REVIEW I Neural Connections and Properties in the Primary JOSE-MANUEL ALONSO Department of Psychology University of Connecticut Storrs, Connecticut

A cubic millimeter of primary visual cortex contains about 100,000 neurons that are heavily interconnected by intrinsic and extrinsic afferents. The effort of many neuroanatomists over the past has revealed the gen- eral outline of these connections; however, their function remains a mystery. Recently, combined physio- logical and anatomical approaches are beginning to reveal the role of these connections in the generation of cortical receptive fields. A common theme emerges from all these studies: cortical connections are remarkably specific and this specificity is determined in great extent by the type of connection and the neu- ronal response properties. Feedforward connections follow relatively rigid rules of wiring selectively target- ing neurons with receptive fields matched in position and polarity (thalamus → cortical layer 4) or position and orientation selectivity (layer 4 → layers 2 + 3). In contrast, horizontal connections follow more flexible rules connecting distant cells that are not retinotopically aligned and neighboring cells with differ- ent orientation preferences. These differences in connectivity may give a hint on how visual stimuli are processed in the primary visual cortex. An attractive hypothesis is that local stimuli use the highly selective feedforward inputs to reliably drive cortical neurons while background stimuli modulate their activity through more flexible horizontal (and feedback) connections. NEUROSCIENTIST 8(5):443–456, 2002. DOI: 10.1177/107385802236967

KEY WORDS Lateral geniculate nucleus, Intracortical, Thalamocortical, Cortical circuitry

With the aid of a small microscope and the Golgi stain- A systematic study of neural connections in the primary ing method, Santiago Ramón y Cajal drew the first gen- visual cortex is leading to more accurate hypotheses about eral outline of neural connections within the primary the role of specific circuits in visual processing. This visual cortex (Cajal 1899). The Golgi staining yielded a review focuses on connections that are likely to be in- complete view of neuronal bodies and dendrites; howev- volved in the construction of two types of cortical recep- er, a full reconstruction of the cortical circuitry would tive fields: layer 4 simple cells and layers 2+3 complex have to wait for future generations and more modern cells. The study of cortical circuitry has benefited enor- techniques—the Golgi staining did not adequately mously from technical tools such as anatomical tracers impregnate myelinated axons. With the use of anatomi- and electron microscopy. However, these approaches fell cal tracers and single labeling, axons were better short of answering important questions at the single cell reconstructed and a more complete scheme of the corti- level, as they could not reveal the synaptic strength of cal circuitry became available. As Cajal found, the cor- the connections and the neuronal response properties. tices of different species shared many features in com- With the advent of additional techniques, a more com- mon. These similarities motivated the study of a large plete picture is emerging. Intracellular recordings in variety of circuits, from mice to primates, to learn les- vitro made it possible to simultaneously record from two sons about connectivity and neural processing. Of all the or more connected neurons and measure the connection species studied, the cat has been by far the most inten- strength. In addition, simultaneous extracellular record- sively investigated. As Payne and Peters recently stated, ings from multiple neurons and intracellular recordings “the cat primary visual cortex is probably one of the best in vivo allowed us to study the response properties of studied areas in the brain of any species” (Payne and connected neurons. Also, studies using optical imaging Peters 2002). and 2-deoxyglucose revealed the several maps in which cortical circuits are embedded. This review is centered on the cat primary visual cor- I thank Harvey Swadlow and Marty Usrey for insightful comments on the manuscript and for scientific discussions. Data tex but refers to other species frequently as certain cir- from Figures 2, 3, and 4 come from experiments done in collaboration cuits are better understood in primates or rodents. It with Clay Reid, Marty Usrey, and Luis Martinez. focuses on connections that are likely to be involved in Address correspondence to: Jose-Manuel Alonso, Department of the generation of response properties as opposed to con- Psychology, University of Connecticut, 406 Babbidge Road, U-20, nections that diffusely modulate excitability (e.g., brain Storrs, CT 06269 (e-mail: [email protected]). stem afferents). There are several thousand references

Volume 8, Number 5, 2002 THE NEUROSCIENTIST 443 Copyright © 2002 Sage Publications ISSN 1073-8584 about the circuitry of the cat primary visual cortex, so obviously many important ones must be omitted to pres- ent a concise review. In general, this review covers in most detail circuits that have been studied by the author (e.g., feedforward connections are discussed more extensively than horizontal connections). The primary visual cortex receives many different names in the liter- ature (e.g., striate cortex, V-1, area 17). Here, I use area 17 for cats and V-1 for other species including primates.

Feedforward Inputs from Subcortical Structures

General Characteristics The main thalamic input to the primary visual cortex originates in the lateral geniculate nucleus (LGN). In the cat, the primary visual cortex receives geniculate input from at least three different pathways: X, Y, and W. These pathways differ in several response properties such as conduction velocity, receptive field size, and lin- earity of spatial summation within the receptive field. Y cells have the fastest conduction velocities, largest receptive field sizes, and nonlinear spatial summation. X cells have intermediate conduction velocities, small receptive field sizes, and linear spatial summation. Finally, the W cells are a diverse group of neurons with very slow conduction velocities, large receptive field sizes, and linear or nonlinear spatial summation (for Fig. 1. Parallel pathways originating in the lateral geniculate review, see Orban 1984; Sherman and Guillery 2001). nucleus (LGN). Top, The cat lateral geniculate nucleus is - ized in three main layers (A, A , and C) that have X cells (in red) The LGN of the cat is organized in three main layers, 1 and Y cells (in black). Other smaller layers bellow layer C (C , C , two contralateral (A and C) and one ipsilateral (A1). 1 2 and C3) have mostly W cells (in blue). There is an overrepresen- Whereas layer C has almost exclusively Y cells, the A tation of the contralateral eye in the cat LGN (C: contralateral; I: layers have a mixture of X and Y cells with a bias toward ipsilateral; compare with the macaque below). The MIN (medial X cells (particularly near the area centralis; LeVay and interlaminar nucleus of the thalamus) has mostly Y and W cells, Ferster 1977). Below layer C, the cat LGN also has three and it is also subdivided in contralateral and ipsilateral layers (not shown for simplicity). Bottom, The macaque LGN is organ- smaller parvocellular layers, two contralateral (C1, C3) ized in six main layers that have parvocellular cells (in red) and and one ipsilateral (C2), that contain mostly W cells magnocellular cells (in black). Intercalated with the main layers, (Fig. 1, top). X, Y, and W cells differ not only in their there are another six thinner layers that contain koniocellular laminar location within the LGN but also in their pro- cells (in blue). jection patterns within the cortex. X cells project almost exclusively to area 17, Y cells project to area 17 and area ed in different layers at the level of the LGN (Fig. 1, bot- 18, and W cells project to many areas but predominant- tom). The M, P, and K pathways, respectively, target cor- ly to area 19 (Stone and others 1979; Kawano 1998). tical layers 4Cα, 4Cβ and the cytochrome oxidase-rich Within area 17, X and Y cells project, respectively, to the blobs in the superficial layers (Hubel and Wiesel 1972; bottom and top of layer 4 (Ferster and LeVay 1978; Fitzpatrick and others 1983). In addition, there are some Gilbert and Wiesel 1979; Humphrey and others 1985), weaker projections to layer 6 (M and P pathways), layer whereas W cells project to the borders of this layer 4A (P pathway), and layer 1 (K pathway) (Fig. 2, bot- embracing the X/Y projection (LeVay and Gilbert 1976). tom). The projections from the P, M, and K pathways in In addition, there are weaker projections to layer 6 (X, Y) the monkey share certain resemblances to the projec- and layer 1 (W), and some X cells project through the tions from the X, Y, and W pathways in the cat (Florence entire layer 4 (Humphrey and others 1985). In summary, and Casagrande 1987). However, the parvocellular path- the projection from three different pathways in the cat way in the monkey may be considered as a “totally new visual cortex—X, Y, and W—is partially segregated pathway” owing to its color selectivity, and the magno- across cortical areas (areas 17, 18, and 19) and across cellular pathway is sometimes subdivided into Mx and layers within area 17 (Fig. 2, top). My based on the linearity of spatial summation like X Similar to the cat, the monkey has three and Y cells in the cat (Kaplan and Shapley 1982). main pathways—the magnocellular (M), parvocellular An important difference between the visual pathways (P), and koniocellular (K) pathways—that are segregat- of cats and primates is the extent in which the LGN pro-

444 THE NEUROSCIENTIST Neural Connections lack of knowledge about their circuitry. A more detailed knowledge of this circuitry will eventually lead to more precise comparisons and let us benefit from the large amount of data gathered in both species over the past. In addition to the main geniculate layers, cat area 17 receives a scant projection from the MIN (medial inter- laminar nucleus of the thalamus), a nucleus that is only present in carnivores. The MIN contains mostly Y cells and W cells (Humphrey and Murthy 1999); Y cells proj- ect to the top of layer 4 and W cells to layer 1 (Leventhal 1979). Finally, another source of subcortical input that should not be neglected is the claustrum. The caudal end of this nucleus contains visually driven cells, and it is retinotopically organized. The claustrum receives input from layer 6 of area 17 and projects back to area 17 ter- minating predominantly within layers 4 and 6 (LeVay and Sherk 1981).

Topography and Clustering of Synaptic Terminals The geniculocortical pathway has an exquisite retino- topic organization. Each axonal arbor is restricted to a very small portion of the cortex (Fig. 2, top). X axons are the most restrictive ones and cover an area of 0.6 to 0.9 square millimeters, with most of the boutons con- centrated in layer 4 and a smaller proportion in layer 6 (layer 6 receives 10% of all boutons; Humphrey and oth- Fig. 2. Feedforward geniculocortical pathways to the primary ers 1985). Y axons cover a cortical area twice as large as visual cortex. Top, Three different geniculocortical pathways X axons and make several clusters that align with the project to the cat primary visual cortex (X in red, Y in black, and ocular dominance columns (1–1.8 square millimeters W in blue). The cartoon illustrates the laminar targets, the later- al spread, and the cluster organization of the strongest axonal with gaps of 500 microns; Ferster and Levay 1978; projections from each pathway based on data obtained from Gilbert and Wiesel 1983; Humphrey and others 1985). single axon labeling (Ferster and Levay 1978; Humphrey and On average, Y axons have twice as many synaptic bou- others 1985). For simplicity, the cartoon does not illustrate the tons as X axons (Y: 4280; X: 2620) and give a signifi- projection of some X cells through the entire layer 4 and differ- cantly larger number of boutons to layer 6 (~14% of all ences in projection strength (e.g., the X projection is 9 times stronger in layer 4 than in layer 6). Also, it should be noticed boutons; Humphrey and others 1985). Moreover, Y cells that the illustration for the W cell projection is based on rela- make more synaptic contacts per neuron (n = 3–6) than tively sparse data (Ferster and Levay 1978). Bottom, Three dif- X cells (n = 2–3) and tend to target cortical cells with ferent geniculocortical pathways project to the macaque pri- larger somata (Freund and others 1985). mary visual cortex (Parvocellular in red, Magnocellular in black, and Koniocellular in blue). The cartoon illustrates the laminar We know little about the span of W axons in the cortex targets, the lateral spread, and the cluster organization of the and the number of per axon. Ferster and Levay strongest axonal projections from each pathway based on data (1978) filled some very thin axons after injecting HRP obtained from single axon labeling in the macaque (Blasdel and in the optic radiations that are likely to belong to W cells. Lund 1983). The cartoon illustrates the targets of two different Based on this study, W axons make clusters separated by types of thin axons (in dark blue and blue) labeled by Blasdel and Lund (1983). 500-micron gaps and cover distances of up to 3.8 mm mainly within layer 1 (twice as large as the Y axons). Like the W axons, some very thin axons in the monkey (prob- jects to extrastriate cortical areas. Whereas the cat LGN ably from the K pathway) can span distances of 2 mm projects to many areas [17, 18 19, lateral suprasylvian area within layer 1, making clusters separated by 300-micron (LS)], the LGN in monkeys projects mostly to area 17 gaps (Fig. 2, bottom). Magnocellular axons make clus- (although there is some marginal input to V-2, V-4, and ters with the same periodicity (~300-micron gaps), but inferotemporal cortex that originate mostly in the K path- they only span 1 mm laterally. Finally, the parvocellular way; e.g., Wong-Riley 1976; Bullier and Kennedy 1983). axons in monkeys can be restricted to a single terminal This difference in the geniculocortical projection may field of 200 microns (Blasdel and Lund 1983). On aver- not be so pronounced if, as suggested by several authors, age, the cortical area covered by a geniculate axon is both cat area 17 and area 18 are considered as part of the larger in the cat than in the monkey. Consequently, the primary visual cortex (Payne and Peters 2002). The com- cortical area containing cells with overlapping receptive parison between the two best-studied primary visual cor- fields is also larger in the cat (cat: 5 mm2 [Albus 1975]; tices—cat and primate—is still rather loose owing to our monkey: 3.1 mm2 [Hubel and Wiesel 1974]).

Volume 8, Number 5, 2002 THE NEUROSCIENTIST 445 Response Properties to a are aligned in visual space (Reid and Alonso 1995; Alonso and others 2001; also see The specificity of the geniculocortical pathway goes fur- Chapman and others 1991). Second, the synaptic poten- ther than a precise retinotopic organization. Based only tials of simple cells maintain their orientation selectivity on the size of the axonal arbor in the cat visual cortex, an even if most cortical inputs are inactivated (Chung and X cell could potentially contact 15,000 cortical cells Ferster 1998; Ferster and others 1996). And third, orien- (Peters and Payne 1993); however, bouton counts sug- tation selectivity can be modeled by combining conver- gest that this number is much lower. For example, if a Y gent geniculate inputs with a push-pull mechanism in a cell makes 3600 synapses within layer 4 (Humphrey and circuit that is very consistent with the Hubel and Wiesel others 1985) and makes 5 contacts per cortical neuron model (Troyer and others 1998; but see Somers and oth- (Freund and others 1985), then each Y axon would con- ers 1995 as an example of an alternative model). tact 720 neurons. The idea that each geniculate axon targets a small Feedback Inputs from Other Cortical Areas number of cortical neurons is very consistent with phys- iological studies (Reid and Alonso 1995; Alonso and others 2001; see also Tanaka 1983). The connections General Characteristics between geniculate cells and layer 4 neurons are strongly determined by the cells’ receptive field proper- The primary visual cortex also receives feedback input ties. In the cat, the receptive fields of geniculate cells from other cortical areas. In monkeys, V-1 is clearly the and layer 4 cells have very different geometry (Fig. 3a). lowest area in a cortical hierarchy because it is by far the Whereas geniculate receptive fields are roughly circular main recipient of geniculate input. In the cat, however, and have a center-surround organization (e.g., on-center/ hierarchies and feedback are more difficult to establish off-surround), most layer 4 cells have simple receptive because geniculate connections target several cortical fields made of separate and elongated subregions (e.g., areas with similar strength. In fact, areas 17 and 18 in the on-subregion flanked by off-subregions). As would be cat share more connections in common than any other expected from the anatomy, geniculocortical connec- combination of cat visual areas (Symonds and tions link cells that are retinotopically aligned—in Rosenquist 1984), and both should be probably consid- almost every connection the receptive field center of the ered as part of the primary visual cortex (Bullier and geniculate cell precisely overlaps the receptive field of others 1984; Payne and Peters 2002). the layer-4 neuron. In addition, geniculocortical connec- In the monkey, feedback connections to V-1 originate tions are strongly determined by a precise match in other in several cortical areas including V-2, V-3, V-4, MT, and response properties. The probability of finding a mono- the inferotemporal cortex (see Salin and Bullier 1995 synaptic connection between a geniculate cell and a for review). Connections from higher areas originate layer 4 simple cell is highest when 1) the geniculate cen- mainly in infragranular layers, whereas those from lower ter is superimposed with a simple cell subregion of the areas originate in both supragranular and infragranular same sign (e.g., on-center superimposed with on-subre- layers. The connections from the highest areas target almost gion), 2) the geniculate center and the overlapped simple exclusively layer 1, whereas those from lower areas tar- cell subregion generate responses with similar time get a large variety of layers including 1-3, 4B, and 5-6 courses, 3) the geniculate center overlaps the strongest (Rockland and Pandya 1979; see Fig. 4, bottom). In some subregion of the simple cell, and 4) the diameter of the cases, a cortical area sends feedback to the layers of V-1 geniculate center equals (or is slightly larger) than the that give origin to the feedforward input for that area. For width of the simple cell subregion (Alonso and others example, layer 4B of V-1 both receives and sends input 2001). Figure 3a shows the receptive fields of a genicu- to MT. However, although there is some evidence for bi- late cell and a layer 4 simple-cell that follow all these directional feedforward–feedback circuits in the rat rules of connectivity (receptive field position, sign, tim- (Johnson and Burkhalter 1997), these closed loops are ing, subregion strength and size). not a general rule in feedback connections. For example, The remarkable precision of the geniculocortical con- MT sends feedback to the deep layers of V-2, but these nections has important implications for models of recep- layers do not project to MT (Rockland and Knutson tive field generation. For many years, two general mod- 2000). Moreover, the feedback axons from V-2 to V-1 are els attempted to explain how orientation selectivity was slightly horizontally offset from the feedforward neurons generated in the visual cortex. In the Hubel and Wiesel that project from V-1 to V-2 (Rockland and Virga 1989). model, the orientation selectivity of simple cells originat- A remarkable feature of feedback pathways is their ed from the convergence of geniculate inputs with recep- anatomical diversity. Whereas V-2 axons target layers 1, tive fields aligned in visual space. In cross-orientation 2, 3, and 5 (Rockland and Virga 1989), MT axons target models, orientation selectivity emerged as a result of layers 1, 4B, and 6. Moreover, a single MT axon may tar- inhibitory connections between cells with different ori- get only layer 1, only layer 4B, layers 1 and 4B, or layers entation preferences (see Ferster and Koch 1987 for 1, 4B, and 6 (Rockland and Knutson 2000). This diver- review). Recent studies have provided strong support for sity of connection patterns could indicate the existence the original Hubel and Wiesel model (Hubel and Wiesel of parallel feedback pathways as there are parallel feed- 1962). First, the receptive fields of the geniculate inputs forward pathways. Consistent with this idea, Henry and

446 THE NEUROSCIENTIST Neural Connections Fig. 3. Response properties and strength of geniculocortical connections. A, On the left, the figure shows the receptive fields from a geniculate cell (top) and a simple cell (bottom) that were monosynaptically connected. Each receptive field is shown as a contour plot at three different time delays between and response. On-responses are represented in gray, and off-responses in black (the grid can be used as spatial reference to superimpose both receptive fields). The geniculate receptive field is roughly circular and has a center-surround organization; on-center (first frame: 0–25 ms) and off-surround (second frame: 25–50 ms). The simple receptive field has two elongated and parallel subregions, one off- and the other on- (first frame: 0–25 ms). These strong subregions are flanked by weaker subregions that can be seen on the second frame (25–50 ms). The geniculate center is overlapped with a simple-cell subre- gion of the same sign (on- superimposed with on-) and similar response time-course (both responses start at the 0–25 ms frame and peak at the 25–50 ms frame). On the right, there is a correlogram showing a narrow peak displaced from zero (asterisk) indicating that the geniculate cell was monosynaptically connected to the simple cell. (Reproduced from Alonso and others 2001 with permission from The Journal of Neuroscience). B, Visual responses of a simple cell to a moving bar. On the left, a histogram shows the total num- ber of spikes generated by each bar sweep (each histogram bin is a bar sweep). On the right, a raster illustrates the individual spikes (each spike is represented by a dot, and each bar sweep by a raster line). The simple cell had three subregions that were sequential- ly stimulated by the sweeping bar and can be seen as three columns of spikes in the raster. The arrows indicate the injections of tiny volumes of GABA in a region of LGN (layer A) that was retinotopically aligned with the simple receptive field. The largest injec- tions completely inactivated the response of the simple cell for several seconds (15 nl represented by the largest black circle at the bottom). The smallest injections (smallest black circle at the top) inactivated only the third subregion of the simple cell. At the bottom, the duration of the blockade is shown as a function of the volume of GABA injected in LGN. (Reproduced from Martinez and Alonso, 2001 with permission from Neuron). C, A tiny injection of GABA in LGN (layer A) is able to inactivate a single subregion in the recep- tive field of a simple cell. The dotted circle represents the receptive field of the geniculate multiunit activity recorded at the center of the injection.

Volume 8, Number 5, 2002 THE NEUROSCIENTIST 447 nearby areas (Rockland and Knutson 2000). At least in part, this distance rule could reflect differences in recep- tive field size (receptive field size is larger in farther areas than nearby areas to V-1). Although feedback connections can cover large V-1 distances, they are far from being diffuse. Like genicu- late axons, they form clusters. The periodicity and the presence of clusters of axonal arbors vary for different cortical layers. For example, MT axons usually form clusters within layer 4B (250 to 750 microns) but rarely within layer 6 (Rockland and Virga 1989). At least for the case of MT, the cluster organization could be related with the patchy distribution of projecting feedforward neurons from V-1 (Boyd and Casagrande 1999).

Response Properties We know little about the response properties of cells that receive or send feedback inputs and the properties shared between neurons connected by feedback pathways. In fact, we can hardly answer elementary questions about the retinotopic topography of these pathways. For exam- ple, we know that many V-1 cells sharing input from a common MT axon are not retinotopically aligned (MT axonal arbors can cover distances of up to 8 mm within V-1). However, we still do not know whether MT neu- rons are retinotopically aligned with all its V-1 targets— the receptive field of an MT neuron may be large enough to overlap the receptive fields of all the V-1 cells it feeds. In comparison with feedforward pathways, feedback pathways target a smaller percentage of inhibitory neurons (Johnson and Burkhalter 1996). Feedback pathways are Fig. 4. Feedback pathways to the primary visual cortex. Top, also weaker than feedforward pathways, and their inacti- Three different feedback pathways to cat area 17 originate in vation rarely silences a V-1 cell (Alonso and others 1993) area 18 (red), area 19 (black), and the lateral suprasylvian area (blue). The cartoon does not illustrate the lateral spread and the even if a large number of feedback connections are inac- cluster organization of the axonal projections in the cat due to tivated or removed (Mignard and Malpeli 1991; Hupe lack of enough data from single axon labeling (Henry and oth- and others 1998). In contrast, the inactivation of a small ers 1990; Shipp and Grant 1991). Bottom, Three different feed- group of feedforward geniculate inputs has a dramatic back pathways to monkey V-1 originate in V-2 (red), MT (black), effect on cortical activity (Malpeli 1983; Martinez and and the inferotemporal area (blue). The cartoon illustrates the laminar targets and lateral spread of the three pathways Alonso 2001). Figures 3b and 3c show the visual respons- (Rockland and Virga 1989; Rockland and others 1994; es of a simple cell in area 17 during the inactivation of Rockland and Knutson 2000). The cluster organization is very its geniculate inputs. By injecting tiny volumes of GABA diverse and is not represented. in layer A of the LGN, it is possible to inactivate the response of a cortical cell entirely (Fig. 3b) or inactivate others (1990) suggested that cells in the superficial and restricted portions of its receptive field (Fig. 3b and c). deep layers of cat area 18 form two parallel pathways This level of precision is consistent with the idea that each that, respectively, target the superficial and deep layers strong subregion in the receptive field of a simple cell is of area 17 (Fig. 4, top). dominated (or driven) by just a few geniculate inputs. Recently Sherman and Guillery (1998) and Crick and Topography and Clustering of Synaptic Terminals Koch (1998) reemphasized the importance of classifying neural connections as drivers or modulators based on their Feedback axons cover larger cortical distances than synaptic strength. Paraphrasing Crick and Koch (1998), feedforward axons (Figs. 2, 4). On average, axonal the drivers are inputs that, by themselves, can make the arbors from V-2, V-4, and TEO span distances of 1, 5, relevant neurons fire strongly. And the modulators are and 6 mm, respectively, and the axonal arbors from inputs that, by themselves, cannot make the relevant neu- MT/V5 can span distances of up to 8 mm within layer rons fire strongly, but can modify the firing produced by 4B of V-1 (Rockland and Virga 1989; Rockland and oth- the driving inputs. Under this distinction, the results from ers 1994; Rockland and Knutson 2000). There seems to inactivation studies suggest that feedforward inputs are be a “distance rule” in feedback connections—areas that the drivers of cortical activity and feedback inputs the are farther from V-1 cover larger cortical regions than modulators. An interesting hypothesis is that feedback

448 THE NEUROSCIENTIST Neural Connections pathways serve to modulate the gain of lower cortical In addition to their layer 4 inputs, layers 2+3 receive areas during selective visual attention (Desimone and Dun- connections from basically every cortical layer. If verti- can 1995) and improve the discrimination between fore- cal connections are seen as part of a serial circuit (for ground and background stimuli (Hupe and others 1998). cat: layer 4→layers 2+3→layer 5→layer 6), the inputs from layer 4 could be considered as vertical feedforward Inputs from Vertical Connections whereas the inputs from the other layers would be verti- cal feedback (Callaway 1998; Fig. 5a). In support of this interpretation, feedforward and feedback vertical inputs General Characteristics and Clustering have been shown to target different types of neurons. For of Synaptic Terminals example, within layers 2+3, layer 4 inputs target pyram- Both feedforward and feedback afferents feed into the idal cells and fast spiking cells (the main drivers of exci- intrinsic circuitry of the primary visual cortex. The pri- tatory and inhibitory activity within layers 2+3), where- mary visual cortex is organized in layers of neurons that as layer 5 inputs target a population of adapting inhibito- are crossed by vertical connections running orthogonal ry neurons that are mainly modulators (Fig. 5b; Dantzker to the cortical surface. In cat area 17, layer 4 projects to and Callaway 2000). layers 2+3, layers 2+3 project to layer 5, and layer 5 The connections from layer 6 to layer 4 can be also projects to layer 6 (in addition, layers 5 and 6 project to considered as vertical feedback in that layer 4 neurons the superficial layers and layer 6 projects to layer 4). In remain strongly active during the inactivation of layer 6 the monkey, a very similar circuit can be proposed if (Bolz and Gilbert 1986; Grieve and Sillito 1991). Feed- layer 4C and layers 2-4B are considered to be analogous back connections from layer 6 to layer 4 originate specif- ically in corticogeniculate neurons (Katz 1987), and there to cat layer 4 and layers 2+3, respectively (the connec- are at least two populations of these neurons in monkeys. tions from layer 5 to layer 6 have not been described in One population is dominated by magnocellular input and the monkey; for review, see Gilbert 1983; Callaway 1998). targets layer 4Cα, whereas the other population is domi- Layer 4, the main recipient of geniculate input in the nated by parvocellular input and targets predominantly primary visual cortex, sends its main output to layers layer 4Cβ (Briggs and Callaway 2001). In the cat, layer 4 2+3. These connections are totally unidirectional. That also receives indirect feedback from a different popula- is, all excitatory connections run in the direction from tion of layer 6 cells through the claustrum (layer layer 4 to layers 2+3 (Alonso and Martinez 1998; 6→claustrum→layer 4; LeVay and Sherk 1981). Martinez and Alonso 2001; see also Feldmeyer and oth- ers 2002). The connections from layer 4 to layers 2+3 are also relatively strong and fast. In vitro studies in the rat Response Properties somatosensory cortex (Feldmeyer and others 2002) indi- While the geniculocortical connections link cells with cate that the axon from a layer 4 cell makes about four to receptive fields matched in position and response sign five synaptic contacts with the basal dendrites of a layer (on- or off-), the connections from layer 4 to layers 2+3 2+3 pyramidal neuron generating EPSPs of 0.7 ± 0.6 link cells with receptive fields matched in position and mV. For comparison, a cell in layers 2+3 makes about orientation preference (Alonso and Martinez 1998; one to five synaptic contacts with the apical trunk or Martinez and Alonso 2001). In layers 2+3, receptive proximal oblique dendrites of a layer 5 cell generating field sign is no longer relevant because most neurons are EPSPs of 0.3 ± 0.3 mV (Reyes and Sakmann 1999). complex cells (generate on- and off-responses in the The connections from layer 4 to layers 2+3 are very same region of the receptive field). In contrast, orienta- specific. In the macaque, the two subdivisions of layer tion preference becomes important because the projec- 4C target different cortical layers—layer 4Cα projects to tions from layer 4 to the superficial layers are at the very layer 4B and layer 4Cβ projects to layers 2+3. center of the . The orientation prefer- Furthermore, this specificity is improved at the single ence of a cortical column is likely to be determined cell level within layer 4B—spiny stellate cells receive mainly by vertical feedforward inputs, whereas the band- most of their input from layer 4Cα, whereas pyramidal width of the orientation tuning could be modulated by cells (whose dendrites widely cross layer boundaries) horizontal and feedback connections (Alonso and others receive mixed input from layer 4Cα and layer 4Cβ 1993; White and others 2001). It is important to empha- (Yabuta and others 2001). Similarly, in tree shrew, the size that most layer 4 axons cover very restricted regions cortical depth of a layer-4 neuron determines its projec- in layers 2+3 and their convergence should be able to tion pattern within layers 2+3 (Fitzpatrick 1996). generate narrow orientation bandwidths (e.g., less than Surprisingly, however, this level of specificity has not 45 degrees for arbors 300 microns wide). yet been demonstrated in the cat. In the cat, layer 4 cells Figure 6 illustrates the receptive field properties of a show a diverse pattern of projections some of which are layer 4 simple cell and a layer 2+3 that restricted to a small cortical cylinder in layers 2+3 (~300 show correlated firing consistent with a monosynaptic microns; e.g., Fig. 2 of Hirsch and others 1998a), where- connection (Fig. 6c). The simple cell has a receptive as others span distances of up to 5 mm in the form of field with separate on- and off-subregions and the com- multiple very narrow clusters (~100 microns; e.g., Fig. 9 plex cell an on-off receptive field that could only be of Martin and Whitteridge 1984). mapped with moving bars (both light and dark). Like in

Volume 8, Number 5, 2002 THE NEUROSCIENTIST 449 Wiesel model of receptive field generation (Hubel and Wiesel 1962). According to this model, the convergence of geniculate inputs generates simple receptive fields in layer 4 (Reid and Alonso 1995) and the convergence of layer 4 inputs generates complex receptive fields in lay- ers 2+3 (Alonso and Martinez 1998). Also in support of this model, the inactivation of a small group of genicu- late inputs is enough to silence most layer 4 simple cells and most complex cells in the superficial layers (Martinez and Alonso 2001; cf. Malpeli 1983). Finally, several theoretical models have been successful at con- structing complex receptive fields from simple cell inputs (e.g., Adelson and Bergen 1985; Ohzawa and oth- ers 1990) or simple cell inputs combined with complex cell inputs (Chance and others 1999). Still, some com- plex cells are known to receive direct geniculate input (Hoffmann and Stone 1971) and could be constructed by other mechanisms (e.g., Mel and others 1998). Layers 2+3 and layer 4 also receive vertical feedback from the deep cortical layers. Although little is known about the role of these connections in receptive field generation (Bolz and Gilbert 1986; Grieve and Sillito 1991), several lines of evidence indicate that most of the vertical feedback to layer 4 originates from simple cells. Data from intracellularly labeled neurons show that many layer 6 cells projecting to layer 4 have simple receptive fields (Gilbert and Wiesel 1979; Martin and Whitteridge 1984; Hirsch and others 1998b), and com- bined anatomical and physiological studies demonstrate that most layer 6 cells projecting to layer 4 are cortico- geniculate cells (Katz 1987; Usrey and Fitzpatrick 1996), and most corticogeniculate cells are simple cells (Grieve and Sillito 1995). Finally, the layer 6 cells projecting to the claustrum (another source of input to layer 4) have also simple receptive fields (Grieve and Sillito 1995).

Inhibitory Inputs

General Characteristics and Clustering of Synaptic Terminals Fig. 5. Vertical connections in the primary visual cortex. A, Vertical connections in the cat visual cortex are classified as Local inhibitory neurons are an essential part of the cir- feedforward and feedback assuming the existence of a serial cuitry within the primary visual cortex. Without inhibi- circuit in the cortical column: layer 4→layers 2+3→layer 5→ layer 6 (for the cat; see text for more detail). B, In the rat visual tion, excitation saturates and the selectivity for a large cortex, feedforward and feedback vertical connections target variety of response properties is lost. Orientation selec- different types of cells within layers 2+3. Feedforward inputs tivity, direction selectivity, simple-cell subregion antag- from middle layers target excitatory pyramidal cells and onism, and end-inhibition are just a few examples of inhibitory fast-spiking cells, whereas feedback inputs from the properties that are seriously affected by extracellular deep layers target inhibitory adapting interneurons (Dantzker and Callaway 2000). blockade of inhibition (e.g., Sillito 1975). Cortical inhi- bition is not only crucial to balance excitation but also has an important role in cortical plasticity (Hensch and this example, most excitatory connections between layer others 1998). However, in spite of its undeniable impor- 4 and layers 2+3 link cells with overlapping receptive tance, we know little about the connections made by fields (Fig. 6a) and similar orientation preferences (Fig. inhibitory neurons and their role in generating cortical 6b). In all cases studied, the connections were found to receptive fields. run in the direction from the layer 4 simple cell to the Inhibitory neurons make up about 20% to 25% of all layers 2+3 complex cell and none in the opposite direc- cortical cells (Gabbott and Somogyi 1986) and show a tion (Alonso and Martinez 1998). large variety of morphologies, physiological properties, The properties of the feedforward circuit LGN→layer and molecular structure (Gupta and others 2000). A 4→layers 2+3 are very consistent with a Hubel and large proportion of inhibitory neurons belong to a class

450 THE NEUROSCIENTIST Neural Connections (1899) and is characterized by axons that form tightly intertwined bundles of vertical collaterals across layers. Double bouquet cells are the major source of a rare type of symmetric on dendritic spines of pyramidal cells (DeFelipe and Fariñas 1992). Inhibitory neurons can also be classified based on their physiological properties in at least two categories: fast-spiking and adapting inhibitory neurons (Gibson and others 1999; Dantzker and Callaway 2000). Although the relation between the morphological and physiological classification is still rather loose, most fast-spiking cells are likely to be basket cells. Fast-spiking cells have short- duration spikes and reach high firing rates with little or no adaptation. In contrast, adapting inhibitory neurons have spikes of longer duration and show considerable adaptation in their firing rates. This physiological distinc- tion is important because it relates to specific cortical circuits. Feedforward inputs tend to target fast-spiking cells, whereas feedback and horizontal inputs most fre- quently target adapting inhibitory neurons (Gibson and others 1999; Dantzker and Callaway 2000). Moreover, electrical synapses tend to connect inhibitory neurons of the same type (Gibson and others 1999; Fig. 7b). Recent in vitro studies revealed a dense interconnect- ed network of inhibitory neurons that regulate their out- puts through both chemical and electrical reciprocal connections (Galarreta and Hestrin 1999; Gibson and others 1999) in addition to self-connections or autapses Fig. 6. Response properties of a layer 4 simple cell and a (Tamas and others 1997). Only one type of inhibitory neu- layer 2 complex cell that were monosynaptically connected. A, ron seems to avoid this promiscuous connectivity—the A simple receptive field mapped by reverse correlation with white noise is shown as a contour plot (on-subregion in gray, chandelier cell (Somogyi 1989). Among the reciprocal off-subregion in black). The complex cell did not respond to inhibitory connections, the connections between basket static stimuli, and it was mapped with moving light and dark cells generate the strongest and fastest IPSPs (Tamas and bars (dotted rectangle). The receptive fields of the two cells others 1998) by making an average of 12 synapses per were fully overlapped. B, Both cells had similar orientation pref- connection all located on somata and proximal dendrites. erences. C, The correlogram shows a peak displaced from zero indicative of a monosynaptic connection from the simple cell to Basket cells also make connections with double bouquet the complex cell. (Reproduced from Alonso and Martinez 1998 cells and excitatory cells, but these connections are weak- with permission from Nature Neuroscience). er. The connections between spiny stellate cells and bas- ket cells are likely to be important for receptive field generation—in sthe cat visual cortex, 30% of simultane- identified by Ramon y Cajal (1899) and named by ously recorded spiny stellate cells and basket cells are Marin-Padilla (1969) as basket cells. There are several reciprocally connected (Tarczy-Hornoch and others 1998). types of basket cells that differ in morphological and physiological properties (Kisvarday 1992; Gupta and Response Properties others 2000). Small basket cells are involved in local connections within a few hundred microns, whereas We know little about the response properties of inhibito- large basket cells have axonal fields that can cover up to ry neurons. In vivo intracellular recordings from these 2.5 mm of cortical distance (Buzás and others 2001). neurons are sparse. The available sample suggests that, In addition to basket cells, pyramidal neurons receive like excitatory cells, inhibitory cells can have simple or input from at least two other types of inhibitory neurons: complex receptive fields (Gilbert and Wiesel 1979; chandelier cells and double bouquet cells (Fig. 7a). Martin and others 1983; Azouz and others 1997). Also Chandelier cells are an extraordinary example of speci- like excitatory cells, most inhibitory cells are orientation ficity in the —they only connect to axon selective, although some of them are nonoriented initial segments (Somogyi 1989) mostly of pyramidal (Martin and others 1983). cells (DeFelipe and Fariñas 1992). Among pyramidal Despite these similarities, excitatory and inhibitory neu- cells, corticocortical cells in layers 2+3 receive the rons are likely to differ in several response properties. largest number of axoaxonic synapses (22–28) and cor- An important one is sensitivity. In vivo, extracellularly ticothalamic pyramids the smallest (1–5; DeFelipe and recorded fast-spiking cells respond to higher stimulation Fariñas 1992). The other type of inhibitory neuron—the frequencies and lower stimulus intensities than excitato- double bouquet cell—was first described by Cajal ry cells (Swadlow 1989). Similarly, in vitro inhibitory

Volume 8, Number 5, 2002 THE NEUROSCIENTIST 451 inhibition played a crucial role in generating orientation selectivity by connecting cells with different orientation preferences (for review, see Ferster and Koch 1987). However, this idea is not supported by recent evidence. First, orientation selectivity is not affected by intracellu- lar blockade of inhibition (Nelson and others 1994). And second, the blockade of most cortical inputs to a simple cell (excitatory and inhibitory) does not affect the orien- tation selectivity of its synaptic potentials (Ferster and others 1996; Chung and Ferster 1998). It is still possible that orientation selectivity is modulated beyond the clas- sical receptive field by inhibitory inputs and horizontal connections. This interpretation could explain some strong cross-inhibitory effects observed when using full- field stimuli (e.g., Blakemore and Tobin 1972; Sillito and others 1995; Ringach and others 1997). Indeed, al- though long-range horizontal connections (both excita- tory and inhibitory) link cells with similar orientation preferences (e.g., Ts’o and others 1986; Dalva and others 1997), the axonal arbors are not totally restricted to a given orientation column (Kisvarday and others 1997) and local- ly may be even less specific (Malach and others 1993). Within layer 4, cortical inhibition is likely to play a major role in contrast adaptation (Carandini and Ferster 1997) and in generating subregion antagonism in simple cells (Ferster 1988; Hirsch and others 1998a). In a sim- ple cell, a light spot presented in an on-subregion gener- ates a strong response that is shut down when the spot also covers an adjacent off-subregion. This effect can be eas- ily explained by a push-pull mechanism—off-subregions receive excitatory input from cells that generate off- responses (push) and inhibitory inputs from cells that generate on-responses (pull). The push-pull model has received strong support from both extracellular and intracellular data (Palmer and Davis 1981; Tolhurst and Dean 1987; Ferster 1988; Hirsch and others 1998a). Recent results from Borg-Graham and others (1998) indicate, however, that on- and off-inhibition could be Fig. 7. Inhibitory connections. A, Cartoon of the connections randomly intermingled within the simple receptive field. made by three different types of inhibitory neurons on pyrami- dal cells. B, Two physiological types of inhibitory neurons. In the A possible explanation for Borg-Graham and others’ rat, fast-spiking cells and adapting interneurons receive input results is simply that they recorded from cells that lacked from different cortical layers (middle layers for fast-spiking cells, push-pull (most of these cells are outside layer 4; Hirsch deep layers for adapting interneurons; Dantzker and Callaway and others 1998a). It would be interesting to use Borg- 2000), and only fast-spiking cells receive input from the thala- mus (Gibson and others 1999). Moreover, electrical synapses Graham and others’ approach to measure the distribution link inhibitory cells of the same type (Gibson and others 1999). of inhibition within identified layer 4 cells. A push-pull mechanism is appealing for its simplicity and can be neurons show greater increments in firing rate for a given used to explain many properties of layer 4 simple cells increment of current than excitatory neurons (3 to 4 like orientation selectivity, subregion antagonism, and times greater increments; McCormick and others 1985). certain nonlinearities such as the invariance of orienta- The sensitivity of inhibitory networks is further tion tuning (Troyer and others 1998). increased by a very precise synchrony (± 1 ms) that was described in vivo for fast-spiking cells (Swadlow and oth- Inputs from Horizontal Connections ers 1998). This precise synchrony is probably generated by highly divergent thalamocortical inputs (Swadlow General Characteristics and Clustering and others 1998) and amplified by electrical coupling of Synaptic Terminals (Galarreta and Hestrin 1999; Gibson and others 1999). Intracortical inhibition should have an important role Cortical neurons also make short-range local connec- in shaping cortical response properties. After all, most tions within their own cortical layer. These connections excitatory responses are followed by disynaptic inhibi- are limited to a few hundred microns, they are frequent- tion. Previous pharmacological experiments suggested that ly reciprocal, and they can be quite strong. In the rat

452 THE NEUROSCIENTIST Neural Connections somatosensory cortex, a single layer 4→layer 4 connec- tion within a “barrel” is reciprocal in 30% of the cases and generates EPSPs of 1.55 ± 1.53 mV with 2 to 5 synaptic contacts (Egger and others 1999; Feldmeyer and Sakmann 2000). Similarly, connections within layer 5 cells generate EPSPs of 1.3 ± 1.1 mV amplitude with around 5 synaptic contacts mostly in the basal dendrites (Deuchars and others 1994; Markram and others 1997; Feldmeyer and Sakmann 2000). Connections within layer 4 are highly reliable (Tarczy-Hornoch and others 1998) and generate faster EPSPs than connections with- in layer 5, probably due to differences in the location of the synaptic contacts and the NMDA/AMPA receptor ratios (Deuchars and others 1994; Markram and others 1997; Feldmeyer and Sakmann 2000). In addition to the local connections, some neurons make long-range horizontal connections that can span several millimeters of distance within a single layer (Fig. 8a). A narrow lesion through all cortical layers can produce a horizontal degeneration of several millimeters. This degen- eration is largest (5–6 mm) when the lesion is restricted to layer 4B and smallest (2–3 mm) when the lesion is restricted to layer 4C (Szentagothai 1973). Similarly, injec- tions of HRP in V-1 generate a patchy projection within layers 2+3 that can span 8 mm2 (Rockland and Lund 1982). The patchy organization of long-distance connec- tions has been beautifully demonstrated in intracellular- ly labeled single cells (Gilbert and Wiesel 1979, 1983; Martin and Whitteridge 1984). Clusters of axonal arbors have an average periodicity of 1 mm and can be found in all cortical layers in more than half of the pyramidal and spiny stellate cells (Gilbert and Wiesel 1983). Fig. 8. Horizontal connections and hypothetical model for the circuitry of the primary visual cortex. Top, Cartoon representing Response Properties and Function: the lateral spread and cluster organization of horizontal con- nections in cat area 17. Horizontal connections are classified in Local Horizontal Connections local (left) and long-range (right). Only connections within layer 4 and layers 2+3 are represented. Bottom, Hypothetical model Local horizontal connections make contact with neigh- for the circuitry of the primary visual cortex. The central black boring neurons within a radius of a few hundred circle represents a cortical cell, and the arrows its synaptic microns. Since most neighboring neurons have similar inputs (synaptic strength is illustrated as arrow width; only a response properties (Hubel and Wiesel 1962; DeAngelis few arrows are shown for the sake of simplicity). The y-axis rep- and others 1999), local connections should link cells resents receptive field complexity, and the x-axis a similarity index between the receptive field properties of each input and with similar properties also. There seems to be an impor- the target. If every receptive field in the visual cortex could be tant exception to this rule. Neighboring neurons near mapped with the same level of precision, it should be possible pinwheel centers (layers 2+3) have different orientation to classify all receptive fields according to their complexity. (For preferences and can still be linked by local connections example, to map receptive fields in higher visual areas, we would need more complex stimulus arrangements than to map (e.g., Malach and others 1993). Therefore, the connec- geniculate receptive fields.) Moreover, it should be possible to tivity of local connections within the superficial layers obtain an index of receptive field similarity as we do when com- does not appear to show the specificity for orientation paring the receptive fields of simple cells and geniculate cells that is characteristic of feedforward vertical connections (Alonso and others 2001). If these data were available, we (Alonso and Martinez 1998; Martinez and Alonso 2001). would probably obtain a graph like the one represented in this figure. As illustrated in this hypothetical graph, feedforward Little is known about the role of local horizontal con- inputs are smaller in number, they are stronger, and they share nections in receptive field generation. Within layer 4, more response properties with the cortical target than feedback local connections have been proposed to serve as a cor- and horizontal inputs. tical amplifier for the incoming thalamic inputs (Douglas and others 1995; Somers and others 1995; cates that geniculate inputs are likely to be stronger than Feldmeyer and Sakmann 2000). Original versions of the intracortical inputs. First, thalamocortical synapses are “cortical amplifier” suggested that geniculate inputs larger, have more synaptic release sites, are more reli- were weak because they made only 5% to 25% of the able, and are located more proximally in the dendrites total excitatory synapses on cortical cells (for review, see than corticocortical synapses (Stratford and others 1996; Peters and Payne 1993). However, recent evidence indi- Gil and others 1999). Second, geniculate inputs have

Volume 8, Number 5, 2002 THE NEUROSCIENTIST 453 higher firing rates and are more precisely synchronized and Guillery 1998). In this classification scheme, feed- than the cortical excitatory inputs to layer 4 (Alonso and forward connections (both from LGN and from vertical others 1996; Alonso and Martinez 1998). And third, the inputs) would be the drivers of cortical activity, whereas inactivation of a relatively small group of geniculate horizontal and feedback connections would be the mod- inputs is enough to make a “tiny hole” in the receptive ulators. This organization could provide a basic “feed- field of a layer 4 cell even if most cortical inputs are still forward frame” that is flexible enough to be modulated active (Martinez and Alonso 2001; Figs. 3b,c). through horizontal and feedback connections by new Even if the geniculate inputs are strong, the idea of a stimulus arrangements and experience. cortical amplifier within layer 4 is still attractive. 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