I REVIEWS Parallel processing strategies of the primate visual system Jonathan J. Nassi* and Edward M. Callaway* Abstract | Incoming sensory information is sent to the brain along modality-specific channels corresponding to the five senses. Each of these channels further parses the incoming signals into parallel streams to provide a compact, efficient input to the brain. Ultimately, these parallel input signals must be elaborated on and integrated in the cortex to provide a unified and coherent percept. Recent studies in the primate visual cortex have greatly contributed to our understanding of how this goal is accomplished. Multiple strategies including retinal tiling, hierarchical and parallel processing and modularity, defined spatially and by cell type-specific connectivity, are used by the visual system to recover the intricate detail of our visual surroundings. Percept The perception that arises internally, in the mind, based on an external stimulus, such as a visual stimulus. Parallel processing Simultaneous processing of information through independent circuits. Photoreceptor A specialized cell in the retina that detects light and responds with a change in membrane potential and a change in neurotransmitter release. Tiling Relatively uniform and complete coverage of space. *Harvard Medical School, Department of Neurobiology, 220 Longwood Avenue, Boston, Massachusetts 02115, USA. * The Salk Institute for Biological Studies, Systems Neurobiology, 10010 North Torrey Pines Road, La Jolla, California 92037, USA. Correspondence to E.M.C. e-mail: callawau@salk.edu doi:10.1038/nrn2619 Published online 8 April 2009 Our richest life experiences and longest-lasting memories are formed through our interactions with the sensory world around us and have a profound impact on our personality and sense of self. Each of these sensations is transmitted to our brains through distinct biological machinery such as that found in the nose or under the skin. Yet, rather than perceiving the world as a disj ointed collection of attributes, we most often experience a single unified percept. Parallel processing of sensory information is a commonly used strategy in the mammalian brain, not only between sensory modalities but across features of a single sense as well. Gasser and Erlanger1 first demonstrated that the sensations of pain and temperature are transmitted through axons of different calibre from those that transmit touch. This work was shortly followed up by Bishop2, who proposed that the three different classes of axons he found in the optic nerve process different sensory qualities related to vision. These early discoveries laid the foundation for our current understanding of the nervous system's parallel processing strategies3-8. The need for parallel processing in the visual system is immediately appreciated when one considers the multitude of qualities that are present in the visual environment and the physical limitations of the way this information is initially encoded and signalled to the brain. Colour, depth, shape and motion are just a few of the many dimensions through which we interpret our visual environment and generate appropriate behaviour9. Remarkably, this complexity in our visual surroundings is first encoded as a pattern of light on a two-dimensional array of photoreceptors, with little direct resemblance to the original input or the ultimate percept. Within just a few hundred micrometres of retinal thickness, this initial signal encoded by our photoreceptors must be transformed into an adequate representation of the entire visual scene. This representation, however, must also be sufficiently condensed so that the axons carrying it can pass through the optic nerve, which forms an anatomical bottleneck along the route from the eye to the brain. Probably owing to these constraints, incoming visual signals are processed by at least 80 anatomically and physiologically distinct neural cell populations and 20 separate circuits in the retina. These circuits comprise at least a dozen parallel pathways that project to the brain for further processing10. The visual cortex has the job of extracting the relevant information from this reduced signal and of further elaborating and integrating the information into a unified and coherent perceptual experience. Many years of research have uncovered important details concerning the anatomy and functional organization of the primate visual system. This Review focuses on recent advances in our understanding of how the primary visual cortex (V1) integrates parallel inputs and constructs new, parallel outputs. These findings have been particularly helpful in elucidating the complex relationship between early parallel pathways of the retina and the processing streams in the visual cortex. Instead of attempting to provide a comprehensive analysis at each level of the visual system, we highlight key principles, such as retinal tiling, hierarchical processing, parallel processing and modularity (defined spatially and by cell type-specific connectivity), with the aim of providing a unified and coherent understanding of the processing 360 | MAY 2009 | VOLUME 10 www.natu re.com/reviews/neuro © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS strategies in the visual system. We hope that this will inform the understanding not only of visual perception, but of sensory processing in general. Parallel pathways from the retina to the cortex The first steps in seeing begin in the retina, where a dense array of photoreceptors convert the incoming pattern of light into an electrochemical signal11. The photoreceptor mosaic encodes the intensity of light as a function of position (two dimensions), wavelength and time (BOX 1). Much information is lost from the outset, such as the exact spectral composition of the image. Nevertheless, computations carried out in our visual system are supplied with enough information to support highly precise hue discriminations and other perceptual abilities that inform our everyday behaviour. Remarkably, many of these computations are carried out in the retina, before the visual signals even leave the eye. Specialized circuits extract basic sensory cues, such as spatial contrast and temporal frequency, from the initial intensity distribution and encode these properties across approximately 1.5 million ganglion cells, which form the optic nerve that connects the eye to the brain. Owing to the anatomical bottleneck of the optic nerve, retinal output must be efficiently condensed. The strategy used by the mammalian visual system is to reduce the representation of the visual scene to a limited number of specialized, parallel output channels. Rather than send visual signals from the eye to the brain along a homogeneous population of ganglion cells, in the primate at least 17 distinct ganglion cell types exist in the retina and at least 13 of these project in parallel to the lateral geniculate nucleus (LGN) of the thalamus and on to the visual cortex10 (FIG. 1). Each ganglion cell type is thought to tile the retina, providing a complete Box 1 | From retinal input to cortical processing and perception Hierarchical processing Processing that takes place in serial order, with more sophisticated properties emerging at higher levels through the build-up of simpler properties at lower levels. Modularity When repeating modules are used to conduct similar operations. Typically, in the visual cortex each module will perform an operation related to visual information from a portion of the visual space. Together the modules cover the space so that the operation is conducted over the entire visual scene. Eccentricity Distance from the centre. It is typically used to describe the distance of a visual receptive field from the centre of gaze and is expressed as an angle, in degrees. Colour-opponent signal The signal that results when a visual receptive field is excited in response to one colour and inhibited in response to another. Visual input is initially encoded in the retina as a two-dimensional (2D) distribution of light intensity, expressed as a function of position, wavelength and time in each of the two eyes. This retinal image is transferred to the visual cortex, where sensory cues and, later, inferred attributes are eventually computed (see the figure). Parallel processing strategies are used from the outset to overcome the constraints of individual ganglion cells' limited bandwidth and the anatomical bottleneck of the optic nerve. Figure is modified, with permission, from REF. 9 © (1988) Elsevier. Retinal images Sensory cues Inferred attributes Intensity position (X,Y) wavelength time eye (right/left) Primary Luminance Spectral Feature-based Contrast 2D velocity Disparity 2D orientation 1. 3D form Shape Size Rigidity 2. Surface properties Colour (brightness, hue and saturation) Visual texture Specular reflectance Transparency (shadows and highlights) 3. 3D spatial relationships Relative positions (X, Y and distance Z) 3D Orientation in space 4. 3D movement Trajectory Rotation representation across the entire visual field of the primary sensory cues it conveys to the brain12. These cues include different spatial and temporal frequencies, luminance and colour contrasts in the image. At any given point in the visual field, multiple ganglion cell types convey different aspects of the visual input simultaneously and in parallel to the brain. Each ganglion cell type has its own distinct set of morphological features, such as soma size and dendritic field size and density13. Many of these features vary substantially as a function of retinal eccentricity, but at any given eccentricity they allow for nearly unambiguous cell type classification. Each ganglion cell type also has a distinct pattern of dendritic stratification in the inner plexiform layer (IPL), allowing for highly specific patterns of synaptic connectivity with functionally and/or anatomically defined bipolar and amacrine cell types8 (FIG. la,b). These bipolar and amacrine cell types, in turn, have their own unique connections with photoreceptors and horizontal cells in the outer plexiform layer (OPL), forming distinct anatomical circuits from photorecep-tors to ganglion cells (FIG. 1b). Finally, the somas of each ganglion cell type seem to be regularly spaced across the retina so that, collectively, their dendritic fields cover the retina uniformly and with constant overlap (FIG. 1c). This highly ordered mosaic architecture holds up only among ganglion cells of the same type: subsets of a type do not cover the entire visual field and different types display no systematic spatial relationship12. Together, these structural features suggest that each ganglion cell type is a fundamental unit of the retina and underlies a unique channel of visual information. Three retinal ganglion cell types are particularly well characterized and have been linked to parallel pathways that remain anatomically segregated through the LGN and into the input layers and compartments of V1 (REFS 5,14) (FIG. 2). Midget, parasol and bistratified ganglion cells constitute approximately 90% of all ganglion cells found in the primate retina, and they functionally complement each other to extend the range of vision in the wavelength and spatiotemporal frequency domains15. Midget ganglion cells are considered to be the origin of the parvocellular pathway and constitute approximately 70% of the total population of cells that project to the LGN14. These cells convey a red-green colour-opponent signal to the parvocellular layers of the LGN, which in turn project to layers 4Cp and 6 of V1 (REFS 14,16-19). Cells in this pathway typically have small receptive fields, low contrast sensitivity, slow axonal conduction velocities and sensitivity to high spatial and low temporal frequencies. Parasol ganglion cells are considered to be the origin of the magnocellular pathway and constitute approximately 10% ofthe total population of cells that project to the LGN14. These cells convey a broadband, achromatic signal to the magnocellular layers of the LGN and on to layers 4Ca and 6 of V1 (REFS 16-19). Cells in this pathway generally have large receptive fields, high contrast sensitivity, fast axonal conduction velocities and sensitivity to high temporal and low spatial frequencies. Finally, small and large bistratified ganglion cells make up at least part of the koniocellular pathway and together constitute NATURE REVIEWS | NEUROSCIENCE VOLUME 10 | MAY 2009 | 361 f © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS Monostratified Bistratified Parasol pathway Small bistratified pathway Cones Horizontal cells Bipolar cells P f!f|] DB5 OFF Ganglion cells OFF parasol ON parasol 1 H1 I Diffusell ý OFF ON Small bistratified H2 Blue cone ON Figure 1 | Parallel processing in the retina. a | More than a dozen different ganglion cell types, each with their own distinct set of morphological features, exist in the retina. The top panel illustrates the monostratified or bistratified dendritic arborization of the distinct retinal ganglion cell types. The vertical position of each arbor indicates its characteristic stratification in the inner plexiform layer. The lower panel shows micrographs of the different cell types obtained using retrograde photostaining from rhodamine dextran injections into the lateral geniculate nucleus and the superior colliculus; the scale bars represent 50 um. b | Each ganglion cell type, such as parasol (left) or small bistratified (right), has a unique set of inputs from photoreceptor cells (short (S), middle (M) and long (L)), horizontal cells (H1 and H2), diffuse bipolar cells (DB2, DB3, DB4 and DB5) and amacrine cells (not shown). These retinal subcircuits determine the physiological response properties of the ganglion cells14. c | The receptive field mosaic of a population of ON parasol ganglion cells (yellow; from REF. 12) is overlayed on an example visual scene (not drawn to scale). Each ganglion cell type tiles the retina so that, at any given point in the visual field, multiple ganglion cell types (represented by red, blue and yellow ellipses) signal complementary visual information simultaneously and in parallel to the brain. Part a is reproduced, with permission, from REF. 12 © (2007) Annual Reviews, inc. Data for part b are from REF. 14. approximately 8% of the total population of cells that project to the LGN14. These cells convey a blue-on, yellow-off colour-opponent signal20,21 to koniocellu-lar layers 3 and 4 of the LGN, which in turn project to layer 1 and to the cytochrome oxidase blobs (CO blobs) of layer 2/3 in V1 (REFS 5,17,20,22,23). Koniocellular cells in the LGN are defined as cells that express a-calcium/ calmodulin-dependent protein kinase and/or calbindin22 and are found not only in the intercalated koniocellular layers but also scattered throughout the magnocellu-lar and parvocellular layers. This has made it difficult to characterize the full range of physiological response properties that are carried by the koniocellular pathway. For example, layer 4A of V1 receives a blue-off, yellow-on colour-opponent input from the LGN17, but neither the locations of these LGN cells nor the type of retinal ganglion cell providing their input has been determined with certainty. It is likely that there are many more parallel pathways between the retina and V1. The remaining retinal ganglion cells in this pathway are less numerous (12% of the total), but they consist of more types that are likely to provide diverse information about the visual scene. In fact, assuming that each ganglion cell type uniformly tiles the retina, most of the variation in the numbers of ganglion cells for each cell type might be explained simply by dendritic field size: the larger the cell type's dendritic field size, the fewer of those cells will be required to cover the entire retina12. Whether these additional cell types maintain strict segregation in their connections through the LGN and into V1 remains unclear. Nevertheless, many studies have indicated functional and anatomical heterogeneity in the LGN that might be explained by additional, unidentified parallel pathways. Two prevalent types of visual response properties have been reported in the magnocellular layers of the LGN and three have been reported in the parvocellular lay-ers24,25. Furthermore, there is some indication that the two dorsal, central and ventral koniocellular layers of the LGN each have their own characteristic response properties and projection targets in V1 (REF. 5.) Finally, the rod- and cone-mediated responses of intrinsically photosensitive, melanopsin-expressing retinal ganglion cells have recently been characterized and suggest that this cell population may constitute a separate projection pathway to the visual cortex that conveys luminance and colour-opponent information26. The sensory cues that are carried by the parallel pathways bear little resemblance to our perceptual experience, and the functional role of each pathway is still poorly understood. Visual attributes such as motion, shape and colour must be computed from these sensory cues and integrated in the cortex to create a unified and coherent percept. Lesion studies have shown that computing these attributes does not rely on one pathway alone. Magnocellular lesions, for example, result in a large decrease in luminance contrast sensitivity for stimuli of high temporal and low spatial frequencies27, and have little effect on colour contrast sensitivity27,28 or the speed and direction of motion discriminations. By contrast, parvocellular (and possibly koniocellular) lesions 362 | MAY 2009 | VOLUME 10 www.natu re.com/reviews/neuro a b c © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS Receptive field The location in visual space where a change in light can cause a change in neuronal activity. Broadband Typically used to describe visual receptive fields that are not colour-opponent. Whether a broadband cell is excited or inhibited by a stimulus at a particular part of its receptive field is relatively independent of the wavelength of the light. Cytochrome oxidase blobs Patches in the upper layers of the primate primary visual cortex with high concentrations of the metabolic enzyme cytochrome oxidase. cause an almost complete loss of colour vision28-30, reduce luminance contrast sensitivity for stimuli of high spatial and low temporal frequencies27,28,31, and have little effect on shape discriminations30,32. These findings are consistent with the visual response properties of the cells in each pathway and highlight the fact that no single pathway seems to have a monopoly over any particular set of computations, such as those related to motion or shape perception. Ultimately, the key to uncovering the role of the early parallel pathways may be a better understanding of the relationship between these pathways and processing streams in the visual cortex. V1 and parallel processing strategies Once the condensed and parallel signals from the retina and LGN arrive in the visual cortex, the original components of the visual scene must be extracted, elaborated on and integrated into a unified percept. The visual cortex uses both hierarchical and modular processing to accomplish these goals33. Although the basic tuning properties of cells do not differ substantially between the retina and the LGN, in the first cortical synapses of V1 new and more complex information is extracted, such as orientation, direction and colour selectivity6. These sensory cues (BOX 1) are organized into overlapping functional maps, with a columnar organization for orientation tuning, ocular dominance and visual Figure 2 | Parallel pathways from the retina to the cortex. Midget, parasol and bistratified ganglion cells are well characterized and have been link ed to pa rallel pathways that remain anatomically separate through the lateral geniculate nucleus (LGN) and into the primary visual cortex (V1). Midget ganglion cells project to parvocellular layers of the LGN and on to layer 4C(3 of V1 (red). Parasol ganglion cells project to magnocellular layers of the LGN and on to layer 4Ca of V1 (yellow). Small and large bistratified ganglion cells project to koniocellular layers of the LGN and on to the cytochrome oxidase-expressing patches (or blobs) of layer 2/3 (blue). Although these ganglion cell types are numerically dominant in the retina, many more types are known to exist and are likely to subserve important parallel pathways that are yet to be identified. space34,35. As visual information passes through V1 and on to the extrastriate cortex, the response properties in each subsequent area tend to increase in complexity and selectivity. New computations are carried out along the way, eventually resulting in highly specialized areas concerned with object recognition and sensorimotor integration36. Information flow in this hierarchical network is not unidirectional, and dense feedback connections provide a substrate for recurrent processing37. However, the functional details of this feedback system remain largely unknown and are beyond the scope of this Review. Most visual information from the LGN passes through V1 before being processed further in the extra-striate visual cortex. Different strategies might be used in V1 to transfer parallel input signals into multiple output streams (FIG. 3a). One possibility is that the parallel inputs stay separate in the cortex and continue on past V1. A second possibility is that the parallel inputs converge indiscriminately in V1 and lack any organization or relationship with processing streams in the extrastri-ate cortex. A third possibility, which current evidence favours, is that the parallel inputs converge in V1 but do so in an organized and specific way so that new parallel streams of information are systematically conveyed to the rest of the visual cortex. Originally, it was thought that the early parallel pathways might maintain strict segregation in V1 and underlie separate processing streams in the extrastriate cortex6,38 (FIG. 3b). The distinctive laminar organization of V1 and the alternating light and dark staining for the mitochondrial enzyme CO in the superficial layers39, which reflects the level of metabolic activity in those regions (with the darker-stained areas correlating to areas of direct thalamic input), suggested a high degree of processing modularity and the possibility that parallel inputs to V1 remain well segregated. Furthermore, the functional parcellation of the extrastriate cortex into separate processing streams (discussed further below), which suggested magnocellular- and parvocellular-like segregation of function well beyond V1, led Livingstone and Hubel6 to propose that the parvocellular pathway forms the basis for colour and form processing in the CO blobs (dark staining) and interblobs (light staining) in layer 2/3, and that the magnocellular pathway forms the basis for motion- and depth-related processing in layer 4B. This scheme was attractive in its simplicity and was supported by early studies that suggested there is a clean anatomical segregation of magnocellular and parvocellular inputs to layers 4B and 2/3, respectively40, as well as a functional segregation of fast, achromatic responses in layer 4B and colour-opponent or orientation-selective responses in blobs and interblobs, respectively41-43. More recent studies, however, have called into question such a strict segregation44. Although the concept of modular function in V1 has stood the test of time, it is now clear that, rather than maintain strict segregation, the early parallel pathways converge significantly in the first few synapses in V1 (FIG. 3c). This is most evident in the connections from layer 4C to the CO blobs and interblobs of layer 2/3, NATURE REVIEWS | NEUROSCIENCE VOLUME 10 | MAY 2009 | 363 © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS ab Parallel Cortical Output inputs strategies streams Extrastriate cortex t t t Extrastriate cortex t t t 0 V1 2/3 4A 4B 4Ca 4Cß 5 V1 2/3 4A 4B 4Ca 4Cß 5 Figure 3 | Cortical processing strategies, a | A visual cortical area might use multiple strategies to transform parallel inputs into multiple outputs. One possibility (top) is that the segregation of the inputs is maintained and passed directly on to the outputs. A second possibility (middle) is that these inputs mix indiscriminately and bear no systematic relationship to the outputs. A third possibility (bottom) is that the parallel inputs converge in an organized and specific way so as to form the basis for specialized outputs. b | Early models of the primary visual cortex (V1) proposed that magnocellular (yellow) and parvocellular (red) pathway inputs remained segregated in V1 as they passed through layers 4B and 2/3, respectively, and on to the extrastriate cortex. c | Recent studies have provided evidence for extensive mixing and convergence of magnocellular, parvocellular and koniocellular (blue) pathway inputs, suggesting that V1 outputs bear little or no systematic relationship to its parallel inputs. Cytochrome oxidase-expressing blobs are shown as ellipses in layer 2/3. which provide ample opportunity for mixing of early parallel pathways. The blobs and interblobs of layer 2/3 receive convergent input from magnocellular and parvocellular pathways, with the blobs receiving additional direct input from the koniocellular layers of the LGN22,45-48. Importantly, the koniocellular pathway was discovered after Livingstone and Hubel's theory was first proposed, leaving its contributions to colour, form, motion and depth processing largely unaccounted for. Functionally, the intermixing of magnocellular, parvocellular and koniocellular pathways in V1 has been confirmed by showing that lesions of either magnocellu-lar or parvocellular layers of the LGN can strongly affect the response properties of cells in both CO blobs and interblobs of V1 (REFS 49,50). It is therefore unsurprising that recent studies have often failed to find a clear relationship between the CO-stained compartments and form or colour processing51-53, with several indicating that orientation and colour tuning are commonly found in the same V1 cells and across almost all layers52,54,55. It is tempting to conclude from these data that early parallel pathways converge indiscriminately in V1 and lack any systematic influence on the computations that form outputs to the rest of the brain. Nevertheless, a closer inspection of V1 modularity at the level of specific cell types and their connections tells a different story. Recent evidence suggests that functional modules in the visual cortex are defined not only by their laminar and spatial compartmentalization, but also by their specialized connectivity (FIG. 4). For example, in layer 4B of V1 (FIG. 4a), cells from the magnocellular-recipient layer 4Ca form dense axonal branches, whereas cells from the parvocellular-recipient layer 4Cp pass through layer 4B without branching. Likewise, pyramidal cells in the koniocellular-recipient layer 2/3 blobs have only sparse axonal branches in layer 4B45,56, suggesting that layer 4B is a segregated conduit of information from the mag-nocellular pathway, with little or no intermixing from the parvocellular or koniocellular pathways. However, layer 4B contains two types of morphologically distinct projection neurons: spiny stellates and pyramids. Whereas the dendrites of spiny stellates are almost entirely confined to layers 4B and 4Ca, pyramids have an apical dendrite that extends through layer 2/3 and into layer 1. This places the apical dendrites of pyramids in a position to receive input from both parvocellular and koniocellular pathways in the superficial layers. Photostimulation studies in monkey V1 slices have confirmed that although spiny stellates receive input from only the magnocellular-recipient layer 4Ca, pyramids receive substantial, although less dominant, input from the parvocellular-recipient layer 4Cp as well57 (FIG. 4a). Analysis at the laminar level proved to be misleading, as the most common cell type in layer 4B (pyramids) receives mixed magnocellular and parvocellular inputs and possibly koniocellular inputs as well. Modularity based on cell types and connectivity has been supported by subsequent studies. Photostimulation data have shown that local neurons in layer 3 receive convergent input from both magnocellular-recipient layer 4Ca and parvocellular-recipient layer 4Cp, but projection neurons in that layer receive direct input only from layer 4Ca (FIG. 4b). These layer 3 projection neurons have densely tufted apical dendrites that distinguish them morphologically from neighbouring local neurons58. Many different cell types exist in layer 6 of V1 and each receives a unique combination of inputs from the other layers of V1 (REF. 59). It seems that cell type-specific connectivity allows for systematic combinations of early parallel pathway inputs despite the misleading appearance of indiscriminate intermixing at the laminar or compartmental level (FIGS 3,4). It remains unclear how these different connection patterns might underlie different visual response properties. Eventually, highly specialized functional properties found in V1, including the modularity of function proposed by Livingstone and Hubel, might be mapped onto the different cell types discussed above. The same spatial and cell type-specific modules that allow for specialized intermixing of early parallel pathway input also form the substrates for multiple output streams to the extrastriate cortex (FIG. 4c,d). Outputs from V1 to the second visual area (V2) have been particularly well studied. In V2, there is a repeating pattern of CO-stained compartments known as thick, pale and thin stripes, each with their own characteristic functional properties and afferent and efferent connection patterns60-63. It was originally thought that layer 4B of V1 projected to the thick stripes of V2, and that the CO blobs and interblobs projected to the thin and pale stripes, respectively64,65 (FIG. 4c). However, recent studies using intrinsic optical imaging and/or improved anatomical tracers have shown that such a clean correspondence between compartments in V1 364 | MAY 2009 | VOLUME 10 www.natu re.com/reviews/neuro c 6 6 © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS and V2 is unlikely. One of these studies has suggested that all projection layers underneath interblobs, including layer 4B, project to both thick and pale stripes in V2 (REF. 66), whereas another study has proposed that layer 2/3 blobs and interblobs provide substantial input to thin stripes67. Despite this apparent breakdown in the spatial segregation of outputs from V1 to V2, it is likely that, at a submodular level, segregated outputs do indeed exist. There are increasingly convincing indications that each of the V2 stripe compartments can be further broken down into functionally specialized submodules, such as hue-selective maps in the thin stripes or 2/3 3B 4A 4B 4Ca 4Cß 5 cd V2 2/3 3B 4A 4B 4Ca 4Cß 5 6 - j j ( x Projecting pyramid Local pyramid Thick Tale fflln 80% V1 2/3 4A 4B 4Ca 4Cß 5 Figure 4 | Spatial and cell type-specific connectivity in V1. a | Layer 4B of the primary visual cortex (V1) contains two excitatory cell types known as pyramidal (black, left) and stellate (black, right) cells. Both of these cell types receive direct input from cells in magnocellular-dominated layer 4Ca (yellow), but only pyramids have apical dendrites that pass above layer 4B and into layer 2/3. The apical dendrites of these pyramids are in a position to receive inputs from parvocellular-dominated layer 4C(3 (red) projections into layer 2/3. Mixed magnocellular and parvocellular inputs onto pyramids and magnocellular-only inputs onto stellates have been confirmed in photostimulation studies on macaque monkey V1 slices57. b | Layer 3B contains pyramidal cells that project out of V1 (projecting pyramids) and ones that remain in V1 (local pyramids). Projecting pyramids (left) receive input only from magnocellular-dominated layer 4Ca, whereas local pyramids receive mixed input from both magnocellular-dominated layer 4Ca and parvocellular-dominated layer 4C(3. The red X denotes lack of input from layer 4C(3. c | Outputs from V1 to V2 were originally thought to maintain strict segregation, with layer 4B of V1 projecting to the cytochrome oxidase (CO)-stained thick stripes of V2, and the CO blobs and interblobs of layer 2/3 respectively projecting to the thin and pale stripes of V2 (arrows). This spatial modularity of outputs has recently been called into question with evidence that layer 2/3 blobs and interblobs in V1 provide substantial input to the thin stripes in V2, and with evidence that all projection layers underneath interblobs, including layer 4B, project to thick and/or pale stripes (dashed arrows with question marks). d | Specialized and distinct populations of cells (black) project from layer 4B of V1 to the middle temporal area (MT; also known as visual area V5) or V2. MT receives input from a population of cells with large cell bodies and dense dendritic trees. Most of these cells (80%) are stellates, but a smaller number of pyramids (20% of the cells) also project to MT and are positioned preferentially underneath CO blobs, where their apical dendrites can receive magnocellular inputs from layer 4Ca (yellow circles). V2 receives input from a population of cells with smaller cell bodies and sparse dendritic trees, most of which (80%) are pyramids located preferentially underneath CO interblobs, where their apical dendrites can receive parvocellular inputs from layer 4C(3 (red circles). Together, these anatomical specializations are consistent with layer 4B of V1 relaying a quick, magnocellular-dominated signal to MT and a more mixed magnocellular and parvocellular signal to V2 (REF. 73). NATURE REVIEWS | NEUROSCIENCE VOLUME 10 | MAY 2009 | 365 b a 6 6 © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS Ventral stream Action guidance ♦ Object recognition ♦ Occipital Form cue-invariant motion selectivity Coarse, absolute disparity selectivity Size- and position-variant shape selectivity Form cue-invariant shape selectivity Fine, relative disparity selectivity Identification-related motion selectivity Visual cues Velocity Disparity Orientation J Figure 5 | Parallel processing streams of the extrastriate cortex. Dorsal (left of vertical dotted line) and ventral (right of vertical dotted line) streams const itute separate but interconnected pathways that are processed through the occipital, the parietal and the temporal extrastriate visual cortex. Vertical position indicates the hierarchical relationship between the areas. Interconnections between streams can be found at essentially every level of the hierarchy. For simplicity, not all areas have been included and only those cross-stream connections mentioned in the text have been drawn. Dorsal and ventral processing streams subserve different behavioural goals, with the dorsal stream aimed at the visual control of skilled actions and the ventral stream aimed at object recognition. The same visual cues, such as velocity, disparity and orientation, are processed along both streams, but in each stream distinct computations are performed on these features in order to support different behavioural goals. 7A, visual area 7A; AITd, anterior inferotemporal (dorsal); AITv, anterior inferotemporal (ventral); CITd, central inferotemporal (dorsal); CITv, central inferotemporal (ventral); DP, dorsal prelunate; FST, fundus of superior temporal; LIP, lateral intraparietal; MDP, medial dorsal parietal; MIP, medial intraparietal; MSTd, medial superior temporal (dorsal); MSTl, medial superior temporal (lateral); MT, middle temporal; PIP, posterior intraparietal; PITd, posterior inferotemporal (dorsal); PITv, posterior inferotemporal (ventral); PO, parieto-occipital; STPa, superior temporal polysensory (anterior); STPp, superior temporal polysensory (posterior); V1, visual area 1; V2, visual area 2; V3, visual area 3; V3A, visual area 3A; V4, visual area 4; V4t, visual area 4 transitional; V6, visual area 6; VIP, ventral intraparietal; VOT, ventral occipitotemporal; VP, ventral posterior. disparity-selective clustering in the thick stripes68,69. Although the cell type-specific connection patterns in V2 remain unknown, it is likely that these smaller functional compartments, or even the specific cell types in them, receive segregated input patterns from V1. Inspection of V1 at the level of specific cell types and their connection patterns may also help us to understand the degree of segregation in the outputs from V1 to V2 and the rest of the visual cortex. Output modularity based on cell type-specific connectivity has been demonstrated in the connections between layer 4B of V1 and the extrastriate cortex (FIG. 4d). Cells that project to V2, to the third visual area (V3) or to the middle temporal visual area (MT; also known as visual area V5) are intermixed in layer 4B70-72. It was unclear whether these different output streams were anatomically and/or functionally distinct at a sub-laminar level. Early studies suggested that most of the layer 4B cells that project to MT are large spiny stellates and, as such, anatomically distinct from other output cells in this layer of V1 (REFS 71,72). A recent study using a modified rabies virus that expresses green fluorescent protein confirmed these earlier findings and uncovered other important anatomical differences73. Layer 4B cells that project to MT are large cells with dense dendritic trees that lie close to the bottom of the layer. Most of these cells are spiny stellates, but a substantial minority are pyramidal cells located preferentially underneath CO blobs. By contrast, layer 4B cells that project to V2 are smaller, with sparse dendritic trees situated throughout the layer, and are mostly pyramidal cells located preferentially underneath CO interblobs. These anatomical specializations are consistent with these two cell populations conveying quick74,75, magnocellular-dominated signals to MT and more mixed magnocellular and parvocellular signals to V2. Therefore, it seems that early parallel pathways of the retina and the LGN are recombined in V1 into both spatial and cell type-specific modules to form multiple output channels that project to specific areas of the extrastriate cortex. Processing strategies in the extrastriate cortex The outputs from V1 and V2 to MT and visual area 4 (V4) represent the beginning of a more pronounced anatomical and functional segregation of signals into what are known as the dorsal and ventral streams76 (FIG. 5). MT is specialized for processing motion and depth, whereas V4 is specialized for processing form and possibly colour36,77-79. These two areas reflect earlier segregation in the output modules of V1 and V2, as cells in layer 4B of V1 and the thick stripes of V2 project to MT, whereas the pale and thin stripes of V2 project to V4 (REFS 60,62,70,71,80). Functional evidence provides additional support for such segregation, as layer 4B of V1 and the thick stripes of V2 have a high proportion of direction- and disparity-selective neurons, whereas layer 2/3 of V1 and the pale and thin stripes of V2 consist mainly of neurons that are selective for orientation and colour. It would seem, therefore, that one of the goals of the systematic integration of parallel inputs that occurs in V1 and V2 is to construct new output channels that can support at least two new parallel streams of information flow. Anatomical studies have established that the extra-striate cortex is indeed composed of at least two segregated but interacting parallel processing streams (FIG. 5). The dorsal pathway consists of a large number of interconnected extrastriate cortical areas in the parietal cortex downstream of MT, including the medial superior temporal area (MST), the fundus of the superior temporal area (FST), the superior temporal polysensory area (STP), the ventral intraparietal area (VIP), the lateral intraparietal area (LIP) and visual area 7A, to name just a few81-85. The apparent absence of substantial crosstalk between a dorsal-dorsal pathway through visual area 6 (V6) and the superior parietal lobule (SPL) and a ventral-dorsal pathway through MT and the inferior parietal lobule (IPL) indicates that the dorsal stream may actually consist of two relatively segregated subcircuits86. The ventral pathway also consists of a large number of 366 | MAY 2009 | VOLUME 10 www.natu re.com/reviews/neuro © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS Random-dot stereogram A pair of random-dot images that generate the sensation of depth when the eyes are positioned so that they focus at a location in front of or behind the images. interconnected extrastriate cortical areas in the temporal cortex downstream of V4, including the various subdivisions of the inferotemporal (IT) cortex87-89. It has been suggested that these parallel dorsal and ventral pathways maintain segregation all the way into motor-related frontal cortical areas, such as the frontal eye field (FEF)90. Likewise, in the dorsal stream segregated inputs from the SPL to the dorsal premotor area (PMd) and from the IPL to the ventral premotor area (PMv) have been shown to exist91. Although the dorsal and ventral streams clearly make up two relatively separate circuits, the anatomical segregation between the two streams is by no means absolute. There is clear evidence of crosstalk between the streams, such as the reported connections between V4 and areas MT and LIP81,82,85, as well as between the anterior inferotemporal (AIT) cortex and areas FST, VIP and STP83,84,92. New subdivisions of the parietal and the temporal cortex continue to be established93-95, and the specific connection patterns of these areas have, for the most part, reinforced the notion of segregated but interacting dorsal and ventral processing streams96,97. Functional evidence indicates that the dorsal and ventral processing streams operate relatively independently as well. Neuronal processing along the dorsal stream is best characterized by direction of motion and binocular disparity selectivity in MT98,99, by more complex motion analysis related to locomotion and pursuit or tracking in areas downstream from MT in the STS (MST, FST and STP)100,101, and by computations that inform target selection for arm and eye movements, object manipulation and visuospatial attention in areas of the IPL (LIP, VIP and V6). By contrast, neuronal processing along the ventral stream is best characterized by colour and contour selectivity in V4 (REFS 77,78,102), by more complex combinations of colours, patterns and/or shapes in the posterior inferotemporal (PIT) cortex103,104, and by invariant representations of two-dimensional and three-dimensional shapes and objects in AIT. Lesion studies have further corroborated the observed physiological differences along the two processing streams, with dorsal stream lesions affecting smooth pursuit eye movements, speed discriminations, complex-motion perception and the accurate encoding of visual space105-109, and with ventral stream lesions affecting orientation and complex-shape discriminations, perceptual invariance and attention110-112. Although the existence of relatively separate and independent dorsal and ventral streams is now firmly established, our understanding of these two processing streams has undergone important revision in recent years. Ungerleider and Mishkin7 first proposed that the dorsal and ventral streams mediate spatial and object-related visual capacities, suggesting that each stream might process different visual attributes. In more recent years, however, a slightly different perspective has emphasized distinctions in the processing goals of each stream. In this view, the dorsal stream's goal is to mediate navigation and the visual control of skilled actions directed at objects, whereas the ventral stream's goal is to transform visual inputs into representations that embody the enduring characteristics of objects and their spatial relationships113. Building on this conceptualization, Rizzolatti et al.8 proposed that the two anatomically segregated subcircuits of the dorsal stream might mediate different behavioural goals as well, with the dorsal-dorsal pathway concerned with the control of action 'online' (while the action is ongoing) and the ventral-dorsal pathway concerned with space perception and 'action understanding' (the recognition of actions made by others). This framework implies that the visual attributes that are processed along parallel streams in the extrastriate cortex might actually be similar, and that important differences between the streams can be found in the manner by which these attributes are used to inform their respective goals. This would be consistent with the systematic mixing of parallel inputs that occurs in V1, as the resulting outputs formed there, which subserve the dorsal and ventral streams, do not maintain exclusive rights over the visual cues conveyed along any single input channel. Instead, these cues are integrated in varying combinations and to differing degrees along each output channel, the details of which might be particularly relevant to the computations and behavioural goals of the dorsal and ventral streams. Indeed, it has become clear that the dorsal and ventral streams are likely to process the same set of visual attributes, but for different behavioural goals (FIG. 5). Possibly the best example of a visual feature that is processed along both dorsal and ventral streams is binocular disparity. Binocular disparity information is found dor- sally, in MT and MST114,115, as well as ventrally, in V4 and IT116-118. In recent years, however, it has been shown that there are crucial differences in the way that the two streams encode disparity and in the types of behaviour that such encoding schemes might inform. Sensitivity along the dorsal stream to coarse and absolute disparities and to anti-correlated random-dot stereograms (RDSs) suggests that such processing might be used to spatially orient and guide actions119,120. By contrast, sensitivity along the ventral stream to fine and relative disparities, and reduced or absent responses to anti-correlated random-dot stereograms suggest that such processing might be closely linked to three-dimensional shape perception121,122. Disparity is not the only visual attribute that is processed in both dorsal and ventral streams: shape- and motion-related computations can be found throughout the extrastriate cortex as well123-127. Again, recent studies have shown important differences in the way that these attributes are encoded and in the behaviour or perception that they are likely to inform128-130. Finally, recent studies have also shown that many extras-triate areas can become selective to stimulus properties that are not typically encoded by neurons in that area, such as the shape selectivity that is found in MT following associative learning between directions of motion and static shapes131. These findings demonstrate that the visual signals that can activate cortical neurons can be modified under conditions in which a novel visual cue is associated with the core function that is normally inherent to those cells. Such changes suggest that even those visual cues that are not normally associated with a given NATURE REVIEWS | NEUROSCIENCE VOLUME 10 | MAY 2009 | 367 © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS Disynaptic Traversing two synaptic contacts. If a trans-synaptic anatomical tracer were to spread from one neuron across synaptic contacts to a second neuron, the spread would be monosynaptic. If the tracer continued to spread from the second neuron across more synaptic contacts to a third neuron, the spread would be disynaptic. Meynert cell A large projection neuron in the deep layers of the visual cortex. Antidromic stimulation Stimulation that is used to determine whether a neuron recorded in one location projects to another, distant location. Antidromic stimulation at the distant location generates action potentials that propagate back to, and are detected at, the recorded neuron. Fixating Maintaining the eye position at a particular location. V2 V1 2/3 4A 4B 4Ca 4Cß 5 Figure 6 | Multiple input streams to MT. There are multiple input streams from the lateral genicu late nucleus (LGN) to the middle temporal (MT) area. The major ascending input to MT passes through magnocellular layers of the LGN (yellow) and through layers 4Ca and 4B of the primary visual cortex (V1). V2 and V3 provide indirect inputs from layers 4Ca and 4B of V1, with V2 probably providing inputs from parvocellular layers of the LGN (red) and layer 4C(3 after a small number of additional synapses134. Bypassing layer 4C altogether, a sparse monosynaptic projection from koniocellular layers of the LGN (blue) to MT and a disynaptic projection from magnocellular and parvocellular layers of the LGN through layer 6 Meynert cells in V1 to MT have both been identified132,133. MT is likely to use similar strategies to those found in V1 to process these parallel inputs and transform their signals into multiple output streams. The thickness of each arrow represents the approximate strength of the connection. processing stream can become influential when they are behaviourally relevant. As with V1, each extrastriate cortical area receives inputs from multiple areas upstream and sends outputs to multiple areas downstream. MT provides a good example of such an extrastriate cortical area, as it receives inputs from many sources in parallel (FIG. 6). Although the bulk of visual information to MT passes through layer 4C of V1, it has recently been discovered that MT receives at least two separate input streams that bypass this main route altogether. Sparsely scattered koniocellular cells in the LGN provide a direct, mon-osynaptic input to MT132, and a denser population of magnocellular and parvocellular cells provides a disy-naptic input to MT through layer 6 Meynert cells in V1 (REF. 133). The main ascending input through layer 4B of V1, both directly to MT and indirectly through V3, is dominated by layer 4Ca and the magnocellular pathway. Nevertheless, MT eventually receives parvocellular input through layer 4Cp — probably an indirect input through V2 (REF. 134). These data, along with numerous lesion studies27, suggest that MT and the dorsal stream rely heavily, but not exclusively, on visual information provided by the magnocellular pathway. Each of the input pathways to MT allows varying degrees of mag-nocellular-, parvocellular- and koniocellular-pathway convergence, probably providing visual information that is uniquely suited for specific computations and visual tasks. What type of information might each of these parallel input pathways provide to MT? Few studies have been able to directly assess the function of an identified cell population or pathway in the primate visual cortex. Movshon and Newsome135 used antidromic stimulation to identify and functionally characterize neurons in V1 that project directly to MT. In a technically challenging set of experiments, the authors were able to identify and functionally characterize only 9 MT-projecting cells out of the 745 total cells recorded. Nevertheless, they reported a highly specialized and homogeneous population of direction-selective cells that are distinct from the general population in V1. Whether this direct input from V1 provides information to MT that is different from that provided by indirect inputs through V2 or V3 was investigated in awake, fixating monkeys in which the indirect pathway to MT through V2 and/or V3 was reversibly inactivated by cooling the lunate sulcus136. MT disparity selectivity was severely disrupted even though direction and speed selectivity remained largely intact. These results suggest that the direct pathway from V1 to MT provides speed and direction of motion information, whereas the indirect pathway provides disparity information. Although we know much less about other input pathways to MT and pathways that provide input to other extrastriate cortical areas, segregation of function along parallel inputs is likely to be similar in the case of V4 and the rest of the extrastriate cortex. Box 2 | Parallel processing in other sensory systems Parallel processing is not only a ubiquitous property of the visual system, it is found across the brain in all other sensory modalities as well. The multiple touch receptors underneath our skin and the different olfactory receptors in our nose carry out the beginnings of a similar process by which incoming sensory information is parsed into separate channels of information and eventually recombined to form a unified and coherent percept. Some of the properties discussed in this Review may be unique to the visual system, but many are likely to be shared with other sensory systems. For instance, the mosaic tiling that is found along the body wall in the periphery of the somatosensory system is structured similarly to the tiling that occurs in the retina153-155. There is also evidence for mosaic organization in the olfactory epithelium156, but these mosaics do not show the same degree of spatial order as that found in the retina, probably owing to the fact that the olfactory system processes an essentially non-spatial modality. The modularity that exists in the visual cortex seems to be typical of sensory cortical areas in general157-159, and in the few cases for which it has been studied, cell type-specific connectivity seems to be common as well160-163. Finally, there is substantial support for the existence of hierarchically organized, parallel processing streams in each of the other sensory cortices164-168. 368 | MAY 2009 | VOLUME 10 www.natu re.com/reviews/neuro 6 © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS Ultimately, we must understand how each of these inputs is processed and integrated to form outputs to areas downstream. As the problem faced in the extrastri-ate cortex is so similar to that faced in V1 (parallel inputs and multiple outputs), we might expect to find similar strategies, such as modularity that is defined spatially and by cell type-specific connections. Indeed, in many extrastriate cortical areas there are clear examples of spatial modularity that are similar to those seen in V1 and V2. MT contains direction and disparity columns and clustered speed-tuning modules137-139, and V3 contains modules for disparity and orientation140,141. There is also evidence that V4 contains separate modules142-144, possibly related to segregated processing of colour77. Few studies have directly investigated the vertical organization of extrastriate cortical areas, but those that have find evidence for distinct computations performed in different cortical layers145,146. There is also evidence that these functional modules serve as a substrate for the formation of a new set of segregated outputs to be sent downstream147. We have few details on these modules of the extrastriate cortex, but there is strong evidence that they are ubiquitous and that they have submodular organization and specialized connectivity similar to that seen in the compartments of V1 and V2. Summary and future directions Over the past 50 years, we have gained great insight into the ways in which the brain processes incoming visual inputs and recovers the information that is necessary to adequately inform our perception and everyday behaviour. It is clear that parallel processing is a ubiquitous feature of the visual system. Several key principles of parallel processing strategies have been elucidated that will help us in understanding visual perception and sensory processing in general (BOX 2). In the retina, over a dozen distinct ganglion cell types parse the incoming visual signals into functionally and anatomically specialized channels that project in parallel to the LGN and on to V1. Each of these ganglion cell types tiles the retina and provides a complete representation across the entire visual field of the attributes it conveys to the brain. Once in V1, these parallel input channels are recombined in modules that are defined spatially and by local connectivity, and thus new parallel channels of information are formed that can be sent on to the rest of the brain. The outputs that are formed in V1 and V2 lead to segregated but interacting dorsal and ventral processing streams in the extra-striate cortex. The two streams make use of a similar set of visual attributes but perform different computations in order to mediate non-overlapping behavioural goals. Within each stream, however, each extrastriate cortical area probably uses the same strategies that are found in V1 to recombine and integrate multiple inputs and form new outputs to send downstream. Although much has been uncovered regarding parallel processing strategies in the visual system, many questions remain. How many more parallel pathways are there between the retina and V1, and what are their anatomical and functional properties? How many different output pathways are formed in V1 and what is the functional contribution of each pathway to processing in the dorsal and ventral streams of the extrastriate cortex? In order to answer some of these questions, methods that can directly relate detailed cell morphology and connection patterns to visual response properties and perception will be needed. Some recently developed methods are already helping us in this endeavour73,148-152 (BOX 3). Two-photon microscopy, viral tracing and reversible inactivation or activation methods can all be useful in taking the next step in understanding parallel processing strategies in the visual system. Further research is necessary to fully understand how parallel processing strategies are used in, and between, each sensory modality so that we can enjoy our seamless perception of the world around us. Box 3 I Techniques for investigating parallel processing in the visual system Numerous techniques have recently been developed that will enable us to directly relate detailed cell morphology and connection patterns to visual response properties and perception73 133 134 148-152. These new methods promise to advance our understanding of the mechanisms that underlie parallel processing in the primate visual system. Two-photon Ca2+ imaging Using femtosecond-pulsed laser light in combination with genetically encoded or bulk-loaded fluorescent Ca2+ indicators, it is possible to image the visual response properties of neurons deep in the intact brain. This technique offers the possibility of studying modularity of visual cortical areas at single-cell resolution, as well as the possibility of correlating function with specific cell types and circuits148. Viral tracing Genetically modified viruses have become increasingly useful for tracing mono- and multisynaptic connections and for introducing foreign genes into neurons of the primate brain. Rabies virus, in particular, has proved to be a powerful tool for uncovering multisynaptic connections of the primate visual system with the hope of elucidating the complex circuitry in and between different visual areas73 133 134 150. Reversible activation and inactivation Only recently has the possibility of activating and inactivating specific cell types and circuits become a reality. By introducing non-mammalian receptors into specific neuron populations of the primate visual system and activating them, these neurons can be hyperpolarized or depolarized. For example, activation of the allatostatin receptor by application of its ligand opens inwardly rectifying K+ channels and hyperpolarizes the neurons so that they are no longer visually responsive149. Alternatively, the receptors channelrhodopsin and halorhodopsin can be activated by light and depolarize and hyperpolarize the neurons, respectively 151,152. NATURE REVIEWS | NEUROSCIENCE VOLUME 10 | MAY 2009 | 369 © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS 1. Gasser, H. S. & Erlanger, J. The role of fiber size in the establishment of a nerve block by pressure or cocaine. Am. J. Physiol. 88, 581-591 (1929). 2. Bishop, G. H. Fiber groups in the optic nerves. Am. J. Physiol. 106, 460-470 (1933). 3. Callaway, E. M. Structure and function of parallel pathways in the primate early visual system. J. Physiol. 566, 13-19 (2005). 4. Goodale, M. A. & Milner, A. D. Separate visual pathways for perception and action. Trends Neurosci. 15, 20-25 (1992). 5. Hendry, S. H. & Reid, R. C. The koniocellular pathway in primate vision. Annu. Rev. Neurosci. 23, 127-153 (2000). 6. Livingstone, M. & Hubel, D. Segregation of form, color, movement, and depth: anatomy, physiology, and perception. Science 240, 740-749 (1988). 7. Ungerleider, L. G. & Mishkin, M. in The Analysis of Visual Behavior (eds Ingle, D. J., Mansfield, R. J. W. & Goodale, M. S.) 549-586 (MIT Press, Cambridge, 1982). 8. Wassle, H. Parallel processing in the mammalian retina. Nature Rev. Neurosci. 5, 747-757 (2004). 9. DeYoe, E. A. & Van Essen, D. C. Concurrent processing streams in monkey visual cortex. Trends Neurosci. 11, 219-226 (1988). 10. Dacey, D. M. in The Cognitive Neurosciences (ed. Gazzaniga, M. S.) 281-301 (MIT Press, Cambridge, 2004). 11. Rodieck, R. W. The First Steps in Seeing (Sinauer Associates, 1998). 12. Field, G. D. & Chichilnisky, E. J. Information processing in the primate retina: circuitry and coding. Annu. Rev. Neurosci. 30, 1-30 (2007). 13. Watanabe, M. & Rodieck, R. W. Parasol and midget ganglion cells of the primate retina. J. Comp. Neurol. 289, 434-454 (1989). 14. Dacey, D. M. Parallel pathways for spectral coding in primate retina. Annu. Rev. Neurosci. 23, 743-775 (2000). 15. Schiller, P. H. & Logothetis, N. K. The color-opponent and broad-band channels of the primate visual system. Trends Neurosci. 13, 392-398 (1990). 16. Blasdel, G. G. & Lund, J. S. Termination of afferent axons in macaque striate cortex. J. Neurosci. 3, 1389-1413 (1983). 17. Chatterjee, S. & Callaway, E. M. Parallel colour-opponent pathways to primary visual cortex. Nature 426, 668-671 (2003). This paper showed that colour-opponent LGN neurons with red-green, blue-on or blue-off receptive fields project in parallel to the primate V1 and terminate in anatomically separate compartments. 18. Hendrickson, A. E., Wilson, J. R. & Ogren, M. P. The neuroanatomical organization of pathways between the dorsal lateral geniculate nucleus and visual cortex in Old World and New World primates. J. Comp. Neurol. 182, 123-136 (1978). 19. Michael, C. R. Retinal afferent arborization patterns, dendritic field orientations, and the segregation of function in the lateral geniculate nucleus of the monkey. Proc. Natl Acad. Sci. USA 85, 4914-4918 (1988). 20. Dacey, D. M. & Lee, B. B. The 'blue-on' opponent pathway in primate retina originates from a distinct bistratified ganglion cell type. Nature 367, 731-735 (1994). 21. Dacey, D. M., Peterson, B. B., Robinson, F. R. & Gamlin, P. D. Fireworks in the primate retina: in vitro photodynamics reveals diverse LGN-projecting ganglion cell types. Neuron 37, 15-27 (2003). This paper showed that there are at least a dozen anatomically distinct cell types that project in parallel from the retina to the primate LGN. 22. Hendry, S. H. & Yoshioka, T. A neurochemically distinct third channel in the macaque dorsal lateral geniculate nucleus. Science 264, 575-577 (1994). This paper demonstrated that staining for calbindin or a-calcium/calmodulin-dependent protein kinase reveals a population of neurons in the primate LGN that are distinct from the magnocellular and parvocellular neurons. These are termed koniocellular neurons. 23. Livingstone, M. S. & Hubel, D. H. Thalamic inputs to cytochrome oxidase-rich regions in monkey visual cortex. Proc. Natl Acad. Sci. USA 79, 6098-6101 (1982). 24. Kaplan, E. & Shapley, R. M. X and Y cells in the lateral geniculate nucleus of macaque monkeys. J. Physiol. 330, 125-143 (1982). 25. Xu, X. et al. A comparison of koniocellular, magnocellular and parvocellular receptive field properties in the lateral geniculate nucleus of the owl monkey (Aotus trivirgatus). J. Physiol. 531 , 203-218 (2001). 26. Dacey, D. M. et al. Melanopsin-expressing ganglion cells in primate retina signal colour and irradiance and project to the LGN. Nature 433, 749-754 (2005). 27. Merigan, W. H., Byrne, C. E. & Maunsell, J. H. Does primate motion perception depend on the magnocellular pathway? J. Neurosci. 11, 3422-3429 (1991). This paper demonstrated that motion perception can persist following inactivation of the magnocellular LGN. However, there was some impairment in motion perception at high temporal frequencies and low spatial frequencies. 28. Merigan, W. H., Katz, L. M. & Maunsell, J. H. The effects of parvocellular lateral geniculate lesions on the acuity and contrast sensitivity of macaque monkeys. J. Neurosci. 11 , 994-1001 (1991). 29. Merigan, W. H. Chromatic and achromatic vision of macaques: role of the P pathway. J. Neurosci. 9, 776-783 (1989). 30. Schiller, P. H., Logothetis, N. K. & Charles, E. R. Role of the color-opponent and broad-band channels in vision. Vis. Neurosci. 5, 321-346 (1990). 31. Merigan, W. H. & Eskin, T. A. Spatio-temporal vision of macaques with severe loss of Pp retinal ganglion cells. Vision Res. 26, 1751-1761 (1986). 32. Schiller, P. H., Logothetis, N. K. & Charles, E. R. Functions of the colour-opponent and broad-band channels of the visual system. Nature 343, 68-70 (1990). 33. Zeki, S. & Shipp, S. The functional logic of cortical connections. Nature 335, 311-317 (1988). 34. Bartfeld, E. & Grinvald, A. Relationships between orientation-preference pinwheels, cytochrome oxidase blobs, and ocular-dominance columns in primate striate cortex. Proc. Natl Acad. Sci. USA 89, 11905-11909 (1992). 35. Obermayer, K. & Blasdel, G. G. Geometry of orientation and ocular dominance columns in monkey striate cortex. J. Neurosci. 13, 4114-4129 (1993). 36. Orban, G. A. Higher order visual processing in macaque extrastriate cortex. Physiol. Rev. 88, 59-89 (2008). 37. Bullier, J., Hupe, J. M., James, A. C. & Girard, P. The role of feedback connections in shaping the responses of visual cortical neurons. Prog. Brain Res. 134, 193-204 (2001). 38. Maunsell, J. H. R. in Matters of Intelligence (ed. Vaina, L. M.) 59-87 (Reidel, Dordrecht, Holland, 1987). 39. Horton, J. C. & Hubel, D. H. Regular patchy distribution of cytochrome oxidase staining in primary visual cortex of macaque monkey. Nature 292, 762-764 (1981). This paper demonstrated a modular anatomical feature in the primate V1 that led the way for later studies correlating function and/or connectivity with V1 modularity. 40. Fitzpatrick, D., Lund, J. S. & Blasdel, G. G. Intrinsic connections of macaque striate cortex: afferent and efferent connections of lamina 4C. J. Neurosci. 5, 3329-3349 (1985). 41. Hawken, M. J., Parker, A. J. & Lund, J. S. Laminar organization and contrast sensitivity of direction-selective cells in the striate cortex of the Old World monkey. J. Neurosci. 8, 3541-3548 (1988). 42. Livingstone, M. S. & Hubel, D. H. Anatomy and physiology of a color system in the primate visual cortex. J. Neurosci. 4, 309-356 (1984). This paper demonstrated the functional specialization of CO patches in V1. 43. Ts'o, D. Y. & Gilbert, C. D. The organization of chromatic and spatial interactions in the primate striate cortex. J. Neurosci. 8, 1712-1727 (1988). 44. Sincich, L. C. & Horton, J. C. The circuitry of V1 and V2: integration of color, form, and motion. Annu. Rev. Neurosci. 28, 303-326 (2004). 45. Callaway, E. M. & Wiser, A. K. Contributions of individual layer 2-5 spiny neurons to local circuits in macaque primary visual cortex. Vis. Neurosci. 13, 907-922 (1996). 46. Lachica, E. A., Beck, P. D. & Casagrande, V. A. Parallel pathways in macaque monkey striate cortex: anatomically defined columns in layer III. Proc. Natl Acad. Sci. USA 89, 3566-3570 (1992). This paper showed that neurons in the CO patches of V1 receive convergent input from the magnocellular and parvocellular recipient layers of V1. 47. Yabuta, N. H. & Callaway, E. M. Functional streams and local connections of layer 4C neurons in primary visual cortex of the macaque monkey. J. Neurosci. 18, 9489-9499 (1998). This paper described anatomical substrates for the convergence of information from both magnocellular and parvocellular pathways in both CO patches and interpatches of V1. 48. Yoshioka, T., Levitt, J. B. & Lund, J. S. Independence and merger of thalamocortical channels within macaque monkey primary visual cortex: anatomy of interlaminar projections. Vis. Neurosci. 11, 467-489 (1994) . 49. Malpeli, J. G., Schiller, P. H. & Colby, C. L. Response properties of single cells in monkey striate cortex during reversible inactivation of individual lateral geniculate laminae. J. Neurophysiol. 46, 1102-1119 (1981). 50. Nealey, T. A. & Maunsell, J. H. Magnocellular and parvocellular contributions to the responses of neurons in macaque striate cortex. J. Neurosci. 14, 2069-2079 (1994). This paper demonstrated that, following inactivation of either the magnocellular or the parvocellular pathway, visual responsivity can persist for neurons in both CO patches and interpatches of V1. 51. Edwards, D. P., Purpura, K. P. & Kaplan, E. Contrast sensitivity and spatial frequency response of primate cortical neurons in and around the cytochrome oxidase blobs. Vision Res. 35, 1501-1523 (1995). 52. Leventhal, A. G., Thompson, K. G., Liu, D., Zhou, Y. & Ault, S. J. Concomitant sensitivity to orientation, direction, and color of cells in layers 2, 3, and 4 of monkey striate cortex. J. Neurosci. 15, 1808-1818 (1995) . This paper challenged the tripartite scheme introduced in reference 42. It demonstrated that there is not a strict segregation of V1 neurons selective for orientation, direction and colour. 53. O'Keefe, L. P., Levitt, J. B., Kiper, D. C., Shapley, R. M. & Movshon, J. A. Functional organization of owl monkey lateral geniculate nucleus and visual cortex. J. Neurophysiol. 80, 594-609 (1998). 54. Johnson, E. N., Hawken, M. J. & Shapley, R. The spatial transformation of color in the primary visual cortex of the macaque monkey. Nature Neurosci. 4, 409-416 (2001). 55. Lennie, P., Krauskopf, J. & Sclar, G. Chromatic mechanisms in striate cortex of macaque. J. Neurosci. 10, 649-669 (1990). 56. Anderson, J. C., Martin, K. A. & Whitteridge, D. Form, function, and intracortical projections of neurons in the striate cortex of the monkey Macacus nemestrinus. Cereb. Cortex 3, 412-420 (1993). 57. Yabuta, N. H., Sawatari, A. & Callaway, E. M. Two functional channels from primary visual cortex to dorsal visual cortical areas. Science 292, 297-300 (2001). This paper demonstrated that local inputs to layer 4B neurons in V1 depend on cell type. Spiny stellate neurons receive input only from the magnocellular-recipient layer 4Ca, whereas pyramidal neurons receive input from both layer 4Ca and the parvocellular-recipient layer 4Cß. 58. Sawatari, A. & Callaway, E. M. Diversity and cell type specificity of local excitatory connections to neurons in layer 3B of monkey primary visual cortex. Neuron 25, 459-471 (2000). 59. Briggs, F. & Callaway, E. M. Layer-specific input to distinct cell types in layer 6 of monkey primary visual cortex. J. Neurosci. 21 , 3600-3608 (2001). 60. DeYoe, E. A. & Van Essen, D. C. Segregation of efferent connections and receptive field properties in visual area V2 of the macaque. Nature 317, 58-61 (1985). 61. Roe, A. W. & Ts'o, D. Y. Visual topography in primate V2: multiple representation across functional stripes. J. Neurosci. 15, 3689-3715 (1995). 62. Shipp, S. & Zeki, S. Segregation of pathways leading from area V2 to areas V4 and V5 of macaque monkey visual cortex. Nature 315, 322-325 (1985). 63. Shipp, S. & Zeki, S. The functional organization of area V2, I: specialization across stripes and layers. Vis. Neurosci. 19, 187-210 (2002). 64. Livingstone, M. S. & Hubel, D. H. Specificity of cortico-cortical connections in monkey visual system. Nature 304, 531-534 (1983). 65. Livingstone, M. S. & Hubel, D. H. Connections between layer 4B of area 17 and the thick cytochrome oxidase stripes of area 18 in the squirrel monkey. J. Neurosci. 7, 3371-3377 (1987). 370 | MAY 2009 | VOLUME 10 www.nature.com/reviews/neuro © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS 66. Sincich, L. C. & Horton, J. C. Divided by cytochrome oxidase: a map of the projections from V1 to V2 in macaques. Science 295, 1734-1737 (2002). This paper demonstrated the connectivity between CO-defined modules in primate area V1 and those in area V2. 67. Xiao, Y. & Felleman, D. J. Projections from primary visual cortex to cytochrome oxidase thin stripes and interstripes of macaque visual area 2. Proc. Natl Acad. Sci. USA 101, 7147-7151 (2004). 68. Chen, G., Lu, H. D. & Roe, A. W. A map for horizontal disparity in monkey V2. Neuron 58, 442-450 (2008). 69. Xiao, Y., Wang, Y. & Felleman, D. J. A spatially organized representation of colour in macaque cortical area V2. Nature 421, 535-539 (2003). 70. Burkhalter, A., Felleman, D. J., Newsome, W. T. & Van Essen, D. C. Anatomical and physiological asymmetries related to visual areas V3 and VP in macaque extrastriate cortex. Vision Res. 26, 63-80 (1986). 71. Shipp, S. & Zeki, S. The organization of connections between areas v5 and v1 in macaque monkey visual cortex. Eur. J. Neurosci. 1 , 309-332 (1989). 72. Sincich, L. C. & Horton, J. C. Independent projection streams from macaque striate cortex to the second visual area and middle temporal area. J. Neurosci. 23, 5684-5692 (2003). 73. Nassi, J. J. & Callaway, E. M. Specialized circuits from primary visual cortex to V2 and area MT. Neuron 55, 799-808 (2007). 74. Raiguel, S. E., Lagae, L., Gulyas, B. & Orban, G. A. Response latencies of visual cells in macaque areas V1, V2 and V5. Brain Res. 493, 155-159 (1989). 75. Schmolesky, M. T. et al. Signal timing across the macaque visual system. J. Neurophysiol. 79, 3272-3278 (1998). 76. Maunsell, J. H. & Newsome, W. T. Visual processing in monkey extrastriate cortex. Annu. Rev. Neurosci. 10, 363-401 (1987). 77. Conway, B. R., Moeller, S. & Tsao, D. Y. Specialized color modules in macaque extrastriate cortex. Neuron 56, 560-573 (2007). 78. Pasupathy, A. & Connor, C. E. Responses to contour features in macaque area V4. J. Neurophysiol. 82, 2490-2502 (1999). 79. Schein, S. J. & Desimone, R. Spectral properties of V4 neurons in the macaque. J. Neurosci. 10, 3369-3389 (1990). 80. Felleman, D. J., Burkhalter, A. & Van Essen, D. C. Cortical connections of areas V3 and VP of macaque monkey extrastriate visual cortex. J. Comp. Neurol. 379, 21-47 (1997). 81. Andersen, R. A., Asanuma, C., Essick, G. & Siegel, R. M. Corticocortical connections of anatomically and physiologically defined subdivisions within the inferior parietal lobule. J. Comp. Neurol. 296, 65-113 (1990). 82. Blatt, G. J., Andersen, R. A. & Stoner, G. R. Visual receptive field organization and cortico-cortical connections of the lateral intraparietal area (area LIP) in the macaque. J. Comp. Neurol. 299, 421-445 (1990). 83. Boussaoud, D., Ungerleider, L. G. & Desimone, R. Pathways for motion analysis: cortical connections of the medial superior temporal and fundus of the superior temporal visual areas in the macaque. J. Comp. Neurol. 296, 462-495 (1990). 84. Lewis, J. W. & Van Essen, D. C. Corticocortical connections of visual, sensorimotor, and multimodal processing areas in the parietal lobe of the macaque monkey. J. Comp. Neurol. 428, 112-137 (2000). 85. Maunsell, J. H. & Van Essen, D. C. The connections of the middle temporal visual area (MT) and their relationship to a cortical hierarchy in the macaque monkey. J. Neurosci. 3, 2563-2586 (1983). 86. Rizzolatti, G. & Matelli, M. Two different streams form the dorsal visual system: anatomy and functions. Exp. Brain Res. 153, 146-157 (2003). 87. Distler, C., Boussaoud, D., Desimone, R. & Ungerleider, L. G. Cortical connections of inferior temporal area TEO in macaque monkeys. J. Comp. Neurol. 334, 125-150 (1993). 88. Nakamura, H., Gattass, R., Desimone, R. & Ungerleider, L. G. The modular organization of projections from areas V1 and V2 to areas V4 and TEO in macaques. J. Neurosci. 13, 3681-3691 (1993). 89. Ungerleider, L. G., Galkin, T. W., Desimone, R. & Gattass, R. Cortical connections of area V4 in the macaque. Cereb. Cortex 18, 477-499 (2008). 90. Bullier, J., Schall, J. D. & Morel, A. Functional streams in occipito-frontal connections in the monkey. Behav. Brain Res. 76, 89-97 (1996). 91. Tanne-Gariepy, J., Rouiller, E. M. & Boussaoud, D. Parietal inputs to dorsal versus ventral premotor areas in the macaque monkey: evidence for largely segregated visuomotor pathways. Exp. Brain Res. 145, 91-103 (2002). 92. Saleem, K. S., Suzuki, W., Tanaka, K. & Hashikawa, T. Connections between anterior inferotemporal cortex and superior temporal sulcus regions in the macaque monkey. J. Neurosci. 20, 5083-5101 (2000). 93. Janssen, P., Vogels, R. & Orban, G. A. Selectivity for 3D shape that reveals distinct areas within macaque inferior temporal cortex. Science 288, 2054-2056 (2000). 94. Luppino, G., Hamed, S. B., Gamberini, M., Matelli, M. & Galletti, C. Occipital (V6) and parietal (V6A) areas in the anterior wall of the parieto-occipital sulcus of the macaque: a cytoarchitectonic study. Eur. J. Neurosci. 21 , 3056-3076 (2005). 95. Rozzi, S. et al. Cortical connections of the inferior parietal cortical convexity of the macaque monkey. Cereb. Cortex 16, 1389-1417 (2006). 96. Borra, E. et al. Cortical connections of the macaque anterior intraparietal (A1P) area. Cereb. Cortex 18, 1094-1111 (2008). 97. Galletti, C., Gamberini, M., Kutz, D. F., Baldinotti, 1. & Fattori, P. The relationship between V6 and PO in macaque extrastriate cortex. Eur. J. Neurosci. 21 , 959-970 (2005). 98. Albright, T. D. Direction and orientation selectivity of neurons in visual area MT of the macaque. J. Neurophysiol. 52, 1106-1130 (1984). 99. DeAngelis, G. C., Cumming, B. G. & Newsome, W. T. Cortical area MT and the perception of stereoscopic depth. Nature 394, 677-680 (1998). 100. Lappe, M., Bremmer, F., Pekel, M., Thiele, A. & Hoffmann, K. P. Optic flow processing in monkey STS: a theoretical and experimental approach. J. Neurosci. 16, 6265-6285 (1996). 101. Siegel, R. M. & Read, H. L. Analysis of optic flow in the monkey parietal area 7a. Cereb. Cortex 7, 327-346 (1997). 102. Desimone, R., Schein, S. J., Moran, J. & Ungerleider, L. G. Contour, color and shape analysis beyond the striate cortex. Vision Res. 25, 441-452 (1985) . 103. Desimone, R., Albright, T. D., Gross, C. G. & Bruce, C. Stimulus-selective properties of inferior temporal neurons in the macaque. J. Neurosci. 4, 2051-2062 (1984). 104. Komatsu, H. & 1deura, Y. Relationships between color, shape, and pattern selectivities of neurons in the inferior temporal cortex of the monkey. J. Neurophysiol. 70, 677-694 (1993). 105. Latto, R. The role of inferior parietal cortex and the frontal eye-fields in visuospatial discriminations in the macaque monkey. Behav. Brain Res. 22, 41-52 (1986) . 106. Newsome, W. T. & Pare, E. B. A selective impairment of motion perception following lesions of the middle temporal visual area (MT). J. Neurosci. 8, 2201-2211 (1988). This paper showed that lesions of MT result in the impairment of motion perception. 107. Orban, G. A., Saunders, R. C. & Vandenbussche, E. Lesions of the superior temporal cortical motion areas impair speed discrimination in the macaque monkey. Eur. J. Neurosci. 7, 2261-2276 (1995). 108. Pasternak, T. & Merigan, W. H. Motion perception following lesions of the superior temporal sulcus in the monkey. Cereb. Cortex 4, 247-259 (1994). 109. Quintana, J. & Fuster, J. M. Spatial and temporal factors in the role of prefrontal and parietal cortex in visuomotor integration. Cereb. Cortex 3, 122-132 (1993). 110. De Weerd, P., Peralta, M. R., Desimone, R. & Ungerleider, L. G. Loss of attentional stimulus selection after extrastriate cortical lesions in macaques. Nature Neurosci. 2, 753-758 (1999). 111. Merigan, W. H. Basic visual capacities and shape discrimination after lesions of extrastriate area V4 in macaques. Vis. Neurosci. 13, 51-60 (1996). 112. Vogels, R., Saunders, R. C. & Orban, G. A. Effects of inferior temporal lesions on two types of orientation discrimination in the macaque monkey. Eur. J. Neurosci. 9, 229-245 (1997). 113. Milner, A. D. & Goodale, M. A. Two visual systems re-viewed. Neuropsychologia 46, 774-785 (2008). 114. Maunsell, J. H. & Van Essen, D. C. Functional properties of neurons in middle temporal visual area of the macaque monkey. 11. Binocular interactions and sensitivity to binocular disparity. J. Neurophysiol. 49, 1148-1167 (1983). 115. Roy., J. P., Komatsu, H. & Wurtz, R. H. Disparity sensitivity of neurons in monkey extrastriate area MST. J. Neurosci. 12, 2478-2492 (1992). 116. Janssen, P., Vogels, R. & Orban, G. A. Macaque inferior temporal neurons are selective for disparity-defined three-dimensional shapes. Proc. Natl Acad. Sci. USA 96, 8217-8222 (1999). 117. Uka, T., Tanaka, H., Yoshiyama, K., Kato, M. & Fujita, 1. Disparity selectivity of neurons in monkey inferior temporal cortex. J. Neurophysiol. 84, 120-132 (2000). 118. Watanabe, M., Tanaka, H., Uka, T. & Fujita, 1. Disparity-selective neurons in area V4 of macaque monkeys. J. Neurophysiol. 87, 1960-1973 (2002). 119. Krug, K., Cumming, B. G. & Parker, A. J. Comparing perceptual signals of single V5/MT neurons in two binocular depth tasks. J. Neurophysiol. 92, 1586-1596 (2004). 120. Uka, T. & DeAngelis, G. C. Linking neural representation to function in stereoscopic depth perception: roles of the middle temporal area in coarse versus fine disparity discrimination. J. Neurosci. 26, 6791-6802 (2006). 121. Janssen, P., Vogels, R., Liu, Y. & Orban, G. A. At least at the level of inferior temporal cortex, the stereo correspondence problem is solved. Neuron 37, 693-701 (2003). 122. Umeda, K., Tanabe, S. & Fujita, 1. Representation of stereoscopic depth based on relative disparity in macaque area V4. J. Neurophysiol. 98, 241-252 (2007) . 123. Durand, J. B. et al. Anterior regions of monkey parietal cortex process visual 3D shape. Neuron 55, 493-505 (2007). 124. Ferrera, V. P., Rudolph, K. K. & Maunsell, J. H. Responses of neurons in the parietal and temporal visual pathways during a motion task. J. Neurosci. 14, 6171-6186 (1994). 125. Sereno, A. B. & Maunsell, J. H. Shape selectivity in primate lateral intraparietal cortex. Nature 395, 500-503 (1998). 126. Sereno, M. E., Trinath, T., Augath, M. & Logothetis, N. K. Three-dimensional shape representation in monkey cortex. Neuron 33, 635-652 (2002). 127. Tolias, A. S., Keliris, G. A., Smirnakis, S. M. & Logothetis, N. K. Neurons in macaque area V4 acquire directional tuning after adaptation to motion stimuli. Nature Neurosci. 8, 591-593 (2005) . 128. Lehky, S. R. & Sereno, A. B. Comparison of shape encoding in primate dorsal and ventral visual pathways. J. Neurophysiol. 97, 307-319 (2007). 129. Murata, A., Gallese, V., Luppino, G., Kaseda, M. & Sakata, H. Selectivity for the shape, size, and orientation of objects for grasping in neurons of monkey parietal area A1P. J. Neurophysiol. 83, 2580-2601 (2000). 130. Janssen, P., Srivastava, S., Ombelet, S. & Orban, G. A. Coding of shape and position in macaque lateral intraparietal area. J. Neurosci. 28, 6679-6690 (2008) . 131. Schlack, A. & Albright, T. D. Remembering visual motion: neural correlates of associative plasticity and motion recall in cortical area MT. Neuron 53, 881-890 (2007). 132. Sincich, L. C., Park, K. F., Wohlgemuth, M. J. & Horton, J. C. Bypassing V1: a direct geniculate input to area MT. Nature Neurosci. 7, 1123-1128 (2004). 133. Nassi, J. J., Lyon, D. C. & Callaway, E. M. The parvocellular LGN provides a robust disynaptic input to the visual motion area MT. Neuron 50, 319-327 (2006) . 134. Nassi, J. J. & Callaway, E. M. Multiple circuits relaying primate parallel visual pathways to the middle temporal area. J. Neurosci. 26, 12789-12798 (2006). This paper showed that the different pathways by which visual information is carried from V1 to MT have different relationships to the magnocellular and parvocellular pathways. 135. Movshon, J. A. & Newsome, W. T. Visual response properties of striate cortical neurons projecting to area MT in macaque monkeys. J. Neurosci. 16, 7733-7741 (1996). NATURE REVIEWS | NEUROSCIENCE VOLUME 10 | MAY 2009 | 371 © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS 136. Ponce, C. R., Lomber, S. G. & Born, R. T. Integrating motion and depth via parallel pathways. Nature Neurosci. 11, 216-223 (2008). This paper showed that selective inactivation of indirect pathways from V1 (through V2 and/or V3) to MT results in a selective reduction in disparity tuning but not direction tuning of MT neurons. This suggests that the direct pathway from V1 to MT is sufficient for direction but not disparity tuning. 137. Albright, T. D., Desimone, R. & Gross, C. G. Columnar organization of directionally selective cells in visual area MT of the macaque. J. Neurophysiol. 51, 16-31 (1984). 138. DeAngelis, G. C. & Newsome, W. T. Organization of disparity-selective neurons in macaque area MT. J. Neurosci. 19, 1398-1415 (1999). 139. Liu, J. & Newsome, W. T. Functional organization of speed tuned neurons in visual area MT. J. Neurophysiol. 89, 246-256 (2003). 140. Adams, D. L. & Zeki, S. Functional organization of macaque V3 for stereoscopic depth. J. Neurophysiol. 86, 2195-2203 (2001). 141. Zeki, S. M. The third visual complex of rhesus monkey prestriate cortex. J. Physiol. 211, 245-272 (1978). 142. DeYoe, E. A., Felleman, D. J., Van Essen, D. C. & McClendon, E. Multiple processing streams in occipitotemporal visual cortex. Nature 311, 151-154 (1994). 143. Xiao, Y., Zych, A. & Felleman, D. J. Segregation and convergence of functionally defined V2 thin stripe and interstripe compartment projections to area V4 of macaques. Cereb. Cortex 9, 792-804 (1999). 144. Zeki, S. & Shipp, S. Modular connections between areas V2 and V4 of macaque monkey visual cortex. Eur. J. Neurosci. 1 , 494-506 (1989). 145. Gegenfurtner, K. R., Kiper, D. C. & Levitt, J. B. Functional properties of neurons in macaque area V3. J. Neurophysiol. 11, 1906-1923 (1997). 146. Lagae, L., Gulyas, B., Raiguel, S. & Orban, G. A. Laminar analysis of motion information processing in macaque V5. Brain Res. 496, 361-367 (1989). 147. Berezovskii, V. K. & Born, R. T. Specificity of projections from wide-field and local motion-processing regions within the middle temporal visual area of the owl monkey. J. Neurosci. 20, 1157-1169 (2000) . 148. Ohki, K., Chung, S., Ch'ng, Y. H., Kara, P. & Reid, R. C. Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Nature 433, 597-603 (2005). 149. Tan, E. M. et al. Selective and quickly reversible inactivation of mammalian neurons in vivo using the Drosophila allatostatin receptor. Neuron 51, 157-170 (2006). 150. Wickersham, I. R. et al. Monosynaptic restriction of transsynaptic tracing from single, genetically targeted neurons. Neuron 53, 639-647 (2007). 151. Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G. & Deisseroth, K. Millisecond-timescale, genetically targeted optical control of neural activity. Nature Neurosci. 8, 1263-1268 (2005). 152. Zhang, F. et al. Multimodal fast optical interrogation of neural circuitry. Nature 446, 633-639 (2007). 153. Blackshaw, S. E., Nicholls, J. G. & Parnas, I. Expanded receptive fields of cutaneous mechanoreceptor cells after single neurone deletion in leech central nervous system. J. Physiol. 326, 261-268 (1982). 154. Grueber, W. B., Graubard, K. & Truman, J. W. Tiling of the body wall by multidendritic sensory neurons in Manduca sexta. J. Comp. Neurol. 440, 271-283 (2001) . 155. Grueber, W. B., Jan, L. Y. & Jan, Y. N. Tiling of the Drosophila epidermis by multidendritic sensory neurons. Development 129, 2867-2878 (2002). 156. Ma, M. & Shepherd, G. M. Functional mosaic organization of mouse olfactory receptor neurons. Proc. Natl Acad. Sci. USA 91, 12869-12874 (2000). 157. Schoppa, N. E. & Urban, N. N. Dendritic processing within olfactory bulb circuits. Trends Neurosci. 26, 501-506 (2003). 158. Schreiner, C. E., Read, H. L. & Sutter, M. L. Modular organization of frequency integration in primary auditory cortex. Annu. Rev. Neurosci. 23, 501-529 (2000) . 159. Sur, M., Wall, J. T. & Kaas, J. H. Modular segregation of functional cell classes within the postcentral somatosensory cortex of monkeys. Science 21 2, 1059-1061 (1981). 160. Yu, J. et al. Local-circuit phenotypes of layer 5 neurons in motor-frontal cortex of YFP-H mice. Front. Neural Circuits 2, 6 (2008). 161. Barbour, D. L. & Callaway, E. M. Excitatory local connections of superficial neurons in rat auditory cortex. J. Neurosci. 28, 11174-11185 (2008). 162. Bureau, I., von Saint Paul, F. & Svoboda, K. Interdigitated paralemniscal and lemniscal pathways in the mouse barrel cortex. PLoS Biol. 4, e382 (2006). 163. Xu, X. & Callaway, E. M. Laminar specificity of functional input to distinct types of inhibitory cortical neurons. J. Neurosci. 29, 70-85 (2009). 164. Belin, P. & Zatorre, R. J. 'What', 'where' and 'how' in auditory cortex. Nature Neurosci. 3, 965-966 (2000). 165. Dijkerman, H. C. & de Haan, E. H. Somatosensory processes subserving perception and action. Behav. Brain Sci. 30, 189-201; discussion 201-39 (2007). 166. Kaas, J. H. & Hackett, T. A. 'What' and 'where' processing in auditory cortex. Nature Neurosci. 2, 1045-1047 (1999). 167. Savic, I., Gulyas, B., Larsson, M. & Roland, P. Olfactory functions are mediated by parallel and hierarchical processing. Neuron 26, 735-745 (2000). 168. Tian, B., Reser, D., Durham, A., Kustov, A. & Rauschecker, J. P. Functional specialization in rhesus monkey auditory cortex. Science 292, 290-293 (2001) . Acknowledgements We thank R. Born and J. Maunsell for helpful comments and the US National Institutes of Health for their support (RO1-EY010742 and F32-EY018982). 372 | MAY 2009 | VOLUME 10 © 2009 Macmillan Publishers Limited. All rights reserved www.nature.com/reviews/neuro