Brian A. Wandell

Color constancy: a method for recovering surface spectral reflectance.

Human and machine visual sensing is enhanced when surface properties of objects in scenes, including color, can be reliably estimated despite changes in the ambient lighting conditions. We describe a computational method for estimating surface spectral reflectance when the spectral power distribution of the ambient light is not known.

Visual Field Maps in Human Cortex

Much of the visual cortex is organized into visual field maps: nearby neurons have receptive fields at nearby locations in the image. Mammalian species generally have multiple visual field maps with each species having similar, but not identical, maps. The introduction of functional magnetic resonance imaging made it possible to identify visual field maps in human cortex, including several near (1) medial occipital (V1,V2,V3), (2) lateral occipital (LO-1,LO-2, hMT+), (3) ventral occipital (hV4, VO-1, VO-2), (4) dorsal occipital (V3A, V3B), and (5) posterior parietal cortex (IPS-0 to IPS-4). Evidence is accumulating for additional maps, including some in the frontal lobe. Cortical maps are arranged into clusters in which several maps have parallel eccentricity representations, while the angular representations within a cluster alternate in visual field sign. Visual field maps have been linked to functional and perceptual properties of the visual system at various spatial scales, ranging from the level of individual maps to map clusters to dorsal-ventral streams. We survey recent measurements of human visual field maps, describe hypotheses about the function and relationships between maps, and consider methods to improve map measurements and characterize the response properties of neurons comprising these maps.

A spatial extension of CIELAB for digital color‐image reproduction

Abstract— We describe a spatial extension to the CIELAB color metric that is useful for measuring color reproduction errors of digital images. To compute the error, digital color images are spatially filtered using a pattern-color separable method and then converted into the CIELAB representation. Over patterned regions of the image, the reproduction errors measured using the spatial extension of CIELAB correspond to perceived color errors better than errors computed without the spatial extension. Over uniform spatial regions of the image, errors computed with the extension are equal to errors computed using the standard CIELAB formulae.

Population receptive field estimates in human visual cortex

We introduce functional MRI methods for estimating the neuronal population receptive field (pRF). These methods build on conventional visual field mapping that measures responses to ring and wedge patterns shown at a series of visual field locations and estimates the single position in the visual field that produces the largest response. The new method computes a model of the population receptive field from responses to a wide range of stimuli and estimates the visual field map as well as other neuronal population properties, such as receptive field size and laterality. The visual field maps obtained with the pRF method are more accurate than those obtained using conventional visual field mapping, and we trace with high precision the visual field maps to the center of the foveal representation. We report quantitative estimates of pRF size in medial, lateral and ventral occipital regions of human visual cortex. Also, we quantify the amount of input from ipsi- and contralateral visual fields. The human pRF size estimates in V1-V3 agree well with electrophysiological receptive field measurements at a range of eccentricities in corresponding locations within monkey and human visual field maps. The pRF method is non-invasive and can be applied to a wide range of conditions when it is useful to link fMRI signals in the visual pathways to neuronal receptive fields.

Visual field representations and locations of visual areas V1/2/3 in human visual cortex

The position, surface area and visual field representation of human visual areas V1, V2 and V3 were measured using fMRI in 7 subjects (14 hemispheres). Cortical visual field maps of the central 12 deg were measured using rotating wedge and expanding ring stimuli. The boundaries between areas were identified using an automated procedure to fit an atlas of the expected visual field map to the data. All position and surface area measurements were made along the boundary between white matter and gray matter. The representation of the central 2 deg of visual field in areas V1, V2, V3 and hV4 spans about 2100 mm2 and is centered on the lateral-ventral aspect of the occipital lobes at Talairach coordinates -29, -78, -11 and 25, -80, -9. The mean area between the 2-deg and 12-deg eccentricities for the primary visual areas was: V1: 1470 mm2; V2: 1115 mm2; and V3: 819 mm2. The sizes of areas V1, V2 and V3 varied by about a factor of 2.5 across individuals; the sizes of V1 and V2 are significantly correlated within individuals, but there is a very low correlation between V1 and V3. These in vivo measurements of normal human retinotopic visual areas can be used as a reference for comparison to unusual cases involving developmental plasticity, recovery from injury, identifying homology with animal models, or analyzing the computational resources available within the visual pathways.

Visual field maps and stimulus selectivity in human ventral occipital cortex.

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.

Children's reading performance is correlated with white matter structure measured by diffusion tensor imaging

We investigated the white matter structure in children (n = 14) with a wide range of reading performance levels using diffusion tensor imaging (DTI), a form of magnetic resonance imaging. White matter structure in a left temporo-parietal region that had been previously described as covarying with reading skill in adult readers also differs between children who are normal and poor readers. Specifically, the white matter structure measured using fractional anisotropy (FA) and coherence index (CI) significantly correlated with behavioral measurements of reading, spelling, and rapid naming performance. In general, lower anisotropy and lower coherence were associated with lower performance scores. Although the magnitude of the differences in children are smaller than those in adults, the results support the hypothesis that the structure of left temporoparietal neural pathways is a significant component of the neural system needed to develop fluent reading.

Colour tuning in human visual cortex measured with functional magnetic resonance imaging

The primate retina contains three classes of cones, the L, M and S cones, which respond preferentially to long-, middle- and short-wavelength visible light, respectively. Colour appearance results from neural processing of these cone signals within the retina and the brain. Perceptual experiments have identified three types of neural pathways that represent colour: a red–green pathway that signals differences between L- and M-cone responses; a blue–yellow pathway that signals differences between S-cone responses and a sum of L- and M-cone responses; and a luminance pathway that signals a sum of L- and M-cone responses. It might be expected that there are neurons in the primary visual cortex with response properties that resemble these three perceptual pathways, but attempts to find them have led to inconsistent results. We have therefore used functional magnetic resonance imaging (fMRI) to examine responses in the human brain to a large number of colours. In visual cortical areas V1 and V2, the strongest response is to red–green stimuli, and much of this activity is from neurons receiving opposing inputs from L and M cones. A strong response is also seen with blue–yellow stimuli, and this response declines rapidly as the temporal frequency of the stimulus is increased. These responses resemble psychophysical measurements, suggesting that colour signals relevant for perception are encoded in a large population of neurons in areas V1 and V2.

The Synthesis and Analysis of Color Images

I describe a method for performing the synthesis and analysis of digital color images. The method is based on two principles. First, image data are represented with respect to the separate physical factors, surface reflectance and the spectral power distribution of the ambient light, that give rise to the perceived color of an object. Second, the encoding is made efficient by using a basis expansion for the surface spectral reflectance and spectral power distribution of the ambient light that takes advantage of the high degree of correlation across the visible wavelengths normally found in such functions. Within this framework, the same basic methods can be used to synthesize image data for color display monitors and printed materials, and to analyze image data into estimates of the spectral power distribution and surface spectral reflectances. The method can be applied to a variety of tasks. Examples of applications include the color balancing of color images and the identification of material surface spectral reflectance when the lighting cannot be completely controlled.

Visualization and Measurement of the Cortical Surface

Much of the human cortical surface is obscured from view by the complex pattern of folds, making the spatial relationship between different surface locations hard to interpret. Methods for viewing large portions of the brains surface in a single flattened representation are described. The flattened representation preserves several key spatial relationships between regions on the cortical surface. The principles used in the implementations and evaluations of these implementations using artificial test surfaces are provided. Results of applying the methods to structural magnetic resonance measurements of the human brain are also shown. The implementation details are available in the source code, which is freely available on the Internet.