visual field maps and stimulus responsivity to color, objects and faces in ventral occipital cortex. These measurements support a model that includes a hemifield map, hV4, adjacent to the central field representation of ventral V3. In addition, the measurements demonstrate a cluster of visual field maps in ventral occipital cortex (VO cluster) anterior to hV4. We describe the organization and stimulus responsivity of two new hemifield maps, VO-1 and VO-2, within this cluster. The maps and stimulus responsivity support a general organization of visual cortex based on clusters of maps that serve distinct computational functions.

How do neuronal populations represent concurrent stimuli? We measured population responses in cat primary visual cortex (V1) using electrode arrays. Population responses to two superimposed gratings were weighted sums of the individual grating responses. The weights depended strongly on the relative contrasts of the components. When the contrasts were similar the population performed an approximately equal summation. When the contrasts differed markedly, however, the population performed approximately a winner-take-all competition. Stimuli that were intermediate to these extremes elicited intermediate responses. This entire range of behaviors was explained by a single model of contrast normalization. Normalization captured both the spike responses and the local field potential responses; it even predicted visually evoked currents source-localized to V1 in human subjects. Normalization has profound effects on V1 population responses, and is likely to shape the interpretation of these responses by higher cortical areas.