Anatomical and physiological observations in monkeys indicate that the primate visual system consists of several separate and independent subdivisions that analyze different aspects of the same retinal image: cells in cortical visual areas 1 and 2 and higher visual areas are segregated into three interdigitating subdivisions that differ in their selectivity for color, stereopsis, movement, and orientation. The pathways selective for form and color seem to be derived mainly from the parvocellular geniculate subdivisions, the depth- and movement-selective components from the magnocellular. At lower levels, in the retina and in the geniculate, cells in these two subdivisions differ in their color selectivity, contrast sensitivity, temporal properties, and spatial resolution. These major differences in the properties of cells at lower levels in each of the subdivisions led to the prediction that different visual functions, such as color, depth, movement, and form perception, should exhibit corresponding differences. Human perceptual experiments are remarkably consistent with these predictions. Moreover, perceptual experiments can be designed to ask which subdivisions of the system are responsible for particular visual abilities, such as figure/ground discrimination or perception of depth from perspective or relative movement--functions that might be difficult to deduce from single-cell response properties.

Staining for the mitochondrial enzyme cytochrome oxidase reveals an array of dense regions (blobs) in the primate primary visual cortex. They are most obvious in the upper layers, 2 and 3, but can also be seen in layers 4B, 5, and 6, in register with the blobs in layers 2 and 3. We compared cells inside and outside blobs in macaque and squirrel monkeys, looking at their physiological responses and anatomical connections. Cells within blobs did not show orientation selectivity, whereas cells between blobs were highly orientation selective. Receptive fields of blob cells had circular symmetry and were of three main types, Broad-Band Center-Surround, Red-Green Double-Opponent, and Yellow-Blue Double-Opponent. Double-Opponent cells responded poorly or not at all to white light in any form, or to diffuse light at any wavelength. In contrast to blob cells, none of the cells recorded in layer 4C beta were Double-Opponent: like the majority of cells in the parvocellular geniculate layers, they were either Broad-Band or Color-Opponent Center-Surround, e.g., red-on-center green-off-surround. To our surprise cells in layer 4C alpha were orientation selective. In tangential penetrations throughout layers 2 and 3, optium orientation, when plotted against electrode position, formed long, regular, usually linear sequences, which were interrupted but not perturbed by the blobs. Staining area 18 for cytochrome oxidase reveals a series of alternating wide and narrow dense stripes, separated by paler interstripes. After small injections of horseradish peroxidase into area 18, we saw a precise set of connections from the blobs in area 17 to thin stripes in area 18, and from the interblob regions in area 17 to interstripes in area 18. Specific reciprocal connections also ran from thin stripes to blobs and from interstripes to interblobs. We have not yet determined the area 17 connections to thick stripes in area 18. In addition, within area 18 there are stripe-to-stripe and interstripe-to-interstripe intrinsic connections. These results suggest that a system involved in the processing of color information, especially color-spatial interactions, runs parallel to and separate from the orientation-specific system. Color, encoded in three coordinates by the major blob cell types, red-green, yellow-blue, and black-white, can be transformed into the three coordinates, red, green, and blue, of the Retinex algorithm of Land.

Face perception is a skill crucial to primates. In both humans and macaque monkeys, functional magnetic resonance imaging (fMRI) reveals a system of cortical regions that show increased blood flow when the subject views images of faces, compared with images of objects. However, the stimulus selectivity of single neurons within these fMRI-identified regions has not been studied. We used fMRI to identify and target the largest face-selective region in two macaques for single-unit recording. Almost all (97%) of the visually responsive neurons in this region were strongly face selective, indicating that a dedicated cortical area exists to support face processing in the macaque.Lesion studies show that object recognition depends on the temporal lobe (1), but the principles of temporal lobe organization underlying the representation of objects remain uncertain. In particular, the question of how face processing is functionally organized has been a focus of intense debate (2-4). In humans, several cortical regions have consistently been found in fMRI studies to be more responsive to faces than to other objects, and it has been suggested that the fusiform face area (FFA) is exclusively dedicated to face processing (5). However, physiologists who are recording from the macaque temporal lobe have never found any entirely face-selective region; instead, they have reported scattered clusters of face-selective cells, especially prevalent in the upper and lower banks of the superior temporal sulcus (STS), with, at most, 20 to 30% of the cells in any region being face selective (6-9).It is possible that an area consisting entirely of face-selective cells exists in the macaque and has simply been missed because of single-unit sampling limitations. Alternatively, no such †To whom correspondence should be addressed.

Physiological and anatomical findings in the primate visual system, as well as clinical evidence in humans, suggest that different components of visual information processing are segregated into largely independent parallel pathways. Such a segregation leads to certain predictions about human vision. In this paper we describe psychophysical experiments on the interactions of color, form, depth, and movement in human perception, and we attempt to correlate these aspects of visual perception with the different subdivisions of the visual system.

Several behavioral studies have shown that developmental dyslexics do poorly in tests requiring rapid visual processing. In primates fast, low-contrast visual information is carried by the magnocellular subdivision of the visual pathway, and slow, high-contrast information is carried by the parvocellular division. In this study, we found that dyslexic subjects showed diminished visually evoked potentials to rapid, low-contrast stimuli but normal responses to slow or highcontrast stimuli. The abnormalities in the dyslexic subjects' evoked potentials were consistent with a defect in the magnocellular pathway at the level of visual area 1 or earlier. We then compared the lateral geniculate nuclei from five dyslexic brains to five control brains and found abnormalities in the magnocelular, but not the parvocellular, layers. Studies using auditory and somatosensory tests have shown that dyslexics do poorly in these modalities only when the tests require rapid discriminations. We therefore hypothesize that many cortical systems are similarly divided into a fast and a slow subdivision and that dyslexia specifically affects the fast subdivisions.Developmental dyslexia is the selective impairment of reading skills despite normal intelligence, sensory acuity, motivation, and instruction. Several perceptual studies have suggested that dyslexic subjects process visual information more slowly than normal subjects. The flicker fusion rate, which is the fastest rate at which a contrast reversal of a stimulus can be seen, is abnormally slow in dyslexic children at low spatial frequencies and low contrasts (1). Moreover, such visual abnormalities were reported to be found in >75% of the reading-disabled children tested (2). When two visual stimuli are presented in rapid succession, the two images fuse and appear as a single presentation; the temporal separation necessary to distinguish two presentations measures visual persistence, and this is up to 100 msec longer for dyslexic than for normal children, particularly for low spatial frequency stimuli (3-6). Dyslexic subjects also have trouble distinguishing the order of two rapidly flashed visual stimuli (7). In contrast, dyslexics perform normally on tests having prolonged stimulus presentations (2).These perceptual studies suggest an abnormality in dyslexia affecting some part of the visual system that is fast and transient and has high contrast sensitivity and low spatial selectivity. Exactly these properties characterize the magnocellular subdivision of the visual pathway (8, 9). The primate visual system is composed mainly of two major processing pathways that remain largely segregated and independent throughout the visual system. This subdivision begins in the retina but is most apparent in, and was first discovered in, the lateral geniculate nucleus (LGN), where cells in the ventral, or magnocellular, layers are larger than cells in the dorsal, or parvocellular, layers. In the retina and the LGN, the magno and parvo subdivisions differ physiologically in four major...

The ability of primates to effortlessly recognize faces has been attributed to the existence of specialized face areas. One such area, the macaque middle face patch, consists almost entirely of cells that are selective for faces, but the principles by which these cells analyze faces are unknown. We found that middle face patch neurons detect and differentiate faces using a strategy that is both part based and holistic. Cells detected distinct constellations of face parts. Furthermore, cells were tuned to the geometry of facial features. Tuning was most often ramp-shaped, with a one-to-one mapping of feature magnitude to firing rate. Tuning amplitude depended on the presence of a whole, upright face and features were interpreted according to their position in a whole, upright face. Thus, cells in the middle face patch encode axes of a face space specialized for whole, upright faces.Viewing the world, we are confronted by myriad visual objects. How does the brain extract these objects from the incoming bits and pieces of information? The representation of an object (as opposed to a spot, edge or smear of color) must involve a mechanism for representing its gestalt. What is the neural mechanism by which curves and spots are assembled into coherent objects? And how does the brain preserve fine distinctions between individual objects throughout this process?We have a good understanding of how edges, a form common to all objects, are coded by cells in area V1 (ref. 1), but the mechanisms by which the brain analyzes shapes at the next level are less understood. One major experimental difficulty is that there are so many different forms and no clear approach to choosing one set of forms over another for testing each cell. It is clear, however, that any study of object recognition must employ a restricted set of all possible forms. The challenge, then, is to find a way to constrain the stimulus space by incorporating prior knowledge about the cells' stimulus preferences.Functional magnetic resonance imaging (fMRI) provides a solution to this challenge 2 . Using fMRI in macaque monkeys, we found a cortical area in the temporal lobe that is activated much more by faces than by nonface objects3. Subsequent single-unit recordings showed that this area, the middle face patch, consists almost entirely of face-selective cells4. Targeting single-© 2009 Nature America, Inc. All rights reserved.Correspondence should be addressed to W. A.F. (winrich.freiwald@googlemail.com). 6 These authors contributed equally to this work.Note: Supplementary information is available on the Nature Neuroscience website.Reprints and permissions information is available online at http://www.nature.com/reprintsandpermissions/. The space of faces still contains an infinite variety of particular forms (as it must for face perception to be useful). An effective strategy to further reduce the stimulus space is to represent faces as cartoons5. This approach has several justifications. First, the nameable features making up a cartoon (eyes, nose, etc...

Faces are among the most informative stimuli we ever perceive: Even a split-second glimpse of a person's face tells us his identity, sex, mood, age, race, and direction of attention. The specialness of face processing is acknowledged in the artificial vision community, where contests for face-recognition algorithms abound. Neurological evidence strongly implicates a dedicated machinery for face processing in the human brain to explain the double dissociability of face- and object-recognition deficits. Furthermore, recent evidence shows that macaques too have specialized neural machinery for processing faces. Here we propose a unifying hypothesis, deduced from computational, neurological, fMRI, and single-unit experiments: that what makes face processing special is that it is gated by an obligatory detection process. We clarify this idea in concrete algorithmic terms and show how it can explain a variety of phenomena associated with face processing.

The blood-brain barrier (BBB) prevents entry of most drugs into the brain and is a major hurdle to the use of drugs for brain tumors and other central nervous system disorders. Work in small animals has shown that ultrasound combined with an intravenously circulating microbubble agent can temporarily permeabilize the BBB. Here, we evaluated whether this targeted drug delivery method can be applied safely, reliably, and in a controlled manner on rhesus macaques using a focused ultrasound system. We identified a clear safety window during which BBB disruption could be produced without evident tissue damage, and the acoustic pressure amplitude where the probability for BBB disruption was 50% was found to be half of the value that would produce tissue damage. Acoustic emission measurements appeared promising for predicting BBB disruption and damage. In addition, we performed repeated BBB disruption to central visual field targets over several weeks in animals trained to perform complex visual acuity tasks. All animals recovered from each session without behavioral deficits, visual deficits, or loss in visual acuity. Together, our findings demonstrate that BBB disruption can be reliably and repeatedly produced without evident histological or functional damage in a clinically-relevant animal model using a clinical device. These results therefore support clinical testing of this noninvasive targeted drug delivery method.