INTRODUCTION

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION REFERENCES

A number of studies have identified suppressive influences that reduce the responses of neurons in primate V1 when areas of visual space surrounding the classical receptive field are stimulated (Born and Tootell 1991; Kapadia et al. 1999; Knierim and Van Essen 1992; Nothdurft et al. 1999; Sceniak et al. 1999; Sillito et al. 1995). Some have reported these surround influences to be restricted to cells in the upper layers of V1 only (Born and Tootell 1991), although a recent study of the effect of contrast on spatial summation in V1 neurons (Sceniak et al. 1999) would suggest that common mechanisms may apply through all cortical layers. Indeed this latter study suggests that surround effects can be explained in terms of a difference of Gaussians model with overlapping Gaussians for the inhibitory and excitatory fields centered on the same point. In this sense, the mechanism underlying surround suppression would be an integrated component of the classical receptive field, and terms such as center and surround mechanisms become rather misleading. However, it seems likely that several mechanisms would have to underlie both the excitatory and the inhibitory Gaussians, and their interaction may not be linear and may depend on the spatial organization of the stimulus. For example, a layer 4 cell would receive direct thalamic input and horizontally linked intracortical excitatory connections together with inputs from cells in the underlying layer 6 (Ahmed et al. 1994; Callaway 1998; Ferster and Lindstrom 1985a,b; Peters et al. 1994). Present evidence suggests the synaptic efficacy of these different components of the excitatory input could be quite different (Ferster and Lindstrom 1985a,b; Stratford et al. 1996). Likewise a range of inhibitory processes will provide both a direct influence on individual cells and an indirect effect via their influence on the cells driving the intra-cortical facilitation. The potential dynamic complexity of these interactions is underlined by the work of Kapadia et al. (1995, 1999) in primates. Experiments in area MT have also reported suppressive surrounds of varying degrees of complexity with an organization that may encompass local to local motion comparisons and the extraction of complex features of the visual environment (Raiguel et al. 1995; Xiao et al. 1995, 1997a,b). This raises the possibility of a complexity to the organization of surround mechanisms in V1 that go beyond that predicted from an overlapping Gaussians model. In particular, the feedback from MT to V1 raises the possibility of complex motion-dependent effects drawing on the influence of MT. Thus following from our earlier report of surround driven suppressive and facilitatory effects in primate V1 (Sillito et al. 1995), we have utilized drifting stimuli to make a detailed examination of the strength, spatial organization, direction dependence, and laminar distribution of surround suppression in an attempt to further characterize the way in which it is implemented. The stimuli we have used here were all effective in driving MT cells (in some of these experiments we made simultaneous recordings in MT) (H. E. Jones, W. Wang, T. E. Salt, and A. M. Sillito, unpublished data) and also enabled comparison with a number of other studies in MT and cat and primate V1. Our data here suggest a much stronger influence of surround suppression through all laminae than hitherto reported in primate V1, clear dependency on the relative direction of motion for the surround stimulus and two distinct patterns of bias to the spatial organization underlying the suppressive mechanisms. These observations are discussed in the context of the insight they suggest into the processing mechanisms pertaining in V1.

	METHODS

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION REFERENCES

Subjects

The experiments were carried out on 14 adult Macaca mulatta monkeys. The animals were treated according to the published guidelines on the use of animals in research (European Communities Council Directive 86/609/EEC) and the National Institutes of Health guidelines for the use of laboratory animals.

Animal preparation

Animals were initially premedicated with atropine sulfate (0.04 mg/kg im) and acepromazine maleate (0.05 mg/kg im). Anesthesia was induced with intramuscular injection of ketamine (10-15 mg/kg). Surgical procedures were carried out under ketamine anesthesia, and a solution of bupivicaine hydrochloride (0.75% wt/vol) was applied to all wound margins. After cannulation of the saphenous veins and trachea, the animal was transferred to a stereotactic frame. The ear bars of the stereotactic apparatus were coated with lignocaine hydrochloride gel. The dura overlying V1 was exposed via a craniotomy. Anesthesia was maintained throughout the course of the experiment either with halothane (0.1-0.4%) or sufentanil (4-8 µg · kg¹ · h¹) and a mixture of 70% N₂O and 30% O₂. End-tidal CO₂ levels, the electrocardiogram (ECG) waveform, intersystolic interval, and the frequency of spindles in the electroencephalogram (EEG) waveform were monitored at all times through the experiment. The rate and depth of artificial ventilation was adjusted to maintain end-tidal CO₂ at 3.8-4.2%; after completion of all surgical procedures, the level of anesthetic agent was adjusted to give a state of light anesthesia. Once a stable state was reached, any variation in the monitored parameters (change in the frequency of spindles, fall or fluctuation in intersystolic interval, rise in end-tidal CO₂) commensurate with a change in the depth of anesthesia was immediately compensated for by an increase in the level of anesthetic reagent. Following completion of all surgical procedures and after a stable state of anesthesia had been established, animals were immobilized with an infusion of vecuronium bromide (0.1 mg · kg¹ · h¹) in glucose-enriched lactated Ringer solution. Temperature was maintained at 38°C by use of a thermostatically controlled electric heating blanket. All wound margins were dusted with topical application of Neomycin sulfate and Noricillin [procaine penicillin (15 mg/kg) and benzathine penicillin (11.25 mg/kg)im] was administered daily. Dexamethasone (1 mg/kg iv) was administered daily to reduce cerebral edema.

The pupils were dilated and accommodation paralyzed with topical application of atropine methonitrate (2% wt/vol). The eyes were protected with gas permeable contact lenses, and brought to focus on a semi-opaque tangent screen/front surface mirror at a distance of 0.57 or 1 m, using supplementary lenses and 2-mm diam artificial pupils. The locations of the blind spot and fovea were located and plotted using a reversible ophthalmoscope.

Apparatus

Single-unit activity was recorded from area V1 using arrays of tungsten in glass microelectrodes (Merrill and Ainsworth 1972). Electrode penetrations were angled to avoid recording from locations underlying the array entry point. Data were collected and visual stimuli generated using the Cambridge Electronic Design (Cambridge, UK) VS system in conjunction with a Picasso Image Generator (John Daughman, USA), presented on a Tektronix 608 tube. For further details, refer to Sillito et al. (1993). Spikes were stored with a 0.1-ms interval resolution and could subsequently be processed with respect to any aspect of the stimulus variables used during data collection. We first identified and hand mapped receptive fields using an overhead projector and the tangent screen of a plotting table. Once the receptive fields had been characterized in this way, we introduced a 45° front-surfaced mirror into the light path, deflecting the animal's plane of vision to a vertically mounted, 608 Tektronix tube at a distance of 0.57 or 1 m for controlled presentation of visual stimuli. The 608 tube was mounted on a cradle that could be shifted over a set of floor mounted tracks and tracks mounted in a slave carrier to roughly center the display on one of the receptive fields. We utilized the alignment of the receptive field on the tangent screen and 45° beam splitter to achieve this. We could fine tune the centering of the receptive field on the 608 tube using micrometer adjustments on the carrier mechanisms and software adjustment of the display center. These adjustments were checked with reference to the magnitude of the responses generated either by small flashing spots or small patches of an optimally oriented drifting sinusoidal grating presented in a range of spatial locations forming a sequential grid over the field. Accurate centering of the display over the receptive fields studied was critical to our experiments, and so the fine tuning of the centering was a standardized procedure for every cell and was checked throughout data gathering sequences.

Visual stimuli

For the preliminary evaluation of cell response properties, we used simple visual stimuli comprising flashing spots, drifting bars, and patches and annuli of drifting sinusoidal gratings. Parameters such as spatial frequency, temporal frequency, orientation, and bar length or spot/patch diameter were varied in a randomly interleaved sequence. A blank stimulus was included in each block for the assessment of spontaneous activity levels. The contrasts (L_max  L_min)/(L_max + L_min) routinely used were in the range 0.1-0.36 with a mean luminance of 14 cd m². To explore the effects of direction contrast on patch suppression, we used concentric bipartite sinusoidal gratings centered over the receptive field. We kept the contrast, spatial frequency, and drift rate constant in both inner and outer stimuli but varied the direction of drift of the inner and outer stimuli. The phase of our inner and outer displays were locked together with reference to the center of the display so that for concentric stimuli, when the direction of drift of both components was the same, they appeared as a single grating. Central patch size and inner diameter of the outer field ranged between 0.3 and 6.0°. Spatial frequency was in the range 1-4 cycles/° (cpd) and drift rate was 1.0-4.0 Hz. All tests were done with monocular visual stimulation of the cell's dominant eye.

To examine the spatial location of suppressive zones, we used two square patches of optimally oriented sinusoidal grating. The gratings drifted within each patch, and spatial frequency, direction of motion, and drift rate were kept constant in both patches. One grating patch (the notional inner stimulus) was centered over the CRF while the second stimulus patch was presented in randomized sequence at a range of locations around the field. Central and outer patch sizes ranged from 0.5 to 2°. For some cells, we also explored the effect of reversing the direction of drift of the grating in the second patch.

Experimental protocol and analysis

PRELIMINARY EVALUATION OF RECEPTIVE FIELDS. Isolated single units were classified as simple or complex according to conventional criteria (Hubel and Wiesel 1962; Skottun et al. 1991). After the receptive field center had been localized as described in the preceding text, we quantitatively checked preferred orientation and direction of motion using a patch of sinusoidal grating localized over the receptive field center with orientation and direction of drift varied in a randomized and interleaved sequence.

MAPPING THE CLASSICAL RECEPTIVE FIELD. Because of the way the mechanisms driving center and surround mediated influences overlap in primate V1, it is difficult to define what is precisely meant by the term classical receptive field. It might be taken to include the spatial borders of the processes driving surround effects, but these are often difficult to define. Equally the area of visual space from which excitatory responses can be obtained may not define the extent of the excitatory mechanism or excitatory field because the underlying inhibitory mechanism may suppress the weaker excitatory influences. In this study, we have used the term classical receptive field, CRF, to indicate the area of visual space from which excitatory responses, as judged by the spiking activity of the cell, could be obtained. The precise measurement is influenced by the procedure used to map the field.

QUANTIFYING RESPONSES. Responses were computed from the mean firing rate averaged over the full number of stimulus presentations. Typically we presented three to five stimulus cycles of each stimulus condition repeated over 5-20 trials. For each cell, we calculated a patch suppression index (PSI) according to the formula PSI = [1  (R_plat/R_opt)]*100, where R_opt and R_plat denote the responses elicited by the optimal and plateau stimuli, respectively. Thus cells showing no suppression to large diameter stimuli would have a PSI of 0, while those showing total response suppression would have a PSI of 100. To explore the effects of direction contrast on patch suppression, we used concentric bipartite sinusoidal gratings centered over the receptive field and varied the direction of drift of the inner and outer stimuli. Cells were regarded as showing no direction contrast if the response to the inner stimulus drifting in the preferred direction in the presence of an outer stimulus drifting in the reverse direction was not significantly different to the response observed when the inner and outer stimuli both drifted in the same direction (P = >0.05, paired t-test). Cells were regarded as showing direction contrast modulation if the response to the reverse direction configuration was significantly larger (P < 0.05) than the response observed when the inner and outer stimuli both drifted in the preferred direction [thus "direction contrast modulation" is analogous to the term "orientation contrast" (Knierim and Van Essen 1992)]. In some cases, the response to the direction contrast stimulus configuration exceeded the response to the inner stimulus presented alone ("direction contrast facilitation"). To quantify this, we calculated the percentage response increase elicited by the reverse direction configuration with respect to the response level elicited by the inner patch of grating presented alone. Cells were only regarded as showing direction contrast facilitation if the response to the reverse direction configuration was significantly larger (P < 0.05) than the responses to the same direction configuration and the inner stimulus alone and exceeded that to the inner alone by 10% or more. (We observed one example where the response to the reverse direction configuration was significantly smaller than the response to the same direction configuration. For simplicity, this cell was included in the no direction contrast grouping.)

RECONSTRUCTION OF RECORDING SITES. At the end of each electrode penetration, key recording sites were marked by electrolytic lesions (3-5 µA for 3-5 s, electrode negative). At the conclusion of the experiment, animals were overdosed with pentobarbital sodium, desanguinated with phosphate-buffered saline (PBS), and perfused with paraformaldehyde followed by sucrose in PBS. Frozen sections were cut at 40 µ, and alternate sections were stained by the Nissl method and an enhanced cytochrome oxidase method, respectively. Sections containing electrolytic lesions were drawn at low power. Adjacent sections were aligned precisely using blood vessels and section outlines as reference points.

	RESULTS

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION REFERENCES

The results reported here derive from 105 cells recorded in layers 2-6 of primate V1 at eccentricities from 2-6°. Our sample comprised 61 S type cells and 44 C type cells. All the effects reported applied equally to both S and C types.

Spatial summation curves and suppression

For all the cells in our sample (105), we determined the change in response as the diameter of a patch of optimally oriented drifting grating was varied. The core procedures we used to center on the CRF, map its size, and examine its spatial summation characteristics are illustrated in Fig. 1 for a layer 5 cell. The histogram (Fig. 1A) shows the response of the cell to an optimally oriented 0.3° square of drifting grating presented in a randomized sequence at a range of locations over and around the receptive field. The responsive regions are clearly defined. The contour plot (Fig. 1B) provides an overview of the shape of the field as determined by this method. The spatial summation curve (Fig. 1C) shows the response of the cell to varying the diameter of an optimally oriented patch of drifting grating. The response rose and then fell as the stimulus reached and then exceeded 0.75° in diameter, suggesting a potent suppressive or disfacilitatory influence beyond this point. This spatial summation curve was typical of the majority of cells we saw in primate V1. In addition to quantifying the response to varying the diameter of a circular patch, we also plotted the response to varying the diameter of the inner wall of an annulus of drifting grating. This provided a mirror image probe to the sequence of patch diameters and enabled us to assess the response of the cell to stimulation of outer regions of the receptive field in the absence of stimulation of the central region. The bottom right curve shows the response to varying the diameter of the inner wall of an optimally oriented annulus of drifting grating. This started to exert a small excitatory effect at 0.75°. For the sake of simplicity, we have used the term CRF here to indicate the area of visual space from which the cell showed clear excitatory responses with the tests used. In the case of the example shown in Fig. 1, we defined this as 0.75°.

View larger version (35K): [in this window] [in a new window]   Fig. 1. Classical receptive field and spatial summation properties. A: the 3-dimensional (3-D) histogram documents the response to a small patch of an optimally oriented, drifting sinusoidal grating presented at a range of spatial locations spanning a 3 × 3° area of visual space encompassing the cell's receptive field location. Responses (computed from the mean response rate averaged from the full stimulus cycle over 15 stimulus repeats) were elicited only from a very circumscribed area of visual space. [Patch diameter, 0.3°. Spatial frequency (SF), 2 cycles/degree (cpd). Temporal frequency (TF), 3 Hz. Contrast 0.36. Vertical scale denotes response in imp/s. C type layer 5 cell.] B: contour plot delineating the shape of the receptive field shown in A. The magnitude of the cell's response is shown by the shading of the contours as denoted by the color scale to the left. The scale bar shown in red denotes 0.5°. See METHODS for further details. C: the tuning curve plots the variation in response magnitude for increasing diameters of an optimally oriented patch of grating centered over the receptive field center. Responses were normalized to the response value elicited by the optimal diameter patch (9 imp/s). Error bars indicate ±1 SE. Black line to the right denotes spontaneous activity level. The patch suppression index for this cell (see METHODS) was 43%. Stimulus details as in A but 50 stimulus repeats. D: the tuning curve documents the response to varying the inner diameter of an annulus of optimally oriented grating. Responses were normalized to the maximal response seen in the patch tuning curve (C). Stimulus details as in C.

We show two further examples of spatial summation curves for a circular patch of drifting grating in Fig. 2, A and B. The variation in patch suppression over our cell sample is shown by the histogram in Fig. 2C. Here we have quantified the degree of suppression in terms of the percentage reduction in the response observed at the plateau of the spatial summation curve elicited by larger diameter stimuli in comparison to the response seen to an optimal diameter patch (see METHODS). The percentage reduction in response is represented in steps along the abscissa and number of cells in each category on the ordinate. The majority of the cells (99/105, 94%) exhibited response suppression to large diameter stimuli with a mean suppression of 67% (±2.07%; mean ± SE). This decrement in response with increasing stimulus diameter was highly significant across the population (P < 0.001 Wilcoxon test) and reflected a potent reduction in the output of V1 cells for optimally oriented stimuli extending beyond the CRF. Indeed it is worth underlining the fact that 80% of the sample exhibited a more than 50% suppression and 43% a more than 70% suppression in response. We recognize two possible sources of error in these observations. The first was that in a few cases, we were unable to generate stimuli large enough to be sure that we had accessed the full extent of the surround suppression and the second that in a few cases, we were unable to generate stimuli small enough to be sure we had accessed the cell's optimal response. However, both these would cause us to underestimate the degree of surround suppression and so would emphasize rather than diminish the finding that the majority of primate V1 cells are strongly suppressed by stimuli extending beyond their CRF.

View larger version (20K): [in this window] [in a new window]   Fig. 2. Patch suppression across our V1 cell sample. A and B: 2 further examples of spatial summation curves. Conventions as for Fig. 1C. For A, the patch suppression index was 69% and the optimal response 167 imp/s. (30 stimulus repeats. SF, 2cpd; TF, 3 Hz; contrast, 0.36. C type layer 4B cell.) For B, PSI was 64% and optimal response 33 imp/s. (Further details as in A. S type layer 4C cell.) C: block histogram plotting the distribution of patch suppression across the V1 cell population (n = 105). Cells were subdivided into 10 categories of patch tuning, binned in 10% epochs. Thus cells in category 0-9% had little or no patch tuning, cells in category >90% showed little or no response to large diameter patches (see METHODS for details of quantification).

These observations might follow from a sample restricted to the superficial layers (cf. Born and Tootell 1991), or they might encompass a substantial laminar variation in the degree of patch suppression. Given the variation in connectivity of the different layers, it might be expected that cells in the different layers would show large variations in the degree of patch suppression. Interestingly, as shown in Figs. 3 and 4, we were unable to demonstrate a laminar variation in the distribution of cells showing surround suppression. The range of the indices of patch suppression was similar through all laminae. Figure 3, A-C, shows the laminar distribution of cells showing a more than 25, 50, and 70% reduction in response with stimulus diameter while Fig. 4 shows the number of cells in each lamina falling in the groups summarized in Fig. 2C. We also compared the distribution of optimal summation diameters and the distribution of stimulus diameters eliciting maximal suppressive effects across cortical layers. The scatter diagrams in Fig. 5 plot, for each lamina, the magnitude of patch suppression versus optimal summation diameter (top) and versus maximal suppression diameter (bottom). Again, there is little evidence to support any obvious differences across layers. In Table 1, we summarize, for each layer, the mean (±SE) values observed for patch suppression, optimal summation diameter, maximal suppressive diameter and spatial frequency used. Once more, there appears to be little laminar variation in the mean values observed for any of these parameters, although, interestingly, the optimal summation diameter for layer 5 and 6 cells was nearly double that seen for the other cortical layers. In general, the mechanism underlying patch suppression would appear to be common to all processing steps within V1 and possibly represents a general algorithm pertaining at this level in the system. The distribution of surround suppression through all layers of V1, plus the numbers of cells showing high levels of suppression, underlines the fact that extensive stimuli (4-9° diameter) will tend to minimize the output of a column. Furthermore, for eccentricities in the region of 5° as explored in the present work, even a 2° stimulus will result in substantive attenuation of the output of many cells in a column.

View larger version (16K): [in this window] [in a new window]   Fig. 3. Laminar distribution of patch-suppressed cells. Cortical layers were assigned according to the criteria of Lund (1988). The 3 block histograms show the percentage of patch suppressed cells in each lamina. For the histogram in A, any cell showing 25% or more suppression was regarded as patch suppressed. B: only cells showing 50% or more suppression were regarded as patch suppressed. C: cells were classed as patch suppressed only if the suppression with large diameter patches exceeded 70%. Regardless of the cutoff value chosen, patch suppressed cells were distributed across all laminae.

View larger version (22K): [in this window] [in a new window]   Fig. 4. Block histograms plot the distribution of patch suppression for different cortical layers (noted above each histogram). Cells were subdivided into ten categories of patch tuning, binned in 10% epochs as described in the legend to Fig. 2C.

View larger version (38K): [in this window] [in a new window]   Fig. 5. The scatter diagrams plot the magnitude of patch suppression (%) vs. optimal summation diameter (top row) and vs. maximal suppression diameter (bottom row) for different cortical layers (noted above each plot).

Dissection of the spatial organization of suppressive mechanisms

Generally, suppression in the receptive fields of cat V1 cells has been associated with either suppressive end zones, suppressive side bands, or both (DeAngelis et al. 1994; Hubel and Wiesel 1965; Kato et al. 1978; Orban et al. 1979a,b; Walker et al. 1999). It is important to know how the suppression we examined here with patches of varying diameter links to discretely identifiable end zones or side bands. Hence we included in our tests a protocol examining the influence of a second discrete patch of grating introduced at a stepped series of locations around a patch of rectangular drifting grating overlying the CRF. Examples of the data obtained from this are shown in Fig. 6, A-J. These surface plots show the variation in response magnitude to the stimulus overlying the CRF induced by the presentation of the second stimulus at any of the locations around the CRF (in a randomized interleaved sequence) as indicated by the matrix of points in the icon diagram above the records. The plots are all oriented so that the axis of the optimal orientation of the cell lies along the plane indicated in the icon diagram. In each case the center point of the records and the color, dark green, indicates the response level associated with the inner stimulus alone. All the cells in the examples A-J in Fig. 6 exhibited strong surround suppression with increase in the diameter of a circular patch of drifting grating. However, the detailed dissection of the zones around the CRF revealed patterns of influence that bore no relation to the degree of suppression following from an increase in the diameter of a circular patch of grating. The cell in Fig. 6A was not suppressed by the second stimulus at any location around the CRF and that in Fig. 6B showed a slight suppression at one location only, while the cells in Fig. 6, I and J, were suppressed at all locations around the CRF. The other examples encompass patterns that show clear end zones and side bands (Fig. 6C) and those where suppressive effects partially surrounded the field or sat at either corner of the receptive field. The scatter diagram in Fig. 7 compares the amount of suppression observed at the plateau level of the patch summation curve to that observed using a discrete patch of grating positioned at the most effective surround location. As is clear, there was little correlation between the plateau level large diameter patch suppression and the most effective suppression elicited by a discrete patch. Indeed, for more than half the sample (58%), we were unable to detect any significant influence from side bands, end zones or corner zones (ANOVA) in cells showing significant patch suppression (P < 0.05 Wilcoxon test and ANOVA). Thus for these cells, a stimulus uniformly surrounding the CRF appeared to recruit otherwise subthreshold effects to exert a potent suppressive influence. Where there were clearly defined suppressive foci around the CRF, our data suggest a wide variety of configurations for their spatial organization. To quantify the degree of heterogeneity in these cells, we have used circular statistics (Batschelet 1981; Xiao et al. 1995, 1997b) to analyze the data. We used the criteria described by Xiao et al. (1997b) (see METHODS) to subdivide the cells into three groups, those exhibiting spatially uniform surround suppression, spatially asymmetric surround suppression, and bilaterally symmetric surround suppression. The majority of the cells analyzed in this way (81%) exhibited spatial heterogeneity of surround locations, although 19% showed spatially uniform surround suppression (an example is shown in Fig. 6J). Cells exhibiting heterogenous surrounds were divided approximately equally into spatially asymmetric cells (44%) where the surround suppression was biased toward one location (e.g., Fig. 6B) and bilaterally symmetric cells (37%) where the surround effect was localized to two opposing regions along a single axis (e.g., Fig. 6F). For cells that exhibited spatially heterogenous surrounds, we asked whether the suppressive effects were localized to the ends, sides, or corners of the field. Interestingly, suppressive effects were nearly equally distributed in all directions round the CRF; there was no evidence to suggest that suppressive effects were concentrated in end-zone or side-band regions. As previously described, for 58% of cells showing significant patch suppression to a large grating patch, we were unable to detect any significant suppressive influence from a discrete second stimulus presented at any location around the CRF. Nonetheless, we also checked the degree of heterogeneity in the spatial organization of the surround for this subgroup of cells using the circular statistics method described in the preceding text. The results were essentially in accord with those for the 42% of cells that did show significant suppressive influences to a discrete second stimulus located at some position around the CRF. Thus the majority of cells showed heterogenous surrounds, and these were again divided approximately equally into spatially asymmetric and bilaterally symmetric types.

View larger version (34K): [in this window] [in a new window]   Fig. 6. Spatial organization of suppressive effects. The surface plots depict the modulatory effect of a 2nd stimulus presented at a range of spatial locations on the response to a central stimulus for 10 patch suppressed cells recorded in primate V1. The stimulus configuration comprised an inner stimulus (a square patch centered over the CRF containing an optimally oriented grating drifting in the cell's preferred direction of motion) and a 2nd stimulus (another square patch of optimally oriented grating drifting in the same direction of motion) that was positioned at a range of xy locations around the central stimulus (as depicted by the schematic diagram above). In each plot, the responses are normalized with respect to the response elicited by the center patch alone (100% in each case, dark green). Suppressive effects are denoted by blue colors, facilitatory effects by light green to yellow colors (see color scale bar top right). Center patch diameter ranged from 1 to 2° depending on each cell's CRF size. Spatial frequency ranged from 2 to 3 cpd. Temporal frequency, 3 Hz; contrast, 0.36.

View larger version (25K): [in this window] [in a new window]   Fig. 7. Comparison of the amount of suppression observed at the plateau level of the patch summation curve to that observed using a discrete patch of grating positioned at the most effective surround location. The scatter diagram plots the degree of suppression (%) elicited by a large diameter patch along the x axis vs. the degree of suppression (%) elicited by the most effectively located discrete patch of grating along the y axis.

Dissection of surround effects with annuli

The spatial summation curves constructed from a circular patch of varying diameter reflect a situation where the receptive field center mechanism is always part of the integration driven by the stimulus. For this reason, we examined the effect of varying the diameter of the inner wall of an annulus of drifting grating so that we could explore the effect of a stimulus encroaching on the field from the surround without optimally activating the center mechanism. The data obtained revealed some interesting variances in the pattern of integration of surround influences and the mechanisms driving responses from the center of the CRF.

We explored these effects in detail for 54 cells in our sample by comparing the responses obtained in the patch tuning curves to effects elicited by annuli encroaching into the CRF but excluding the very center of the field. We grouped the data obtained with the annuli into three categories, those obtained with the inner border of the annulus in the outer 25% of the diameter of the CRF, those obtained with the annulus border in the middle 50%, and those obtained with the annulus border in the inner 25%. For the general comparisons, we have taken the category giving the largest response. Essentially these data highlighted the presence of cells with contrasting patterns of responses to the annuli. On the basis that an annulus by definition excludes the receptive field center, but encompasses all the surround, it is logical to expect that the best response to an annulus would be less than the plateau in the area summation curve. This indeed was the case for many cells (20/54, 37%). We separated out those cells showing responses lower than the plateau in the area summation curve using the criterion that the responses to the most effective annulus had to be significantly smaller than the plateau of the area summation curve (P < 0.05 level, t-test). For these cells, the mean response to the annulus was 61 ± 6.55% smaller than the value of the plateau in the patch tuning curve. Taking each category of the annulus encroachment within the CRF in turn the responses were 76 ± 6.41% smaller for the outer 25%, 64 ± 7.95% smaller for the middle category, and 68 ± 13.89% smaller for the inner category. Examples of the pattern of effect we saw are shown in Fig. 8. It is clear in Fig. 8, A and B, that the annulus exerted a small but increasing excitatory effect as it encroached into the CRF, but one that was smaller than the plateau in the patch tuning curve (marked by the dashed line). These observations would be consistent with the predictions either for a suppressive field that surrounded the excitatory CRF or for those following from the difference of Gaussians model with overlapping inhibitory and excitatory fields.

View larger version (44K): [in this window] [in a new window]   Fig. 8. Block histograms comparing the responses elicited by patches of varying diameter to those to annuli of a fixed outer diameter and a varying inner wall diameter. A: patch responses are denoted by the dark gray stippled bars to the left of the figure, annulus responses by the light gray stippled bars on the right. Stimulus configuration is denoted schematically above each bar. Patch and annulus inner wall diameters are indicated below each bar. The best response to an annulus (for an annulus with an inner wall diameter of 0.5°) was considerably smaller than the response elicited by the largest patch (response level denoted by dashed line). (50 stimulus repeats, SF, 2 c/d; TF, 3 Hz; contrast, 0.36. C type layer 4B cell.) B: stimulus conventions as in A. (Details as for A, but patch/annulus inner wall diameters are 1, 2, 3, and 9°. TF, 4 Hz; C type layer 3 cell.)

However, for the majority of the cells in our sample (34/54, 63%), the largest response to an annulus was either not significantly different to (7/34 cells) or was significantly more than (27/34 cells) the plateau in the area summation curve (P < 0.05). Two examples are shown in Fig. 9. In both cases, the response to an annulus within the CRF substantially exceeded that to the plateau in the patch tuning curve (picked up by the dashed line) and indeed the response to the optimal patch diameter (picked up by the dotted line). Thus for both these cells, including the very center of the CRF in a stimulus that extended beyond the CRF reduced the response rather than enhanced it suggesting an increase in the magnitude of the "suppressive effect." Interestingly, the example in Fig. 9A shows that the response to the annulus decreased as it encroached further into the central region of the CRF. For these two examples, one could argue that the optimal stimulus was an annulus excluding the very center of the CRF. For the group as a whole, the mean best response to an annulus driving the CRF was 195 ± 68.10% larger than the response level for the plateau in the patch tuning curve. Taking each category of annulus encroachment into the CRF in turn, the responses for the outer 25% were 100 ± 82.53% larger, middle category 83 ± 25.21% larger, and inner category 85 ± 35.63% larger. It is clear for these cells that including the very center of the CRF in a stimulus extending beyond the borders of the CRF reduced the response rather than enhanced it. Thus for these cells, the surround suppressive mechanism appeared to be enhanced by, and in some cases require (as in Fig. 9), activation of the CRF center. This pattern of effect is neither simply predicted by the differences of Gaussians model or a surrounding inhibitory field.

View larger version (42K): [in this window] [in a new window]   Fig. 9. Block histograms showing that excitatory response to an annulus falling within the CRF can exceed the responses to the plateau in the patch tuning curve. A: patch responses are denoted by the dark gray stippled bars to the left of the figure, annulus responses by the light gray stippled bars on the right. Stimulus configuration is denoted schematically above each bar. Patch and annulus inner wall diameters are indicated below each bar (0.3, 0.5, and 4°, respectively). The best response to an annulus exceeded the response seen in the patch tuning curve at the plateau (response level denoted by dashed line) and the optimal response in the patch tuning curve (dotted line). (24 stimulus repeats, SF, 2 c/d; TF, 3 Hz; contrast, 0.36. layer 4C cell.) B: stimulus convention as for A. (Details as for A, but patch/annulus inner wall diameters are 0.5, 1, 6, and 9°. 50 stimulus repeats, SF, 1 cpd; Layer 6 cell.)

To simplify the description, we refer to those cells showing annulus responses that were significantly below the plateau in the patch tuning curve as classical surround suppression (CSS) cells and the others as center gated surround suppression (CGSS) cells. The block histogram in Fig. 10A summarizes the differences in the mean relative response levels of the CSS and CGSS category cells to annuli in comparison to the plateau response from the patch tuning curve. The distinction between the two groups is further highlighted if one considers the response magnitudes with respect to the optimal. For the CSS category, the best annulus responses were 84 ± 3.22% smaller than the optimal while for the CGSS group the best annulus responses were only 34 ± 7.65% smaller than the optimal, as shown in Fig. 10B. We highlight the CSS and CGSS behavior because it underlines patterns of response that are sufficiently different to suggest distinct roles in the processing of the visual input. This point is underlined by the scatter diagram in Fig. 10C that plots the response to a large patch driving plateau-level response against the response to an annulus with the inner wall set at the diameter eliciting the best response. Cells with CSS properties are denoted by circles in the plot and those with CGSS properties by triangles. The dashed line identifies the diagonal denoting equal responses to annuli and large patches driving plateau-level responses. The broad distinction between the two categories is clear, although it remains open to question as to whether they reflect distinct groupings or two ends of a continuum deriving from a varying level implementation of the process generating the deviation of CGSS cell response from that which might be predicted from simpler mechanisms. The essential point though is that the two extremes encompass cells that, on the one hand, respond better to an annulus of drifting grating that excludes the center and, on the other, respond better to a patch of drifting grating that excludes the surround.

View larger version (20K): [in this window] [in a new window]   Fig. 10. A and B: block histograms summarizing the mean relative responses of our population of classical surround suppression (CSS) and center-gated surround suppression (CGSS) cells to annuli in comparison to the plateau response from the patch tuning curve (A) or the optimal response from the patch tuning curve (B). In A, the histogram plots the mean difference in response for the most effective annulus tested in comparison to the response level seen for the plateau of the patch tuning curve. The response at the plateau of the patch tuning curve (marked by the arrow head) is set to 0 so that negative values indicate that the response to the annulus was smaller than that at the plateau of the patch tuning curve, whereas positive values indicate that the responses were larger. CSS cells are denoted by the gray bar, CGSS cells by the black bar. Error bars indicate 1 SE. In B, the histogram plots the difference in response for the most effective annulus tested in comparison to the optimal inner patch response. The optimal patch response (marked by the arrow) is set to 0 so that negative values indicate that the response to the annulus was smaller than the optimal patch response. Bar conventions as in A. C: distribution of plateau vs. annulus responses for CSS and CGSS cell groups. The graph plots the response (in imp/s) to a large diameter patch along the x axis vs. the best response observed to an annulus along the y axis. CSS cells are denoted by circles and CGSS cells by triangles.

We were interested to ascertain whether we could isolate another measure of the distinction between these two groups. If the suppression derived from the surround, then the annulus response would be a mirror reflected image of the patch response. Assuming this to be the case, one can compute the number of excess spikes (if any) that an annulus produced over the prediction. We have thus computed the number of excess spikes produced by an annulus over the prediction based on the shape of the mirror-image patch-tuning curve (but resetting the prediction to 0 if the prediction was negative). This produced figures of 3.6 ± 0.69 (SE) imp/s for CSS cells and 11.7 ± 1.60 imp/s for CGSS cells. These values were statistically significantly different at the P < 0.001 level (Mann-Whitney U test). The difference was not because CGSS cells had a higher overall firing rate than CSS cells because the mean optimal firing rate for CSS cells was if anything slightly higher at 29 ± 5.00 imp/s than that for CGSS cells (25 ± 3.56 imp/s), although the differences were not statistically significant. We also quantified the number of excess spikes as a percentage of the optimal patch response. The mean value for CSS cells was 13.6 ± 2.48% and that for CGSS cells was 59.4 ± 6.56%. These values were statistically significantly different at the P < 0.001 level (Mann-Whitney U test). These figures show that both the CSS and CGSS cells drive extra spikes, but there seems to be a very robust enhancement of the effect in the transition to CGSS cells. Overall this supports the concept of a mechanism, potentially present across all cells in the sample but implemented with varying strength, to form two extrema in the pattern of responses to annuli.

Influence of direction of stimulus motion on surround suppression

It is clear from previous and current work in our laboratory (Sillito et al. 1995) and that of others (Born and Tootell 1991; Knierim and Van Essen 1992; Nothdurft et al. 1999) that surround suppression in primate V1 is generally tuned to the same orientation as a cell's excitatory response. Thus it is likely that the connections between cortical columns tuned to the same orientation (Bringuier et al. 1999; Gilbert and Wiesel 1989; Kisvárday and Eysel 1992; Malach et al. 1993; Ts'o and Gilbert 1988; Ts'o et al. 1986) must provide a significant contribution to the degree of surround suppression. However, this could be either via direct facilitatory inputs that might tend to decrease the degree of suppression or indirect connections via inhibitory interneurons that would enhance it. Additionally it is not clear whether the pattern of influence would be the same when the direction of the surround stimulus is reversed. Although effects have been described for a range of stimulus configurations involving motion contrast (Lamme 1995; Orban 1994; Orban et al. 1989), this has not been systematically examined in the context of the mechanisms underlying surround suppression in the primate. At least one reason for this is that the incidence and strength of surround suppression in primate V1 has not previously been appreciated. We thus examined the effect of reversing the direction of motion of the surround stimulus. These observations were made on 51 cells of our sample. All cells included in the analysis exhibited a PSI more than 20%. We examined the effect of reversing the direction of motion of the surround stimulus at range of different interface diameters for the center surround border. This was to enable us to examine the effect of reversing the direction of motion on surround suppression for a border within, on the edge of, and outside the CRF. We observed different types of effect from the reverse direction configuration. In the first instance, we have summarized these for the interface diameter generating the largest effect (where there was an effect of reversing the direction), and then we examine the influence of the location of the interface border with respect to the CRF.

For 22% of the cells tested (11/51), reversing the direction of drift of the surround had no effect on the magnitude of suppression at any interface diameter tested. For this subgroup, the mean suppression (with respect to the response to the inner stimulus alone) for the iso-direction surround was 45 ± 9.31% compared with a value of 49 ± 8.24% for the reverse direction surround. An example of the tests carried out on one of these cells is illustrated in Fig. 11A. The icons above the bar chart indicate the stimulus configurations. The cell exhibited directional selectivity to the inner stimulus alone but for either direction introducing an outer stimulus drifting in either the same or opposite direction reduced the response. For these cells, the mechanism driving the surround suppression would appear to integrate both directions of motion equally, even where, as for the example in Fig. 11A, the excitatory response driven from the field center was directionally selective. We should qualify our comments for this group with the comment that one of the cells showed a small, but just significant, increase in suppression when the direction of motion of the outer stimulus was reversed. This shift is included in the average change for the group quoted in the preceding text. These cells were thus not sensitive to direction contrast but were sensitive to the size of the stimulus.

View larger version (52K): [in this window] [in a new window]   Fig. 11. These histograms document the responses of 2 V1 cells to a direction contrast stimulus. A: the 4 columns on the left plot, respectively, the response (in imp/s) to an inner patch of grating drifting in the cell's preferred direction of motion (column 1), the response to an annulus of grating drifting in the preferred direction (column 2) and then the response to the inner patch of grating drifting in the preferred direction presented simultaneously with the annulus of grating drifting in the same (column 3) or opposite (column 4) direction. The 4 columns to the right plot the response for the opposite direction of drift of the inner stimulus. Stimulus conditions are summarized schematically above each record. Error bars denote +1 SE. (Patch/interface diameter 1°. TF, 3 Hz; SF, 2 cpd; contrast, 0.36. 25 stimulus repeats. S type layer 4A cell.) B: convention as in A. (Patch/interface diameter, 0.75°. Further stimulus details as in A, but SF, 3 cpd; S type layer 4 B cell.)

The remaining cells were all sensitive to direction contrast, showing significant changes in surround suppression when the direction of drift of the outer was opposite to that of the inner. These cells fell into two groups, one showing a direction-contrast-dependent modulation of the strength of surround suppression and the other a direction-contrast-driven facilitation of responses. The group exhibiting direction-contrast modulation constituted 41% (21/51) of our sample and showed a reduction from a mean suppression of 70 ± 4.11% for the iso-direction surround to 22 ± 5.31% for the reverse direction surround, thus reflecting a partial but not total reduction in the strength of the surround suppression. An example of the responses of one of these cells is shown in Fig. 11B. The cell showed no directional selectivity to the inner stimulus, suppression when the outer stimulus moved in the same direction, and a reduction in surround suppression when the direction of the outer stimulus was reversed. This would seem to indicate that the mechanism integrating the suppression in these cells was only fully enabled when the surrounding and central area of visual space were engaged by the same direction of motion. Equally, a significant component of suppression (22%) remained in the reverse direction configuration, suggesting the possibility of two groups of lateral interactions driving the surround suppression.

Some of the complexities in the process generating suppression are underlined by the responses of the cells showing direction contrast facilitation. These constituted 37% (19/51) of our sample, and when the direction of the outer stimulus was opposite to that of the inner, their responses exceeded that to the inner alone. For these cells, the iso-direction surround stimulus elicited a suppression of 28 ± 5.79% of the response to the inner alone at the interface diameter used for the test, while the response in the presence of the reverse direction surround was a mean facilitation of 74 ± 15.69%. Examples of this pattern of response are given in Fig. 12, A-C. Note that in Fig. 12, A-C, the diameter of the central patch used for the tests was larger than the optimal diameter for a single patch. For each of these cells, although the reverse direction configuration evoked a response level higher than that to the inner stimulus used in the test, the responses did not exceed the response elicited by the optimal single stimulus. Thus the reverse direction enhancement may reflect a disinhibitory mechanism serving to reset the lower firing level associated with the particular inner stimulus toward the cell's optimal (see DISCUSSION and following text). In some cases, as in Fig. 12D, the response to the direction contrast configuration exceeded that evoked by the optimal single patch diameter stimulus. Of the cells showing direction-contrast facilitation, 26% (5/19) showed this "supra-optimal" facilitation. For this group in isolation, the mean response reduction associated with the iso-direction surround was 23 ± 14.67% at the interface diameter used for the test, while the mean response increase for the reverse direction configuration was 133 ± 45.87%. This translated into a mean increase of 95% above the value for the optimal diameter stimulus alone. The lower degree of iso-direction suppression reported here for the examples showing reverse direction facilitation and supra-optimal facilitation merely reflects the fact that many of these effects were only observed with interface diameters where the inner stimulus exceeded the CRF size (and was hence already driving a component of surround suppression, see following text). There was no significant difference (P > 0.05, Mann-Whitney U test) in the absolute degree of surround suppression derived from the area summation curves for the group of cells showing direction contrast facilitation and those that did not.

View larger version (27K): [in this window] [in a new window]   Fig. 12. Further examples of the effects of direction contrast between iso-oriented stimulus components. Conventions as for Fig. 11. A: patch/interface diameter 1°. TF, 3 Hz; SF, 2 cpd; contrast, 0.36. 15 stimulus repeats. C type layer 4B cell. B: further details as for Fig. 12A. S type layer 4B cell. C: further details as for Fig. 12A but patch/interface diameter 1.5°. S type layer 4C cell. D: further details as for Fig. 12A but 20 stimulus repeats. Patch/interface diameter was 1°. The 1° patch was the optimal single stimulus for this cell. C type layer 4B cell.

For the cells showing direction contrast facilitation, changing the interface diameter could change the response. An example is given in Fig. 13, A and B, where it is clear that adding a surround stimulus to a 1° inner stimulus (the optimal diameter for this cell) caused a strong suppression when it drifted in the same direction and a still clear but weaker suppression in the other direction. However, when the stimulus diameter was increased to 2°, although adding a surround drifting in the same direction again strongly suppressed the cell's response to the inner alone, reversing the direction of drift of the outer resulted in a response level exceeding that to the 2° inner alone. It is to be noted that the response level associated with the reverse direction configuration at 2° did not exceed that to the 1° inner (optimal diameter) alone, but the reverse direction configuration at 2° resulted in a response that was substantially larger than that to the reverse direction configuration at 1°. It is important to emphasize that none of the cells placed in the category exhibiting equal suppression to either direction of drift of the outer stimulus showed any other effect at any other diameter. Similarly none of the cells placed in the category showing direction contrast modulation of the level of surround suppression with direction of drift exhibited direction contrast facilitation at any stimulus interface diameter [and the majority exhibited similar effects at diameters smaller (57%) or larger (83%) than that showing the largest directionally dependent modulation]. For the cells showing direction contrast facilitation, 80% exhibited either equal effects or simple modulation of surround strength for the reverse direction configuration at smaller interface diameters than those revealing the largest facilitation and 89% at larger diameters.

View larger version (49K): [in this window] [in a new window]   Fig. 13. Histograms show the effect of changing the patch/interface diameter on direction contrast effects for an S type cell recorded in layer 3. Conventions as for Fig. 11. Top row: the responses obtained with a patch/interface diameter of 1°; bottom row: the response of the cell to the same stimulus configuration but with the patch/interface diameter held at 2°. (Patch/interface diameter 1°. TF, 3 Hz; SF, 2 cpd; contrast, 0.36. 35 stimulus repeats.)

The distribution of effects observed across our sample is summarized in the scatter diagram in Fig. 14A that compares the modulatory effect of a surround stimulus drifting in the same direction as the center stimulus (x axis) to that of a surround stimulus drifting in the opposite direction (y axis), on the response elicited by the center stimulus alone. Suppressive effects are denoted by negative values, response enhancements by positive values. In nearly all cases, the iso-direction surround stimulus reduced the response to the center stimulus alone so that virtually all points fall in the left two quadrants of the plot. Cells where both directions of the surround elicited equal suppressive effects, as shown in Fig. 11A, lie along the diagonal (). We have termed this group "no direction contrast effects." Less than a quarter of the cells tested showed this pattern of effect. The remaining cells all lie above the diagonal, indicating that an iso-direction surround elicited more suppression than a reverse direction surround. Cells such as that shown in Fig. 11B, where both drift directions of the surround stimulus suppress the center response, but where the suppressive effect elicited by the reverse direction surround is weaker, fall in the lower left quadrant, above the diagonal (). We have termed this pattern of effect "direction contrast modulation." Cells such as those shown in Fig. 12, where the reverse direction stimulus enhances the response to the center stimulus lie in the upper left quadrant (). We termed this pattern of effect "direction contrast facilitation." For five cells, the magnitude of the response observed exceeded the response elicited by the optimal single stimulus () as illustrated in Fig. 12D. We have termed this effect "supra-optimal direction contrast facilitation."

View larger version (35K): [in this window] [in a new window]   Fig. 14. A: comparison of the modulatory effects elicited by surround stimuli drifting in the same direction and in the opposite direction to the center stimulus on the response elicited by the center stimulus alone. The modulatory effect of the iso-direction surround stimulus is plotted along the x axis and that of the reverse-direction surround stimulus along the y axis. Suppressive effects are denoted by negative values, response enhancements by positive values. Cells where both directions of the surround elicited equal suppressive effects, as shown in Fig. 11A, lie along the diagonal (, no direction contrast cells). Cells where both drift directions of the surround stimulus suppress the center response but where the suppressive effect elicited by the reverse direction surround is weaker, fall in the lower left quadrant, above the diagonal (, direction contrast modulation cells). Cells where the reverse direction stimulus enhances the response to the center stimulus lie in the upper left quadrant (, direction contrast facilitation). Cells where the magnitude of the response observed to the reverse direction configuration exceeded the response elicited by the optimal single stimulus are marked by the  (supra-optimal direction contrast facilitation). B: summary histograms documenting the prevalence of the various patterns of direction contrast effects with respect to whether the interface border between the inner and outer stimulus components was within, on the edge of, or out