- Email: [email protected]
Responses of visual cortical neurons to curved stimuli and chevrons
Vision Res. Vol. 30. No. 2, pp.235-248, 1990 Printed in Great Britain. All rights reserved
0042-6989/90
53.00 + 0.00
Copyright0 1990F%rgamon Pressplc
RESPONSES OF VISUAL CORTICAL NEURONS CURVED STIMULI AND CHEVRONS
TO
MARK VERSAVEL,GUY A. ORBAN+ and LIEVENLAG@ Laboratorium voor Neuro- en Psychofysiologie. Katholieke Universiteit te Leuven, Campus Gasthuisberg, Herestraat. R-3000 Leuven, Relgium (Received 13 October 1988; in wired form 12 April 1989) Abstract-Single cells were recorded in area 17 of anaesthetixed and paralyxed cats and their responses to curved stimuli and chevrons compared. Striate cells exhibited three different response patterns. A first group responded optimally to a straight line (i.e. xero curvature) and responded similarly to chevrons and to curved lines. A second group responded to all curvatures and was broadly tuned for the straight line when tested with chevrons. A third groupresponded only to large curvatures, many (2/3) to both signs of curvature and a number (l/3) to only one sign. Cells in this group responded differently to chevrons and curved lines. Cells in these three classes differed both in length-response curve and in width of orientation tuning. Laminar analysis revealed that the three classes are distributed differently across cortical layers. These data shed new light on the finding of Malpeli and coworkers that orientation is extracted at least twice in a cortical column. Curvature
Orientation
Endstopping
Angular diiercnce
Striate cortex
Single cells
cats
INTRODUCTION
Although Hubel and Wiesel(l965), had suggested that hypercomplex cells could serve to Since Attneave (1954) first demonstrated the measure curvature, the initial physiological significance of maximum curvature points for studies of striate cell responses to bent stimuli human form perception, several psychophysical (Heggelund & Hohmann, 1975; Hammond & studies have been devoted to the perception of Andrews, 1978) were restricted to endfree, curvature (Ogilvie & Daicar, 1967; Riggs, 1973, i.e. non-hypercomplex cells. Heggelund and Andrews, Butchner & Buckley, 1973; MacKay Hohmann (1975) who used curved edges, ob& MacKay, 1974, Blakemore & Over, 1974; served that simple cells’ (n = 8) responses deWatt & Andrews, 1982; Watt, 1984; Wilson, pended upon curvature, the optimum generally 1985). A number of these studies (Andrews et being zero curvature (straight line), while comal., 1973; Riggs, 1973; MacKay & MacKay, plex cells’ (n = 5) responses were insensitive to 1974)have suggested the existence of “curvature curvature changes. Hammond and Andrews detectors”, i.e. cells encoding curvature or (1978) compared responses of 20 striate cells to explicitly representing curvature in addition to chevrons and straight lines. In this study, the orientation. Other studies (Blakemore & Over, best response was always obtained using a 1974; Wilson, 1985) have concluded the oppostraight line of optimal orientation. Hence these site and have suggested that curvature is initially two studies concluded that individual striate sampled by local orientation selective mechcells could not detect curvature. It has been only anisms and subsequently computed from the recently that Hubel and Wiesel’s suggestion has output of these lower order mechanisms by been tested explicitly by Dobbins, Zucker comparing orientations at different positions. and Cynader (1987). These experiments were Finally Watt and Andrews (1982) suggested that triggered by the computational theory of curvature estimation is performed in parallel by orientation selection developed by Zucker two mechanisms, one for straight lines and one (1985). According to this author, the initial for highly curved lines. measurements of orientation obtained by orientation selective mechanisms are insufficient to estimate orientation. However, if curvature in*Towhom correspondence should be addressed. formation is available, inappropriate responses tResearch fellow of the National Research Council of can be eliminated at a second stage, since Relgium. 235
236
MARK VERSAVELet al
curvature represents the spatial derivative of orientation. Dobbins et al. (1987) reported that all 15 carefully examined endstopped (or hypercomplex) striate cells had a clearly peaked curvature response curve, while a nonspecified number of endfree (or non-hypercomplex) striate cells had a non-peaked curve, which in fact, judging from their figure, seemed to be broadly tuned for zero and small curvatures. Furthermore, Dobbins et al. (1987) suggested that striate cells cannot only encode curvature magnitude, but also curvature sign, since onethird of the endstopped cells responded more strongly to one direction of curvature than to the other. The present experiments were undertaken to test how different the curvature response curves of endfree and endstopped striate cells really are, since it has been shown that a number of striate cells have intermediate endstopping (Rose, 1977; Kato, Bishop & Orban, 1978). Since earlier positive and negative physiological reports not only focused on different cell types, but also used different stimuli, a second objective of the present study was to compare responses of striate cells to curved lines with those to chevrons. The final aim of this study was to relate curvature selectivity to other cell properties such as orientation selectivity and laminar position, in order to get insight into the mechanisms underlying curvature selectivity. METHODS
General procedure Our methods are very similar to those described previously (Orban, Kennedy & Maes 1981) and only a brief description is needed here. Cats were anesthetized with ketamine or alfathesine for initial surgical procedures. The experiments were performed on cats placed in the stereotaxic apparatus by means of a painless headholding device cemented to the skull and anesthetized with a N,O/O, (70: 30 mixture) and a continuous perfusion of Nembutal (1 mg *kg-’ *hr- I). The animals were paralyzed with a continuous infusion of Flaxedil and d-tubocurarine. The expiratory CO2 and rectal temperature were held constant. Pupils were dilated, corneas protected by afocal Silflex contact lenses and refractive errors corrected by spectacle lenses. Single units in the visual cortex (area 17) recorded with glass-coated tungsten electrodes, were explored qualitatively with handheld stimuli and studied quantitatively with moving stimuli rear-projected onto a pola-
coat screen located 1.71 m from the cat. Several electrolytic lesions were made in a penetration. Penetrations were histologically reconstructed on frozen sections stained with cresyl violet. Handplotting was used to determine the preferred orientation, the width of orientation tuning, the ocular dominance and the degree of endstopping. The minimum discharge field was measured using a narrow moving light bar (Kato et al., 1978). The receptive field (RF) width is defined as the dimension of the minimum field orthogonal to the line of optimal orientation. The position of the RF was referred to the assumed position of the area centralis derived from the position of the blind spot (Bishop, Kozak & Vakkur, 1962; Nikara, Bishop & Pettigrew, 1968). Frequent back projection of the blind spot allowed us to correct for the slow drift of the eyes. Visual stimulation Two visual stimulators, both under computer control, were used. In both stimulation systems slides were projected onto the tangent polacoat screen facing the cat. The images of the two stimulators were mixed by a beam splitter. The images could be moved by turning mirrors mounted on a General Scanning@ motor whereby the computer controlled speed and position of the images. Since the computer had no direct control of the shape of the stimuli shown by the slide projector, slides with multiple stimuli were used to reduce the amount of manipulation necessary to test curvature selectivity and to offset variability. Five stimuli were presented on one slide and moved through the RF in succession. The separation between stimuli was 7 deg ensuring that for slowly moving stimuli (typically l-4 deg/sec) the responses were clearly separated in time. Each slide included as center stimulus a 0.3 deg wide straight line, used as reference for normalization. One set of slides, used for endfree cells, contained 12 deg long bars as references and a second set, used for endstopped cells, included 2 deg long bars as references. For the preliminary testing of length summation, orientation tuning and lengthwise centering of the stimuli, such slides with multiple stimuli were used. A set of two slides was used to present 0.3 deg wide bars of 7 different lengths ranging from 0.5 to 12 deg length. In this set, both 2 and 12 deg long bars were present in the two slides. In order to determine the optimal orientation, a single slide was used containing
Responses of visual cortical neurons
0.3 deg wide bars, either 12 or 2 deg long and ranging in orientation from - &(anticlockwise) to 30 deg in 15 deg steps, or from - 20 to 20 deg in 10 deg steps. In order to test the lengthwise centering, a slide with 3 deg long bars offset lengthwise from -3 deg (below center) to + 3 deg (above center) in 1.5 deg steps was used for endfree cells. For endstopped cells, a slide with 1 deg long lines offset from -2 to +2 deg was used. Four slides were used to test curved lines and chevrons, yielding 16 different curvatures or chevrons plus the straight line (zero curvature). Eight curved lines or chevrons were convex in the forward direction of motion and given a positive sign and eight curved lines or chevrons were concave in the forward direction of motion and given a negative sign. Since comparing responses to opposite signs of curvature was critical, each slide contained only two curvatures or two chevrons angles each with the two stimuli of opposite sign. Chevrons were made of two 6 deg long, 0.3 deg wide line segments deviating from the straight tine by an angle (the chevron angle) ranging from 10 to 80 deg in
237
10 deg steps and these line segments were disposed symmetrically with respect to the tangent line of the RFs prefemd orientation. Curved lines were 0.3 deg wide and made of segments of circles with 8 different radii ranging from 0.5 to 16.66 deg. For small radii (up to 3 deg) half circles were used. For larger radii (from 4.5 deg on) the chord length was limited to 6 deg, resulting in segments which were less than half circles. Stimulus curvature is defined as the inverse of the radius, ranging from 2 to 0.06. For the curved lines with small curvatures (up to 0.22 i.e. radius of 4.5 deg) the chord length was equal to the length of the chevron line segments. The curvature values were chosen in such a way that the orientation of the chord equalled that of the chevrons segments of angles ranging from 10 to 40 deg. For large curvatures this was not possible since orientation of the chords remained at 45 deg from the straight line while the angle of chevrons increased up to 80 deg. All these slides were available either as light stimuli or as dark stimuli on a homogeneous background of 4.9cd/m* and with a contrast
UNIT 13309
2SC ,...” ,,..‘.
.~
1
,,_.”
:.“’ .’ ,:’ .,: ,;’
_.
,r
/’
1
,.,...‘..
,, ,_... .‘.’
,.: ,.:.
,?’,,.:. ,:’,t
/...‘.:’
,
..’
i/-
,/.’ 0
a
4 lorlolh
6 s cdmomr1
Fig. 1. Complete test series of a cell preferring zero curvature (class I). (A) Orientation tuning. (B) Length-excitability pro&. (C) Lengtkesponse curve. (D) Curvatur+response curve and (E) chevron ang&rupoa~ curve.The full line connecting dots represent the medium response; the stippkd lines upper and lower quartiles. Number of stimulus presentations: (A, B and C) 8 presentations; (C and D) 10 presentations.
lo
l-2
MARKVERSAVELet al.
238
(log AI/Z) of -0.09 in positive (light) or negative (dark) polarity. Quantitative testing The neurons were tested quantitatively with a multihistogram technique (velocity series) or a multiple stimuli technique (other parameter series) to offset response variability. The times of occurrence of the action potentials were stored on disc for further offline analysis. A 0.3 deg wide optimally oriented light and dark bar were presented to the dominant eye for the light and dark bar velocity multihistogram. The length was 30deg for endfree cells and a shorter, optimal length for endstopped cells. In the light and dark bar velocity multihistogram 4 x 11 conditions were interleaved corresponding to two directions of motion of light and dark bars and 11 speeds ranging from 0.5 to 512 deg/sec. By superimposing the light slit projected by one projector onto the light part of the dark bar projected by the other stimulator, one can arrange the stimuli in such a way that the contrast of both bars is of opposite polarity but equal in magnitude. This test provides quantitative definition of RF structure, direction selectivity and velocity sensitivity. Cells were classified with respect to these three characteristics as described previously (Gulyas, Orban, Duysens & Maes, 1987). The light and dark bar velocity test was used to select the optimal speed as well as the contrast polarity used for the following tests. The next test was a length series in order to measure the length-response curve. The degree of endstopping determined the
A
B
choice of long or short reference lines in the subsequent testing. Once the optima1 orientation had been checked quantitatively, the lengthwise centering was controlled. Cells were tested for curvature and chevron angle only after these preliminary tests had been completed (see Fig. 1). Analysis of the multiple stimuli tests While the analysis of the velocity multihistograms was done according to procedures standard to our laboratory (Orban et al., 1981; Gulyas et al., 1987), the analysis of tests based on slides with multiple stimuli is novel. A peak detection program was used to locate and to determine the limits of the five responses in the PSTH corresponding to the five stimuli moving through the RF. This histograms were constructed with binwidths adapted to the stimulus speed, starting with a binwidth of 512 msec for 0.5 deg/sec speed and halving the binwidth each time the speed doubled up to 32 msec for 8 deg/sec, the fastest speed used in the multiple stimuli tests. Histograms were smoothed by applying the algorithm
nine times, where ci is the number of spikes in bin i. Peaks were detected as those bins where the firing rate exceeded the 95% significance level centered on local maxima. The peak limits were set by taking 7 bins exceeding the significance level and centered as much as possible on the highest bin. The computer then performed a run-by-run analysis to measure the average
C
Fig. 2. Comparison of tuning width for curvature, chevron an& and orientation range. (A) Definition of the cquivaknt chevron: a is the chevrou an$c of the equi*t chevron of the 4wved stimulus. (B)Tuaing~dthofdarIforcurnt~~ut\laial~fort&eequivlrknt~~piottad as a function of actual tuning width for dtevrons. (C) Tuning width for chevrons of class I and II c&b plotted as a function of their orientation mqe. Lets rafer to &la shown in other figures: (a) unit 133096 (Fig. I); (b) unit 11615 (Fig. 3).
Rcsponscs of visual cortical neurons
firing rate in the intervals between the peak limits for each stimulus presentation. The median and quartiles of these response distributions were computed. Finally responses belonging to a single stimulus series (such as length, curvature or chevron angle series) but measured in different RSTHs, corresponding to different slides, were normalixed by expressing these responses as a percentage of the responses to the reference stimuli. These relative responses were then converted back to absolute values by multiplying the control response (100%) with the average response evoked by the reference stimulus in different slides. The amount of normalization was relatively small, since the median amount for all tests and cells was 1, the first and third quartiles were 0.8 and 1.5 respectively, and the extreme values 0.2 and 4.5. The degree of endstopping of a cell was derived from the length-response curve as follows: the difference between the response to the bar of optimal length and a 12 deg bar was expressed as the percent of the optimal response.
239 UNIT 11615
RESULTS
Curvature response curves were obtained for 45 area 17 cells. With the exception of 3 cells, their RFs were located within 10 deg of the fixation point. The layering of 37 cells was recovered from the histological reconstruction of the penetrations: 8 cells were lotted in layers 2-3, 7 in layer 4, 6 in layer 5 and 16 in layer 6. 30 of the 45 cells were also tested with chevrons. Cortical cells responded to curved stimuli and chevrons in 3 different patterns. Each of these response classes will first be described before indicating the general properties of these three groups.
Fig. 3. Cell without preference for curvature (class II). (A) Curvatumaponre curve. (B) Chevron angle-rqonac curve. Same convention as Fig. 1. Ten stimulus presentations.
this cell was 33 deg, which is very similar to that obtained with straight lines (27 deg). In order to compare the tuning for curved stimuli and chevrons, we de&d the equivalent chevron for curved stimuli as follows: it is the chevron of which the stripes are tangent to the curved stimulus at the points halfway between the Cells preferring straight lines (zero curvature) RF center and the ends of the length axis of RF measured from the length-response curve Figure 1 shows the behaviour of a cell typical (Fig. 2). For cell 13309 the tuning width for of this group. The cell in Fig. 1 was a velocity curvatures corresponded to a width at half low pass, non-direction selective S cell, sharply height for the equivalent chevron ,of 36 deg, tuned for orientation (the width at half height close to the value actually obtained with was 27 deg). The cell showed considerable chevrons. length summation, and the endstopping index For the whok group of cells in this class, the was zero (Fig. 1C). When tested with curved tuning width obtained with chevrons and the stimuli the cell responded only for near-zero one derived from the responses to curved stimuli curvatures, the straight line being optimal were almost identical. As shown in Fig. 2, the (Fig. 1D). Similarly, when tested with chevrons, data (a = 9) were ahnost perfectly fitted by a straight lines and obtuse chevrons (i.e. small diagonal line through the origin chevron angles) were optimal. The width of tuning at half height obtained with chevrons for (Y = - 1.7 + 1.03 x, r - 0.99, P < O.OOOOOl).
MARK VERSAVEL~~~I.
240
If the equivalent chevron was defined as the chevron tangent to the curved stimulus at the endpoints of the RF, the datapoints plotting the two tuning widths were fitted by a straight line through the origin of slope 2 rather than 1. This means that for these cells a curved stimulus is equivalent to a chevron whose diagonal stripes have the orientation of the chords fitted to the part of the curved stimulus covering the RF. Celis without preference for curvature A substantial proportion of cells had little preference for any curvature. Figure 3 illustrates the response pattern of this class of cells. The cell in Fig. 3 was a non-direction selective velocity broad-band C cell recorded in layer 6. The cell had a relatively broad o~entation tuning (orientation range estimated manually at 60 deg) and showed only marginal endstopping (endstopping index 23). The length-response curve aiso revealed that the c&l responded well to short stimuli: its response to a 0.5 deg long bar was about 70% of the optimal response to a 2 deg long bar. As shown in Fig. 3A, this cell responded equally well to all curvatures. In fact
the responses to the extreme curvatures are even slightly larger than that to the straight line. While cells in the previous group responded very similarly to chevrons and curved stimuli, cells in this group characteristically responded dgerently to the two types of stimuli. As shown in Fig. 3B cell 11615 did not respond to acute chevrons (i.e. large chevron angles) although it did respond well to extreme curvatures. In fact for chevrons the cell is broadly tuned to zero chevron angle i.e. a straight line. In this cell, the width of tuning at half height for chevrons was 85 deg. This was fairly typical, since the tuning for chevrons was considerabie wider in this group of cells than for the previous group: median width at half height was 62 deg (n = 9) for group II cells compared to 40 deg (n = 9) for the previous group. This is in keeping with the fact that on average, this group of cells had a wider orientation tuning than that of the previous group (see below). Considering group I and group II cells together, there was an excellent correlation (r = 0.86) between the tuning width for chevrons and the orientation range measured by handplotting (Fig. 2C).
UNIT
c
12w4
2s
i 1
10 ~
5
._...
..:
~
I
I
-1.5
-1
-QS
0
QS
3
N-
Fig. 4. Cds p&ring
extreme curvatures (clam III). (A, C) Curvature-response curves. (B, D) Chevron
angle-rcsponsccurves. (A, B) Cell without adcctivity for curvature sign (IS stimulus presentations). (C, D) till preferring negdvc curvatures (12 stimulus presentations).
15
Rcsponscsof visual cortical neurons
241
Cells preferring extreme curvatures
In contrast with cells of the first group, which responded only to near-zero curvatures, a numher of cells responded only to extremely curved stimuli. As for cells of the second class, responses of the cells preferring extreme curvatures were di&ent for curved stimuli and chevrons. Figure 4 illustrates two cells of this type. The cell in Fig. 4A was a non-direction selective, velocity broad-band HC cell recorded in layer 6. Characteristically this cell was strongly endstopped: its endstopping index was 97. Consequently this cell hardly responded to a long straight line but fired vigorously when the two most curved stimuli traversed its RF. Comparison of the response strength for these optimal curvatures to that for an optimal, 2 deg long bar showed that the response levels were equivalent. Cell 13411 responded equally well to convex and concave curved stimuli, but responded better to a convex than to a concave acute chevron (Fig. 3B). The response level reached for the convex acute chevron was about the same as that elicited by extremely curved stimuli and a 2 deg long bar. Whereas cell 13411 responded equally well to both signs of curvature, cell 12914 (Fig. 4C) responded differently to both signs. Although there was some variability in the response to the extreme negative curvature, the response to the negative extreme curvature was significantly larger (0.1% on Mann-Whitney U test) than the response to the positive extreme curvature. Cell 12914 was a nondirection selective velocity low pass HS cell recorded in layer 6. Cell i2914 hardly responded to chevrons: the responses elicited by chevrons was about l/4 that elicited by the optimal curvatures. Also, the response of the cell to the optimal short bar (0.5 deg length) was less than half of that to the optimal curvature. On average, responses of cells in this group were about equal for optimal short bars and optimal curvatures: in 3 cells optimal curvature was better than the optimal bar (as in cell 12914), in 3 cells the reverse held, and in 4 cells (as in cell 13411) both types of stimuli elicited about the same response. Three out of 10 cells in this class responded well to curvatures of one sign and not to the other: two preferred negative curvatures (concave), one positive curvature (convex). For all three cells the response to opposite signs were significantly different at the 0.1% level when the responses to the extreme curvatures were compared. The preferred curva-
aJw*La.
indm
Fig. 5. Distribution of the curvature index in our sample: hatched area, class I cells, light axea class II cells, stippled area claw III ceils.
ture was one of the two most extreme curvatures. With respect to chevrons, only five cells were tested with this type of pattern. Two cells responded weakly to chevrons (as cell 12914), their response to the optimal chevron being at least four times weaker than that to the optimal curved stimulus, and three cells responded equally well to chevrons and curved stimuli (as cell 13411).These latter three cells, as cell 13411, responded as well to positive as to negative large curvatures, but responded better to acute chevrons of one sign than to acute chevrons of the other sign. How distinct are the three groups? The three groups described are defined by their relative response to zero curvature (straight lines) and extreme curvatures. Therefore we calculated for each cell the curvature index (CI) defined as follows. The difference in response between the average responses to the extreme curvatures of positive and negative sign and the response to zero curvature was normalized by dividing this difference by the largest of the two numbers and multiplying by 100. The distribution of this index CI is given in Fig. 5. Cells in group I (n = 14) all had CI smaller than - 60 while cells in group III (n = 10) all had CI larger than 60. The cell of Fig. 1 had a CI of - 100 and those of Fig. 4 a CI of 76 and 97 respectively. Cells in group II (n = 21) had CIs between - 50 and 50, meaning that the response to extreme and zero curvature differed at most by a factor of 2. The cell of Fig. 3 had a CI of -22. It is clear from Fig. 6 that the neurons in our sample are distributed along a continuum, and that they are assigned to discrete classes as a matter of convenience. A similar index was calculated for chevron responses. For group I the index was only
MARK VFJLWVEL et al.
242
marginally different for curved stimuli and chevrons. The median indices for cells of class I (n = 9) were -97 and - 79 for chevrons and curved stimuli respectively. For cells of class II however, the difference was much larger. For this class, the medians (n = 16) were - 89 (Q, = -95, Qj= -56) and -27 (Ql = -38, Q, + 18) for chevrons and curved stimuli respectively. For cells of class III, the indices were positive for chevrons, as they were for curved stimuli: the median index for the three of the five cells tested which responded well to chevrons was +95, a value close to +97, their median CI for curved stimuli.
to estimate quantitatively the tuning width. However, for those cells for which both measurements were available, there was a good correlation between quantitative and qualitative estimations, in agreement with previous studies (Wilson & Sherman, 1976; Blasdel, Mitchell, Muir & Pettigrew, 1977; Bullier, Kennedy & Orban, unpublished). Classes I and III are very distinct in the orientation range-endstopping index diagram (Fig. 6). Cells in class I all had endstopping indices below 30 and small orientation tuning ranges: the median values are 13 (quartiles 0 and 26) and 44 deg (quartiles 26 and 63 deg) for the endstopping index and the orientation range respectively. Cells in class III all had endstopping indices above 55 and had medium orientation ranges. The median endstopping index was 90 (quartiles 74 and 100) and the median orientation range was 57 deg (quartiles 50 and 83 deg). Cells of class II are more widely scattered and include those with little endstopping and wide orientation tuning as well as cells with moderate endstopping and narrow orientation tuning. Class II cells with an endstopping index below 50 had a significantly (P < 0.025) wider orientation tuning than those with an endstopping index above 50. The median endstopping index for class II was 38 (quartiles 22 and 53). The median orientation range 81 deg (quartiles 58 and 112 deg). Both values were significantly different from those of the other two classes.
Characteristics of the 3 groups
From the description given of the 3 cell groups it is clear that they differ not only in degree of endstopping but also in selectivity for orientation. We have used the orientation range as estimate for orientation selectivity and have plotted the orientation tuning range as a function of the endstopping index for all three classes (Fig. 6). Although less accurate than the width of orientation tuning at half-height, the orientation range measured by handplotting was available for all cells. Indeed the quantitative determination of orientation tuning was intended only to provide an estimate of the optimum orientation. In a number of cells the initial estimate of the optimal orientation was off by more than 10 deg, making it impossible
N.O.
.J +
140 -
+ +o
_ E -0
120’
l
++ loo-
0
0
l*
x 3 no-
*
0
5 ‘L 0
0
60-
Lo
0
l
0
a+ q
40-
;-
20-
o
D
0
+00+-E-
+
E ‘S 2
OA
+
+
4
+
0 0
+ 0
0
+
+
0
0
0 0’ I
0
I
,
I
,
10
20
SO
48
1
S
Endstopping
60
I
I
1
I
70
60
60
100
( Ye )
Fig. 6. Orientation range plottedaaa function of endstopping indexz (0) clam I cdls; (+) classI1 ceils; (0) classIII cells. Letters refer to units shown in other 5gum: (a) unit 13309 (Fig. 1); (b) unit 11615 (Fig. 3); (c) unit 12914 (Fig. 4 right); (d) unit 13411 (Fig. 4 left); (e) unit 12006 (gcniculate affmnt, Fig. 7).
Responses of visual cortical neurons
The three classes of striate cells differed not only in degree of endstopping, but their entire length-response curve was different. While class I cells hardly responded to short bars, classes II and III did respond relatively well. This is reflected by the response to 0.5 deg bar expressed as a percentage of the response to the optimal length. The median value of this parameter ranged from 0% (quartiles 0%, and 13%) in class I cells to 34% (quartiles 7% and 54%) and 53% (quartiles 31% and 100%) in classes II and III respectively. Also, the optimal length differed between classes: the median optimal length was 6 deg (quartiles 4 and 12 deg) for class I, 2 deg (quartiles 1 and 2.7 deg) for class II and 1 deg (quartiles 0.5 and 2 deg) for class III. There were relatively few correlations with other response properties, although cells of class III more frequently belonged to the S family (60%) than those of class II (33%). There was, however, a striking correlation with laminar position. Class II cells occurred mainly in layers 4 and 5, and to a lesser degree in the superficial layers, while the vast majority of the cells of the other two classes were located in layer 6 or to a lesser extent in layers 2 and 3 (Table 1). The higher incidence of class II cells in layers 4 and 5 compared to the other two classes was highly significant (x2 =i 7.75, d.f. = 1, P
Figure 6 suggests that the curvature index depends both on the degree of endstopping and the orientation range, but does not allow us to tease apart the contribution of these two factors. Therefore the curvature index has been plotted
243
Table 1. Laminar position of classes of curvature-response curves 2-3 3 4
Layer class I Class II Class III Total
:
4 0 6 1 7
5 I 4 :,
6 8 3 5 16
Total 12 17 8 37
as a function of the percent endstopping and the orientation range in Fig. 7. There is an excellent correlation (r = 0.85) between curvature index and percent endstopping (Fig. 7A) while there is no simple relationship between curvature index and orientation range (Fig. 7B). There is a second-order relationship between these parameters, as indicated on the figure, which is related to the fact that class II neurons had larger orientation ranges than class I or class II cells. If, however, only those cells with endstopping below 50 are considered, there is a correlation between curvature index and orientation range (Fig. 7C). This analysis shows that the curvature index depends mainly upon the percent endstopping, the orientation range playing a permissive role for cells with weak and moderate endstopping. DISCUSSION
Our results show that cat striate cells fall into three broad classes: (1) cells without preference for curvature, i.e. with a flat curvaturoresponse curve; (2) cells preferring zero curvature (straight lines); and (3) cells preferring large curvatures. While the first two classes respond well to chevrons and are tuned to zero chevron angle (straight lines), the third group responds little to chevrons or prefers acute chevrons.
A ,m
r
. ,.
*o.ae
. .
l.
0 /
.
. .
.
Fig. 7. Factors determining the curvature index. (A) Curvatureindex plotted as a function of percent endstopping. (B and C) Curvaturein&x plotted as a function of orientation range for all cells (B) and for cells with endstopping below 50% (C). The stippled he in B indicates the second-order(parabolic) relationship between orientation range and curvature index.
244
MARK VmuvEL et al.
This behaviour of striate cells is dictated by both their orientation selectivity and their endstopping, or better so by their length-response curve. Finally these three classes differ significantly in laminar position: class II cells occur predominantly in layers 4 and 5, while the other two classes occur mainly in layer 6 but also in layers 2 and 3. Our results are in very good agreement with previous studies. Indeed, as Hammond and Andrews (1978), we observed that striate endfree cells respond to chevrons with relatively small angles and that the straight line is in fact always the optimal stimulus. As Dobbins et al. (1987), we observed that cells preferring large curvatures are clearly endstopped cells, while those preferring zero curvature are endfree cells. We extended their observations by showing that the curvature response curve depends not only on endstopping but also on orientation tuning and that almost half of the striate cells have no preference for curvature. This latter observation is in agreement with the report of Heggelund and Hohmann (1975), who mention that none of their 5 complex cells had a clear preference for curvature. In our sample more than half of the C cells belonged to class II. Our results are also in good agreement with other studies of length-response curves of cortical cells. About one quarter of our sample was weakly endstopped (endstopping index between 30 and 60), and it has been repeatedly argued that all degrees of endstopping exist in the striate cortex of the cat (Rose, 1977; Gilbert, 1977). Kato et al. (1978) reported relatively few cells with intermediate endstopping, which may be due to the relative small contribution of layer 4 to their sample, since many layer 4 cells display intermediate endstopping (Mustari. Bullier & Henry, 1982). The observation that class I cells occur outside layer 4 agrees with the findings of Gilbert (1977), who showed that summation length is shorter in layer 4 than in any other layer, and with those of Mustari et al. (1982), who showed that the summation length of monosynaptically driven S cells never exceeds 3 deg in layer 4, but ranges from 2 to 6 deg in layer 6. Our observation that most layer 4 cells belong to class II, fits with those reports showing that many layer 4 cells have intermediate endstopping (Gilbert, 1977; Mustari et al., 1982). Our finding that a number of layer 6 cells belong to class III seems to contradict Gilbert’s (1977) report in which only 1 in 26 layer 6 cells was clearly endstopped. However, others
(Kato et al., 1978; Bullier & Henry, 1979) have reported substantial proportions of endstopped cells in layer 6. Our results are also in agreement with those of Saito, Tanaka, Fukuda and Oyamada (1988). Indeed, our class III cells, which responded well to a very short bar, probably correspond to their dot responsive cells while class I and II cells correspond to their elongation-requiring cells. These authors also showed that while area 19 dot-responsive cells are sensitive to discontinuities, area 17 dotresponsive cells are not. It may therefore be that endstopped cells have different roles in areas 17 and 19: those in area 17 devoted to curvature detection, and those in area 19 in discontinuity detection, although area 19 dotresponsive cells may be sensitive both to curvature and discontinuities. The curvature-response curve of striate cells can be predicted from two other already wellexplored properties of cortical cells, namely the length-response curve and the orientation selectivity. The behaviour of class I cells can be completely accounted for by their narrow orientation tuning and their large length summation. Because of their strong length summation, these cells only respond to stimuli for which they are narrowly orientation tuned. These cells react similarly to curved lines and chevrons, and a curved line is equivalent to a chevron tangent to the curved line (at points halfway between the RF center and the endpoints of the RF). Because of their narrow orientation tuning, the orientation of the segments of this equivalent chevron fall outside of the orientation range of the cell as soon as curvature increases. The behaviour of most class II cells can also be explained by their orientation tuning. Most of these cells have a broad tuning and respond relatively well to short bars for which the orientation tuning will be even broader (Henry, Bishop & Dreher, 1974a, b). The orientation of the chords of the curved lines used never differed more than 45 deg from that of a straight line (see Methods), therefore the orientation of the segments of the equivalent chevron will never differ more than 45 deg from the optimal orientation, and thus remains within the orientation range of the cells. When chevrons are used as stimuli, the orientation of their segments will angle away from the optimum as chevron angle increases, and since the length of the segments remains constant, will fall outside the range of the neuron. And indeed the width of tuning for chevrons follows closely the
Responses of visual cortical neurons
orientation range of the class II cells. The difference in orientations present in curved stimuli and chevrons explains the large difference between the curvature index for curved stimuli and for chevrons observed for most cells in this class. For these cells endstopping contributes little to the chevron responses. Endstopping determines the ends of the curvature-response curve by changing the ratio of responses to zero and large curvatures, making the curvatureresponse curves slightly convex (i.e. bell-shaped) in endfree cells and slightly concave (i.e. Ushaped) in the endstopped cells. Since in most cases the absence of curvature preference depends critically on a broad orientation tuning, one could predict that LGN cells, which lack orientation tuning for bars (Hubel & Wiesel, 1962) and display moderate endstopping (Cleland et al., 1983), also exhibit a class II behaviour. An occasional recording from geniculate terminals in the striate cortex confirms this prediction (Fig. 8). A few class II cells were moderately endstopped and had a relatively narrow orientation tuning. In these cells both endstopping and orientation tuning determine the curvature response curves. These cells respond relatively poorly to zero and small curvatures because of their endstopping. Larger curvatures do not invade the endzones but still fail to fire the cell, since the orientation of the segments of the equivalent chevron falls outside of the narrow orientation range of the cell. One would therefore predict that such cells respond poorly to any curved line. This was indeed the case, these cells responded much more vigorously to a short optimal line than to any curved line. The behaviour of class III cells can be explained largely by the degree of endstopping. In these cells large curvatures do fire the cells, since they avoid the inhibitory endzones, and the orientation of the segments of the equivalent chevron still falls within the relatively broad range of the cell. However, the orientation tuning of class III cells was only on average larger than that of class II cells with similar endstopping (Fig. 6). An additional factor could be a difference in length dependence of the orientation tuning curve of endstopped cells (Orban, Kato & Bishop, 1979). The response of class III cells to chevrons seems to depend more upon the orientation tuning than upon the response to curved stimuli, since the class III cells responding weakly to chevrons had much narrower tuning than those responding well to
50
245
A
! 1
1
5
, -lb
1
-1
I
-0.5.
I
0
as
1
I
1.3
cwvaIw0
-rrolrI-)
Fig. 8. Curvature-mpo MCcurve (A) and chevron angle responsecurve (B) of a gcnidate a&rent t&c recordedin the cortex (11 stimulus presentations).
chevrons. While endstopping can account for the selectivity of class III cells for curvature magnitude, it does not account for the selectivity for curvature sign of some class III cells. An additional factor such as the odd symmetry of the RFs generating the inhibitory endxones, as proposed by Dobbins et al. (1987), is needed to explain this property. The three classes of cortical cells described differ markedly in laminar position. Class II cells occur predominantly in layers 4 and 5, while classes I and III predominated in layers 2 and 3 and 6. Cells in layer 4 are mostly monosynaptically connected with the afferent LGN (Toyama, Matsunami, Ohno & Tokashiki, 1974; Bullier & Henry, 1979; Ferster & Lindstrtim, 1983). Cells in layers 2, 3 and 6 are disynaptically activated, although a number of cells in layers 3 and 6 are monosynaptically activated (Toyama et al., 1974; Bullier & Henry, 1979; Ferster & Lindstr6m, 1983; Martin & Whitteridge, 1984). This suggest that class II cells, at least those in layer 4, are first-order cells. This is functionally meaningful, since
246
MARK VFRSAVEL
these cells respond to all curvatures. Like their geniculate afferents, they sample curved contours. Unlike their afferents they also put bounds on orientation, albeit broad bounds. Because of their laminar position, class I and III could be higher order cells. Mustari et al. (1982) have shown that all monosynaptically-driven layer 6 cells lack endstopping. This suggests that, at least in layer 6, class I can be first-order cells while class III cells are second-order cells (Fig. 9). This also makes functional sense, since in current models class III cells require input from other cortical cells (Dobbins et al., 1987). This then is to say that there are three different types of orientation tuned cells, which differ in tuning width and, more strikingly, in their processing of curved contours: class II cells sample contours, class I cells make explicit zero curvature while class III cells make explicit large curvatures. While from this functional viewpoint it does not matter whether class I cells are first-order or second-order cells, it is mandatory that both class II and class I signals are available and that most class II cells are first-order and all class III second-order cells. This need to generate both class I and class II signals independently, may be met by generating them in separate layers. The small stellate cells of layer 4 sampling a restricted number of geniculate afferents are well-suited for generating class II cells. The pyramidal cells in layers 3 and 6 sampling the geniculate input in layer 4 by means of their widespread basal (layer 3) or apical (layer 6) dendrites are in good position to generate class I signals. Such a scheme could explain why orientation is apparently generated at least twice in a cortical column as suggested by Malpeli’s (1983) experiments. This author showed that disabling the input from the geniculate A lamina silences cells in layer 4, while cells in the supragranular layers remain responsive and orientation tuned. The interpretation given to our results suggests a parallel operation between the supragranular layers and layer 6 (Fig. 8). This parallellism is also suggested by the results of Malpeli et al. (1986) and of Schwark, Malpeli, Weyand & Lee (1986). Indeed, these authors showed that while A lamina input is sufficient and necessary for layers 4 and 6, both A and C laminae inputs are sufficient to drive the supragranular layers. Furthermore layer 6 cells do not require supragranular input to exhibit their normal properties. With respect to layer 6 cells it is worth mentioning that many of them do not project
et al.
A
LGN
:.
............_.
Fig. 9. Hypothetical circuit diagram for the three d&rent cell dasses. (A) Flow diagram. (B) JMailed connections depending on laminar position.
outside the striate cortex (Katz, 1987). Some of these cells, supposedly class I cells could, through local inter-neurons, provide the inhibitory input to class III cells. Others, both class I and III, could provide input to class II layer 4 cells in agreement with anatomical studies (Katz, 1987). This recurrent signal could be used to evaluate the signals in layer 4 (Van Hulle & Orban, 1989). Our experiments are in good agreement with the psychophysical experiments suggesting that the human visual system contains mechanisms selective for curvature (Riggs, 1973; Andrews et al., 1973; MacKay & MacKay, 1974). In fact our results map perfectly onto those of Watt and Andrews (1982) suggesting that curvature is processed in parallel by two mechanisms, one for near-zero curvatures and one for highly curved stimuli. Class I cells could correspond to the former and class III cells to the latter. Our results also provide an explanation as to why Wilson (1985) failed to replicate Watt and Andnws’ results. Indeed Wilson (1985) used as stimuli parabolic arcs joned smoothly to straight line segments oriented at f4S deg, rather than the circular arcs as used by Watt and Andrew-s (1982) and in the present study. Stimuli such as those used by Wilson (1985) are unlikely to drive class III cells well. Indeed the long straight segments, which make this stimulus relatively similar to chevrons, are oriented
Responses of vist tal cortical neurons
deg’ from the optimum and fall on the edge of the tuning range of the cell. Furthermore, since e&ones are relatively wide and are broadly tuned for orientation, the straight line segments will not only trigger the excitatory input weakly, but also trigger the inhibitory endzone input. Hence only class II and I cells will respond to these patterns. Therefore it should indeed be possible to account for the data obtained by Wilson by using a line model i.e. with orientation selective filters derived from orientation and spatial frequency discrimination experiments (Wilson, 1985). Our results are therefore in agreement with our present knowledge of the cat striate cortex, as well as with psychophysical and computational results on curvature processing. Further experimentation is however required to fully understand how curvature and orientation are processed in the visual system of cats and primates.
45
REFERENCES Andrews, D. P., Butchner, A. K. & Buckley, B. R. (1973). Acuities for spatial arrangement in the figures: Human and ideal observers compared. Vision Research, 13, 599-620. Attneave, F. (1954). Some informational aspects of visual perception. PsychologicalReviews, 61, 183-193. Bishop, P. O., Koxak, W. B Vakkur, G. J. (1962). Some quantitative aspects of the cat’s eye: Axis and plane of reference, visual field co-ordinates and optics. Journal of Physiology, London, 163, 466-502. Blokemore, C. & Over, R. (1974). Curvature detectors in human vision? Perception, 3, 3-7. Blasdel, G. G., Mitchell, D. E., Muir, D. W. & Pettigrew, J. D. (1977) A physiological and behavioural study in cats of the e&t of early visual experiena with contours of a single orientation. Journal of Physiology, London, 265, 615-636. Bullier. J. & Henry, G. H. (1979). Laminar distribution of tirst-order neurons and a&rent terminals in cat striate cortex. Journal of Neurophysioiogy,42, 1271-1281. Cleland, B. G., Lee, B. B. & Vidyasagar, T. R. (1983). Response of neurons in the cat’s lateral geniculate nucleus to moving bars of different length. Journal of Neuroscience, 3, 108-116. Dobbins, A., Zucker, S. W. & Cynader, M. S. (1987). Endstopped neurons in the visual cortex as a substrate for calculating curvature. Nature, London, 329, 438-441. Ferster, D. & Lindstr6m, S. (1983). An intracellular analysis of geniculo-cortical connectivity in area 17 of the cat. Journal of Physiology, Lundon, 342, 181-215. Gilbert, C. D. (1977). Laminar differences in receptive field properties of cells in cat primary visual cortex. Journal of Physiology, London, 268, 391-42 1. Gulyaa, B., Orban. G. A., Duysens, J. & Maes, H. (1987). The suppressive influence of moving textured backgrounds on responses of cat striate neurons to moving bars. Journal of Neurophysiology,57, 1767-1791. Hammond, P. & Andrews, D. P. (1978). Collinearity
247
tolerance of cells in amas 17 and 18 of the cat’s visual cortex: Relative mnsltivity to straight lines and chevrons. Expninvntal Brain Research, 31, 329-339. Heggelund, P. & Hohmann, A. (1975). Responses of striate cortical cells to moving edges of diBbrent curvatures. Exg&mental B&n Research, 23, 211-216. Henry, G. H., Bishop, P. 0. & Dreher. B. (1974a). Orientation, axis and direction as stimulus pammeters for striate alls. Virion Research, 14, 761-777. Henry, G. H., Dreber, B. & Bishop, P. 0. (1974b). Orientation specificity of cells in the cat striate cortex. Journal of Neurophysioiogy, 37, 1394409. Hubel, D. H. & Wiesel, T. N. (1%2). Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. Journal of Physiology, London, 160, 106-154. Hubel, D. H. & Wiesel, T. N. (1%5). Receptive fields and functional architectum in two nonstriate visual areas (18 and 19) of the cat. Journal of Neurophysiology, 28, 229-289. Kato, H., Bishop, P. 0. & Orban, G. A. (1978). Hypercomplex and the simple/complex all classifications in cat striate cortex. Jouinal of Neurophysiology,41, 1071-1095. Katz, L. C. (1987). Local circuitry of identified projection neurons in cat visual cortex brain slices. Journal of Neuroscience, 7, 1223-1249. MacKay, D. M. & MacKay, V. (1974). Do curvaturecontingent chromatic aftereffects require ‘Detectors for curvature”‘? Vision Research, 14, 1285-1287. Malpeli, J. G. (1983). Activity of cells in area 17 of the cat in absence of input from layer A of lateral geniculate nucleus. Journal of Neurophysiology,49, 595-610. Malpeli, J. G., Lee, C., Schwark, H. D. & Weyand, T. G. (1986). Cat area 17. I. Pattern of thalamic control of cortical layers. Journal of Neurophysiology, 56, 1062-1073. Martin, K. A. C. & Whitteridge., D. (1984). Form, function and intracortical projections of spiny neurones in the striate visual cortex of the cat. Journal of Physiology, London, 353, 463-504. Mustari, M. J., Bull& J. & Henry, G. H. (1982). Comparison of response properties of three types of monosynaptic S-cell in cat striate cortex. Journal of Neurophysiology,47, 439-454. Nikara, T., Bishop, P. 0. & Pettigrew, J. D. (1968). Analysis of retinal corrcspondcna by studying receptive fields of binocular single units in cat striate cortex. Experimenfal Brain Research, G, 353-372. Ogilvie, J. & Daicar, E. (1967). The perception of curvature. Canadian Journal of Physiology, 21, 521-525. Orban, G. A., Kato, H. & Bishop, P. 0. (1979). End-zone region in receptive fields of hypercomplex and other striate neurons in the cat. Journal of Neurophysiology,42, 818-832. Orban, G. A., Kennedy, H. & Maes, H. (1981). Response to movement of neurons in areas 17 and 18 of the cat: Velocity sensitivity. Journal of Neurophysiology, 45, 1043-1058. Riggs, L. A. (1973). Curvature as a feature of pattern vision. Science, New York, 181, 1070-1072. Rose, D. (1977). Responses of single units in cat visual cortex to moving bars of light as a function of bar length. Journal of Physiology, London, 271, l-23. Saito, H., Tanaka, K., Fukuda, Y. & Oyamada, H. (1988). Analysis of discontinuity in visual contours in area 19 of the cat. Journal of Neuroscience, 8, 1131-I 143.
248
MARK VERSAVEL et al.
Schwark, H. D., Malpeli, J. G., Weyand, T. G. & Lee, C. (1986). Cat area 17. II. Response properties of infragranular layer neurons in the absence of supragranular layer activity. Journal of Neurophysiology. 56, 1074-1087. Toyama, K., Matsunami, K., Ohno, T. & Tokashiki, S. (1974). An intracellular study of neuronal organization in the visual cortex. Experimental Brain Research, 21,45-66. Van Hulle, M. & Orban, G. A. (1989). Entropy driven artificial neuronal networks and sensorial representation: A proposal. Journal of Parallel and Distributed Computation, 6, 264-290.
Watt, R. 1. (1984). Further evidence concerning the analysis of curvature in human fovea1 vision. Vision Research, 24, 251-253.
Watt, R. J. & Andrews, D. P. (1982). Contour curvature analysis: Hyperacuities in the discrimination of detailed shape. Vision Research, 22, 449-460. Wilson, H. R. (1985). Discrimination of contour curvature: Data and theory. Journal of the Optical Society qf America A, 2, 1191-1198. Wilson, H. R. & Sherman, S. M. (1976). Receptive-field characteristics of neurons in cat striate cortex: Changes with visual field eccentricity. Journal of Neurophvsiology, 39, 512-533.
Zucker, S. W. (1985). Early orientation selection: Tangent fields and the dimensionality on their support. Computer 74-103.
Vision, Graphics and Image
Processing,
32,
0042-6989/90
53.00 + 0.00
Copyright0 1990F%rgamon Pressplc
RESPONSES OF VISUAL CORTICAL NEURONS CURVED STIMULI AND CHEVRONS
TO
MARK VERSAVEL,GUY A. ORBAN+ and LIEVENLAG@ Laboratorium voor Neuro- en Psychofysiologie. Katholieke Universiteit te Leuven, Campus Gasthuisberg, Herestraat. R-3000 Leuven, Relgium (Received 13 October 1988; in wired form 12 April 1989) Abstract-Single cells were recorded in area 17 of anaesthetixed and paralyxed cats and their responses to curved stimuli and chevrons compared. Striate cells exhibited three different response patterns. A first group responded optimally to a straight line (i.e. xero curvature) and responded similarly to chevrons and to curved lines. A second group responded to all curvatures and was broadly tuned for the straight line when tested with chevrons. A third groupresponded only to large curvatures, many (2/3) to both signs of curvature and a number (l/3) to only one sign. Cells in this group responded differently to chevrons and curved lines. Cells in these three classes differed both in length-response curve and in width of orientation tuning. Laminar analysis revealed that the three classes are distributed differently across cortical layers. These data shed new light on the finding of Malpeli and coworkers that orientation is extracted at least twice in a cortical column. Curvature
Orientation
Endstopping
Angular diiercnce
Striate cortex
Single cells
cats
INTRODUCTION
Although Hubel and Wiesel(l965), had suggested that hypercomplex cells could serve to Since Attneave (1954) first demonstrated the measure curvature, the initial physiological significance of maximum curvature points for studies of striate cell responses to bent stimuli human form perception, several psychophysical (Heggelund & Hohmann, 1975; Hammond & studies have been devoted to the perception of Andrews, 1978) were restricted to endfree, curvature (Ogilvie & Daicar, 1967; Riggs, 1973, i.e. non-hypercomplex cells. Heggelund and Andrews, Butchner & Buckley, 1973; MacKay Hohmann (1975) who used curved edges, ob& MacKay, 1974, Blakemore & Over, 1974; served that simple cells’ (n = 8) responses deWatt & Andrews, 1982; Watt, 1984; Wilson, pended upon curvature, the optimum generally 1985). A number of these studies (Andrews et being zero curvature (straight line), while comal., 1973; Riggs, 1973; MacKay & MacKay, plex cells’ (n = 5) responses were insensitive to 1974)have suggested the existence of “curvature curvature changes. Hammond and Andrews detectors”, i.e. cells encoding curvature or (1978) compared responses of 20 striate cells to explicitly representing curvature in addition to chevrons and straight lines. In this study, the orientation. Other studies (Blakemore & Over, best response was always obtained using a 1974; Wilson, 1985) have concluded the oppostraight line of optimal orientation. Hence these site and have suggested that curvature is initially two studies concluded that individual striate sampled by local orientation selective mechcells could not detect curvature. It has been only anisms and subsequently computed from the recently that Hubel and Wiesel’s suggestion has output of these lower order mechanisms by been tested explicitly by Dobbins, Zucker comparing orientations at different positions. and Cynader (1987). These experiments were Finally Watt and Andrews (1982) suggested that triggered by the computational theory of curvature estimation is performed in parallel by orientation selection developed by Zucker two mechanisms, one for straight lines and one (1985). According to this author, the initial for highly curved lines. measurements of orientation obtained by orientation selective mechanisms are insufficient to estimate orientation. However, if curvature in*Towhom correspondence should be addressed. formation is available, inappropriate responses tResearch fellow of the National Research Council of can be eliminated at a second stage, since Relgium. 235
236
MARK VERSAVELet al
curvature represents the spatial derivative of orientation. Dobbins et al. (1987) reported that all 15 carefully examined endstopped (or hypercomplex) striate cells had a clearly peaked curvature response curve, while a nonspecified number of endfree (or non-hypercomplex) striate cells had a non-peaked curve, which in fact, judging from their figure, seemed to be broadly tuned for zero and small curvatures. Furthermore, Dobbins et al. (1987) suggested that striate cells cannot only encode curvature magnitude, but also curvature sign, since onethird of the endstopped cells responded more strongly to one direction of curvature than to the other. The present experiments were undertaken to test how different the curvature response curves of endfree and endstopped striate cells really are, since it has been shown that a number of striate cells have intermediate endstopping (Rose, 1977; Kato, Bishop & Orban, 1978). Since earlier positive and negative physiological reports not only focused on different cell types, but also used different stimuli, a second objective of the present study was to compare responses of striate cells to curved lines with those to chevrons. The final aim of this study was to relate curvature selectivity to other cell properties such as orientation selectivity and laminar position, in order to get insight into the mechanisms underlying curvature selectivity. METHODS
General procedure Our methods are very similar to those described previously (Orban, Kennedy & Maes 1981) and only a brief description is needed here. Cats were anesthetized with ketamine or alfathesine for initial surgical procedures. The experiments were performed on cats placed in the stereotaxic apparatus by means of a painless headholding device cemented to the skull and anesthetized with a N,O/O, (70: 30 mixture) and a continuous perfusion of Nembutal (1 mg *kg-’ *hr- I). The animals were paralyzed with a continuous infusion of Flaxedil and d-tubocurarine. The expiratory CO2 and rectal temperature were held constant. Pupils were dilated, corneas protected by afocal Silflex contact lenses and refractive errors corrected by spectacle lenses. Single units in the visual cortex (area 17) recorded with glass-coated tungsten electrodes, were explored qualitatively with handheld stimuli and studied quantitatively with moving stimuli rear-projected onto a pola-
coat screen located 1.71 m from the cat. Several electrolytic lesions were made in a penetration. Penetrations were histologically reconstructed on frozen sections stained with cresyl violet. Handplotting was used to determine the preferred orientation, the width of orientation tuning, the ocular dominance and the degree of endstopping. The minimum discharge field was measured using a narrow moving light bar (Kato et al., 1978). The receptive field (RF) width is defined as the dimension of the minimum field orthogonal to the line of optimal orientation. The position of the RF was referred to the assumed position of the area centralis derived from the position of the blind spot (Bishop, Kozak & Vakkur, 1962; Nikara, Bishop & Pettigrew, 1968). Frequent back projection of the blind spot allowed us to correct for the slow drift of the eyes. Visual stimulation Two visual stimulators, both under computer control, were used. In both stimulation systems slides were projected onto the tangent polacoat screen facing the cat. The images of the two stimulators were mixed by a beam splitter. The images could be moved by turning mirrors mounted on a General Scanning@ motor whereby the computer controlled speed and position of the images. Since the computer had no direct control of the shape of the stimuli shown by the slide projector, slides with multiple stimuli were used to reduce the amount of manipulation necessary to test curvature selectivity and to offset variability. Five stimuli were presented on one slide and moved through the RF in succession. The separation between stimuli was 7 deg ensuring that for slowly moving stimuli (typically l-4 deg/sec) the responses were clearly separated in time. Each slide included as center stimulus a 0.3 deg wide straight line, used as reference for normalization. One set of slides, used for endfree cells, contained 12 deg long bars as references and a second set, used for endstopped cells, included 2 deg long bars as references. For the preliminary testing of length summation, orientation tuning and lengthwise centering of the stimuli, such slides with multiple stimuli were used. A set of two slides was used to present 0.3 deg wide bars of 7 different lengths ranging from 0.5 to 12 deg length. In this set, both 2 and 12 deg long bars were present in the two slides. In order to determine the optimal orientation, a single slide was used containing
Responses of visual cortical neurons
0.3 deg wide bars, either 12 or 2 deg long and ranging in orientation from - &(anticlockwise) to 30 deg in 15 deg steps, or from - 20 to 20 deg in 10 deg steps. In order to test the lengthwise centering, a slide with 3 deg long bars offset lengthwise from -3 deg (below center) to + 3 deg (above center) in 1.5 deg steps was used for endfree cells. For endstopped cells, a slide with 1 deg long lines offset from -2 to +2 deg was used. Four slides were used to test curved lines and chevrons, yielding 16 different curvatures or chevrons plus the straight line (zero curvature). Eight curved lines or chevrons were convex in the forward direction of motion and given a positive sign and eight curved lines or chevrons were concave in the forward direction of motion and given a negative sign. Since comparing responses to opposite signs of curvature was critical, each slide contained only two curvatures or two chevrons angles each with the two stimuli of opposite sign. Chevrons were made of two 6 deg long, 0.3 deg wide line segments deviating from the straight tine by an angle (the chevron angle) ranging from 10 to 80 deg in
237
10 deg steps and these line segments were disposed symmetrically with respect to the tangent line of the RFs prefemd orientation. Curved lines were 0.3 deg wide and made of segments of circles with 8 different radii ranging from 0.5 to 16.66 deg. For small radii (up to 3 deg) half circles were used. For larger radii (from 4.5 deg on) the chord length was limited to 6 deg, resulting in segments which were less than half circles. Stimulus curvature is defined as the inverse of the radius, ranging from 2 to 0.06. For the curved lines with small curvatures (up to 0.22 i.e. radius of 4.5 deg) the chord length was equal to the length of the chevron line segments. The curvature values were chosen in such a way that the orientation of the chord equalled that of the chevrons segments of angles ranging from 10 to 40 deg. For large curvatures this was not possible since orientation of the chords remained at 45 deg from the straight line while the angle of chevrons increased up to 80 deg. All these slides were available either as light stimuli or as dark stimuli on a homogeneous background of 4.9cd/m* and with a contrast
UNIT 13309
2SC ,...” ,,..‘.
.~
1
,,_.”
:.“’ .’ ,:’ .,: ,;’
_.
,r
/’
1
,.,...‘..
,, ,_... .‘.’
,.: ,.:.
,?’,,.:. ,:’,t
/...‘.:’
,
..’
i/-
,/.’ 0
a
4 lorlolh
6 s cdmomr1
Fig. 1. Complete test series of a cell preferring zero curvature (class I). (A) Orientation tuning. (B) Length-excitability pro&. (C) Lengtkesponse curve. (D) Curvatur+response curve and (E) chevron ang&rupoa~ curve.The full line connecting dots represent the medium response; the stippkd lines upper and lower quartiles. Number of stimulus presentations: (A, B and C) 8 presentations; (C and D) 10 presentations.
lo
l-2
MARKVERSAVELet al.
238
(log AI/Z) of -0.09 in positive (light) or negative (dark) polarity. Quantitative testing The neurons were tested quantitatively with a multihistogram technique (velocity series) or a multiple stimuli technique (other parameter series) to offset response variability. The times of occurrence of the action potentials were stored on disc for further offline analysis. A 0.3 deg wide optimally oriented light and dark bar were presented to the dominant eye for the light and dark bar velocity multihistogram. The length was 30deg for endfree cells and a shorter, optimal length for endstopped cells. In the light and dark bar velocity multihistogram 4 x 11 conditions were interleaved corresponding to two directions of motion of light and dark bars and 11 speeds ranging from 0.5 to 512 deg/sec. By superimposing the light slit projected by one projector onto the light part of the dark bar projected by the other stimulator, one can arrange the stimuli in such a way that the contrast of both bars is of opposite polarity but equal in magnitude. This test provides quantitative definition of RF structure, direction selectivity and velocity sensitivity. Cells were classified with respect to these three characteristics as described previously (Gulyas, Orban, Duysens & Maes, 1987). The light and dark bar velocity test was used to select the optimal speed as well as the contrast polarity used for the following tests. The next test was a length series in order to measure the length-response curve. The degree of endstopping determined the
A
B
choice of long or short reference lines in the subsequent testing. Once the optima1 orientation had been checked quantitatively, the lengthwise centering was controlled. Cells were tested for curvature and chevron angle only after these preliminary tests had been completed (see Fig. 1). Analysis of the multiple stimuli tests While the analysis of the velocity multihistograms was done according to procedures standard to our laboratory (Orban et al., 1981; Gulyas et al., 1987), the analysis of tests based on slides with multiple stimuli is novel. A peak detection program was used to locate and to determine the limits of the five responses in the PSTH corresponding to the five stimuli moving through the RF. This histograms were constructed with binwidths adapted to the stimulus speed, starting with a binwidth of 512 msec for 0.5 deg/sec speed and halving the binwidth each time the speed doubled up to 32 msec for 8 deg/sec, the fastest speed used in the multiple stimuli tests. Histograms were smoothed by applying the algorithm
nine times, where ci is the number of spikes in bin i. Peaks were detected as those bins where the firing rate exceeded the 95% significance level centered on local maxima. The peak limits were set by taking 7 bins exceeding the significance level and centered as much as possible on the highest bin. The computer then performed a run-by-run analysis to measure the average
C
Fig. 2. Comparison of tuning width for curvature, chevron an& and orientation range. (A) Definition of the cquivaknt chevron: a is the chevrou an$c of the equi*t chevron of the 4wved stimulus. (B)Tuaing~dthofdarIforcurnt~~ut\laial~fort&eequivlrknt~~piottad as a function of actual tuning width for dtevrons. (C) Tuning width for chevrons of class I and II c&b plotted as a function of their orientation mqe. Lets rafer to &la shown in other figures: (a) unit 133096 (Fig. I); (b) unit 11615 (Fig. 3).
Rcsponscs of visual cortical neurons
firing rate in the intervals between the peak limits for each stimulus presentation. The median and quartiles of these response distributions were computed. Finally responses belonging to a single stimulus series (such as length, curvature or chevron angle series) but measured in different RSTHs, corresponding to different slides, were normalixed by expressing these responses as a percentage of the responses to the reference stimuli. These relative responses were then converted back to absolute values by multiplying the control response (100%) with the average response evoked by the reference stimulus in different slides. The amount of normalization was relatively small, since the median amount for all tests and cells was 1, the first and third quartiles were 0.8 and 1.5 respectively, and the extreme values 0.2 and 4.5. The degree of endstopping of a cell was derived from the length-response curve as follows: the difference between the response to the bar of optimal length and a 12 deg bar was expressed as the percent of the optimal response.
239 UNIT 11615
RESULTS
Curvature response curves were obtained for 45 area 17 cells. With the exception of 3 cells, their RFs were located within 10 deg of the fixation point. The layering of 37 cells was recovered from the histological reconstruction of the penetrations: 8 cells were lotted in layers 2-3, 7 in layer 4, 6 in layer 5 and 16 in layer 6. 30 of the 45 cells were also tested with chevrons. Cortical cells responded to curved stimuli and chevrons in 3 different patterns. Each of these response classes will first be described before indicating the general properties of these three groups.
Fig. 3. Cell without preference for curvature (class II). (A) Curvatumaponre curve. (B) Chevron angle-rqonac curve. Same convention as Fig. 1. Ten stimulus presentations.
this cell was 33 deg, which is very similar to that obtained with straight lines (27 deg). In order to compare the tuning for curved stimuli and chevrons, we de&d the equivalent chevron for curved stimuli as follows: it is the chevron of which the stripes are tangent to the curved stimulus at the points halfway between the Cells preferring straight lines (zero curvature) RF center and the ends of the length axis of RF measured from the length-response curve Figure 1 shows the behaviour of a cell typical (Fig. 2). For cell 13309 the tuning width for of this group. The cell in Fig. 1 was a velocity curvatures corresponded to a width at half low pass, non-direction selective S cell, sharply height for the equivalent chevron ,of 36 deg, tuned for orientation (the width at half height close to the value actually obtained with was 27 deg). The cell showed considerable chevrons. length summation, and the endstopping index For the whok group of cells in this class, the was zero (Fig. 1C). When tested with curved tuning width obtained with chevrons and the stimuli the cell responded only for near-zero one derived from the responses to curved stimuli curvatures, the straight line being optimal were almost identical. As shown in Fig. 2, the (Fig. 1D). Similarly, when tested with chevrons, data (a = 9) were ahnost perfectly fitted by a straight lines and obtuse chevrons (i.e. small diagonal line through the origin chevron angles) were optimal. The width of tuning at half height obtained with chevrons for (Y = - 1.7 + 1.03 x, r - 0.99, P < O.OOOOOl).
MARK VERSAVEL~~~I.
240
If the equivalent chevron was defined as the chevron tangent to the curved stimulus at the endpoints of the RF, the datapoints plotting the two tuning widths were fitted by a straight line through the origin of slope 2 rather than 1. This means that for these cells a curved stimulus is equivalent to a chevron whose diagonal stripes have the orientation of the chords fitted to the part of the curved stimulus covering the RF. Celis without preference for curvature A substantial proportion of cells had little preference for any curvature. Figure 3 illustrates the response pattern of this class of cells. The cell in Fig. 3 was a non-direction selective velocity broad-band C cell recorded in layer 6. The cell had a relatively broad o~entation tuning (orientation range estimated manually at 60 deg) and showed only marginal endstopping (endstopping index 23). The length-response curve aiso revealed that the c&l responded well to short stimuli: its response to a 0.5 deg long bar was about 70% of the optimal response to a 2 deg long bar. As shown in Fig. 3A, this cell responded equally well to all curvatures. In fact
the responses to the extreme curvatures are even slightly larger than that to the straight line. While cells in the previous group responded very similarly to chevrons and curved stimuli, cells in this group characteristically responded dgerently to the two types of stimuli. As shown in Fig. 3B cell 11615 did not respond to acute chevrons (i.e. large chevron angles) although it did respond well to extreme curvatures. In fact for chevrons the cell is broadly tuned to zero chevron angle i.e. a straight line. In this cell, the width of tuning at half height for chevrons was 85 deg. This was fairly typical, since the tuning for chevrons was considerabie wider in this group of cells than for the previous group: median width at half height was 62 deg (n = 9) for group II cells compared to 40 deg (n = 9) for the previous group. This is in keeping with the fact that on average, this group of cells had a wider orientation tuning than that of the previous group (see below). Considering group I and group II cells together, there was an excellent correlation (r = 0.86) between the tuning width for chevrons and the orientation range measured by handplotting (Fig. 2C).
UNIT
c
12w4
2s
i 1
10 ~
5
._...
..:
~
I
I
-1.5
-1
-QS
0
QS
3
N-
Fig. 4. Cds p&ring
extreme curvatures (clam III). (A, C) Curvature-response curves. (B, D) Chevron
angle-rcsponsccurves. (A, B) Cell without adcctivity for curvature sign (IS stimulus presentations). (C, D) till preferring negdvc curvatures (12 stimulus presentations).
15
Rcsponscsof visual cortical neurons
241
Cells preferring extreme curvatures
In contrast with cells of the first group, which responded only to near-zero curvatures, a numher of cells responded only to extremely curved stimuli. As for cells of the second class, responses of the cells preferring extreme curvatures were di&ent for curved stimuli and chevrons. Figure 4 illustrates two cells of this type. The cell in Fig. 4A was a non-direction selective, velocity broad-band HC cell recorded in layer 6. Characteristically this cell was strongly endstopped: its endstopping index was 97. Consequently this cell hardly responded to a long straight line but fired vigorously when the two most curved stimuli traversed its RF. Comparison of the response strength for these optimal curvatures to that for an optimal, 2 deg long bar showed that the response levels were equivalent. Cell 13411 responded equally well to convex and concave curved stimuli, but responded better to a convex than to a concave acute chevron (Fig. 3B). The response level reached for the convex acute chevron was about the same as that elicited by extremely curved stimuli and a 2 deg long bar. Whereas cell 13411 responded equally well to both signs of curvature, cell 12914 (Fig. 4C) responded differently to both signs. Although there was some variability in the response to the extreme negative curvature, the response to the negative extreme curvature was significantly larger (0.1% on Mann-Whitney U test) than the response to the positive extreme curvature. Cell 12914 was a nondirection selective velocity low pass HS cell recorded in layer 6. Cell i2914 hardly responded to chevrons: the responses elicited by chevrons was about l/4 that elicited by the optimal curvatures. Also, the response of the cell to the optimal short bar (0.5 deg length) was less than half of that to the optimal curvature. On average, responses of cells in this group were about equal for optimal short bars and optimal curvatures: in 3 cells optimal curvature was better than the optimal bar (as in cell 12914), in 3 cells the reverse held, and in 4 cells (as in cell 13411) both types of stimuli elicited about the same response. Three out of 10 cells in this class responded well to curvatures of one sign and not to the other: two preferred negative curvatures (concave), one positive curvature (convex). For all three cells the response to opposite signs were significantly different at the 0.1% level when the responses to the extreme curvatures were compared. The preferred curva-
aJw*La.
indm
Fig. 5. Distribution of the curvature index in our sample: hatched area, class I cells, light axea class II cells, stippled area claw III ceils.
ture was one of the two most extreme curvatures. With respect to chevrons, only five cells were tested with this type of pattern. Two cells responded weakly to chevrons (as cell 12914), their response to the optimal chevron being at least four times weaker than that to the optimal curved stimulus, and three cells responded equally well to chevrons and curved stimuli (as cell 13411).These latter three cells, as cell 13411, responded as well to positive as to negative large curvatures, but responded better to acute chevrons of one sign than to acute chevrons of the other sign. How distinct are the three groups? The three groups described are defined by their relative response to zero curvature (straight lines) and extreme curvatures. Therefore we calculated for each cell the curvature index (CI) defined as follows. The difference in response between the average responses to the extreme curvatures of positive and negative sign and the response to zero curvature was normalized by dividing this difference by the largest of the two numbers and multiplying by 100. The distribution of this index CI is given in Fig. 5. Cells in group I (n = 14) all had CI smaller than - 60 while cells in group III (n = 10) all had CI larger than 60. The cell of Fig. 1 had a CI of - 100 and those of Fig. 4 a CI of 76 and 97 respectively. Cells in group II (n = 21) had CIs between - 50 and 50, meaning that the response to extreme and zero curvature differed at most by a factor of 2. The cell of Fig. 3 had a CI of -22. It is clear from Fig. 6 that the neurons in our sample are distributed along a continuum, and that they are assigned to discrete classes as a matter of convenience. A similar index was calculated for chevron responses. For group I the index was only
MARK VFJLWVEL et al.
242
marginally different for curved stimuli and chevrons. The median indices for cells of class I (n = 9) were -97 and - 79 for chevrons and curved stimuli respectively. For cells of class II however, the difference was much larger. For this class, the medians (n = 16) were - 89 (Q, = -95, Qj= -56) and -27 (Ql = -38, Q, + 18) for chevrons and curved stimuli respectively. For cells of class III, the indices were positive for chevrons, as they were for curved stimuli: the median index for the three of the five cells tested which responded well to chevrons was +95, a value close to +97, their median CI for curved stimuli.
to estimate quantitatively the tuning width. However, for those cells for which both measurements were available, there was a good correlation between quantitative and qualitative estimations, in agreement with previous studies (Wilson & Sherman, 1976; Blasdel, Mitchell, Muir & Pettigrew, 1977; Bullier, Kennedy & Orban, unpublished). Classes I and III are very distinct in the orientation range-endstopping index diagram (Fig. 6). Cells in class I all had endstopping indices below 30 and small orientation tuning ranges: the median values are 13 (quartiles 0 and 26) and 44 deg (quartiles 26 and 63 deg) for the endstopping index and the orientation range respectively. Cells in class III all had endstopping indices above 55 and had medium orientation ranges. The median endstopping index was 90 (quartiles 74 and 100) and the median orientation range was 57 deg (quartiles 50 and 83 deg). Cells of class II are more widely scattered and include those with little endstopping and wide orientation tuning as well as cells with moderate endstopping and narrow orientation tuning. Class II cells with an endstopping index below 50 had a significantly (P < 0.025) wider orientation tuning than those with an endstopping index above 50. The median endstopping index for class II was 38 (quartiles 22 and 53). The median orientation range 81 deg (quartiles 58 and 112 deg). Both values were significantly different from those of the other two classes.
Characteristics of the 3 groups
From the description given of the 3 cell groups it is clear that they differ not only in degree of endstopping but also in selectivity for orientation. We have used the orientation range as estimate for orientation selectivity and have plotted the orientation tuning range as a function of the endstopping index for all three classes (Fig. 6). Although less accurate than the width of orientation tuning at half-height, the orientation range measured by handplotting was available for all cells. Indeed the quantitative determination of orientation tuning was intended only to provide an estimate of the optimum orientation. In a number of cells the initial estimate of the optimal orientation was off by more than 10 deg, making it impossible
N.O.
.J +
140 -
+ +o
_ E -0
120’
l
++ loo-
0
0
l*
x 3 no-
*
0
5 ‘L 0
0
60-
Lo
0
l
0
a+ q
40-
;-
20-
o
D
0
+00+-E-
+
E ‘S 2
OA
+
+
4
+
0 0
+ 0
0
+
+
0
0
0 0’ I
0
I
,
I
,
10
20
SO
48
1
S
Endstopping
60
I
I
1
I
70
60
60
100
( Ye )
Fig. 6. Orientation range plottedaaa function of endstopping indexz (0) clam I cdls; (+) classI1 ceils; (0) classIII cells. Letters refer to units shown in other 5gum: (a) unit 13309 (Fig. 1); (b) unit 11615 (Fig. 3); (c) unit 12914 (Fig. 4 right); (d) unit 13411 (Fig. 4 left); (e) unit 12006 (gcniculate affmnt, Fig. 7).
Responses of visual cortical neurons
The three classes of striate cells differed not only in degree of endstopping, but their entire length-response curve was different. While class I cells hardly responded to short bars, classes II and III did respond relatively well. This is reflected by the response to 0.5 deg bar expressed as a percentage of the response to the optimal length. The median value of this parameter ranged from 0% (quartiles 0%, and 13%) in class I cells to 34% (quartiles 7% and 54%) and 53% (quartiles 31% and 100%) in classes II and III respectively. Also, the optimal length differed between classes: the median optimal length was 6 deg (quartiles 4 and 12 deg) for class I, 2 deg (quartiles 1 and 2.7 deg) for class II and 1 deg (quartiles 0.5 and 2 deg) for class III. There were relatively few correlations with other response properties, although cells of class III more frequently belonged to the S family (60%) than those of class II (33%). There was, however, a striking correlation with laminar position. Class II cells occurred mainly in layers 4 and 5, and to a lesser degree in the superficial layers, while the vast majority of the cells of the other two classes were located in layer 6 or to a lesser extent in layers 2 and 3 (Table 1). The higher incidence of class II cells in layers 4 and 5 compared to the other two classes was highly significant (x2 =i 7.75, d.f. = 1, P
Figure 6 suggests that the curvature index depends both on the degree of endstopping and the orientation range, but does not allow us to tease apart the contribution of these two factors. Therefore the curvature index has been plotted
243
Table 1. Laminar position of classes of curvature-response curves 2-3 3 4
Layer class I Class II Class III Total
:
4 0 6 1 7
5 I 4 :,
6 8 3 5 16
Total 12 17 8 37
as a function of the percent endstopping and the orientation range in Fig. 7. There is an excellent correlation (r = 0.85) between curvature index and percent endstopping (Fig. 7A) while there is no simple relationship between curvature index and orientation range (Fig. 7B). There is a second-order relationship between these parameters, as indicated on the figure, which is related to the fact that class II neurons had larger orientation ranges than class I or class II cells. If, however, only those cells with endstopping below 50 are considered, there is a correlation between curvature index and orientation range (Fig. 7C). This analysis shows that the curvature index depends mainly upon the percent endstopping, the orientation range playing a permissive role for cells with weak and moderate endstopping. DISCUSSION
Our results show that cat striate cells fall into three broad classes: (1) cells without preference for curvature, i.e. with a flat curvaturoresponse curve; (2) cells preferring zero curvature (straight lines); and (3) cells preferring large curvatures. While the first two classes respond well to chevrons and are tuned to zero chevron angle (straight lines), the third group responds little to chevrons or prefers acute chevrons.
A ,m
r
. ,.
*o.ae
. .
l.
0 /
.
. .
.
Fig. 7. Factors determining the curvature index. (A) Curvatureindex plotted as a function of percent endstopping. (B and C) Curvaturein&x plotted as a function of orientation range for all cells (B) and for cells with endstopping below 50% (C). The stippled he in B indicates the second-order(parabolic) relationship between orientation range and curvature index.
244
MARK VmuvEL et al.
This behaviour of striate cells is dictated by both their orientation selectivity and their endstopping, or better so by their length-response curve. Finally these three classes differ significantly in laminar position: class II cells occur predominantly in layers 4 and 5, while the other two classes occur mainly in layer 6 but also in layers 2 and 3. Our results are in very good agreement with previous studies. Indeed, as Hammond and Andrews (1978), we observed that striate endfree cells respond to chevrons with relatively small angles and that the straight line is in fact always the optimal stimulus. As Dobbins et al. (1987), we observed that cells preferring large curvatures are clearly endstopped cells, while those preferring zero curvature are endfree cells. We extended their observations by showing that the curvature response curve depends not only on endstopping but also on orientation tuning and that almost half of the striate cells have no preference for curvature. This latter observation is in agreement with the report of Heggelund and Hohmann (1975), who mention that none of their 5 complex cells had a clear preference for curvature. In our sample more than half of the C cells belonged to class II. Our results are also in good agreement with other studies of length-response curves of cortical cells. About one quarter of our sample was weakly endstopped (endstopping index between 30 and 60), and it has been repeatedly argued that all degrees of endstopping exist in the striate cortex of the cat (Rose, 1977; Gilbert, 1977). Kato et al. (1978) reported relatively few cells with intermediate endstopping, which may be due to the relative small contribution of layer 4 to their sample, since many layer 4 cells display intermediate endstopping (Mustari. Bullier & Henry, 1982). The observation that class I cells occur outside layer 4 agrees with the findings of Gilbert (1977), who showed that summation length is shorter in layer 4 than in any other layer, and with those of Mustari et al. (1982), who showed that the summation length of monosynaptically driven S cells never exceeds 3 deg in layer 4, but ranges from 2 to 6 deg in layer 6. Our observation that most layer 4 cells belong to class II, fits with those reports showing that many layer 4 cells have intermediate endstopping (Gilbert, 1977; Mustari et al., 1982). Our finding that a number of layer 6 cells belong to class III seems to contradict Gilbert’s (1977) report in which only 1 in 26 layer 6 cells was clearly endstopped. However, others
(Kato et al., 1978; Bullier & Henry, 1979) have reported substantial proportions of endstopped cells in layer 6. Our results are also in agreement with those of Saito, Tanaka, Fukuda and Oyamada (1988). Indeed, our class III cells, which responded well to a very short bar, probably correspond to their dot responsive cells while class I and II cells correspond to their elongation-requiring cells. These authors also showed that while area 19 dot-responsive cells are sensitive to discontinuities, area 17 dotresponsive cells are not. It may therefore be that endstopped cells have different roles in areas 17 and 19: those in area 17 devoted to curvature detection, and those in area 19 in discontinuity detection, although area 19 dotresponsive cells may be sensitive both to curvature and discontinuities. The curvature-response curve of striate cells can be predicted from two other already wellexplored properties of cortical cells, namely the length-response curve and the orientation selectivity. The behaviour of class I cells can be completely accounted for by their narrow orientation tuning and their large length summation. Because of their strong length summation, these cells only respond to stimuli for which they are narrowly orientation tuned. These cells react similarly to curved lines and chevrons, and a curved line is equivalent to a chevron tangent to the curved line (at points halfway between the RF center and the endpoints of the RF). Because of their narrow orientation tuning, the orientation of the segments of this equivalent chevron fall outside of the orientation range of the cell as soon as curvature increases. The behaviour of most class II cells can also be explained by their orientation tuning. Most of these cells have a broad tuning and respond relatively well to short bars for which the orientation tuning will be even broader (Henry, Bishop & Dreher, 1974a, b). The orientation of the chords of the curved lines used never differed more than 45 deg from that of a straight line (see Methods), therefore the orientation of the segments of the equivalent chevron will never differ more than 45 deg from the optimal orientation, and thus remains within the orientation range of the cells. When chevrons are used as stimuli, the orientation of their segments will angle away from the optimum as chevron angle increases, and since the length of the segments remains constant, will fall outside the range of the neuron. And indeed the width of tuning for chevrons follows closely the
Responses of visual cortical neurons
orientation range of the class II cells. The difference in orientations present in curved stimuli and chevrons explains the large difference between the curvature index for curved stimuli and for chevrons observed for most cells in this class. For these cells endstopping contributes little to the chevron responses. Endstopping determines the ends of the curvature-response curve by changing the ratio of responses to zero and large curvatures, making the curvatureresponse curves slightly convex (i.e. bell-shaped) in endfree cells and slightly concave (i.e. Ushaped) in the endstopped cells. Since in most cases the absence of curvature preference depends critically on a broad orientation tuning, one could predict that LGN cells, which lack orientation tuning for bars (Hubel & Wiesel, 1962) and display moderate endstopping (Cleland et al., 1983), also exhibit a class II behaviour. An occasional recording from geniculate terminals in the striate cortex confirms this prediction (Fig. 8). A few class II cells were moderately endstopped and had a relatively narrow orientation tuning. In these cells both endstopping and orientation tuning determine the curvature response curves. These cells respond relatively poorly to zero and small curvatures because of their endstopping. Larger curvatures do not invade the endzones but still fail to fire the cell, since the orientation of the segments of the equivalent chevron falls outside of the narrow orientation range of the cell. One would therefore predict that such cells respond poorly to any curved line. This was indeed the case, these cells responded much more vigorously to a short optimal line than to any curved line. The behaviour of class III cells can be explained largely by the degree of endstopping. In these cells large curvatures do fire the cells, since they avoid the inhibitory endzones, and the orientation of the segments of the equivalent chevron still falls within the relatively broad range of the cell. However, the orientation tuning of class III cells was only on average larger than that of class II cells with similar endstopping (Fig. 6). An additional factor could be a difference in length dependence of the orientation tuning curve of endstopped cells (Orban, Kato & Bishop, 1979). The response of class III cells to chevrons seems to depend more upon the orientation tuning than upon the response to curved stimuli, since the class III cells responding weakly to chevrons had much narrower tuning than those responding well to
50
245
A
! 1
1
5
, -lb
1
-1
I
-0.5.
I
0
as
1
I
1.3
cwvaIw0
-rrolrI-)
Fig. 8. Curvature-mpo MCcurve (A) and chevron angle responsecurve (B) of a gcnidate a&rent t&c recordedin the cortex (11 stimulus presentations).
chevrons. While endstopping can account for the selectivity of class III cells for curvature magnitude, it does not account for the selectivity for curvature sign of some class III cells. An additional factor such as the odd symmetry of the RFs generating the inhibitory endxones, as proposed by Dobbins et al. (1987), is needed to explain this property. The three classes of cortical cells described differ markedly in laminar position. Class II cells occur predominantly in layers 4 and 5, while classes I and III predominated in layers 2 and 3 and 6. Cells in layer 4 are mostly monosynaptically connected with the afferent LGN (Toyama, Matsunami, Ohno & Tokashiki, 1974; Bullier & Henry, 1979; Ferster & Lindstrtim, 1983). Cells in layers 2, 3 and 6 are disynaptically activated, although a number of cells in layers 3 and 6 are monosynaptically activated (Toyama et al., 1974; Bullier & Henry, 1979; Ferster & Lindstr6m, 1983; Martin & Whitteridge, 1984). This suggest that class II cells, at least those in layer 4, are first-order cells. This is functionally meaningful, since
246
MARK VFRSAVEL
these cells respond to all curvatures. Like their geniculate afferents, they sample curved contours. Unlike their afferents they also put bounds on orientation, albeit broad bounds. Because of their laminar position, class I and III could be higher order cells. Mustari et al. (1982) have shown that all monosynaptically-driven layer 6 cells lack endstopping. This suggests that, at least in layer 6, class I can be first-order cells while class III cells are second-order cells (Fig. 9). This also makes functional sense, since in current models class III cells require input from other cortical cells (Dobbins et al., 1987). This then is to say that there are three different types of orientation tuned cells, which differ in tuning width and, more strikingly, in their processing of curved contours: class II cells sample contours, class I cells make explicit zero curvature while class III cells make explicit large curvatures. While from this functional viewpoint it does not matter whether class I cells are first-order or second-order cells, it is mandatory that both class II and class I signals are available and that most class II cells are first-order and all class III second-order cells. This need to generate both class I and class II signals independently, may be met by generating them in separate layers. The small stellate cells of layer 4 sampling a restricted number of geniculate afferents are well-suited for generating class II cells. The pyramidal cells in layers 3 and 6 sampling the geniculate input in layer 4 by means of their widespread basal (layer 3) or apical (layer 6) dendrites are in good position to generate class I signals. Such a scheme could explain why orientation is apparently generated at least twice in a cortical column as suggested by Malpeli’s (1983) experiments. This author showed that disabling the input from the geniculate A lamina silences cells in layer 4, while cells in the supragranular layers remain responsive and orientation tuned. The interpretation given to our results suggests a parallel operation between the supragranular layers and layer 6 (Fig. 8). This parallellism is also suggested by the results of Malpeli et al. (1986) and of Schwark, Malpeli, Weyand & Lee (1986). Indeed, these authors showed that while A lamina input is sufficient and necessary for layers 4 and 6, both A and C laminae inputs are sufficient to drive the supragranular layers. Furthermore layer 6 cells do not require supragranular input to exhibit their normal properties. With respect to layer 6 cells it is worth mentioning that many of them do not project
et al.
A
LGN
:.
............_.
Fig. 9. Hypothetical circuit diagram for the three d&rent cell dasses. (A) Flow diagram. (B) JMailed connections depending on laminar position.
outside the striate cortex (Katz, 1987). Some of these cells, supposedly class I cells could, through local inter-neurons, provide the inhibitory input to class III cells. Others, both class I and III, could provide input to class II layer 4 cells in agreement with anatomical studies (Katz, 1987). This recurrent signal could be used to evaluate the signals in layer 4 (Van Hulle & Orban, 1989). Our experiments are in good agreement with the psychophysical experiments suggesting that the human visual system contains mechanisms selective for curvature (Riggs, 1973; Andrews et al., 1973; MacKay & MacKay, 1974). In fact our results map perfectly onto those of Watt and Andrews (1982) suggesting that curvature is processed in parallel by two mechanisms, one for near-zero curvatures and one for highly curved stimuli. Class I cells could correspond to the former and class III cells to the latter. Our results also provide an explanation as to why Wilson (1985) failed to replicate Watt and Andnws’ results. Indeed Wilson (1985) used as stimuli parabolic arcs joned smoothly to straight line segments oriented at f4S deg, rather than the circular arcs as used by Watt and Andrew-s (1982) and in the present study. Stimuli such as those used by Wilson (1985) are unlikely to drive class III cells well. Indeed the long straight segments, which make this stimulus relatively similar to chevrons, are oriented
Responses of vist tal cortical neurons
deg’ from the optimum and fall on the edge of the tuning range of the cell. Furthermore, since e&ones are relatively wide and are broadly tuned for orientation, the straight line segments will not only trigger the excitatory input weakly, but also trigger the inhibitory endzone input. Hence only class II and I cells will respond to these patterns. Therefore it should indeed be possible to account for the data obtained by Wilson by using a line model i.e. with orientation selective filters derived from orientation and spatial frequency discrimination experiments (Wilson, 1985). Our results are therefore in agreement with our present knowledge of the cat striate cortex, as well as with psychophysical and computational results on curvature processing. Further experimentation is however required to fully understand how curvature and orientation are processed in the visual system of cats and primates.
45
REFERENCES Andrews, D. P., Butchner, A. K. & Buckley, B. R. (1973). Acuities for spatial arrangement in the figures: Human and ideal observers compared. Vision Research, 13, 599-620. Attneave, F. (1954). Some informational aspects of visual perception. PsychologicalReviews, 61, 183-193. Bishop, P. O., Koxak, W. B Vakkur, G. J. (1962). Some quantitative aspects of the cat’s eye: Axis and plane of reference, visual field co-ordinates and optics. Journal of Physiology, London, 163, 466-502. Blokemore, C. & Over, R. (1974). Curvature detectors in human vision? Perception, 3, 3-7. Blasdel, G. G., Mitchell, D. E., Muir, D. W. & Pettigrew, J. D. (1977) A physiological and behavioural study in cats of the e&t of early visual experiena with contours of a single orientation. Journal of Physiology, London, 265, 615-636. Bullier. J. & Henry, G. H. (1979). Laminar distribution of tirst-order neurons and a&rent terminals in cat striate cortex. Journal of Neurophysioiogy,42, 1271-1281. Cleland, B. G., Lee, B. B. & Vidyasagar, T. R. (1983). Response of neurons in the cat’s lateral geniculate nucleus to moving bars of different length. Journal of Neuroscience, 3, 108-116. Dobbins, A., Zucker, S. W. & Cynader, M. S. (1987). Endstopped neurons in the visual cortex as a substrate for calculating curvature. Nature, London, 329, 438-441. Ferster, D. & Lindstr6m, S. (1983). An intracellular analysis of geniculo-cortical connectivity in area 17 of the cat. Journal of Physiology, Lundon, 342, 181-215. Gilbert, C. D. (1977). Laminar differences in receptive field properties of cells in cat primary visual cortex. Journal of Physiology, London, 268, 391-42 1. Gulyaa, B., Orban. G. A., Duysens, J. & Maes, H. (1987). The suppressive influence of moving textured backgrounds on responses of cat striate neurons to moving bars. Journal of Neurophysiology,57, 1767-1791. Hammond, P. & Andrews, D. P. (1978). Collinearity
247
tolerance of cells in amas 17 and 18 of the cat’s visual cortex: Relative mnsltivity to straight lines and chevrons. Expninvntal Brain Research, 31, 329-339. Heggelund, P. & Hohmann, A. (1975). Responses of striate cortical cells to moving edges of diBbrent curvatures. Exg&mental B&n Research, 23, 211-216. Henry, G. H., Bishop, P. 0. & Dreher. B. (1974a). Orientation, axis and direction as stimulus pammeters for striate alls. Virion Research, 14, 761-777. Henry, G. H., Dreber, B. & Bishop, P. 0. (1974b). Orientation specificity of cells in the cat striate cortex. Journal of Neurophysioiogy, 37, 1394409. Hubel, D. H. & Wiesel, T. N. (1%2). Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. Journal of Physiology, London, 160, 106-154. Hubel, D. H. & Wiesel, T. N. (1%5). Receptive fields and functional architectum in two nonstriate visual areas (18 and 19) of the cat. Journal of Neurophysiology, 28, 229-289. Kato, H., Bishop, P. 0. & Orban, G. A. (1978). Hypercomplex and the simple/complex all classifications in cat striate cortex. Jouinal of Neurophysiology,41, 1071-1095. Katz, L. C. (1987). Local circuitry of identified projection neurons in cat visual cortex brain slices. Journal of Neuroscience, 7, 1223-1249. MacKay, D. M. & MacKay, V. (1974). Do curvaturecontingent chromatic aftereffects require ‘Detectors for curvature”‘? Vision Research, 14, 1285-1287. Malpeli, J. G. (1983). Activity of cells in area 17 of the cat in absence of input from layer A of lateral geniculate nucleus. Journal of Neurophysiology,49, 595-610. Malpeli, J. G., Lee, C., Schwark, H. D. & Weyand, T. G. (1986). Cat area 17. I. Pattern of thalamic control of cortical layers. Journal of Neurophysiology, 56, 1062-1073. Martin, K. A. C. & Whitteridge., D. (1984). Form, function and intracortical projections of spiny neurones in the striate visual cortex of the cat. Journal of Physiology, London, 353, 463-504. Mustari, M. J., Bull& J. & Henry, G. H. (1982). Comparison of response properties of three types of monosynaptic S-cell in cat striate cortex. Journal of Neurophysiology,47, 439-454. Nikara, T., Bishop, P. 0. & Pettigrew, J. D. (1968). Analysis of retinal corrcspondcna by studying receptive fields of binocular single units in cat striate cortex. Experimenfal Brain Research, G, 353-372. Ogilvie, J. & Daicar, E. (1967). The perception of curvature. Canadian Journal of Physiology, 21, 521-525. Orban, G. A., Kato, H. & Bishop, P. 0. (1979). End-zone region in receptive fields of hypercomplex and other striate neurons in the cat. Journal of Neurophysiology,42, 818-832. Orban, G. A., Kennedy, H. & Maes, H. (1981). Response to movement of neurons in areas 17 and 18 of the cat: Velocity sensitivity. Journal of Neurophysiology, 45, 1043-1058. Riggs, L. A. (1973). Curvature as a feature of pattern vision. Science, New York, 181, 1070-1072. Rose, D. (1977). Responses of single units in cat visual cortex to moving bars of light as a function of bar length. Journal of Physiology, London, 271, l-23. Saito, H., Tanaka, K., Fukuda, Y. & Oyamada, H. (1988). Analysis of discontinuity in visual contours in area 19 of the cat. Journal of Neuroscience, 8, 1131-I 143.
248
MARK VERSAVEL et al.
Schwark, H. D., Malpeli, J. G., Weyand, T. G. & Lee, C. (1986). Cat area 17. II. Response properties of infragranular layer neurons in the absence of supragranular layer activity. Journal of Neurophysiology. 56, 1074-1087. Toyama, K., Matsunami, K., Ohno, T. & Tokashiki, S. (1974). An intracellular study of neuronal organization in the visual cortex. Experimental Brain Research, 21,45-66. Van Hulle, M. & Orban, G. A. (1989). Entropy driven artificial neuronal networks and sensorial representation: A proposal. Journal of Parallel and Distributed Computation, 6, 264-290.
Watt, R. 1. (1984). Further evidence concerning the analysis of curvature in human fovea1 vision. Vision Research, 24, 251-253.
Watt, R. J. & Andrews, D. P. (1982). Contour curvature analysis: Hyperacuities in the discrimination of detailed shape. Vision Research, 22, 449-460. Wilson, H. R. (1985). Discrimination of contour curvature: Data and theory. Journal of the Optical Society qf America A, 2, 1191-1198. Wilson, H. R. & Sherman, S. M. (1976). Receptive-field characteristics of neurons in cat striate cortex: Changes with visual field eccentricity. Journal of Neurophvsiology, 39, 512-533.
Zucker, S. W. (1985). Early orientation selection: Tangent fields and the dimensionality on their support. Computer 74-103.
Vision, Graphics and Image
Processing,
32,