The Journal of Neurophysiology Vol. 77 No. 2 February 1997, pp. 562-570
Copyright ©1997 by the American Physiological Society

Simulated Optic Flow and Extrastriate Cortex. II. Responses to Bar Versus Large-Field Stimuli

Kathleen Mulligan, Jong-Nam Kim, and Helen Sherk

Department of Biological Structure, University of Washington, Seattle, Washington 98195-7420

	ABSTRACT

Abstract Introduction Methods Results Discussion References

Mulligan, Kathleen, Jong-Nam Kim, and Helen Sherk. Simulated optic flow and extrastriate cortex. II. Responses to bar versus large-field stimuli. J. Neurophysiol. 77: 562-570, 1997. In the preceding paper we described the responses of cells in the cat's lateral suprasylvian visual area (LS) to large-field optic flow and texture movies. To assess response properties such as direction selectivity, cells were also tested with moving bar stimuli. We expected that there would be good agreement between response properties elicited with optic flow movies and those revealed with bar stimuli. We first asked how well bar response properties predicted responsiveness to optic flow movies. There was no correlation between responsiveness to movies and the degree of end-stopping, length summation, or preference for bars that accelerated and expanded. We then considered only the 322 cells that responded to both bars and optic flow or texture movies and asked how well the strength of their response to movies could be predicted from the direction-tuning curves generated with bar stimuli. One-third of these cells responded much more strongly to movies than could be predicted from their direction-tuning curves. Generally, such cells were rather well tuned for the direction of bar motion and preferred a direction substantially different from what they saw in optic flow movies. Optic flow movies shown in the forward direction were the most effective variety of movie for two-thirds of these cells. To see whether this outcome stemmed from differential direction tuning for bars and large multielement displays, in a second series of experiments we compared direction tuning for bars and large-field texture movies. Many cells showed substantially different direction tuning for the two kinds of stimulus: almost 1/3 of 409 cells had tuning curves that overlapped each other by <50%. But only a small number of cells (<10%) responded much better to texture movies than to bars in the predominant direction of image motion in optic flow movies. This result, like that reported in the preceding paper, suggests that cells in LS respond differently to optic flow than to texture displays lacking optic flow motion cues.

	INTRODUCTION

Abstract Introduction Methods Results Discussion References

In the preceding paper we compared the responses of cells in area LS (the cat's lateral suprasylvian visual area) to large displays simulating optic flow, with responses to displays representing frontoparallel motion ("texture" movies). Because of the preponderance of cells preferring optic flow, we concluded that a substantial population in LS may be critically involved in visual analysis during locomotion. However, it has long been known that most cells in LS also respond well to simple stimuli, such as solitary bars or slits moving against a blank background (e.g., Hubel and Wiesel 1969; Spear and Baumann 1975; Wright 1969). To see how responses to such stimuli were related to responses to large, complex displays, we tested cells with conventional bar stimuli as well as optic flow and texture movies.

We expected that, for a given cell, the response properties revealed by bar stimuli would predict responsiveness to such movies. For example, a cell with a preferred bar direction coinciding with the predominant direction of motion in optic flow movies should respond well to such movies; a cell with an orthogonal preferred bar direction should not. Surprisingly, it became apparent that many cells did not conform to these expectations.

This outcome prompted us to perform a second series of experiments, in which we systematically compared direction tuning for bars and for texture movies. Many cells had substantially different direction tuning for the two kinds of stimulus. However, the differences rarely coincided with the predominant direction of motion in optic flow movies and did not explain the strong responses to optic flow observed in the first series of experiments.

	METHODS

Abstract Introduction Methods Results Discussion References

Bar stimuli, first experimental series

Two series of experiments were performed. The first was described in the preceding paper, and the only methodological details to be added concern the moving bar stimuli. The bar was either white and the background black, or the bar was black and the background light gray, yielding a contrast 67% that of the white bar display. Three different kinds of tests were performed using bar stimuli.

DIRECTION PREFERENCE. A bar was swept across the receptive field in eight different directions. One direction was that judged by the experimenter to be optimal, and the other seven differed from this in steps of 45°. Bar size, speed, and sign of contrast (dark on light background, or the reverse) were adjusted according to the cell's preferences. The eight directions were shown in pseudorandom order for a total of five presentations of each. Often, the sequence was repeated using a different stimulus (e.g., a white instead of a black bar, or a bar moving at a different velocity).

LENGTH PREFERENCE. Bars of five different lengths were tested in pseudorandom order for a total of five trials each. The lengths were 2, 4, 9, 14, and 19°; speed and direction were those judged optimal for each cell.

EXPANSION/ACCELERATION. This stimulus set included five conditions. In the first four, a bar of constant size and velocity moving in one of four different directions 90° apart, one direction being optimal for the cell. In the fifth condition, an accelerating and expanding bar moved in the optimal direction. The size and speed of the accelerating/expanding bar as it passed through the receptive-field center were identical to the size and speed of the constant size/speed bar.

All but six cells were tested for direction preference. Subsets of cells were tested with the use of the other bar stimulus paradigms.

Bar and texture stimuli, second experimental series

In the second series of experiments, responses to bar and large-field texture stimuli were studied in seven cats. All receptive fields were centered in the lower left quadrant. Experimental methods were identical to those used in the first series except in regard to stimulus presentation. The stimulus display was larger (62 × 62°), with a horizontal resolution of ~10 pixels/deg. Stimuli were rear-projected onto a translucent tangent screen with an LCD panel (InFocus Systems); the viewing distance was 57.3 cm. Bar direction preference was tested as described above; the other two tests using bar stimuli were not performed.

View larger version (28K): [in this window] [in a new window]   FIG. 1. Responses of all cells to an optimal moving bar plotted as a function of the response to the most effective movie. Response strengths to the 2 kinds of stimulus tended to be correlated. Cells indicated by arrow responded to movies but not to bars.

View larger version (16K): [in this window] [in a new window]   FIG. 2. A: directions of image motion in an optic flow movie seen by 1 receptive field (gray rectangle). The receptive field is centered just below the horizontal meridian (HM) in the lower left quadrant. Long arrows show directions of image motion through the receptive field, all originating from the simulated heading point on the vertical meridian (VM). B: polar histogram showing incidence of optic flow directions for all cells responsive to movies (see text). Direction of each line corresponds to one optic flow direction, and length of the line shows the number of cells that saw that direction.

"Texture" stimuli were composed of small randomly distributed, partially overlapping disks of various shades of gray, filling the entire display area (see Fig. 1B of previous paper). All elements in a texture movie moved in the same direction at constant velocity, simulating frontoparallel motion. Direction tuning for texture movies was tested in the same fashion as described for bars. For a given cell, the same set of eight directions were tested using bars and texture moving at the same speed.

Data analysis

Preferred direction was determined from bar responses by fitting a Gaussian curve to the major peak in the direction-tuning curve. Direction tuning was measured as half-width at half-height of the fitted curve. An index of direction preference along the optimal axis of motion was calculated by the use of the conventional formula, direction index = 1  response to nonpreferred direction/response to preferred direction. We also computed direction preference for bars on a scale ranging from 1 to +1 as described in the preceding paper (Movie Direction Index). The intent was to evaluate direction preference for bars along the "optic flow" axis; that is, the axis of motion passing through the receptive-field center in optic flow movies. When computed for bars, forward motion in this index was replaced with directions down and to the left, and reverse motion, with directions up and to the right. Thus if a cell's response to down/left bar motion was greater than to up/right motion, the index value was 1  response to up/right motion/response to down/left motion. Otherwise, the index value was (1  response to down/left motion/response to up/right motion).

View larger version (18K): [in this window] [in a new window]   FIG. 3. Preferred bar directions. A: best directions for 258 cells responsive to movies. B: best directions for 105 cells not responsive to movies. Cells with weak direction preferences (direction index for bars < 0.25) were excluded.

	RESULTS

Abstract Introduction Methods Results Discussion References

Two series of experiments were performed in this study. In the first series, we compared the responses of LS cells to bars and to the optic flow movies described in the preceding paper. In the second series, we compared cells' direction tuning using two kinds of stimulus, a moving bar and a large textured field moving in a frontoparallel plane.

Cell responses to optimal moving bars and to optic flow or texture movies are compared in Fig. 1. In most cases the comparison was made with the use of the response to an optic flow movie because this was the more effective stimulus, but when responses to texture movies were stronger, these are illustrated. In general, responses were stronger to bars than to movies, although a small subset of cells (marked with an arrow in Fig. 1) responded well to movies but failed to respond to any bar.

Do bar response properties predict responsiveness to large-field movies?

We looked for a correlation between responsiveness to movies and selectivity for bar length. Strongly end-stopped cells might respond poorly to movies because any suppressive receptive-field regions responsible for end-stopping presumably would be stimulated to some degree by large-field movies. Similarly, cells that summate strongly for bar length might not respond well to a display composed of small disks. However, in a sample of 277 cells, we found no relationship between either end-stopping or length summation and responsiveness to movies.

Because images in an optic flow field expand and accelerate as the observer locomotes, a preference for optic flow over texture movies (which lack these motion cues) might be linked to a preference for expanding, accelerating bars. For 101 cells, responses were compared for 2 optimal bars moving in the cell's preferred direction: one bar expanded and accelerated, and the other maintained constant size and speed. We found that cells responded similarly to the two kinds of bar, even when they strongly preferred optic flow to texture movies.

View larger version (25K): [in this window] [in a new window]   FIG. 4. Strength of response to movies as a function of the difference between preferred bar direction and optic flow direction (same cells as in Fig. 3A). Black dots represent cells that preferred movies shown in the forward direction, and white dots, cells that preferred movies shown in reverse. There is no correlation between responsiveness to movies, and the similarity between preferred bar direction and optic flow direction.

Direction of motion is a potent motion cue for cells in LS (e.g., Camarda and Rizzolatti 1976; Hubel and Wiesel 1969; Spear and Baumann 1975; Wright 1969). One would expect that the agreement between a cell's preferred direction and the directions of motion that it saw in movies would determine the strength of its movie response. Because the cat's fixation point was constant relative to its simulated heading point, the direction of motion seen in movies depended solely on receptive-field location. Although images move in many directions in an optic flow movie, the range of directions seen by a single receptive field in LS is fairly modest, as illustrated in Fig. 2A. All the receptive fields we studied were located in the lower left quadrant. For such a receptive field, what we might refer to as the "optic flow" direction (that is, the direction of image motion through the receptive-field center when the movie was run in the forward direction) will be down and to the left. A polar histogram of the optic flow directions seen by our cell sample is shown in Fig. 2B.

View larger version (24K): [in this window] [in a new window]   FIG. 5. Direction tuning for bars, measured as half-width at half-height of the Gaussian curve fitted to each cell's bar responses. A: cells responsive to movies. B: cells not responsive to movies. Overall, cells in the 1st group were more broadly tuned than those in the 2nd group (2 test, P < 0.005, df = 12), but even so, the majority of cells responding to movies had tuning half-widths of <30°.

The preferred bar directions of our cells, shown in Fig. 3, matched this distribution of optic flow directions only poorly. The sample contained a dearth of preferences for directions down and to the left, and this was equally true of cells that responded to movies, and ones that did not.

We expected to find that cells whose preferred direction (as measured with bars) was close to their optic flow direction would respond better to movies than cells with inappropriate preferred directions. But there was no such correlation. Figure 4 shows that responsiveness was similar whether there was a good match between preferred direction and the optic flow direction, or a poor match.

Not only preferred direction, but breadth of direction tuning must be considered when asking whether a cell is likely to respond to a particular optic flow movie. A broadly tuned cell presumably would tolerate a greater discrepancy between the directions of image motion in movies and its own preferred direction than would a sharply tuned cell. A comparison of cells that did respond to movies with those that did not lends some support to this idea (see Fig. 5). Cells responsive to movies had a median direction-tuning value of 31° (measured as half-width at half-height of the fitted Gaussian curve; Fig. 5A). Cells that did not respond to movies were significantly more sharply tuned (Fig. 5B), with a median value of 24° (² test, P < 0.005). However, many cells that failed to respond to movies were as broadly tuned as those that did. Conversely, a number of sharply tuned cells responded well to movies.

View larger version (19K): [in this window] [in a new window]   FIG. 6. Direction preference along the optic flow axis (A and B), or along the axis optimal for bars (C). A: direction preference for movies. Movie Direction Index values are redrawn from the preceding paper, excluding cells that did not respond significantly to bars. B: direction preference for bars along the optic flow axis, calculated with the formula for Movie Direction Index (see METHODS). On the whole, direction preferences were weak or nonexistent for bars along this axis. C: conventional direction index for bars, calculated on a scale from 0 to 1 along the axis optimal for bars.

View larger version (25K): [in this window] [in a new window]   FIG. 7. Polar plots for 8 cells showing direction tuning for bars (shaded gray), and responses to optic flow movies (black line terminated with black dots). For 2 cells (A and D), responses to texture movies are shown instead. Scales indicate response level in spikes/s.

Discrepant responses to bars and movies

An unexpected finding was that cells usually had a much stronger direction preference for movies than for bars along their optic flow axis. In the preceding paper we reported that most cells, if they responded at all to movies, had a strong preference for one of the two directions tested (forward or reverse). These data (excluding cells that did not respond significantly to bars) are shown again in Fig. 6A; the median value for cells preferring forward motion was 0.8, and for reverse motion, 0.77. But the strength of direction preference for bars along the optic flow axis was generally much weaker. The distribution of these bar direction preferences was broad and unimodal around 0 (Fig. 6B; note that a value of 0 signifies no direction preference). When strength of direction preference was calculated with the use of each cell's preferred bar direction, as is conventional, slightly higher values were found (median = 0.48, Fig. 6C), but still substantially lower than we obtained using movies.

The most interesting discrepancy between responses to bars and to movies occurred for cells that responded well to movies, but much more weakly or not at all to bars moving in the same direction seen in movies (that is, the optic flow direction). About one-third of the cells that responded to movies fell in this category. Figure 7 illustrates this phenomenon for eight cells. Polar plots show direction tuning for bars, and the black line indicates responses to optic flow movies run in the forward and reverse directions. Most commonly, the best direction for bar stimuli was substantially different from that seen in movies. The strong responses to movies are particularly surprising given the sharp directional tuning of these cells for bars.

Cells exhibiting this sort of paradoxical behavior differed in some respects from those that did not. They overwhelmingly preferred movies shown in the forward direction and exhibited particularly strong directional preferences for movies. In both respects the difference between cell groups was significant (² test, P < 0.005).

Cells that instead responded better to bars than to movies along the optic flow axis were in the minority, forming 23% of the sample. Curiously, all but three of them had receptive fields located within 10° of the vertical meridian, whereas receptive fields for the sample as a whole had azimuths of up to 30°.

Discrepant direction tuning for bars and texture movies

The strong responses of many cells to optic flow movies in directions that yielded poor responses to bars suggested that their direction tuning for large, complex stimuli might be rather different from that for bars. We tested this possibility in a second set of experiments in which we compared direction tuning for optimal moving bars with direction tuning for texture movies. Given the preference of such cells for optic flow movies, it would have been desirable to test direction tuning using these stimuli, but technically this was not possible.

We constructed polar plots showing each cell's direction tuning for bars and for texture movies. As we found in the first set of experiments, responses were generally stronger to bars than to texture, and we excluded cells with texture responses <33% of their bar responses because determination of direction tuning from very weak responses may be unreliable. The remaining sample was still sizable (407 cells). The similarity between direction tuning for the two kinds of stimuli was measured as the percentage of overlap between the two normalized direction-tuning curves, with the area of the broader direction-tuning curve taken to equal 100%. The overlaps for all cells are shown in Fig. 8. The majority of cells showed some similarity in direction tuning for the two kinds of stimulus; the median overlap was just over 60%. However, we also found cells whose direction-tuning curves for bars and texture were almost nonoverlapping.

View larger version (24K): [in this window] [in a new window]   FIG. 8. Histogram of the overlap between the direction-tuning curve found for bars, and the direction-tuning curve found for texture movies, for 407 cells. Overlap is given as a percentage of the tuning curve with the greater area.

A subset of cells (~20%) showed a kind of paradoxical behavior similar to what we had observed when comparing responses to optic flow movies and bars in the first set of experiments. That is, they responded well to a texture stimulus in a direction that elicited little or no response when tested with a bar stimulus. Polar plots of direction tuning are illustrated in Fig. 9 for eight cells. Their preferred direction for texture was different from their preferred direction for bars. There was not, however, any bias for texture directions down and to the left that might explain the preferences of cells for optic flow movies.

View larger version (29K): [in this window] [in a new window]   FIG. 9. Polar plots for 8 cells showing direction-tuning curves for bars (shaded gray), and direction-tuning curves for texture movies (outlined with black line). These cells belonged to a subset whose best direction for texture movies elicited weak or no responses using bars. Scales give response level in spikes/s.

	DISCUSSION

Abstract Introduction Methods Results Discussion References

The central finding of this study was that responses in LS to optic flow and texture movies were not well correlated with responses to solitary moving bar stimuli. Because bars are quite effective stimuli for the great majority of neurons in LS (Camarda and Rizzolatti 1976; Hubel and Wiesel 1969; Spear and Baumann 1975; Wright 1969), we had assumed that response properties demonstrable with bars would generalize to other, less effective stimuli. But we did not find this to be the case.

Perhaps the most puzzling discrepancies between responses to bars and to movies concerned direction-selective behavior. Direction selectivity is one of the most notable characteristics of neurons in LS (see Camarda and Rizzolatti 1976; Hubel and Wiesel 1969; Spear and Baumann 1975; Wright 1969). We found that cells generally showed a much stronger directional preference for optic flow movies than they did for bar stimuli, even though the axis along which directional preference was determined for movies was rarely optimal for the cell. Another surprising finding was that many cells had different preferred directions for texture movies than for bars. Finally, we found that a subset of cells responded well to optic flow or texture movies in directions that elicited only weak responses to bars.

There has not been any systematic comparison of responses in LS to bars and to large, complex stimuli in previous studies. However, in the middle temporal visual area (MT), the probable primate analogue of LS (Payne 1993; Zeki 1974), some neurons may show different direction selectivity for texture than for bars. Albright (1992) found that preferred directions for bars and texture differed by >45° for one-third of his sample from the macaque's MT. The texture stimulus used by Albright was not comparable with ours, however; it was relatively small (11° diam) and contained only second-order motion. Olavarria et al. (1992) tested MT cells with texture displays that were more similar to ours in size and in motion quality. These authors compared the strength of direction preference along the axis optimal for bars and found that for some cells the degree of directional preference for texture differed from that observed for bars. Finally, Felleman and Kaas (1984) made similar observations in the owl monkey's MT, although their sample was quite small (15 cells).

Cells that responded briskly to optic flow movies but not to bars moving in the dominant optic flow direction would appear to have different direction tuning for optic flow movies than for bars. It could be argued, however, that this was an epiphenomenon stemming from the fact that we only tested motion along one axis for optic flow movies. Conceivably, direction tuning is identical for bars and movies, but movies are much more effective stimuli than bars, so they elicit strong responses in a direction in which bars elicit weak responses. Inspection of direction-tuning curves for bars (Fig. 7) makes this argument appear doubtful. For a given cell, the hypothetical direction-tuning curve for optic flow movies would be a scaled-up version of that for bars, with the scaling factor based on the ratio of response to bars and movies along the axis tested for movies. It is obvious that the predicted response levels to movies in the best bar direction would be impossibly high for many cells (for example, 1,692 spikes/s for the cell in Fig. 7A). Moreover, when we directly compared direction tuning for texture movies and for bars, we found that many cells showed strikingly different direction-tuning curves for the two kinds of stimulus (e.g., Fig. 9).

How can we account for strong responses to movies with image motion in directions inappropriate for bars? Both receptive-field centers and surrounds might make a contribution, but a surround mechanism seems particularly likely based on previous studies. LS neurons are reported to have huge silent surrounds, and activation of these surrounds by fine-grained random dots moving in the preferred direction suppresses responses to such motion in the receptive-field center (in LS: Hamada 1987; von Grunau and Frost 1983; in MT: Allman et al. 1985; Tanaka et al. 1986). Random dot motion in the surround in the opposite direction, on the other hand, commonly facilitates center responses (Allman et al. 1985; von Grunau and Frost 1983). From these findings one can predict how cells should respond to large-field texture displays. Responses in the direction preferred for bars should be reduced, but the suppressive effect should diminish for directions increasingly different from optimal, so that the direction-tuning curve for texture should be broader and lower than that for bars. It was common to find cells with broader direction tuning for texture than for bars. However, many cells had direction-tuning curves for texture that were completely different from those for bars (e.g., Fig. 9), a finding not easily explainable by the known properties of the silent surround.

In optic flow movies, unlike texture movies, images in the receptive-field surround move in many directions. It is not known how receptive-field surrounds respond to such motion, and thus we can only speculate that optic flow might engage both suppressive and facilitatory surround mechanisms simultaneously. Interestingly, optic flow movies were more effective than texture in eliciting strong responses in directions poor for bars. In the first set of experiments, the great majority of such responses were elicited by optic flow movies. Moreover, the percentage of cells showing such responses in these experiments (~33%) was considerably greater than the percentage (19%) from the second series of experiments using texture movies. Finally, a strict comparison between the two sets of experiments would limit cells in the second sample to those that responded well to directions close to the optic flow axis (i.e., the axis tested for optic flow movies). Considering motion only along this axis, the number of cells responding much better to texture than to bars drops to 7% in the second series of experiments.

While we have stressed the stimulus-dependent nature of direction tuning, Albright (1992) has instead emphasized what he terms form-cue invariant behavior by cells in MT. He has argued that most cells in MT respond strictly to motion cues, displaying essentially the same preferred direction, degree of direction preference, and direction tuning regardless of other stimulus features. Olavarria et al. (1992), on the other hand, emphasized the sizable minority of cells in MT that do not fit this description. In our samples, many cells clearly departed from strict form-cue invariance, particularly when tested with optic flow movies.

Strong responses to large, complex stimuli moving in directions that were ineffective for bars might be considered a kind of context-dependent behavior. The context in this instance consists of images outside the receptive-field center. In our experiments, the background was a stationary gray field when bar stimuli were presented, and to some extent thus simulated the experience of a stationary observer, who most commonly sees isolated images moving against a static background. Responses to moving bars might accurately predict cell responses in this situation. The visual context during locomotion is entirely different, being an optic flow field in which virtually all background images are in motion. We would expect that the majority of cells showing unexpectedly strong responses to optic flow movies would be active during locomotion, whatever their stimulus selectivity for solitary moving stimuli.

	ACKNOWLEDGEMENTS

  We gratefully acknowledge the helpful comments of P. Abel, D. Dacey, B. O'Brien, and J. Olavarria on this manuscript.

  This work was supported by Grant RO1 4847 and by the Royalty Research Fund of the University of Washington.

	FOOTNOTES

  Address for reprint requests: H. Sherk, Dept. of Biological Structure, University of Washington, Box 35-7420, Seattle, WA 98195-7420.

  Received 1 August 1996; accepted in final form 17 October 1996.

	REFERENCES

Abstract Introduction Methods Results Discussion References

• ALBRIGHT, T. Form-cue invariant motion processing in primate visual cortex. Science Wash. DC 255: 1141-1143, 1992.[Abstract/Free Full Text]
• ALLMAN, J., MIEZIN, F., MCGUINNESS, E. Direction- and velocity-specific responses from beyond the classical receptive field in the middle temporal visual area (MT). Perception 14: 105-126, 1985.[Medline]
• CAMARDA, R., RIZZOLATTI, G. Visual receptive fields in the lateral suprasylvian area (Clare-Bishop area) of the cat. Brain Res. 101: 427-443, 1976.[Medline]
• FELLEMAN, D. J., KAAS, J. H. Receptive field properties of neurons in the middle temporal visual area (MT) of owl monkeys. J. Neurophysiol. 52: 488-513, 1984.[Abstract/Free Full Text]
• HAMADA, T. Neural response to the motion of textures in the lateral suprasylvian area of cats. Behav. Brain Res. 25: 175-185, 1987.[Medline]
• HUBEL, D. H., WIESEL, T. N. Visual area of the lateral suprasylvian gyrus (Clare-Bishop area) of the cat. J. Physiol. Lond. 202: 251-260, 1969.[Abstract/Free Full Text]
• OLAVARRIA, J. F., DEYOE, E. A., KNIERIM, J. J., FOX, J. M., VAN ESSEN, D. C. Neural responses to visual texture patterns in middle temporal area of the macaque monkey. J. Neurophysiol. 68: 164-181, 1992.[Abstract/Free Full Text]
• PAYNE, B. R. Evidence for visual cortical area homologs in cat and macaque monkey. Cereb. Cortex 3: 1-25, 1993.[Abstract/Free Full Text]
• SPEAR, P. D., BAUMANN, T. P. Receptive-field characteristics of single neurons in lateral suprasylvian visual area of the cat. J. Neurophysiol. 38: 1403-1420, 1975.[Abstract/Free Full Text]
• TANAKA, K., HIKOSAKA, K., SAITO, H., YUKIE, M., FUKADA, Y., IWAI, E. Analysis of local and wide-field movements in the superior temporal visual areas of the macaque monkey. J. Neurosci. 6: 134-144, 1986.[Abstract]
• VON GRUNAU, M., FROST, B. J. Double-opponent process mechanism underlying RF-structure of directionally specific cells of cat lateral suprasylvian visual area. Exp. Brain Res. 49: 84-92, 1983.[Medline]
• WRIGHT, M. M. Visual receptive fields of cells in a cortical area remote from the striate cortex in the cat. Nature Lond. 223: 973-975, 1969.[Medline]
• ZEKI, S. M. Functional organization of a visual area in the posterior bank of the superior temporal sulcus of the rhesus monkey. J. Physiol. Lond. 236: 549-573, 1974.[Abstract/Free Full Text]

0022-3077/97 $5.00 Copyright ©1997 The American Physiological Society