As with other organs, the eye's growth is regulated by homeostatic control mechanisms. Unlike other organs, the eye relies on vision as a principal input to guide growth. In this review, we consider several implications of this visual guidance. First, we compare the regulation of eye growth to that of other organs. Second, we ask how the visual system derives signals that distinguish the blur of an eye too large from one too small. Third, we ask what cascade of chemical signals constitutes this growth control system. Finally, if the match between the length and optics of the eye is under homeostatic control, why do children so commonly develop myopia, and why does the myopia not limit itself? Long-neglected studies may provide an answer to this last question.

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

Kay KN, Winawer J, Mezer A, Wandell BA. Compressive spatial summation in human visual cortex. J Neurophysiol 110: 481-494, 2013. First published April 24, 2013 doi:10.1152/jn.00105.2013.-Neurons within a small (a few cubic millimeters) region of visual cortex respond to stimuli within a restricted region of the visual field. Previous studies have characterized the population response of such neurons using a model that sums contrast linearly across the visual field. In this study, we tested linear spatial summation of population responses using blood oxygenation level-dependent (BOLD) functional MRI. We measured BOLD responses to a systematic set of contrast patterns and discovered systematic deviation from linearity: the data are more accurately explained by a model in which a compressive static nonlinearity is applied after linear spatial summation. We found that the nonlinearity is present in early visual areas (e.g., V1, V2) and grows more pronounced in relatively anterior extrastriate areas (e.g., LO-2, VO-2). We then analyzed the effect of compressive spatial summation in terms of changes in the position and size of a viewed object. Compressive spatial summation is consistent with tolerance to changes in position and size, an important characteristic of object representation. (Fig. 1). The validity of this assumption is important to examine, as it affects the accuracy of pRF estimates and may reveal insight into response properties at different stages of the visual map hierarchy. Assessments of linearity of spatial summation have been conducted in both electrophysiology and fMRI, but these have provided conflicting conclusions (e.g., Britten and Heuer 1999;Hansen et al. 2004;Kastner et al. 2001;Pihlaja et al. 2008). Thus the precise nature of spatial pooling, and how well the linear approximation describes physiological responses, remains unclear.In this study, we examine spatial summation using systematic measurements of blood oxygenation level-dependent (BOLD) fMRI responses in human visual cortex to a range of spatial contrast patterns. We uncover a small nonlinear effect (subadditive spatial summation) in primary visual cortex and find that the nonlinear effect is pronounced in extrastriate maps. To account for the effect, we develop a computational model in which a compressive static nonlinearity is applied after linear spatial summation; this model substantially improves cross-validation performance compared with a linear spatial summation model.

A quarter-century ago visual neuroscientists had little information about the number and organization of retinotopic maps in human visual cortex. The advent of functional magnetic resonance imaging (MRI), a non-invasive, spatially-resolved technique for measuring brain activity, provided a wealth of data about human retinotopic maps. Just as there are differences amongst nonhuman primate maps, the human maps have their own unique properties. Many human maps can be measured reliably in individual subjects during experimental sessions lasting less than an hour. The efficiency of the measurements and the relatively large amplitude of functional MRI signals in visual cortex make it possible to develop quantitative models of functional responses within specific maps in individual subjects. During this last quarter century, there has also been significant progress in measuring properties of the human brain at a range of length and time scales, including white matter pathways, macroscopic properties of gray and white matter, and cellular and molecular tissue properties. We hope the next twenty-five years will see a great deal of work that aims to integrate these data by modeling the network of visual signals. We don’t know what such theories will look like, but the characterization of human retinotopic maps from the last twenty-five years is likely to be an important part of future ideas about visual computations.