an analysis of orientation selectivity in the cat's visual cortex

Exp. Brain Res. 20, 1--17 (1974) �9 by Springer-Verlag 1974

An Analysis of Orientation Selectivity in the Cat's Visual Cortex

DAVID ROSE and COLIN BLAKEMORE

The Physiological Laboratory, University of Cambridge, Cambridge (England)

Received June 13, 1973

Summary. The responses of cells in the cat 's visual cortex to a moving bar of light have been analysed quantitatively, using an integration of the post-stimulus- t ime histogram, with particular reference to orientation selectivity. The method is assessed as to its reliability and usefulness; it is shown tha t much precise information about a cell can be derived from its oricntational tuning curve.

Complex cells were found on average to show more spontaneous activity, greater response amplitude, and slightly broader orientational tuning, than either simple or hypercomplex cell types. Correlations between spontaneous and evoked activity and orientational selectivity give information as to the possible mechanisms of excitation and inhibition of the cells. The question of meridional variations in perception has been especially examined: the unexpected finding that many simple cells detecting orientations close to horizontal or vertical are very narrowly tuned, which is not the case for complex or hypercomplex cells, is discussed in relation to human psychophysical variations in orientation discrimination and contrast sensitivity.

Key words: Visual co r t ex - - Orientation selectivity--Meridional acuity differences

Introduction

Acuity in man depends very much on the orientation of the stimulus used to measure it (Howard and Templeton, 1966). In particular, the contrast sensitivity for normal observers, measured with a grating pat tern is much worse when the pat tern is diagonal than when it is horizontal or vertical (Campbell et al., 1966; Maffei and Campbell, 1970). In addition the discrimination of orientation near the principal meridians is better than it is near the diagonals (e.g. Andrews, 1967; Campbell and Maffei, 1971).

The discovery of orientation-selective neurones in the cat and monkey visual cortex (Hubel and Wiesel, 1962, 1968) and the existence of many perceptual phenomena apparent ly dependent on such mechanisms in man (e.g. Blakcmore and Campbell, 1969; Campbell and Kulikowski, 1966) support the idea tha t orientation detectors mediate pat tern perception. Are the meridional variations in resolution explicable in terms of differences in the properties of orientation- selective neurones with different preferred orientations ?

There are at least three models tha t could provide greater sensitivity for vertical and horizontal patterns :

1. Ncurones optimally ' tuned' to horizontal and vertical might be more sensitive in the sense that their contrast threshold is lower.

1 Exp. Brain Res. Vol. 20

2 D. Rose and C. Blakemore

2. There could be greater numbers of neurones tuned to the principal orientations.

3. The range of orientation over which each cell responds might be brvader for neurones optimally sensitive to horizontal or vertical. Thus contours of those orientations would act ivate more neurones than diagonal lines.

The greater discriminability for horizontal and vertical pat terns could be explained by one of the following models, assuming tha t discrimination depends on a comparison of signals f rom different orientation detectors.

The principal orientations might be represented by : 1.1kTeurones with greater sensitivity. 2. Greater numbers of neurones. 3. Neurones with narrower orientation selectivity. This model has already

been proposed by Andrews (1967) on the basis of psyehophysieal judgements of apparent orientation.

Therefore models 1 or 2 (or a combinat ion of them) could account for meridional variations of both threshold and discrimination, but differences in orientation selectivity (model 3) could not.

Campbell et al. (1968), have already quantified some aspects of the angular selectivity of a sample of cortical cells, but t hey used grating pat terns ra ther than single bar stimuli and consequently they did not classify the neurones into the commonly-accepted categories (Hubel and Wiesel, 1962, 1965).

The responses of neurones in the cerebral cortex are notoriously variable, and some form of response averaging is called for. Neither the generation of conventional post-stimulus-time histograms (Perkel et al., 1967), nor the measurement of the time taken for a moving grating pattern to evoke 500 responses (Campbell et al., 1968) retains information as to this variability, knowledge of which is essential for the comparison of responses evoked by different stimuli.

I n this paper we present a quant i ta t ive analysis of the responsiveness and orientation selectivity for a large sample of neurones f rom the cat 's visual cortex, classified by the methods of Hube] and Wiesel (1962, 1965) and retaining and utilizing information about response variability. While it is by no means certain tha t cats also have natura l meridional variations in acuity, our results m a y bear on this question.

Methods

Adult cats initially prepared under short-acting barbiturate anaesthesia (sodium thiamylal or sodium methohexitone), were paralysed by intravenous infusion of Flaxedil (10 mg/kg hr) and artificially ventilated with an 80% N20, 18% 02, 20/o C02 mixture. Eye movements were minimised a) by the relaxant drug, b) by bilateral cervical sympathectomy, and e) occasionally by suturing the eyes to metal rings clamped to the stereotaxic frame. Eye rotation was assessed by photography of the slit pupils before and after surgery. The eorneae were protected with contact lenses, and additional spectacle lenses focused the eyes on a tangent screen 57 cm away. The natural pupils were dilated with Phenylephrine and Homatropine and 3 mm artificial pupils substituted. The projection of the area centralis was plotted on the screen, using a reversible ophthalmoscope.

A glass-insulated tungsten electrode (tip length 10--20 p) was introduced hydraulically through a small craniotomy to record extracellularly from units in the primary visual cortex, using conventional amplification and display techniques. Electrode positions were usually later verified histologically and we are confident that almost all cells were recorded in area 17.

Orientation Selectivity in the Visual Cortex 3

Receptive fields were plotted separately in the two eyes, using back-projection onto the tangent screen, and each cell was classified as simple, complex or hypercomplex according to Hubel and Wiesel's (1962, 1965) criteria, as summarised by Blakemore et al. (1972). For each unit the receptive field in the dominant eye was then stimulated using a bar of light generated electronically on a display oscilloscope (Blakemore and Tobin, 1972). The luminance of the bar was about 30 cd.m -2 while that of the background was about 10 cd.m-a. We varied the length, width, direction and velocity of movement of the bar to maximise the response, judged by ear. The optimal bright bar was then moved across the receptive field and the number of action potentials was recorded by gating a digital counter as the stimulus crossed the receptive field (Blakemore et al., 1972). After eight or more such sweeps in the same direction the mean response was calculated; this mean response is proportional to the area under the post-stimulus-time histogram.

We varied the orientation of the bar (in 5 or 10 degree steps) to derive a 'tuning curve' (Fig. 1). Linear regression lines fitted to each side of the curve (Campbell et al., 1968; Blake- more et al., 1972) enabled quantitative estimation of the preferred orientation, orientation- specificity, and maximum response of the ceil. The spontaneous activity was monitored by counting spikes during the same gating period with the display screen blanked. Working downwards from the maximum response, all points that differed by more than one standard error from the spontaneous level were included in the calculations of the two regression lines (Fig. 1), using the criteria of Blakemore et al. (1972). In some binocular neurones exactly the same analysis was applied separately to the non-dominant eye.

Some of the results analysed in this paper are derived from experiments performed in collaboration with L. Maffei and A. Fiorentini at the Laboratorio di Neurofisiologia del C.N.R., Pisa, using virtually identieal methods. Sign convention ]or orientation and direction o] movement 0 ~ and ~360~ Horizontal bar moving upwards

-}- 90~ Vertical bar moving left 180 ~ Horizontal bar moving downwards

-t-270~ Vertical bar moving right

Results

Responses from 88 cells from 20 cats have been analysed in full; 30 of these cells were s t imula ted through each eye separately, giving a to ta l of 118 tun ing curves. I n the stat ist ical analyses t ha t follow, unless otherwise stated, we have used only the d o m i n a n t eye results ( tuning curve with the greater response at the preferred orientat ion) for cells s tudied through both eyes. Th i r ty -n ine cells (44.3%) were classed as simple, 40 (45.5%) as complex, and nine (10.2%) as hypereomplex. The cells all had receptive fields wi thin 10 deg, and the major i ty wi thin 5 deg of the area centralis.

We will first present some of the charactcrisLics of the t un ing curves, then some correlations between characteristics which perhaps throw light on the sources of exci tat ion of cells in the visual cortex, and finally examine the question of meridional variat ions in perception.

Nomenclature

The tun ing curve of a complex cell, shown in Fig. 1, i l lustrates the terms used in this paper :

Pre/erred orientation is the or ienta t ion at which the two regression lines intersect, 84.0 ~ for this cell.

Spontaneous activity is the mean n u m b e r of impulses per second generated dur ing the gat ing period in the absence of a moving bar, 0.1 impulses in 3 sec for this cell, i.e. 0.03 impulses sec -I .

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Fig. 1. The tuning curve of ~ complex cell. Each point is the mean response, during a 3 sec gating period, for l0 sweeps of the bar at one orientation. Open symbols show responses within one s tandard error of the spontaneous firing level (shown dashed). The regression lines fitted to the remaining points h~ve slopes + 1.13 and --0.89 impulses per degree, with product- moment correlation coefficients -L0.986 and --0.994 respectively. They intersect a t an orientat ion of 84.0 ~ and a response of 47.6 impulses per presentation, and cross the spontaneous level a t orientations of 4].9 o and 137.4 ~ The characteristics of tuning curves are defined in the

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o 2o 8'o iio 14o PEAK RESPONSE AMPLITUDE ( i m p u t s e s . )

Fig. 2. How responsive are cells ? The histograms show the incidence of peak response amplitude for each cell type separately, with the mean response ampli tude shown for each case (open arrows). The differences between the means have been tested for significance in this figure (as in Figs. 3 and 4) using the Cochran and Cox modified t - test for use with unequal population variances. Complex cells are more reactive than either simple (t = 3.74, p<0.001) or hypercomplex (t = 3.77, p<0.01) , bu t simple and hypercomplex cells show no significant difference in their evoked activity (t = 0.62). The non-parametric Mann-Whitney U-test applied to the same data gives essentially similar results: the respective significance levels

reached are l~ 5% and not significant


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SPONTANEOUS ACTIVITY (impulses. see-I) Fig. 3. How spontaneously active are cells ? Histograms of spontaneous activity are shown separately for each cell type, together with the mean spontaneous activity (open arrows). Cells giving no spontaneous impulse within our gating periods are represented by the un- stippled portions of the histograms. The complex cells show greater spontaneous activity than either simple (t = 5.52, p<0.001) or hypereomplex (t = 5.35, 1o<0.001), while the simple and hypercomplex cell distributions do not differ significantly from each other (t = 0.39)

Peak response amplitude = 2a, i.e. the difference between the number of spontaneous impulses and the tota l discharge to a bar at the preferred orientation during the gating period, 47.5 impulses per presentat ion for this cell.

b - F c Average bali-width -- ~ , i.e. half the full-width of the tuning curve at

half maximal amplitude, 23.9 ~ for this cell. b

Ratio o/asymmetry ~ - - , i.e. the ratio of the antielockwise to the clockwise e

half-width, 1.27 for this cell.

Maximum Amplitudes o/Response

The distribution of peak response amplitudes (the dimension 2a in Fig. l) shows a wide spread (Fig. 2), with mode between 10 and 15 impulses per presentation, though the mean peak response ampli tude of all cells is 26.0 impulses per presentat ion (SD 28.3, N ---- 88) due to a number of complex cells with extremely brisk responses. Simple cells t end to be less reactive than complex, while hypercomplex cells resemble simple cells in their responsiveness.

D. Rose and C. Blakemore

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Fig. 4. How broadly tuned are cells ? These histograms show the incidence of average ha l l width for each cell type separately. Open arrows indicate the mean average half-width, in each case. Complex cells tend to be more broadly tuned than simple (t = 1.82, p<0 . l ) but neither simple nor complex cell types show any significant difference in average half-width

from hypercomplex cells (t = 1.81 and 1.21 respectively)

Spontaneous Activity I t is in spontaneous ac t i v i t y t h a t complex cells s t and out most (Fig. 3). Only

one simple cell and no hype rcomplex cell fired spontaneous ly more t h a n twice per second, whereas complex cells were found with f rom 0- -28 .3 impulses sec 1 ac t iv i ty . Each cell in the sample fired on average 3.1 impulses sec -1.

The Range o/Average Hall-Widths Figure 4 shows the average hal f -widths for simple, complex and hype rcomplex

cells (dominan t eye). On the whole s imple cells t e n d to be more na r rowly tuned t h a n complex. The whole cell popu la t ion has a d i s t r ibu t ion of ha l f -widths wi th i ts mode be tween 10 ~ and 12.5 ~ and a long tai l -off beyond 30 ~ giving a mean of

18.2 ~ (SD 9.9 ~ N = 88).

The Symmetry o] Tuning Curves Not all tun ing curves are as symmet r i ca l as t h a t of Fig. 1. F igure 5 shows t h a t

while most cells are qui te symmetr ica l , ex t r eme cases do occur (the most asym- met r ica l tun ing curve in our sample had ha l f -widths of 5.1 ~ and 42.1 ~ ra t io of a s y m m e t r y 1/8.2, i.e. 0.122).

Tuning Curves/or Opposite Directions o/Movement Campbel l et al. (1968) found t h a t cort ical cells responding to e i ther di rect ion

of movement , for a g ra t ing pa t t e rn , have much the same prefer red or ienta t ion, whe ther the p a t t e r n moves in one direct ion or the other.


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Fig. 5. How symmetrical are tuning curves ? This histogram shows the distribution of the ratio of asymmetry (defined in the text) for all units. Cells with greater half-width on the

anticlockwise side of the tuning curve have a ratio greater than one

In four such bi-directional cells (one simple, three complex), we measured tuning curves for both directions of movement. For all four cells the two estimates of preferred orientation matched within 4 ~ Normally, for each cell, only one of the two possible tuning curves was measured, using the preferred direction of movement if motion one way was clearly more effective than the reverse.

The Stability o/These Properties We have performed the necessary control experiment on two complex cells.

Tuning curves were repeatedly taken from the cells several times over a period of about three hours. Curves were actually measured for both directions of movement alternately (four times in each direction for one of the cells). The preferred orientation remained consistent within a range of 3 ~ (Fig. 6). The two cells had very similar average half-widths (15 ~ and 16 ~ each of which varied over a range of less than 4 ~ i.e. within 4-15%, while the ratio of asymmetry varied by less than • 20 %. Thus these properties of the cells were very stable. Spontaneous activity and peak response amplitude fluctuated rather more, but in a way that shows no significant correlation between the two, nor of either with the variations in average half-width.

The Responsiveness o/Cells Simple Cells. Looking now at corre]ations between spontaneous activity, peak

amplitude and breadth of tuning (indices of cellular responsiveness), across all the cells, some interesting interrelationships become apparent, at first sight. The more spontaneously active simple cells apparently have broader tuning and greater peak response (correlations for both significant at the 5% level). These correlations are, however, entirely due to the one simple cell with high spontaneous activity (Fig. 3), which had a large average half-width and a high peak response amplitude; elimination of this one cell from the calculations reduced the correlations to well below significance.


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ORIENTATION (deg)

Fig. 6. How repeatable is the measurement of a tuning curve ? These four curves were taken from one complex cell at intervals of about 45 rain; each curve is displaced vertically for clarity. The repeatability of preferred orientation is clear. The points forming each side of each curve gave product-moment correlation coefficients of modulus greater than 0.95 in every case. Averaging the characteristics of these four curves gives a peak orientation of 215.0 ~ (range + 1.5~ an average half-width of 14.7 ~ (+2~ an asymmetry ratio of 1.03, a peak response of 112.0 impulses per presentation and spontaneous activity of 8.1 impulses sec -1

This provides an example of how easy it is to be misled when using product-moment correlation on data which obviously do not form a bivariate normal distribution; the significance levels of correlation coefficients stated in this paper are all liable to this criticism, although the example above is by far the most aberrant.

Exclusion of simple cells with zero spontaneous ac t iv i ty from the above calculations does no t reveal any strong or significant t rend.

Complex Cells. Looking now at the equivalent calculations for complex cells (Fig. 7) it is evident t ha t :

a) there is no relationship between average half-width and spontaneous activity, and b) there does seem to be a relationship between spontaneous activity and peals

response amplitude, in that the most responsive cells tended to be more spontaneously active. Taking simple, complex and hypercompex together, this last relationship is apparent ly even stronger (r = +0.64, df = 86, p < 0.001), bu t this is due to the clustering (mainly of simple cells) at the lower extremes of both scales.

We obta ined negligible correlations between peak response ampl i tude and average half-width for each type of cell separately and for the whole cell sample together.


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Fig. 7. Do average half-width and peak response amplitude vary with spontaneous activity in complex cells ? a For average half-widths, there is no trend: r = +0.05 (dr = 38, n.s) and the regression line has slope 0.08, b :For peak response amplitude, the highly significant correlation coefficient of +0.57 (df = 38, p<0.001) indicates a broad trend in the data. The

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Fig. 8. Is the average hall-width the same whichever eye is stimulated, or does it depend oll the ocular dominance of the cell ? The response coefficient and the width coefficient (defined in the text) of each of the 30 binocularly-stimulated cells is here plotted, together with the regression line. The correlation between these two coefficients is +0.61, df = 28, p <0.001, and the regression line has slope 0.27 and constant 0.04. A 2 x 2 chi-square transposition of this

figure gives chi-square (after u correction) = 6.8, df = 1, p<0.01

Cells studied in both eyes. The 30 cells s t i m u l a t e d t h r o u g h b o t h eyes sepa ra t e ly do, however , show a l i nk b e t w e e n peak response a m p l i t u d e a n d average ha l f -wid th , in t h a t the eye giving the greater response at its pre/erred orientation also had the broader tuning curve.

I n Fig. 8: Width coe/ficient is def ined as ( C W - - I W ) / ( C W + I W ) where CW, I W are t he ave rage ha l f -w id th of t h e cell 's t u n i n g curve m e a s u r e d in t he con t ra - l a t e ra l a n d ips i l a te ra l eye respec t ive ly . Response coe/ficient is s imi la r ly def ined as


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Fig. 9. Are horizontal and vertical represented by more responsive cells than the diagonals ? The cells have been divided into two groups - - those with preferred orientation within 22.5 ~ of horizontal or vertical, and those within 22.5 ~ of the diagonals. Simple, complex and hypercomplex cells are considered separately. Each stippled block above a plus sign (+) on the abscissa represents cells within the horizontal and vertical preference group, while open blocks above the crosses ( • ) on the abscissa indicate cells preferring diagonals. The height of each block shows the mean peak response amplitude for the cells and the bars indicate +_ 1 standard deviation. A regressional analysis similar to that of Fig. l l for average half-width shows no significant correlation; the product-moment correlation coefficients for simple, complex, hypereomplex, and all cell types combined are .].0.06, --0.18, --0.33 and +0.07, respectively

( C R - - I R ) / ( C R + I R ) where CR, I R are the peak response ampli tudes for the two eyes. The correlation of these two coefficients, shown in Fig. 8, is highly significant

(p < O.OOl).

This relationship is not due to covariat ion with any fluctuations in spontaneous act ivi ty between the measurement of responses from one eye and those from the other: interocular differences in responsiveness and breadth of tun ing (as defined above) were not correlated with any small changes in spontaneous act ivi ty between measurements on the two eyes.

Meridional Variations in the Characteristics o] Cells

I n the In t roduc t ion we described three models t ha t could explain meridional var ia t ions in perception.

1. Variations in sensitivity. We have no data on the absolute contrast- thresh- olds of cells, bu t only on the maximal ampli tudes of response to high contrast stimuli. Since it is possible tha t the two are correlated, we have looked at var ia t ion in peak response ampl i tude with preferred orientat ion. We find no t endency for

Orientation Selectivity in the Visual Cortex I1

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PREFERRED ORIENTATION

Fig. 10. Do more cells respond to horizontal and vertical bars than to diagonals ? Preferred orientation is here divided into four groups - - within 22.5 ~ of horizontal, vertical and the two diagonals. The histograms show the incidence of cells for each cell type separately. For all cells, chi-square -- 3.9, df = 3; n.s. For simple and complex cells respectively the values of

chi-square are 5.6 and 1.6, both df = 3; both n.s.

cells represent ing any one axis to be more responsive, ne i ther for t he whole cell sample nor for any class of cell i nd iv idua l ly {Fig. 9).

g. Variations in cell numbers. There is no clear t endency for one majo r axis to be represen ted b y a grea te r number of eells in the visual cor tex (Fig. 10). Thus a l though, as this figure shows, we found cells sensi t ive to or ien ta t ions near hor izonta l (especially simple) most common, cells sensi t ive to ver t ica l were equa l ly as a b u n d a n t as to diagonal , and the s ta t i s t ica l analyses show the dis t rL but ions to be wi th in the bounds of sampl ing error,

3. Variations in angular selectivity. There is no sys temat ic mer id iona l va r ia t ion in the b r e a d t h of tun ing of the whole cell sample. Looking a t the cell t ypes sepa- ra te ly , however , an in teres t ing p ic ture emerges (Fig. 11). Simple cells responding best to horizontat or vertical bars tend to be more narrowly tuned tha~ those detecting diagonals; while/or complex cells the reverse trend is seen. These t r ends cancel out when all the cell t ypes are combined. The complex cell t r e n d is, however , ma in ly due to one ex t reme resul t ; exclusion of this cell f rom the analysis reduces the signifieanes level to p > 10%. The simple cell t r end is more c lear ly val id, due ma in ly to a large n u m b e r of na r rowly t u n e d cells wi th in 10 ~ of ver t ica l or hor izonta l (Fig. 11).

12 D. Rose and O. Blakemore

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Fig. 11. Are cells more finely or more broadly tuned if they are sensitive to horizontal or vertical than if they prefer diagonals ? The cells are plotted with preferred orientation ex- pressed relative to the nearest prime meridian (horizontal or vertical as 0 ~ on the abscissa). The regression line for simple cells has slope +0.20 degrees of width per degree of orientation, with correlation coefficient +0.36, df = 37, p<0.05. For complex cells, the slope is --0.21, r = --0.31, df = 38, 17<0.1 ; while for hypereomplex cells, the slope is --0.68, r = --0.50, df = 7, n.s. For all cell types combined the slope is --0.05, r = 0.07, df = 86, n.s. Beneath each plot, the cells have been grouped (as in Fig. 9) as responsive to horizontal or vertical ( +_ 22.5 ~ or to diagonals ( _+ 22.5 ~ and the mean average hMf-widths and standard deviations

displayed for each cell type

Discussion

Qua l i t a t i ve obse rva t ion a lone has r evea led a g rea t deal a b o u t the coding proper t i es of neu roncs in t h e ca t ' s v i sua l cortex. I t has shown the cells to be o r i en ta t ion-se lec t ive a n d o f ten d i rec t ion-se lec t ive (e.g. H u b e l a n d Wiesel , 1962), to be sens i t ive to t h e wid ths a n d somet imes t he l eng ths of m o v i n g bars (e.g. I-Iubel a n d Wiesel , 1965) a n d to be d e p e n d e n t on t he b i n o c u l a r d i spa r i t y of t h e s t i m u l u s (e.g. Ba r low et al., 1967). The re h a v e been i n n u m e r a b l e a t t e m p t s to q u a n t i f y va r ious aspects of t h e responses of cor t ical cells, mos t of t h e m u t i l i z ing t he fami l i a r p o s t - s t i m u l u s - t i m e h i s tog ram. I n th is pape r we have a t t e m p t e d to ana lyse t he o r i en t a t i on - se l ec t i v i t y of cor t ical n e u r o n e s us ing a s imple p rocedure


for integrating the post-stimulus-time histogram. This method allows one to describe a mean response to a stimulus and specify its variance. A comparison of responses to bars of different orientation permits the construction of a tuning curve, which gives information about spontaneous and evoked activity, orien- rational preference and its specificity (Fig. 1).

Simple integration of the overall discharge is perfectly suited for the quantifi- cation of many other properties of cortical cells, such as ocular dominance, contrast sensitivity, directional preference, optimal velocity and optimal stimulus shape and size. I t has already been used during investigations of binocular interaction (Blakemore et al., 1972) and spatial interaction between stimulation of the receptive field and the retinal area around it (Blakemore and Tobin, 1972).

On the other hand certain cellular properties, such as the shape, size and position of the receptive field and the exact firing pat tern of the cell cannot be described by this method. Indeed, the technique is only valid for the comparison of responses if the general pat tern of the discharge is similar under different conditions.

The integrated response can not only be used to compare the effectiveness of different stimuli, but also to describe changes in responsiveness to the same stimulus, as a function of t ime or any other variable. For instance, Fig. 6 shows repeated determinations of the tuning curve of a ceil. Any variation of the characteristics of these four estimates of the tuning curve could be due, of course, to a combination of statistical errors in sampling and genuine fluctuations in the properties of the eel]. In fact, the only data points that were regularly statistically ~ignificantly different between these four estimates were the measurements of spontaneous discharge, in the absence of a stimulus. Responses to the same stimulus were rarely significantly different. Therefore the observed variability in the inferred characteristics of the tuning curve itself (such as preferred orientat ion and average half-width) was probably largely due to sampling error, rather than a real change in these characteristics. Indeed the inferred characteristics varied rather little: preferred orientation was repeatable to within 3 deg, and average half-width to within _+15%, despite the large steps in orientation used to define the tuning curve. Henry et al. (1973) recently confirmed tha t these properties of cortical cells are extremely stable and suggested that moment-to- moment changes in overall sensitivity may account for the instability previously reported by some workers.

We have used our measurements of tuning characteristics to consider three questions of theoretical interest.

Di~erences in the Properties o[ Simple, Complex and Hypercomplex Cells The results of these experiments have revealed further distinctions between

the different classes of cortical cell, over and above those used to define them (Hubel and Wiesel, 1962, 1965; Blakemore el al., 1972).

First, simple and hypereomplex cells tend to produce small responses (around 10--15 impulses for the opt imum orientation), while many complex cells have much greater peak response amplitudes ; the responses of complex cells are significantly greater, on average, than those of simple or hypercomplex (Fig. 2).


The receptive fields of complex cells are larger, on the whole, than those of simple cells (gubel and Wiesel, 1962). Therefore the greater evoked activity in complex cells might be thought to be due to a correlation with receptive field size; the larger the receptive field, the longer the stimulus may have been present in the field. Although we have evidence of such a correlation, no conclusions can yet be drawn from it, because the duration of the stimulus within the receptive field depends on the velocity of movement (which we optimized) as well as the size of the field. Pettigrew et al. (1968) found in fact that complex cells prefer a higher stimulus velocity than most simple cells, and this would tend to offset the effect of the larger field size. A full analysis, taking account also of the precise stimulus velocity and the peak instantaneous frequency of firing, is therefore required.

Second, the variation in spontaneous activity is much broader, and the spontaneous discharge significantly higher, in complex cells, than in simple or hypercomplex (Fig. 3), confirming the original observation of Pettigrew et al. (1968).

Third, although there is a large variability in average half-width for all classes, complex cells tend to be slightly more broadly tuned than simple, while hypercomplex cells cover the whole range (Fig. 4).

Finally there are differences in the properties of simple and complex cells representing vertical and horizontal, compared with those responding to diagonals (Fig. 11). Simple cells tend to be more narrowly tuned than those preferring diagonals, while for complex cells the trend, if any, is the reverse. This unexpected finding has implications in the debate about meridional variations in acuity (see below).

The above findings bear on the question of serial or parallel processing in the visual cortex. While they are not totally incompatible with Hubel and Wicsel's (1962, 1965) hicrarchial model (complex cells being driven by simple cell input, and hypereomplex by complex) they are more easily reconciled with the idea that the properties of simple and complex cells, and perhaps hypercomplex too, are largely determined by their own independent inputs from gcnieulate afferent fibres (Hoffman and Stone, 1971; Dreher, 1972).

The Sources o/ Excitation o/Neurones in the Visual Cortex

The section on the responsiveness o I cells examined correlations between three indices of cellular activity: spontaneous activity, evoked activity at the preferred orientation and the breadth of oricntational tuning.

Simple cells, all except for one, had very low spontaneous discharge (Fig. 3) so the range of spontaneous activities encountered was too small, in simple cells, to adequately test correlations with the other characteristics.

However, for complex cells (where the range of spontaneous activities was large: Fig. 3), and for all cells combined, there was a good positive correlation between peak response amplitude and spontaneous activity, but no relationship between average half-width and spontaneous activity (Fig. 7). There was also no correlation between average half-width and peak response amplitude for any class of neurone.

The good correlation between spontaneous and evoked activity implies that the cell's spontaneous discharge is at least partly determined by the spontaneous activity in afferent fibres (specific or non-specific) rather than being entirely dependent on mechanisms within the eel] itself. This same conclusion may be


drawn from the fact tha t undercutting the cortex abolishes spontaneous activity (Burns, 1958).

The lack of any correlation between the width of orientational tuning and either spontaneous activity o1" peak response amplitude suggests that the factors determining the cxact breadth of tuning are different from those that provide spontaneous and evoked excitation. One possibility that could cope well with tMs finding is the notion tha t the narrowness of the tuning curve is part ly determined by intra-eortical lateral inhibition from neighbouring cells with similar preferred orientations (Blakemore st al., 1970; Benevento et al., 1972; Blakemore and Tobin, 1972).

However, for binocularly driven cells, there is a high correlation between the relative peak response amplitude and the relative average half-width for the tuning curves measured through the two eyes (Fig. 8): the dominant eye tends to have somewhat broader tuning than the non-dominant eye. So, for each cell the peak and breadth of the tuning curve co-vary between the two eyes, even though there is no such obvious co-variation for the tuning curves from a number of different cells. Indeed there is much less variation in average half-width between the two eyes for each cell (Fig. 8) than there is between the average half-widths of tuning curves in the dominant eye for many cells (Fig. 4), just as Noda et al. (1971a) have found.

There are a number of models tha t could explain all these findings. One possible scheme, which fits this and other evidence is that the direct inputs to a cell from the two eyes which probably determine the relative responsiveness, are related in orientational tuning; the more responsive input being more broadly tuned. Any further mechanisms (such as intracortical inhibition), which might act on both inputs to improve the narrowness of tuning, would not then disrupt this basic relationship. On the other hand, intracortical inhibition might act very differently from one cell to another, producing great differences in tuning and hence breaking down any fundamental correlation between responsiveness and breadth of tuning which might be inherent in the direct input.

Meridional Variations in Acuity

Much of the evidence suggests that cats do not manifest meridional differences in acuity in the same way as man (Campbell et al., 1973). Nevertheless, our results have some bearing on the models presented in the Introduction for explaining meridional differences in sensitivity and discrimination. Unfortunately, they are not directly relevant to the first model in each case, namely tha t neurones tuned to horizontal or vertical have greater contrast sensitivity than those tuned to the diagonals. I t is possible tha t the supra-threshold responsiveness of a cortical cell, indicated by the peak response amplitude, is simply related to its contrast threshold, and in tha t case there is no difference between neurones representing different angles (Fig. 9).

We examined the variation in cell numbers tuned to different orientation (Fig. 10) but again there was no real difference. Campbell et al. (1968) and Noda et al. (1971b) have also failed to find any significant variation, although Pettigrew et al. (1968) have reported greater representation of the principal meridians for a very particular class of cortical cell, the dh~ection-seleetive simple cells with


recept ive fields very near the visual axis. The diff icul ty in answering this quest ion cannot be over-emphasised. The p rob lem of adequa te sampl ing is enormous because of t he grouping of cells wi th similar prefer red or ienta t ions in to columns in the cor tex (Hube] and Wiesel , 1962, 1965). A n y sample of neurones f rom a l imi ted area of cor tex is bound to cover only a smal l range of or ientat ions. W e t r i ed to preclude this p rob lem b y dr iv ing the electrode d iagonal ly th rough the cor tex across m a n y cort ical columns. I n addi t ion , the ca t ' s visual experience ear ly in life m a y very much de te rmine the numbers of cells represent ing different or ienta t ions (Blakemore and Cooper, 1970).

The remain ing models to explain mer id iona l differences in acu i ty involve the b r ead th of t un ing : bu t the predic t ions to account for var ia t ions in sens i t iv i ty are opposi te to those t h a t might expla in var ia t ions in d iscr iminat ion. I n fact we have found t h a t s imple cells t u n e d to hor izonta l and ver t ica l t end to be more na r rowly tuned t han those sensit ive to diagonal , whereas for complex cells the case is, ff anyth ing , the opposi te (Fig. 11). Could i t be t h a t s imple cells are responsible for discrimination of or ienta t ion, fulfilling Andrews ' (1967) requ i rements for orien- ra t iona l fea ture filters, whereas complex cells might conceivably be more involved in the detection of pa t t e rn s ? The observed differences in tun ing then predic t t h a t both funct ions would be more acute at the pr inc ipa l meridians.

Acknowledgements. We are very grateful to Drs A. Fiorentini, L. Maffei and E.A. Tobin for collaborating in some of these experiments, and to R.D. Loewenbein and J.S. Dormer for technical help. The work was supported by grants (Nos. G970/807/B and G972/463/B) to C.B., from the Medical Research Council, London. D.R. is a MRC scholar.

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