Gouki Okazawa

Image statistics underlying natural texture selectivity of neurons in macaque V4

Significance Our visual world is richly decorated with a great variety of textures, but the brain mechanisms underlying texture perception remain poorly understood. Here we studied the selectivity of neurons in visual area V4 of macaque monkey with synthetic textures having known combinations of higher-order image statistics. We found that V4 neurons typically respond best to particular sparse combinations of these statistics. We also found that population responses of texture-selective V4 neurons can explain human texture discrimination and categorization. Because the statistics of each image can be computed from responses of upstream neurons in visual area V1, our results provide a clear account of how the visual system processes local image features to create the global perception of texture in natural images. Our daily visual experiences are inevitably linked to recognizing the rich variety of textures. However, how the brain encodes and differentiates a plethora of natural textures remains poorly understood. Here, we show that many neurons in macaque V4 selectively encode sparse combinations of higher-order image statistics to represent natural textures. We systematically explored neural selectivity in a high-dimensional texture space by combining texture synthesis and efficient-sampling techniques. This yielded parameterized models for individual texture-selective neurons. The models provided parsimonious but powerful predictors for each neuron’s preferred textures using a sparse combination of image statistics. As a whole population, the neuronal tuning was distributed in a way suitable for categorizing textures and quantitatively predicts human ability to discriminate textures. Together, we suggest that the collective representation of visual image statistics in V4 plays a key role in organizing the natural texture perception.

Representation of the Material Properties of Objects in the Visual Cortex of Nonhuman Primates

Information about the material from which objects are made provide rich and useful clues that enable us to categorize and identify those objects, know their state (e.g., ripeness of fruits), and properly act on them. However, despite its importance, little is known about the neural processes that underlie material perception in nonhuman primates. Here we conducted an fMRI experiment in awake macaque monkeys to explore how information about various real-world materials is represented in the visual areas of monkeys, how these neural representations correlate with perceptual material properties, and how they correspond to those in human visual areas that have been studied previously. Using a machine-learning technique, the representation in each visual area was read out from multivoxel patterns of regional activity elicited in response to images of nine real-world material categories (metal, wood, fur, etc.). The congruence of the neural representations with either a measure of low-level image properties, such as spatial frequency content, or with the visuotactile properties of materials, such as roughness, hardness, and warmness, were tested. We show that monkey V1 shares a common representation with human early visual areas reflecting low-level image properties. By contrast, monkey V4 and the posterior inferior temporal cortex represent the visuotactile properties of material, as in human ventral higher visual areas, although there were some interspecies differences in the representational structures. We suggest that, in monkeys, V4 and the posterior inferior temporal cortex are important stages for constructing information about the material properties of objects from their low-level image features.

Selective responses to specular surfaces in the macaque visual cortex revealed by fMRI

The surface properties of objects, such as gloss, transparency and texture, provide important information about the material characteristics of objects in our visual environment. However, because there have been few reports on the neuronal responses to surface properties in primates, we still lack information about where and how surface properties are processed in the primate visual cortex. In this study, we used functional magnetic resonance imaging (fMRI) to examine the cortical responses to specular surfaces in the macaque visual cortex. Using computer graphics, we generated images of specular and matte objects and prepared scrambled images by locally randomizing the luminance phases of the images with specular and matte objects. In experiment 1, we contrasted the responses to specular images with those to matte and scrambled images. Activation was observed along the ventral visual pathway, including V1, V2, V3, V4 and the posterior inferior temporal (IT) cortex. In experiment 2, we manipulated the contrasts of images and found that the activation observed in these regions could not be explained solely by the global or local contrasts. These results suggest that image features related to specular surface are processed along the ventral visual pathway from V1 to specific regions in the IT cortex. This is consistent with previous human fMRI experiments that showed surface properties are processed in the ventral visual pathway.

Effects of Luminance Contrast on the Color Selectivity of Neurons in the Macaque Area V4 and Inferior Temporal Cortex

Appearance of a color stimulus is significantly affected by the contrast between its luminance and the luminance of the background. In the present study, we used stimuli evenly distributed on the CIE-xy chromaticity diagram to examine how luminance contrast affects neural representation of color in V4 and the anterior inferior temporal (AITC) and posterior inferior temporal (PITC) color areas (Banno et al., 2011). The activities of single neurons were recorded from monkeys performing a visual fixation task, and the effects of luminance contrast on the color selectivity of individual neurons and their population responses were systematically examined by comparing responses to color stimuli that were brighter or darker than the background. We found that the effects of luminance contrast differed considerably across V4 and the PITC and AITC. In both V4 and the PITC, the effects of luminance contrast on the population responses of color-selective neurons depended on color. In V4, the size of the effect was largest for blue and cyan, whereas in the PITC, the effect gradually increased as the saturation of the color stimulus was reduced, and was especially large with neutral colors (white, gray, black). The pattern observed in the PITC resembles the effect of luminance contrast on color appearance, suggesting PITC neurons are closely involved in the formation of the perceived appearance of color. By contrast, the color selectivities of AITC neurons were little affected by luminance contrast, indicating that hue and saturation of color stimuli are represented independently of luminance contrast in the AITC.

Categorical properties of the color term "GOLD".

Humans are able to categorize an infinite variety of surface colors into a small number of color terms. Previous studies have shown that 11 basic color terms are commonly used in fully developed languages. These studies usually used flat matte color plates as stimuli, but we can also perceive the colors of glossy surfaces by discounting the effect of the gloss. However, color terms such as GOLD and SILVER are specifically associated with glossy surfaces. In this study, we conducted a categorical color-naming task to examine whether the color terms GOLD and SILVER could be located in a stimulus space defined by combining CIE xy chromaticity coordinates and surface reflectance and whether they had categorical properties like ordinary basic color terms. We found that GOLD and SILVER were used for specific ranges of chromaticities with stimuli having large specular reflectances. Moreover, the strengths of the categorical properties, as assessed using measures of consistency, consensus, and reaction time, were comparable to those of the basic color terms, indicating that GOLD and SILVER are categorical color terms specifically associated with glossy surfaces. This also indicates that humans do not always discount surface gloss to identify colors but can utilize this information to categorize colors.

Gradual Development of Visual Texture-Selective Properties Between Macaque Areas V2 and V4

Complex shape and texture representations are known to be constructed from V1 along the ventral visual pathway through areas V2 and V4, but the underlying mechanism remains elusive. Recent study suggests that, for processing of textures, a collection of higher-order image statistics computed by combining V1-like filter responses serves as possible representations of textures both in V2 and V4. Here, to gain a clue for how these image statistics are processed in the extrastriate visual areas, we compared neuronal responses to textures in V2 and V4 of macaque monkeys. For individual neurons, we adaptively explored their preferred textures from among thousands of naturalistic textures and fitted the obtained responses using a combination of V1-like filter responses and higher-order statistics. We found that, while the selectivity for image statistics was largely comparable between V2 and V4, V4 showed slightly stronger sensitivity to the higher-order statistics than V2. Consistent with that finding, V4 responses were reduced to a greater extent than V2 responses when the monkeys were shown spectrally matched noise images that lacked higher-order statistics. We therefore suggest that there is a gradual development in representation of higher-order features along the ventral visual hierarchy.

Image Statistics for Golden Appearance of a Painting by a Japanese Edo-era Artist Jakuchu Ito

Humans use color terms to categorize huge amount of colors in the real world. Previous researches have shown that 11 basic color terms are sufficient to represent colors in many languages but recently we have found that color terms gold and silver are frequently used for images of objects with high specular reflectances. However, there are objects that appear golden but do not have clear highlights. One example can be found in Roshohakuho-zu, a painting drawn by a Japanese artist Jakuchu Ito. To find image features generating the golden appearance of this painting, we conducted psychophysical experiments using image patches extracted from the painting. We found that correlation between colors and luminances is related to goldness ratings evaluated by human subjects and manipulation of the color-luminance correlation affects the goldness of images. These results suggest that humans make use of the color-luminance correlation to perceive golden appearance of images.

Selective activation to surface gloss in the macaque visual cortex revealed by fMRI

ing sinusoidal grating with optimal orientation. In addition, we investigated the visual capacity of these rats using a computer-based, two alternative, force-choice visual discrimination task. The spatial visual acuity were significantly lower in rats that underwent either type of deprivation, compared with normal rats. These results suggest that fine-scale cortical networks contribute to the improvement of visual functions through the amplification of the responses in individual cortical neurons to particular visual inputs and a resultant sharpening of the tuning to visual stimulus features, such as orientation. Research fund: KAKENHI(22700373).