The contribution of vertical and horizontal connections to the receptive field center and surround in V1

Neural Networks 17 (2004) 681–693 www.elsevier.com/locate/neunet

2004 Special Issue

The contribution of vertical and horizontal connections to the receptive field center and surround in V1q Heather J. Chisum, David Fitzpatrick* Department of Neurobiology, Duke University Medical Center, DUMC Box 3209, Durham, NC 27710, USA Received 4 May 2004; accepted 4 May 2004

Abstract Here we review the results of anatomical and physiological studies in tree shrew visual cortex which focus on the contribution of vertical and horizontal inputs to receptive field center and surround properties of layer 2/3 neurons. A fundamental feature of both sets of connections is the arrangement of axon arbors in a fashion that respects both the orientation preference and retinotopic displacement of the target site. As a result, layer 2/3 neurons receive convergent input from populations of layer 4 and other layer 2/3 neurons whose receptive fields are displaced along an axis in visual space that corresponds to their preferred orientation. Although, horizontal connections extend for greater distances across the cortical surface than vertical connections, the majority of these inputs link neurons with overlapping receptive fields, emphasizing that both feed-forward and recurrent circuits are likely to play a constructive role in generating properties (such as orientation selectivity) that define the receptive field center. Both within and beyond the dimensions of the receptive field center, the distribution of horizontal connections accords remarkably well with the magnitude and axial tuning of length summation effects. Taken together, these results suggest a continuum of functional properties that transcends the traditional designation of receptive field center and surround. By extension, we suggest that the perceptual effects of stimulus context may arise from stimulus interactions within the receptive field center as well as between center and surround. q 2004 Elsevier Ltd. All rights reserved. Keywords: Recurrent; Feed-forward; Cortical circuitry; Surround modulation; Area 17; Tree shrew; Visual cortex; Review

1. Introduction Primary visual cortex has served as a model system for exploring the functional organization of cortical circuits. In part, the focus on visual cortex reflects the clear emergence of fundamental receptive field properties such as orientation selectivity that are not present at antecedent levels (Hubel, 1982; Hubel & Wiesel, 1962, 1968, 1977). In addition, the activity of visual cortical neurons is influenced by the presentation of stimuli that fall far outside the classical receptive field, effects that are thought to be the substrate for a variety of perceptual phenomena including contour integration, scene segmentation, and filling in. This rich functional landscape is accompanied by an equally rich neural architecture: the highly structured arrangement of neurons into layers and columns, and distinct forms of connections (vertical, or feed-forward, and horizontal, q

This work was supported by National Eye Institute Grant EY06821. * Corresponding author. Tel.: þ 1-919-684-8510; fax: þ1-919-684-4431. E-mail address: [email protected] (D. Fitzpatrick). 0893-6080/$ - see front matter q 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.neunet.2004.05.002

or recurrent) that serve to transmit information between them (for reviews see, Angelucci & Bullier, 2003; Angelucci, Levitt, & Lund, 2002a; Fitzpatrick, 2000; Gilbert, 1992, 1993, 1998; Lund, Angelucci, & Bressloff, 2003; Tucker & Fitzpatrick, 2003). In this review, we focus on efforts to understand the relationships between these three levels of organization: architecture, response properties and perception. Our goal is to provide an account of the prevailing view of these relationships, and to consider recent evidence that both supports and challenges this view.

2. Receptive fields and cortical circuits In the initial characterization of cortical receptive fields with bars and edges, boundaries were established by charting the region of visual space that would evoke a spike discharge with an optimally oriented stimulus, a measure that has come to be known as the minimum discharge field or MDF (Barlow, Blakemore, & Pettigrew,

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1967; Bishop, Burke, & Davis, 1962; Hubel & Wiesel, 1962). However, it was apparent even in these early accounts that stimulation of regions beyond the MDF could often impact the vigor of the neuron’s response (Bishop, Coombs, & Henry, 1973; Blakemore & Tobin, 1972; Hubel & Wiesel, 1962, 1968; Jones, 1970; Maffei & Fiorentini, 1976; Sillito, 1977). In some cases, extension of a stimulus into regions beyond the MDF yielded a reduction in response (due to suppression or end-stopping) and in other cases an increase in response (due to facilitation or length summation). Thus, in its initial conception, the boundaries of the MDF were synonymous with the boundaries of the receptive field center, while regions beyond the MDF were viewed as the receptive field surround. This functional distinction between a central region of the receptive field that elicits spike discharge and a surrounding region that modulates the response to stimuli in the center naturally led to considerations of the cortical circuitry that mediates these effects. The identification of two types of cortical connections that exhibit properties consistent with center and surround offered a simple structure-function correlate (for a review, see Lund et al., 2003; Tucker & Fitzpatrick, 2003). Vertical connections that run perpendicular to the cortical surface and have limited horizontal spread seemed well suited to supply the inputs that define receptive field center properties and insure that neurons in the same column have similar response properties. In contrast, horizontal connections that run parallel to the cortical surface and extend for several millimeters across the cortical surface seemed well suited for supplying modulatory inputs from more distant regions of visual space. In the following sections, we place the distinction between vertical and horizontal connections in the context of layer 2/3 pyramidal neurons, neurons that serve as the major source of output to neurons in extrastriate areas. The principle source of vertical inputs to these neurons (and the one that we focus on here) arises from neurons in cortical layer 4 (Fig. 1). Most of the inputs from the LGN terminate in layer 4; thus the pathway from layers 4 to 2/3 is the major route by which the activity of retinal neurons is transmitted to layer 2/3 neurons. The pathway between layers 4 and 2/3 can be characterized as strictly feed-forward in its actions: there is little sign that neurons in layer 2/3 (at least excitatory projection neurons) have axons that synapse with layer 4 neurons. As would be expected most of the projections from layers 4 to 2/3 originate from spiny stellate neurons that utilize glutamate as their transmitter and exert an excitatory influence on their target neurons, while a smaller fraction of these feed-forward inputs arise from smooth dendritic GABAergic neurons (Anderson, Douglas, Martin, & Nelson, 1994; Lund, Yoshioka, & Levitt, 1994; Somogyi, Cowey, Kisvarday, Freund, & Szentagothai, 1983). The bulk of the horizontal connections within layer 2/3 arise from pyramidal neurons, and most of our attention

Fig. 1. Elements of the cortical circuit in primary visual cortex. A Nissl stained histological section through primary visual cortex shows the cortical lamina. The schematic overlay depicts the flow of visual information through primary feed-forward and recurrent pathways to a layer 2/3 neuron (central, yellow cell). The feed-forward pathway travels from the retina, to the lateral geniculate nucleus in the thalamus (LGN), to cortical layer 4 (red cell), and on to layer 2/3. This pathway has often been credited with establishing the response properties of the receptive field center (depicted in red above the cortical section). Recurrent, or horizontal, connections between layer 2/3 neurons (flanking yellow cells) have been thought of as the source for the modulatory effects of the receptive field surround (yellow annulus above).

will be directed to this population of neurons (Bosking, Zhang, Schofield, & Fitzpatrick, 1997; Gilbert & Wiesel, 1979, 1983; Keller & Asanuma, 1993; McGuire, Gilbert, Rivlin, & Wiesel, 1991; Rockland & Lund, 1982). Unlike the inputs from layer 4, horizontal connections are strongly recurrent, forming a network of reciprocal connections between individual participants. While the majority of the connections are excitatory, it is important to emphasize that there is at least one class of smooth dendritic GABAergic neuron (basket cell) that contributes to long-range horizontal connections in layer 2/3 (Kisvarday & Eysel, 1993; Martin, Somogyi, & Whitteridge, 1983). In addition, GABAergic neurons in layer 2/3 with local axonal arbors are likely to receive inputs from both layer 4 inputs as well as from the horizontal network in layer 2/3 (Anderson et al., 1994; Keller & Asanuma, 1993; Kisvarday, Martin, Freund, Magloczky, Whitteridge, & Somogyi, 1986; McGuire et al., 1991).

3. Properties of layer 4 inputs are consistent with construction of receptive field center properties The strength of synaptic input clearly indicates a powerful role for layer 4 inputs in establishing responses to stimuli presented to the receptive field center of layer 2/3 neurons. The feed-forward projection from layers 4 to 2/3

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provides the most powerful source of input to layer 2/3. In vitro, experiments have shown that layer 4 inputs reliably evoke EPSPs in layer 2/3 (Feldmeyer, Lubke, Silver, & Sakmann, 2002) and that these EPSPs are larger and less variable than those evoked by inputs from other layer 2/3 neurons (Hirsch & Gilbert, 1991; Yoshimura, Sato, Imamura, & Watanabe, 2000). Furthermore, stimulation of layer 4 inputs is more likely to drive a neuron to fire action potentials than stimulation of long-range horizontal connections (Hirsch & Gilbert, 1991). While much of the work evaluating the strength of layer 4 inputs has been performed in slices, these results are consistent with an in vivo examination of population activity in layer 2/3 using intrinsic signal optical imaging in tree shrews. Even when using stimuli designed to elicit high levels of activity in the horizontal network, horizontal connections were insufficient to evoke detectable signal in layer 2/3 neurons unless accompanied by activation of layer 4 inputs (Chisum, Mooser, & Fitzpatrick, 2003). Taken together, these results suggest that activation of feed-forward inputs from layer 4 is required for the visually driven responses of layer 2/3 neurons. But does specificity in the arrangement of layer 4 inputs contribute to the selective responses that layer 2/3 neurons exhibit for visual stimuli? Most of the work directed at understanding the mechanisms responsible for generating cortical response properties has been done in the cat, where the properties that distinguish the responses of cortical neurons from neurons in the LGN (for example, tuning for orientation of edges) are exhibited by layer 4 neurons. Thus, in this species, specificity for orientation is generated in layer 4 and the job of layer 4 axonal connections is to transmit orientation tuned responses to layer 2/3 neurons, rather than to generate orientation tuning de novo within layer 2/3. This is not the case in all species, however. In the original descriptions of responses in layer 4 of monkey striate cortex, Hubel and Wiesel (Hubel & Wiesel, 1968, 1977) noted that neurons in layer 4C were poorly tuned for orientation, an observation that has been confirmed for neurons in the parvocellular-recipient region of layer 4 (4CB) in several other studies (Blasdel and Fitzpatrick, 1984; Bullier and Henry, 1980; but also see Ringach et al., 2002). Similarly, neurons in layer 4 of tree shrew striate cortex are poorly tuned for orientation (Chisum et al., 2003; Humphrey & Norton, 1980; Humphrey, Skeen, & Norton, 1980). Since most of the neurons in layer 2/3 of both monkey and tree shrew are well tuned for orientation, the intracortical projection from layers 4 to 2/3 could play an important role in generating orientation tuned responses. Recent results from studies in the tree shrew suggest that this is the case (Mooser, Bosking, & Fitzpatrick, in press). To explain the emergence of orientation tuning in cat layer 4 neurons, Hubel and Wiesel proposed a simple mechanism: layer 4 neurons receive input from multiple LGN cells whose receptive fields are displaced along an axis in visual space, creating an elongated receptive field with an

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axis of preferred orientation (Hubel & Wiesel, 1962). Evidence for such a selective convergence of LGN inputs in layer 4 has been found in the cat and ferret (Alonso, Usrey, & Reid, 2001; Chapman, Zahs, & Stryker, 1991; Chung & Ferster, 1998; Ferster, Chung, & Wheat, 1996; Lampl, Anderson, Gillespie, & Ferster, 2001; Reid & Alonso, 1995). Experiments in the tree shrew were designed to determine whether a similar convergence of layer 4 inputs contributes to the orientation tuning of layer 2/3 neurons. Unlike the experiments in the cat and ferret, however, anatomical tracing techniques were used to evaluate this issue. The results show that the Hubel – Wiesel model is applicable to the generation of orientation tuning via intracortical circuits, and they provide evidence for the source of the anisotropic sampling bias that lies at the heart of the model: specificity in the arrangement of layer 4 axon arbors (Mooser et al., submitted). Mooser and colleagues placed small extracellular injections of the neural tracer biocytin into cortical layer 4 allowing the terminal distribution of labeled axons and boutons in layer 2/3 to be reconstructed and compared with maps of visual space and orientation preference visualized with optical imaging techniques (Fig. 2A and B). If the axon arbors of layer 4 neurons contribute to the orientation tuning of layer 2/3 neurons, the Hubel –Wiesel model makes a specific prediction about the distribution of labeled boutons. For target sites in layer 2/3 whose receptive field centers are displaced from those in layer 4, an orientation specific bias will be established only if the orientation preference of the target site matches the axis of receptive field displacement. A quantitative analysis of the distribution of layer 4 boutons revealed that this is indeed the case: layer 4 neurons preferentially target layer 2/3 sites whose orientation preference matches the axis of displacement from the center of the injection site (Fig. 2B and C). The number of bouton target sites whose orientation preference matched the axis of displacement was more than three times greater than those whose orientation preference was orthogonal to the axis of displacement. Moreover, the same data can be used to estimate the spatial profile of the layer 4 inputs that contribute to the average receptive field of a neuron in layer 2/3 (Fig. 2D –G). The density of layer 4 inputs is greatest near the center of the layer 2/3 cell receptive field and falls with distance along both the preferred and orthogonal axes. However, the drop in density is more gradual along the axis of preferred orientation, resulting in an elongation of layer 4 inputs. On average, layer 4 inputs extend 1.6 times farther along the preferred axis than along the orthogonal axis. These results provide a clear demonstration of how the feed-forward inputs from layer 4 could contribute to the orientation selective responses of layer 2/3 neurons. Of course, this assumes that the dendritic processes of layer 2/3 neurons sample their layer 4 inputs in a fashion that preserves the microtopography within the layer 4 axonal

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Fig. 2. Specificity and extent of the projection from layers 4 to 2/3. (A) Three examples of the projection of a small group of layer 4 neurons (cell bodies plotted in red) to layer 2/3 (boutons plotted in black). (B) Plot of bouton density for one example case (the upper most case in part A) with the map of orientation preference (obtained by intrinsic signal optical imaging) overlayed on the plot. Areas with the highest density of boutons are brightest. Preferred orientation is coded by color; key is at bottom. The plot has been oriented according to the cortical map of visual space, so that upper visual space is up, lower visual space is down, etc. Dashed line highlights the magenta area—orientation preference of 1358—along the 1358 axis in visual space. There are also yellow areas— orientation preference of 458—along the 458 axis. Scale bar is 500 mm. (C) A histogram plots the match between the axis of displacement of the target from the injection site and orientation preference of the target. The large number of boutons for which the axis of displacement and target orientation match, stand as anatomic evidence of the selective convergence of non-oriented inputs onto orientation tuned neurons. Error bars are SEM. (D) A sample of 100 labeled boutons (white squares) selected at random from a single case (not the same case as B) shown in cortical coordinates on the map of orientation preference. The location of the injection site is shown in red and lines depict the axes of the map of visual space (vertical from upper left to lower right). Scale bar is 500 mm. (E) The receptive fields (RFs) of the layer 2/3 sites contacted by the boutons in D (blue ellipses) shown relative to the RF of a cell at the injection site (red circle). (F) The same set of 100 inputs now shown in layer 2/3 receptive field coordinates. The relationship of each target (blue RFs) to its origin (red RF) has been preserved, while the target RFs were aligned. Thus the divergent projection of one layer 4 site to many layer 2/3 sites has been transformed into the convergent projection of many layer 4 sites to one layer 2/3 site, allowing the prediction of the functional organization of the layer 4 input to layer 2/3 shown in G. (G) Average RF density plot from six cases. The density of layer 4 input (darker red indicates stronger input) to a layer 2/3 cell RF (blue ellipse) demonstrates a strong contribution at the center of the RF with an anisotropy that aligns with the elongation of the RF. Figures adapted from Mooser et al. (in press).

plexus. One simple way in which the microtopography might be maintained is if the layer 4 inputs terminate primarily on the proximal portion of the dendrites of layer 2/3 neurons. While the site of layer 4 terminations in visual cortex remains to be determined, results in barrel cortex are consistent with this idea (Feldmeyer et al., 2002). Also, there is precedent for visual feed-forward pathways to preferentially target the proximal portion of the dendritic field; such is the case for the inputs from the LGN to neurons in layer 4 of cat visual cortex (Ahmed, Anderson, Martin, & Nelson, 1997; Freund, Martin, Somogyi, & Whitteridge, 1985).

4. Are layer 4 inputs sufficient to explain the receptive field properties of layer 2/3 neurons? Despite the strength of the feed-forward inputs and the evidence that they are arranged in a fashion that could contribute to the orientation tuning of layer 2/3 neurons, more detailed comparisons of the anatomy of feed-forward inputs with the response properties of layer 2/3 neurons suggest that feed-forward inputs, by themselves, are insufficient to fully account for the receptive field properties of layer 2/3 neurons. For example, the average aspect ratio of a layer 2/3 cell receptive field (length along

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the preferred axis/width along the orthogonal axis) is 2.3:1 (Chisum et al., 2003), significantly greater than the 1.6:1 ratio supplied by the arrangement of layer 4 inputs. Likewise, the full-width at half-height of the average orientation tuning curve for layer 2/3 neurons is 438 (Chisum et al., 2003) a value that is substantially less than that predicted from the axis-dependent orientation tuning of the bouton distribution (668) (Mooser et al., in press). Furthermore, the average spike discharge rate to orthogonally oriented stimuli is roughly one-tenth that to the preferred stimuli (Chisum et al., 2003), yet connections from sites that are arrayed orthogonal to the preferred orientation account for roughly one third of the inputs from layer 4. Spike-threshold non-linearities may at least partially account for these discrepancies in orientation tuning. Subthreshold responses to non-preferred stimuli can often be significant even when such stimuli elicit little or no change in spike rate (Carandini & Ferster, 2000). Also GABAergic inhibitory inputs arising either within layer 2/3 or within layer 4 could contribute to reducing the response to orthogonal stimuli. If a significant number of the bouton target sites that do not adhere to the orientation specificaxial bias originate from GABAergic neurons, or reflect excitatory inputs to layer 2/3 GABAergic neurons, these connections could serve to strengthen the orientation tuning of layer 2/3 neurons by reducing the responses to nonpreferred orientations. But, as we consider in the next sections, the arrangement of horizontal connections within layer 2/3 suggests that they play an important role not only in surround modulation, but in shaping the properties that define the receptive field center including receptive field aspect ratio and orientation tuning.

5. Horizontal connections and surround modulation The view that long range horizontal connections play a role in establishing receptive field surround effects rests largely on their extent: horizontal connections extend for distances across the cortical surface that allows them to link neurons with non-overlapping MDFs—exactly what is required to explain modulatory effects from regions of visual space that do not elicit spike discharges (Bosking et al., 1997; Gilbert & Wiesel, 1983, 1989; Rockland & Lund, 1982; Rockland, Lund, & Humphrey, 1982). In addition, these connections terminate in a patchy fashion, targeting regions of the cortex with similar orientation preference. At a qualitative level, these properties make horizontal connections well suited for a variety of perceptual effects including contour integration (Angelucci et al., 2002b; Gilbert, Das, Ito, Kapadia, & Westheimer, 1996; Kapadia, Ito, Gilbert, & Westheimer, 1995; Stettler, Das, Bennett, & Gilbert, 2002) and the extraction of texture and shading flow (Ben-Shahar, Huggins, Izo, & Zucker, 2003). Recent efforts to provide a more quantitative comparison between response properties and the extent of horizontal

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connections have focused on length or size tuning: changes in the response of neurons to different lengths of an appropriately oriented line or grating stimulus centered on the neuron’s receptive field. Increases in the diameter of a grating stimulus centered on a neuron’s receptive field are accompanied by increases in discharge rate that reach a maximum and then plateau or decrease with continued increases in stimulus length (Angelucci et al., 2002b; Bair, Cavanaugh, & Movshon, 2003; Chisum et al., 2003; DeAngelis, Freeman, & Ohzawa, 1992, 1994; Levitt & Lund, 1997, 2002; Walker, Ohzawa, & Freeman, 2000). The nature of this curve depends on stimulus contrast: at high contrast, the summation peaks at relatively small stimulus sizes, while at low contrast, responses continue to augment for sizes that can be two to three times that found for high contrast stimuli (Angelucci et al., 2002b; Cavanaugh, Bair, & Movshon, 2002a; Levitt & Lund, 2002; Sceniak, Ringach, Hawken, & Shapley, 1999). Studies in macaque V1 show that the average size of the summation field measured with low contrast stimuli accords well with the average extent of horizontal connections in this species (Angelucci et al., 2002b; Cavanaugh et al., 2002a; Levitt & Lund, 2002). It is worth pointing out that suppressive effects could often be found for regions beyond the low contrast summation zone. Since, these effects occur at distances that exceed the extent of horizontal connections, feedback connections from extrastriate areas are a likely source (Angelucci et al., 2002b; Cavanaugh et al., 2002a; Levitt & Lund, 2002). The organization of horizontal connections in the tree shrew presented a unique opportunity for comparing the arrangement of horizontal connections with the response properties of layer 2/3 neurons. Horizontal connections in layer 2/3 of the tree shrew not only target sites that have similar preferred orientation (as in other species), they also show a strong preference for terminating along the axis of preferred orientation in the map of visual space. Small injections of biocytin into cortical layer 2/3 produce labeled axons that extend for a longer distance and give rise to a greater number of boutons along the axis of preferred orientation in the map of visual space (Bosking et al., 1997). The average extent of horizontal connections along the preferred axis matches remarkably well with the distance over which layer 2/3 neurons summate to an increasingly long bar of the preferred orientation (Fig. 3) (Chisum et al., 2003). On average the stimulus length required to achieve 90% of maximal summation was 19.98. This distance corresponds to 3.9 mm on the cortical surface, a length which, on average, encompasses 95% of horizontal connection sites along the preferred axis (Bosking et al., 1997; Chisum et al., 2003). If horizontal connections are responsible for these length summation effects, then the effects should exhibit tuning for the axial position of the stimuli in visual space (the effects should be much greater along the axis of preferred orientation than along the orthogonal axis) and they should

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Fig. 3. The correspondence between horizontal connections and length summation in layer 2/3 neurons. (A) A plot of labeled boutons within layer 2/3 of area V1 resulting from a biocytin injection into a site with an orientation preference of 408 (adapted from Bosking et al., 1997). The dorsal surface of V1 is outlined, with the caudal pole to the left, medial edge down, and V1/V2 border to the right. The axes of preferred (408) orientation is indicated with a gray dashed line, both in the icon of visual space to the right and on the cortical surface. Solid gray lines show the areas over which boutons were counted (^308 from the preferred axis). Scale bar, 500 mm or 2.558 of visual space. (B) Cumulative bouton distribution (gray line; average for 10 cases) plotted with the average length tuning curve (black line) obtained with extracellular recordings from layer 2/3 neurons ðn ¼ 37Þ: Error bars are 1 SD. Adapted from Chisum et al. (2003) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.).

also be tuned to the orientation of the stimulus. Tuning of responses to the axial position and the orientation of the surround stimulation was tested using rows of Gabor stimuli extending far into the receptive field surround (Chisum et al., 2003). All neurons showed facilitated responses to rows of collinear stimuli (i.e. when stimulus axis and Gabor orientation was the same as the neuron’s preferred orientation), with an average increase in response of 154% (Fig. 4A). Response rate decreased systematically as the axis of the Gabor array deviated from the neuron’s preferred orientation defining an axial tuning curve that peaked on the axis that matched the neurons preferred orientation and had a full width at half height of 38.48 (Fig. 4B). This physiological tuning curve is remarkably similar to the tuning curve constructed from the axial distribution of boutons in layer 2/3 following small injections of biocytin (FWHH ¼ 42.98 Fig. 4C). Furthermore, when the orientation of the Gabor elements in the surround was changed to the non-preferred orientation, no facilitation was observed for any axis, demonstrating that surround modulation, like horizontal connections, is tuned for axis as well as orientation (Fig. 4D).

6. Horizontal connections also make a significant contribution to receptive field center properties While the extent, axial distribution and orientation specificity of horizontal connections makes them a likely source of receptive field surround effects, there is no reason to exclude them from contributing to responses evoked by stimulation of the receptive field center. Indeed, analysis of the numbers of horizontal connections as a function of the distance from the injection site in the tree shrew suggests that horizontal connections are likely to exert a stronger influence over events that occur within the dimensions of

the receptive field center than in the surround (Chisum et al., 2003). Along both the collinear and orthogonal axes, for example, 90– 95% of horizontal connections link neurons with at least partially overlapping MDFs, leaving less than 10% of connections projecting to sites with non-overlapping MDFs. Furthermore, for 70 –75% of horizontal connections the area of overlap includes not just the weaker edges of the receptive field, but includes the very centers of the MDFs. Thus, one would expect the network of horizontal connections to be significantly activated by a stimulus that just fills the average MDF of a layer 2/3 neuron rather than only being activated by stimuli outside of the receptive field. In addition to the fact that these connections are most numerous between neurons that have overlapping receptive fields, the specificity in the arrangement of connections at these distances could contribute to properties such as orientation tuning. Like the feed-forward projection, the horizontal network provides densest input from sources that lie along the axis of the preferred orientation and this axial bias is present at cortical distances that correspond to the dimensions of the MDF. For example, the density of inputs from sites along the axis of preferred orientation is about twice that along the orthogonal axis at a distance of 0.5 mm from the injection site, and nearly five times greater at a distance of 1 mm (Chisum et al., 2003). This bias may serve both to sharpen orientation tuning and to increase the aspect ratio of the MDF, features that (as noted previously) cannot be accounted for solely by the arrangement of feed-forward inputs from layer 4. Thus, it would appear that both feedforward and recurrent inputs have the requisite specificity to contribute an orientation selective bias to the responses of layer 2/3 neurons. It is worth emphasizing that the axial bias in the organization of horizontal inputs exists at a scale that is considerably finer than the dimensions of the MDF. It has often been assumed that the selective convergence of axially

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Fig. 4. Collinear facilitation in layer 2/3 neurons reflects the axis and orientation specificity of horizontal connections. (A) Response to a collinear stimulus configuration (left) shows facilitation relative to the response to a single Gabor element for all sites (responses increased between 30 and 600%). Responses to non-collinear conditions (one of which is shown at right) failed to produce consistent change from the single Gabor condition. Results for individual recording sites are arranged according to strength of collinear facilitation. (B) Axis tuning curves in response to iso-oriented Gabor arrays arranged along different axes for all recording sites (n ¼ 35; thin gray lines), normalized to each site’s preferred orientation, are plotted with the Gaussian fit (black curve) of the median response (dots). The straight black line shows the average response to a single Gabor element; dashed lines are ^1 SD. (C) Axis tuning curves for layer 2/3 horizontal connections; 10 cases are shown is gray with median (dots) and Gaussian fit (black). (D) Physiological axis tuning curves using orthogonal-topreferred surround Gabors (example stimuli at left). Individual recording sites ðn ¼ 26Þ are plotted in gray, with median (dots) and single Gabor response ^1 SD (solid and dashed lines). Adapted from Chisum et al. (2003) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.).

aligned inputs form an elongated receptive field (or elongated ON/OFF subfields), and it is that elongation of the field that creates the tuning for orientation. A finer bias seems necessary to explain the fact that orientation specific responses can be elicited by stimuli that occupy only a fraction of the MDF (Chisum et al., 2003). A difference in the density of horizontal inputs that arise along the axis of preferred orientation vs. the orthogonal axis is present at distances on the order of 200 mm from the center of the injection site—a cortical distance that corresponds to 18 of visual space, roughly an order of magnitude smaller than the long axis of the average layer 2/3 cell receptive field (Chisum

et al., 2003). Similarly for the feed-forward inputs (layers 4 to 2/3), the density is three times greater along the preferred axis than the orthogonal at a distance of 0.5 mm from the injection site, and differences in density are detectible at much smaller distances as well (Mooser et al., submitted).

7. Center vs. surround: distinct processing regions or a continuum? These anatomic considerations suggest a different interpretation of the relationship between vertical

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and horizontal connections and the receptive field center and surround: both vertical and horizontal connections are likely to contribute substantially to the properties of the receptive field center, while horizontal connections (as well as connections from extrastriate cortex) contribute to the properties of the surround. The continuity of horizontal connections throughout the receptive field suggests a corresponding continuity of functional properties. This view seems difficult to reconcile with much of the work on center-surround interactions, which treats these regions as substantially different in their fundamental properties. The receptive field center is commonly regarded as a homogenous entity, the region in which the presentation of additional inputs causes incremental changes in response rate. In fact, a common approach to defining the receptive field center is to use an areal summation measure: as the diameter of a grating stimulus is increased, the location of the peak or plateau in response rate is defined as the boundary of the receptive field center (Angelucci et al., 2002b; Bair et al., 2003; Levitt & Lund, 2002; Sceniak et al., 1999). Attention is then directed to the effects of stimulating the region that lies beyond this summation zone, to probe for potential modulatory effects. Why should efforts to understand the impact of context be so heavily focused on interactions between surround and center stimulation, rather than giving equal weight to interactions that occur within the center or between stimuli that span the center/surround border? In part this may reflect the fact that the center of the receptive fields of cells in V1 of primate (particularly in foveal and parafoveal representation) are generally small, affording only a limited range of stimulus interactions. However, this is not true for more eccentric regions of V1, and for V1 in species that lack a fovea and have correspondingly larger receptive fields in the central visual field representation. An equally likely reason is the seductive analogy between the spatial relation of the receptive field center and surround and perceptual effects that can be induced by placing a central test stimulus in different surround conditions. Indeed, perceptual effects elicited by different surround conditions are often viewed as a consequence of receptive field center-surround interactions. While this is an appealing way to conceptualize the problem, it seems unlikely that perceptual judgments are made solely on the basis of the activity of neurons whose receptive field centers and surrounds are in ideal alignment with the stimulus configuration. Rather stimulus interactions at all positions within the receptive field center and surround are likely to be significant for perception, and potential contributors to perceptual context effects. Moreover, as we consider below, what is known about the effects of interactions within the receptive field center suggests that they can be as strong as or stronger than center-surround interactions and share at least some of the same properties. As mentioned previously, the effects of surround stimulation can be facilitatory or suppressive depending on the type of stimulus used and the contrast of that

stimulus. A number of studies have examined the effects of surround stimulation using a grating annulus surrounding an optimized central bar or grating patch. At low contrast, the effects elicited by such a stimulus are predominately facilitatory, while at high contrast they are predominantly suppressive (Angelucci et al., 2002b; Kapadia, Westheimer, & Gilbert, 1999; Levitt & Lund, 1997, 2002; Sceniak et al., 1999). Regardless of the sign of the effect, surround interactions are generally well tuned to the orientation of the stimulus—the strongest effects are in response to a surround stimulus that matches the cell’s preferred orientation (Bair et al., 2003; Blakemore & Tobin, 1972; Fries, Albus, & Creutzfeldt, 1977; Gilbert & Wiesel, 1990; Nelson & Frost, 1978). Although, it is common to explore surround properties using annuli that provide homogenous stimulation to the entire region, experiments using spatially restricted stimuli reveal that surround effects often originate from discrete regions of visual space (Cavanaugh, Bair, & Movshon, 2002b; Chisum , 2003; Chisum et al., 2003; Das & Gilbert, 1999; DeAngelis et al., 1994; Kapadia et al., 1999; Kapadia, Westheimer, & Gilbert, 2000; Nelson & Frost, 1985; Polat & Sagi, 1993; Walker, Ohzawa, & Freeman, 1999). We have already discussed the results from the tree shrew where facilitatory effects are robust along the long axis of the receptive field and rare along the orthogonal axis (Chisum et al., 2003). Similar results have been described in the monkey (Kapadia et al., 1995, 2000; but also see, Angelucci et al., 2002a,b; Sceniak et al., 1999) and the cat (Crook, Engelmann, & Lowel, 2002; Polat, Mizobe, Pettet, Kasamatsu, & Norcia, 1998) using low contrast or sparse stimulation. Other work in the cat using high contrast grating patches as stimuli has demonstrated a considerable variability in the location of surround suppressive zones (DeAngelis et al., 1994; Walker et al., 1999). Suppression can occur along the sides either in combination with or without end suppression, although there is a bias for suppressive zones to occur along the long ends of the receptive field. An overview of the literature emphasizes that surround effects are complex, stimulus dependent, and vary to some degree from neuron to neuron. Surround regions appear to possess specific tuning properties (e.g. spatial and orientation tuning) relevant for understanding stimulus interactions. Although, there is much less information about stimulus interactions within the receptive field center, the available evidence suggests that the effects of such interactions are equal in magnitude to those induced by stimulation of the surround; they can be either facilitatory or inhibitory, and the magnitude and sign of the effect also varies with position within the receptive field center. For example, the facilitatory effects induced by increases in line length of stimuli described previously are continuous across the MDF and into the surround or summation field—consistent with the continuous distribution of horizontal connections (Fig. 3) (Angelucci et al., 2002b; Chisum et al., 2003; DeAngelis

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et al., 1994; Levitt and Lund, 2002; Sceniak et al., 1999). In addition, the presentation of discrete stimuli within the receptive field center can either augment or reduce spike discharge rate depending on the orientation and position of the stimulus (Henry, Goodwin, & Bishop, 1978; Jones, 1970). As described previously, in tree shrew V1, facilitatory effects dominate interactions within the receptive field (and surround) along the axis of preferred orientation. However, the most common effect of presenting pairs of parallel bars at the preferred orientation within the MDF is suppression (Chisum & Fitzpatrick, submitted). These discrete interactions revealed restricted, asymmetric regions of facilitation and suppression that could be located anywhere within the MDF or surround, or spanning the MDF border (Fig. 5A). Similar to surround effects measured with discrete stimuli, there is considerable variability in center

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interaction effects precluding identification of a stereotypical interaction profile. However, suppression was the most common interaction near the center of the MDF with very few instances of facilitation (response greater than the response to either stimulus alone) within the MDF. The incidence of suppression declined continuously from center to surround, while the frequency of facilitatory interactions remained steady and low. Comparison of the frequencies of facilitatory and suppressive interactions with the distributions of feedforward and horizontal connections along the orthogonal axis revealed no single, clear correlation between interaction effects and either anatomic input (Fig. 5B). Rather, the lowest frequencies of facilitation and highest frequencies of suppression were coincident with the presence of feed-forward connections. Elevated rates of suppression fell off across the same distance as horizontal connections,

Fig. 5. Stimulus interactions with parallel bars within and outside the MDF. (A) Examples of interaction profiles for three neurons show the variability of interaction responses. Position tuning curves (gray dashed lines) show the ON response to a single bar stimulus at each position, providing a profile of the MDF. The prediction for the interaction response (gray) was set as the greater of the responses to the central position (position 0) or the response to the test position (nonzero positions) in a trial-by-trial fashion. Actual interaction responses to a bar presented at each test position in combination with a bar at the central position were plotted in black. Filled symbols indicate a significant difference between prediction and response (t-test, p , 0:05) for that position. Top, note suppression near the center of the MDF. Middle, strong suppression outside the MDF. Bottom, facilitation on the left flank of the MDF and suppression within the MDF. Error bars are SEM. (B) The frequency of suppressive (solid black line) and facilitatory (solid gray line) interactions was plotted over distance and juxtaposed with the distributions of feed-forward (dashed gray line) and horizontal connections (dashed black line) over distance. Adapted from Chisum and Fitzpatrick (submitted) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.).

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indicating a potential role in mediating this response property. However, the frequency of both suppression and facilitation plateau in the surround while horizontal connections continue to diminish. This suggests that another source of inputs, perhaps feedback from extrastriate cortex, might contribute to these effects. Recent results from studies in monkey visual cortex also provide evidence consistent with a role for feedback from extrastriate cortex as a source for long distance surround effects (Angelucci & Bullier, 2003; Angelucci et al., 2002b; Bair et al., 2003; Cavanaugh et al., 2002a,b; Levitt & Lund, 2002). There is one type of stimulus interaction within the receptive field center that has received considerable attention and that seems quite distinct from the effects that are seen with stimulation of the surround: cross-orientation suppression. The superimposition of a grating of the optimal orientation and a grating of a non-preferred orientation in the receptive field center will often act to suppress the response to the preferred stimulus (Bonds, 1989; Crook, Kisvarday, & Eysel, 1998; DeAngelis et al., 1992; Endo, Kaas, Jain, Smith, & Chino, 2000; Freeman, Durand, Kiper, & Carandini, 2002). It has been suggested that inhibition of non-preferred orientations by local cortical inhibition (particularly by basket cells) may serve to enhance orientation tuning as well as drive this effect (Crook et al., 1998; Eysel, Crook, & Machemer, 1990; Kisvarday & Eysel, 1993). While an enhancement of tuning may be the outcome, neither the physiological suppression nor the projections of the local neurons are preferentially tuned for the orthogonal orientation. ‘Cross-orientation’ suppression can actually be achieved by the addition of a grating of any orientation (DeAngelis et al., 1992), and local inhibitory projections have been shown to preferentially target neurons of like orientation preference, similar to, although with broader tuning than, excitatory horizontal connections (Buzas, Eysel, Adorjan, & Kisvarday, 2001; Dalva, Weliky, & Katz, 1997; Kisvarday, Toth, Rausch, & Eysel, 1997; Roerig & Chen, 2002). Indeed, recent results question whether ‘cross-orientation’ suppression is dependent on cortical circuits, showing that the effect operates over different ranges of spatial and temporal frequency than cortical receptive fields (Freeman et al., 2002), and suggesting that it may reflect stimulus induced suppression of LGN synapses in cortical layer 4 (Carandini, Heeger, & Senn, 2002). Regardless of the mechanism, it seems unlikely that such broad suppressive effects would be limited to interactions that occur in the receptive field center. Superimposing a second grating stimulus in the receptive field surround should reduce the response of the neurons that contribute these effects, much the same as it reduces the center response. Taken together these observations emphasize that stimulus interactions, whether they occur between center and surround or within the center, can have powerful effects on the responses of V1 neurons. Indeed there are considerable similarities in the nature of stimulus

interactions across receptive field boundaries; such a continuity of response properties may be the manifestation of the continuity in the underlying pattern of connectivity.

8. Summary and conclusion The pioneering work of Hubel and Wiesel (1977) set the stage for much of our current thinking about structurefunction relationships in primary visual cortex. The demonstration of an exquisite columnar arrangement of neurons with similar response properties, the systematic shift in response properties across the cortical surface, and the demonstration of strong radial connections with little lateral spread provided convergent evidence that receptive field center properties were constructed within the column. The demonstration some years later of a system of horizontal connections within layer 2/3 could easily be accommodated within this framework by assuming these connections served a different function—receptive field surround effects. The results reviewed here suggest a further refinement, one that acknowledges the extent of cortical surface area that is activated by stimuli that are presented to the receptive field center, and the correspondence between this area and the bulk of connections established by horizontal connections. These considerations suggest that recurrent connections play a significant role in shaping the receptive field center properties of layer 2/3 neurons, a view that receives support from other lines of evidence, both experimental and computational (Cavanaugh et al., 2002a,b; Douglas, Koch, Mahowald, Martin, & Suarez, 1995; Grossberg & Olson, 1998; McLaughlin, McLaughlin, Shapley, & Shelley, 2003; Ringach, Hawken, & Shapley, 1997; Ross, Grossberg, & Mingolla, 2000; Somers et al., 1998). Moreover, the continuity of horizontal connections throughout the receptive field center and surround suggests a functional unity that is often obscured by the use of operational definitions that depend on spike threshold. As has been noted previously, the receptive field center encompasses the tip of the iceberg of neuronal sensitivity (Bringuier, Chavane, Glaeser, & Fregnac, 1999); it seems likely that processes serving center/surround interactions are in fact present and capable of mediating stimulus interactions within the receptive field center as well.

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