VLrion Res. Vol. 32, No. 12, pp. 2289-2293, Printed in Great Britain
1992
0042-6989/92
$5.00 + 0.00
Pergamon Press Ltd
Visual Acuity in the Horse BRIAN TIMNEY,*
KATHY
KEIL*
Received 2 January 1992; in revised form 27 May 1992
We assessed the ease with which horses could learn visual discriminations and measured their resolution acuity. We trained three horses to press their noses against one of two large wooden panels to receive a small food reward. Following training on a series of two-choice discrimination tasks, resolution acuity was measured. Although there was some variability between animals, the best acuity obtained was 23.3 c deg-‘. Within the margin of error imposed by limited anatomical data, the obtained values are consistent with predictions based on retinal ganglion cell density estimates and posterior nodal distance/axial length ratios. They suggest that the resolution acuity of the horse is limited by ganglion cell density in the temporal portion of the narrow visual streak. Horse
Visual acuity
Visual discrimination
INTRODUCTION
The visual system of the horse is a curious one and poses an interesting problem for the student of visual acuity. In absolute terms the equine eye is one of the largest of any mammal, thus creating a large retinal image. However, the advantage conferred by a large eye must be tempered by consideration of the topographic organisation of the retina. In an anatomical study, Francois, Wouters, Victoria-Troncoso, de Rouck and van Gerven (1980) reported that at all locations sampled cones made up a relatively small proportion of the receptor population. They concluded that their observations “explain(ed) the poor vision of the horse, particularly under photopic conditions” (p. 348). However, they provide no other evidence for their claim of weak vision, nor do they take into account the absolute density of the receptors or the potential role played by other photoreceptors in determining the acuity of the horse. In contrast to Francois et al., Walls (1942) argued that horses have excellent vision. His evidence was based on an Arab legend concerning horses’ ability to recognize their masters from great distances. Hebel (1976) examined retinal whole mounts of three horses. He reported the presence of a narrow horizontal visual streak slightly dorsal to the optic disk. The streak extended about 22 mm into the nasal and temporal retinae, although a region of high density was apparent almost to the ora serrata nasalward. In the temporal portion of the streak, ganglion cell density reached a peak of 6500 cells mm-*. Outside the streak, the ganglion cell density was the lowest of all of the species examined by Hebel (pig, sheep, ox, and dog), at ~500 cells mm-*. Under the assumption that ganglion cell density is of relevance for resolution acuity, Hebel *Department Ontario,
of Pyschology, University Canada N6A 5C2.
of Western
Ontario,
London,
concluded that the horse has the poorest acuity of all domestic mammals. However, he made no attempt to take into account the fact that cell density within the streak itself was comparable to that of other species or that the large size of the horse eye provided for a large retinal magnification factor. Another factor that may play a role in the determination of acuity is accommodative ability. Although an early report suggested that the horse possessed a ramp retina and no dynamic lenticular accommodation (Nicholas, 1930), more recent data provide no support for these assertions (Sivak & Allen, 1975). It is difficult to provide a quantitative estimate of visual acuity based solely on anatomical, physiological, optical or anecdotal evidence. The purpose of the present study was to use behavioural techniques coupled with standard psychophysical procedures to obtain such an estimate. Previous investigators have shown that horses are able to learn visual discrimination tasks with relative ease (Baer, Potter, Friend & Beaver, 1983; Fiske & Potter, 1979; Hierd, Lokey & Logan, 1986; Kratzer, Netherland, Pulse & Baker, 1977; Mader & Price, 1980), although the limits of their discriminative abilities have not been tested. METHODS Subjects
Three animals were used in the present experiment: a lZyr-old thoroughbred mare (Hl), a 5-yr-old warmblood mare (H2) and a lCyr-old part-Arabian small mare (H3). Routine ocular examinations prior to testing showed clear ocular media and no sign of any eye disorder. During the course of the study H2 suffered an episode of uveitis in one eye. The animal was not tested at this time and following treatment she showed no apparent ill effects or change in performance. The
2290
BRIAN
TIMNEY
animals were not food deprived and had free access to water and salt. They were housed individually and exercised daiIy. Apparatus The apparatus (shown in Fig. 1) exploited the natural tendency of horses to push at objects with their noses. It consisted of a rectangular wooden board mounted on a stand at nose height for the horses. The stimuli were mounted on two counterweighted trapdoor panels, designed to open slowly when pushed. Each door could be locked when necessary. Food rewards (Horse Krunch; Masterfeeds) were placed on a small tray behind each door. A divider between the trapdoors set the minimum distance at which the animals were forced to make a decision about the door to approach. As training proceeded the length of the divider was increased from 40 to 231 cm. Stimuli The stimuli were 20 by 25 cm high contrast (>0.9) square-wave gratings with periods ranging from a maximum of 30.0 mm to a minimum of 1.3 mm. At the highest frequencies the step sizes were a little less than 1 mm. Two small tungsten lamps (40 W) illuminated the gratings, providing a space-averaged luminan~ of approx. 30 cd m-‘. The negative stimulus was a grating with a spatial frequency beyond the animals’ resolution acuity. To minimise the possibility that the horses might be using brightness cues to make the discrimination, we used three different negative gratings, one whose spaceaveraged luminance was matched as closely as possible to that of the other gratings in the series and the other two which were slightly lighter or darker (34 and 23 cd m-‘). All were used during a threshold measuring session. Spatial frequency for all gratings was calculated as the frequency subtended at the end of the divider, the closest point to the apparatus before the horse was
md
KATHY
KEIL
forced to make a decision. This frequency, :4 ncccssar-11) a conservative estimate: it seemed from ohscrvation ot the animals that they made their choice several tens oi centimetres in front of the divider. although it WI’; difficult to specify this distance. Procedurr Initiul training. Training proceeded in stages, first to famiharise the animals with the apparatus and then to provide a set of progressively more difficult discriminations. Three different training discriminations were used: white vs black, low frequency grating vs black, and low frequency grating vs “grey”. Each daily session comprised 40 trials and the horses were required to reach a criterion level of 27 correct trials out of 30 consecutive trials. When position preferences developed, they were corrected by giving repeated trials on the non-preferred side. All trials, including the correction series, were used in calculating the numbers of trials and errors to criterion. Once the horses reached criterion on all of these tasks with the small divider, a series of additional trials to criterion were run with longer dividers, after which measurements of visual acuity were begun. Measurement qf w&al acuity. A modified method of limits was used to obtain a preliminary threshold estimate. A testing session began with the presentation of a low frequency grating. Following a correct response the spatial frequency was increased on the next trial. This procedure was continued until the horse made an error and permitted us to move rapidly to gratings that were more difficult to discriminate. For the rest of the session, stimuli were presented in blocks of five trials. If the horse achieved four or five correct the spatial frequency was increased for the next trial block. Tf three were correct another set of five trials was run at the same spatial frequency, and if fewer than two trials were correct the spatial frequency was decreased on the next set. .A typical experimental session continued until the horse
-
FIGURE
I. Apparatus
used to measure
the resolution
acuity
of the horse.
Not drawn
to scale
ACUITY
IN THE
had failed to meet criterion on at least two trial blocks. Occasionally, sessions were ended because a horse refused to continue. To obtain a final threshold estimate, a method of constant stimuli was used. Five gratings that covered a range of spatial frequencies that bracketed the preliminary threshold estimate were used. These gratings were presented in random order in blocks of five trials until all five gratings had been presented. A second series was then run. In a typical session, 10 trials were obtained for each frequency and sessions were repeated until a total of 50 trials had been run at each frequency. RESULTS
Initial training All three horses learned the initial discrimination tasks quickly. A summary of the trials and errors to criterion is presented in Fig. 2. The easiest discrimination was the initial black vs white and the most difficult was the grating vs “grey” task. There were also quite marked individual differences in both performance and attitude towards the task. For example H2 needed only about half as many daily sessions as the two other horses to learn the three initial discriminations. However, this horse had very variable performance during the daily
2291
HORSE
testing sessions. Hl required more trials to learn all three discrimination tasks than the other two but had the least variability. Threshold estimates For two of the horses, Hl and H2, the percentage of correct responses made during the constant stimuli sessions was calculated and a psychometric function was fitted using probit analysis (Finney, 1971). Acuity threshold was taken as the point at which the fitted curve fell to 70% correct. The third horse, H3, was much more variable in performance and it proved impossible to obtain a complete set of constant stimuli data from this animal. Instead, a psychometric function was derived from the data obtained during the preliminary threshold sessions. The results from all three horses are shown in Fig. 3.
Hl
loo!%80 70 a50 -
250 200 150 100 50
5
10
I5
20
25
30
35
H3
I
II
III
Spatial frequency
(cyc/deg)
Task FIGURE 2. Summary of the average number of trials and errors prior to reaching criterion for the three initial training discriminations. Task I = black vs white; Task II = grating vs black; Task III = grating vs grey. Bars represent 1 SEM.
FIGURE 3. Psychometric functions showing percentage of correct responses as a function of spatial frequency for each of the three horses. Data for Hl and H2 are based on at least 100 trials per point gathered using a method of constants. Data for H3 were obtained using a method of limits with an average of 25 trials per point.
2292
BRIAN
TIMNEY
The final a&ties obtained were 23.3 c deg- ’ (Hl), 21.2 c deg-’ (H2), and 10.9 c deg-’ (H3). It may be seen from the figure also that there were large differences in the slopes of the psychometric functions. It is likely that these are a reflection of each animal’s approach to the task.
DISCUSSION The initial training results obtained in the present experiment are consistent with previous literature regarding the training and learning abilities in horses (Baer et al., 1983; Fiske & Potter, 1979; Hierd et al., 1986; Kratzer et al., 1977; Mader & Price, 1980). Observation of the present animals suggested that they learned the basic requirements of the task very quickly; subsequent performance reflected the difficulty of the task. It is worth noting also that these animals retained their knowledge of the task for long periods, For example, H 1 was retested for a different experiment after a 6 month lay-off and required only half the number of trials to learn the initial discriminations again. There is almost a two-fold difference between the mean threshold of the two larger horses and the threshold of the smaller horse. It seems likely that the differences may be attributed primarily to behavioural and procedural factors. Certainly a major factor was the general disposition of the horses. For example, Hl responded very well to praise and affection while H2 was much more highly motivated by the food reward and typically worked more enthusiastically. H3 was not motivated very strongly by either food or verbal praise. She performed the tasks very slowly and reluctantly. It was difficult to motivate her, especially when presented with gratings near threshold. Because of the reluctance of this horse to work, we were unable to obtain constant stimuli data for her. Her threshold was obtained from the preliminary runs using the method of limits and an average of 25 trials per datum point. In contrast we were able to collect 100 trials per datum point from H2 with much less variability. Thus it seems likely that the low acuity estimate for H3 was a result of her lack of interest in the task rather than a difference between different breeds of horse, although this is a question that should be explored. The best acuity we obtained was a little over 23 c deg. ‘. As we indicated, this value may be conservative because the horses typically made their decisions prior to reaching the divider. On most trials they would not stop at the divider, but instead would veer towards their chosen side shortly before they reached the end of the divider. If we assume that a decision was made at a distance of 3 m, the acuity estimates increase to 30.8, 27.6, and 14.2 c deg-’ respectively. The limits of the spatial resolving power are set by several factors. These include: the optics of the eye, the size and brightness of the retinal image, the grain of the photoreceptors, and the convergence of the receptors onto higher order neurons. In practice, the optical resolution of most eyes exceeds that of the neural
and KATHY
KEIL
limitations, and under photopic conditions a reasonable estimate of potential acuity may be obtained given an estimate of the retinal magnification factor and the peak ganglion cell density of the retina (Hughes. 1977). Although the accuracy of the estimate depends upon the validity of several assumptions concerning the relationship between receptors and ganglion cells, as well as the accuracy of the anatomical data, the general validity of the approach has been demonstrated for several species (Hughes, 1977). Another factor to be taken into account concerns the population of ganglion cells that may be responsible for limiting acuity (Hughes, 1981). In cat, acuity varies with eccentricity as a function of /I-ganglion cell density (Blake & Bellhorn. 1978). Also in cat. the /I-cell population contains approximately equal proportions of ONand OFF-cells (Wassle, Boycott & Illing, 198 I). Behavioural measurements of resolution acuity (Hall & Mitchell, 1991) suggest that the ON- and OFF-P-cells may be regarded as a single heterogeneous population (Hughes, 1981). On the other hand, there is evidence to suggest that in primates, acuity is limited by the density of ON- OYOFF-cells (Merigan & Katz, 1990; Perry & Cowey, 1988). No measurements of p-cell density have been made in the horse, nor is anything known about the ON- and OFF-properties of such cells. For this reason we have chosen to use total ganglion cell density as the basis for calculations. As we mentioned earlier, the horse has one of the largest eyes of any mammal, although there is some variability in the data on axial length. Nicholas (1930) reported a value of 43.7 mm while Prince. Diesem. Eglitis and Russell (1960) gave a range of 32 38 mm. In a more recent study, Sivak and Allen (1975) obtained a range of 37.641.0 mm with a mean of 40.6, and Knill, Eagleton and Harver (1977) reported an axial length of 37.8 mm. To calculate the retinal magnification factor, it is necessary also to know the focal length of the eye. This is given by the posterior nodal distance (PND), or the distance from the retina to the posterior nodal point. To our knowledge, this value is not available in the literature; however, Pettigrew. Dreher, Hopkins. McCall and Brown (1988) report that the mean ratio of the PND to axial length for diurnal eyes is 0.67. Taking Sivak and Allen’s (1975) estimate of 40.6 mm for the axial length. this gives a PND of 27.02 mm. The retinal magnification factor (RMF) expressed as distance on the retina that subtends 1 deg of visual angle may then be calculated from the equation: RMF = (2rcPND/360)
mm deg
’
(Pettigrew et al., 1988). Using these values, the RMF for the horse is 0.47 mm deg-‘. An estimate of visual acuity may then be calculated based on ganglion cell density (Hughes, 1977; Pettigrew et al.. 1988). Hebel (1976) reported a peak density of about 6500 cells mm ’ in the temporal visual streak, giving a density of 1436 cells deg-‘. Assuming a hexagonal array, maximum acuity is 20.37 c deg -‘. An alternative estimate of the PND/axial length ratio is given by Hughes (1977). who gives a value
ACUITY IN THE HORSE
of approx. 0.38 as the RMF of the horse [her Fig. 9(b)]. Using her values, the estimated acuity is 16.4 c deg-‘. These values are somewhat lower than the best values we obtained, but according to Hughes (personal communication) these measurements were made on a relatively small horse and may represent the lower end of the range. Given the range of uncertainty in the anatomically based estimates, the fit with the empirical data is reasonable. REFERENCES Baer, K. L., Potter, G. D., Friend, T. H. & Beaver, B. H. (1983). Observation effects of learning in horses. Applied Animal Ethology, II, 123-129.
Blake, R. & Bellhorn, R. W. (1978). Visual acuity in cats with central retinal lesions. Vision Research, f8, 15-18. Finney, D. J. (1971). Probit analysis. Cambridge: Cambridge University Press. Fiske, J. C. & Potter, G. D. (1979). Discrimination reversal learning in yearling horses. Journal of Animal Science, 49, 583-588. Francois, J., Wouters, L., Victoria-Troncoso, V., de Rouck, A. & van Gerven, A. (1980). Morphometric and electrophysiologic study of the photoreceptors in the horse. Ophthalmologica, 181, 340-349.
Hall, S. E. & Mitchell, D. E. (1991). Grating acuity of cats measured with detection and discrimination tasks. Behavioural Brain Research, 44, l-9.
Hebel, R. (1976). Distribution of retinal ganglion cells in five mammalian species. Anatomy and Embryology, 150, 45-51. Hierd, J. C., Lokey, C. E. & Logan, D. C. (1986). Repeatability and comparison of two maze tests to measure learning ability in horses. Applied Animal Behavior Science,
2293
Knill, L. M., Eagleton, R. D. & Harver, E. (1977). Physical optics of the equine eye. American Journal of Veterinary Research, 38, 735-737.
Kratzer, D. D., Netherland, W. M., Pulse, R. E. & Baker, J. P. (1977). Maze learning in quarter horses. Journal of Animal Science, 46, 896902. Mader, D. R. & Price, E. 0. (1980). Discrimination learning in horses: Effects of breed, age and social dominance. Journal of Animal Science, SO, 962-965. Merigan, W. H. & Katz, L. M. (1990). Spatial resolution across the macaque retina. Vision Research, 30, 985-991. Nicholas, E. (1930). Veterinary and comparative ophthalmology. London: H. & W. Brown. Perry, V. H. & Cowey, A. (1988). The lengths of the fibres of Henle in the retina of macaque monkeys: Implications for vision. Neuroscience, 12, 225-236. Pettigrew, J. D., Dreher, B., Hopkins, C. S., McCall, M. J. & Brown, M. (1988). The peak density and distribution of ganglion cells in the retinae of microchiropteran bats: Implications for visual acuity. Brain, Behavior and Evolution, 32, 39-56.
Prince, J. H., Disem, C. D., Eglitis, I. & Russell, G. I. (1960). Anatomy and histology of the eye and orbit of domestic animals. Springfield, Ill.: Thomas. Sivak, J. G. & Allen, D. B. (1975). An evaluation of the “ramp” retina of the horse eye. Vision Research, 15, 1353-1356. Swenson, M. J. (1984). Duke’s physiology of domestic animals (10th edn). Ithaca: Cornell University Press. Walls, G. L. (1942). The vertebrate eye and its adaptive radiation. Bloomfield Hills, Mich.: Cranbrook Institute of Science. Wissle, H., Boycott, B. B. & Illing, R. B. (1981). Morphology and mosaic of on- and off-beta cells in the cat retina and some functional considerations. Proceedings of the Royal Society of London, Series B, 121, 177-195.
16, 103-I 19.
Hughes, A. (1977). The topography of vision in mammals in contrasting lifestyle: Comparative optics and retinal organization. In Crescitelli, F. (Ed.), The visual system in vertebrates. Handbook of sensory physiology (Vol. VII/s, pp. 61k-756). Berlin: Springer. Hughes, A. (1981). Cat retina and sampling theorem: The relation of transient and sustained brisk-unit cut-off frequency to a- and /?-mode cell density. Experimental Brain Research, 42, 196-202.
Acknowledgements-We
thank Carol Birchmore and Allison Smith for their kindness in making their horses available to us and John Orphan who helped design and constructed the apparatus. We thank also Dr Geoff Faulkner for conducting the ophthalmic examinations. Supported in part by a Dean’s grant from the Faculty of Social Science, University of Western Ontario.
1992
0042-6989/92
$5.00 + 0.00
Pergamon Press Ltd
Visual Acuity in the Horse BRIAN TIMNEY,*
KATHY
KEIL*
Received 2 January 1992; in revised form 27 May 1992
We assessed the ease with which horses could learn visual discriminations and measured their resolution acuity. We trained three horses to press their noses against one of two large wooden panels to receive a small food reward. Following training on a series of two-choice discrimination tasks, resolution acuity was measured. Although there was some variability between animals, the best acuity obtained was 23.3 c deg-‘. Within the margin of error imposed by limited anatomical data, the obtained values are consistent with predictions based on retinal ganglion cell density estimates and posterior nodal distance/axial length ratios. They suggest that the resolution acuity of the horse is limited by ganglion cell density in the temporal portion of the narrow visual streak. Horse
Visual acuity
Visual discrimination
INTRODUCTION
The visual system of the horse is a curious one and poses an interesting problem for the student of visual acuity. In absolute terms the equine eye is one of the largest of any mammal, thus creating a large retinal image. However, the advantage conferred by a large eye must be tempered by consideration of the topographic organisation of the retina. In an anatomical study, Francois, Wouters, Victoria-Troncoso, de Rouck and van Gerven (1980) reported that at all locations sampled cones made up a relatively small proportion of the receptor population. They concluded that their observations “explain(ed) the poor vision of the horse, particularly under photopic conditions” (p. 348). However, they provide no other evidence for their claim of weak vision, nor do they take into account the absolute density of the receptors or the potential role played by other photoreceptors in determining the acuity of the horse. In contrast to Francois et al., Walls (1942) argued that horses have excellent vision. His evidence was based on an Arab legend concerning horses’ ability to recognize their masters from great distances. Hebel (1976) examined retinal whole mounts of three horses. He reported the presence of a narrow horizontal visual streak slightly dorsal to the optic disk. The streak extended about 22 mm into the nasal and temporal retinae, although a region of high density was apparent almost to the ora serrata nasalward. In the temporal portion of the streak, ganglion cell density reached a peak of 6500 cells mm-*. Outside the streak, the ganglion cell density was the lowest of all of the species examined by Hebel (pig, sheep, ox, and dog), at ~500 cells mm-*. Under the assumption that ganglion cell density is of relevance for resolution acuity, Hebel *Department Ontario,
of Pyschology, University Canada N6A 5C2.
of Western
Ontario,
London,
concluded that the horse has the poorest acuity of all domestic mammals. However, he made no attempt to take into account the fact that cell density within the streak itself was comparable to that of other species or that the large size of the horse eye provided for a large retinal magnification factor. Another factor that may play a role in the determination of acuity is accommodative ability. Although an early report suggested that the horse possessed a ramp retina and no dynamic lenticular accommodation (Nicholas, 1930), more recent data provide no support for these assertions (Sivak & Allen, 1975). It is difficult to provide a quantitative estimate of visual acuity based solely on anatomical, physiological, optical or anecdotal evidence. The purpose of the present study was to use behavioural techniques coupled with standard psychophysical procedures to obtain such an estimate. Previous investigators have shown that horses are able to learn visual discrimination tasks with relative ease (Baer, Potter, Friend & Beaver, 1983; Fiske & Potter, 1979; Hierd, Lokey & Logan, 1986; Kratzer, Netherland, Pulse & Baker, 1977; Mader & Price, 1980), although the limits of their discriminative abilities have not been tested. METHODS Subjects
Three animals were used in the present experiment: a lZyr-old thoroughbred mare (Hl), a 5-yr-old warmblood mare (H2) and a lCyr-old part-Arabian small mare (H3). Routine ocular examinations prior to testing showed clear ocular media and no sign of any eye disorder. During the course of the study H2 suffered an episode of uveitis in one eye. The animal was not tested at this time and following treatment she showed no apparent ill effects or change in performance. The
2290
BRIAN
TIMNEY
animals were not food deprived and had free access to water and salt. They were housed individually and exercised daiIy. Apparatus The apparatus (shown in Fig. 1) exploited the natural tendency of horses to push at objects with their noses. It consisted of a rectangular wooden board mounted on a stand at nose height for the horses. The stimuli were mounted on two counterweighted trapdoor panels, designed to open slowly when pushed. Each door could be locked when necessary. Food rewards (Horse Krunch; Masterfeeds) were placed on a small tray behind each door. A divider between the trapdoors set the minimum distance at which the animals were forced to make a decision about the door to approach. As training proceeded the length of the divider was increased from 40 to 231 cm. Stimuli The stimuli were 20 by 25 cm high contrast (>0.9) square-wave gratings with periods ranging from a maximum of 30.0 mm to a minimum of 1.3 mm. At the highest frequencies the step sizes were a little less than 1 mm. Two small tungsten lamps (40 W) illuminated the gratings, providing a space-averaged luminan~ of approx. 30 cd m-‘. The negative stimulus was a grating with a spatial frequency beyond the animals’ resolution acuity. To minimise the possibility that the horses might be using brightness cues to make the discrimination, we used three different negative gratings, one whose spaceaveraged luminance was matched as closely as possible to that of the other gratings in the series and the other two which were slightly lighter or darker (34 and 23 cd m-‘). All were used during a threshold measuring session. Spatial frequency for all gratings was calculated as the frequency subtended at the end of the divider, the closest point to the apparatus before the horse was
md
KATHY
KEIL
forced to make a decision. This frequency, :4 ncccssar-11) a conservative estimate: it seemed from ohscrvation ot the animals that they made their choice several tens oi centimetres in front of the divider. although it WI’; difficult to specify this distance. Procedurr Initiul training. Training proceeded in stages, first to famiharise the animals with the apparatus and then to provide a set of progressively more difficult discriminations. Three different training discriminations were used: white vs black, low frequency grating vs black, and low frequency grating vs “grey”. Each daily session comprised 40 trials and the horses were required to reach a criterion level of 27 correct trials out of 30 consecutive trials. When position preferences developed, they were corrected by giving repeated trials on the non-preferred side. All trials, including the correction series, were used in calculating the numbers of trials and errors to criterion. Once the horses reached criterion on all of these tasks with the small divider, a series of additional trials to criterion were run with longer dividers, after which measurements of visual acuity were begun. Measurement qf w&al acuity. A modified method of limits was used to obtain a preliminary threshold estimate. A testing session began with the presentation of a low frequency grating. Following a correct response the spatial frequency was increased on the next trial. This procedure was continued until the horse made an error and permitted us to move rapidly to gratings that were more difficult to discriminate. For the rest of the session, stimuli were presented in blocks of five trials. If the horse achieved four or five correct the spatial frequency was increased for the next trial block. Tf three were correct another set of five trials was run at the same spatial frequency, and if fewer than two trials were correct the spatial frequency was decreased on the next set. .A typical experimental session continued until the horse
-
FIGURE
I. Apparatus
used to measure
the resolution
acuity
of the horse.
Not drawn
to scale
ACUITY
IN THE
had failed to meet criterion on at least two trial blocks. Occasionally, sessions were ended because a horse refused to continue. To obtain a final threshold estimate, a method of constant stimuli was used. Five gratings that covered a range of spatial frequencies that bracketed the preliminary threshold estimate were used. These gratings were presented in random order in blocks of five trials until all five gratings had been presented. A second series was then run. In a typical session, 10 trials were obtained for each frequency and sessions were repeated until a total of 50 trials had been run at each frequency. RESULTS
Initial training All three horses learned the initial discrimination tasks quickly. A summary of the trials and errors to criterion is presented in Fig. 2. The easiest discrimination was the initial black vs white and the most difficult was the grating vs “grey” task. There were also quite marked individual differences in both performance and attitude towards the task. For example H2 needed only about half as many daily sessions as the two other horses to learn the three initial discriminations. However, this horse had very variable performance during the daily
2291
HORSE
testing sessions. Hl required more trials to learn all three discrimination tasks than the other two but had the least variability. Threshold estimates For two of the horses, Hl and H2, the percentage of correct responses made during the constant stimuli sessions was calculated and a psychometric function was fitted using probit analysis (Finney, 1971). Acuity threshold was taken as the point at which the fitted curve fell to 70% correct. The third horse, H3, was much more variable in performance and it proved impossible to obtain a complete set of constant stimuli data from this animal. Instead, a psychometric function was derived from the data obtained during the preliminary threshold sessions. The results from all three horses are shown in Fig. 3.
Hl
loo!%80 70 a50 -
250 200 150 100 50
5
10
I5
20
25
30
35
H3
I
II
III
Spatial frequency
(cyc/deg)
Task FIGURE 2. Summary of the average number of trials and errors prior to reaching criterion for the three initial training discriminations. Task I = black vs white; Task II = grating vs black; Task III = grating vs grey. Bars represent 1 SEM.
FIGURE 3. Psychometric functions showing percentage of correct responses as a function of spatial frequency for each of the three horses. Data for Hl and H2 are based on at least 100 trials per point gathered using a method of constants. Data for H3 were obtained using a method of limits with an average of 25 trials per point.
2292
BRIAN
TIMNEY
The final a&ties obtained were 23.3 c deg- ’ (Hl), 21.2 c deg-’ (H2), and 10.9 c deg-’ (H3). It may be seen from the figure also that there were large differences in the slopes of the psychometric functions. It is likely that these are a reflection of each animal’s approach to the task.
DISCUSSION The initial training results obtained in the present experiment are consistent with previous literature regarding the training and learning abilities in horses (Baer et al., 1983; Fiske & Potter, 1979; Hierd et al., 1986; Kratzer et al., 1977; Mader & Price, 1980). Observation of the present animals suggested that they learned the basic requirements of the task very quickly; subsequent performance reflected the difficulty of the task. It is worth noting also that these animals retained their knowledge of the task for long periods, For example, H 1 was retested for a different experiment after a 6 month lay-off and required only half the number of trials to learn the initial discriminations again. There is almost a two-fold difference between the mean threshold of the two larger horses and the threshold of the smaller horse. It seems likely that the differences may be attributed primarily to behavioural and procedural factors. Certainly a major factor was the general disposition of the horses. For example, Hl responded very well to praise and affection while H2 was much more highly motivated by the food reward and typically worked more enthusiastically. H3 was not motivated very strongly by either food or verbal praise. She performed the tasks very slowly and reluctantly. It was difficult to motivate her, especially when presented with gratings near threshold. Because of the reluctance of this horse to work, we were unable to obtain constant stimuli data for her. Her threshold was obtained from the preliminary runs using the method of limits and an average of 25 trials per datum point. In contrast we were able to collect 100 trials per datum point from H2 with much less variability. Thus it seems likely that the low acuity estimate for H3 was a result of her lack of interest in the task rather than a difference between different breeds of horse, although this is a question that should be explored. The best acuity we obtained was a little over 23 c deg. ‘. As we indicated, this value may be conservative because the horses typically made their decisions prior to reaching the divider. On most trials they would not stop at the divider, but instead would veer towards their chosen side shortly before they reached the end of the divider. If we assume that a decision was made at a distance of 3 m, the acuity estimates increase to 30.8, 27.6, and 14.2 c deg-’ respectively. The limits of the spatial resolving power are set by several factors. These include: the optics of the eye, the size and brightness of the retinal image, the grain of the photoreceptors, and the convergence of the receptors onto higher order neurons. In practice, the optical resolution of most eyes exceeds that of the neural
and KATHY
KEIL
limitations, and under photopic conditions a reasonable estimate of potential acuity may be obtained given an estimate of the retinal magnification factor and the peak ganglion cell density of the retina (Hughes. 1977). Although the accuracy of the estimate depends upon the validity of several assumptions concerning the relationship between receptors and ganglion cells, as well as the accuracy of the anatomical data, the general validity of the approach has been demonstrated for several species (Hughes, 1977). Another factor to be taken into account concerns the population of ganglion cells that may be responsible for limiting acuity (Hughes, 1981). In cat, acuity varies with eccentricity as a function of /I-ganglion cell density (Blake & Bellhorn. 1978). Also in cat. the /I-cell population contains approximately equal proportions of ONand OFF-cells (Wassle, Boycott & Illing, 198 I). Behavioural measurements of resolution acuity (Hall & Mitchell, 1991) suggest that the ON- and OFF-P-cells may be regarded as a single heterogeneous population (Hughes, 1981). On the other hand, there is evidence to suggest that in primates, acuity is limited by the density of ON- OYOFF-cells (Merigan & Katz, 1990; Perry & Cowey, 1988). No measurements of p-cell density have been made in the horse, nor is anything known about the ON- and OFF-properties of such cells. For this reason we have chosen to use total ganglion cell density as the basis for calculations. As we mentioned earlier, the horse has one of the largest eyes of any mammal, although there is some variability in the data on axial length. Nicholas (1930) reported a value of 43.7 mm while Prince. Diesem. Eglitis and Russell (1960) gave a range of 32 38 mm. In a more recent study, Sivak and Allen (1975) obtained a range of 37.641.0 mm with a mean of 40.6, and Knill, Eagleton and Harver (1977) reported an axial length of 37.8 mm. To calculate the retinal magnification factor, it is necessary also to know the focal length of the eye. This is given by the posterior nodal distance (PND), or the distance from the retina to the posterior nodal point. To our knowledge, this value is not available in the literature; however, Pettigrew. Dreher, Hopkins. McCall and Brown (1988) report that the mean ratio of the PND to axial length for diurnal eyes is 0.67. Taking Sivak and Allen’s (1975) estimate of 40.6 mm for the axial length. this gives a PND of 27.02 mm. The retinal magnification factor (RMF) expressed as distance on the retina that subtends 1 deg of visual angle may then be calculated from the equation: RMF = (2rcPND/360)
mm deg
’
(Pettigrew et al., 1988). Using these values, the RMF for the horse is 0.47 mm deg-‘. An estimate of visual acuity may then be calculated based on ganglion cell density (Hughes, 1977; Pettigrew et al.. 1988). Hebel (1976) reported a peak density of about 6500 cells mm ’ in the temporal visual streak, giving a density of 1436 cells deg-‘. Assuming a hexagonal array, maximum acuity is 20.37 c deg -‘. An alternative estimate of the PND/axial length ratio is given by Hughes (1977). who gives a value
ACUITY IN THE HORSE
of approx. 0.38 as the RMF of the horse [her Fig. 9(b)]. Using her values, the estimated acuity is 16.4 c deg-‘. These values are somewhat lower than the best values we obtained, but according to Hughes (personal communication) these measurements were made on a relatively small horse and may represent the lower end of the range. Given the range of uncertainty in the anatomically based estimates, the fit with the empirical data is reasonable. REFERENCES Baer, K. L., Potter, G. D., Friend, T. H. & Beaver, B. H. (1983). Observation effects of learning in horses. Applied Animal Ethology, II, 123-129.
Blake, R. & Bellhorn, R. W. (1978). Visual acuity in cats with central retinal lesions. Vision Research, f8, 15-18. Finney, D. J. (1971). Probit analysis. Cambridge: Cambridge University Press. Fiske, J. C. & Potter, G. D. (1979). Discrimination reversal learning in yearling horses. Journal of Animal Science, 49, 583-588. Francois, J., Wouters, L., Victoria-Troncoso, V., de Rouck, A. & van Gerven, A. (1980). Morphometric and electrophysiologic study of the photoreceptors in the horse. Ophthalmologica, 181, 340-349.
Hall, S. E. & Mitchell, D. E. (1991). Grating acuity of cats measured with detection and discrimination tasks. Behavioural Brain Research, 44, l-9.
Hebel, R. (1976). Distribution of retinal ganglion cells in five mammalian species. Anatomy and Embryology, 150, 45-51. Hierd, J. C., Lokey, C. E. & Logan, D. C. (1986). Repeatability and comparison of two maze tests to measure learning ability in horses. Applied Animal Behavior Science,
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Knill, L. M., Eagleton, R. D. & Harver, E. (1977). Physical optics of the equine eye. American Journal of Veterinary Research, 38, 735-737.
Kratzer, D. D., Netherland, W. M., Pulse, R. E. & Baker, J. P. (1977). Maze learning in quarter horses. Journal of Animal Science, 46, 896902. Mader, D. R. & Price, E. 0. (1980). Discrimination learning in horses: Effects of breed, age and social dominance. Journal of Animal Science, SO, 962-965. Merigan, W. H. & Katz, L. M. (1990). Spatial resolution across the macaque retina. Vision Research, 30, 985-991. Nicholas, E. (1930). Veterinary and comparative ophthalmology. London: H. & W. Brown. Perry, V. H. & Cowey, A. (1988). The lengths of the fibres of Henle in the retina of macaque monkeys: Implications for vision. Neuroscience, 12, 225-236. Pettigrew, J. D., Dreher, B., Hopkins, C. S., McCall, M. J. & Brown, M. (1988). The peak density and distribution of ganglion cells in the retinae of microchiropteran bats: Implications for visual acuity. Brain, Behavior and Evolution, 32, 39-56.
Prince, J. H., Disem, C. D., Eglitis, I. & Russell, G. I. (1960). Anatomy and histology of the eye and orbit of domestic animals. Springfield, Ill.: Thomas. Sivak, J. G. & Allen, D. B. (1975). An evaluation of the “ramp” retina of the horse eye. Vision Research, 15, 1353-1356. Swenson, M. J. (1984). Duke’s physiology of domestic animals (10th edn). Ithaca: Cornell University Press. Walls, G. L. (1942). The vertebrate eye and its adaptive radiation. Bloomfield Hills, Mich.: Cranbrook Institute of Science. Wissle, H., Boycott, B. B. & Illing, R. B. (1981). Morphology and mosaic of on- and off-beta cells in the cat retina and some functional considerations. Proceedings of the Royal Society of London, Series B, 121, 177-195.
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Hughes, A. (1977). The topography of vision in mammals in contrasting lifestyle: Comparative optics and retinal organization. In Crescitelli, F. (Ed.), The visual system in vertebrates. Handbook of sensory physiology (Vol. VII/s, pp. 61k-756). Berlin: Springer. Hughes, A. (1981). Cat retina and sampling theorem: The relation of transient and sustained brisk-unit cut-off frequency to a- and /?-mode cell density. Experimental Brain Research, 42, 196-202.
Acknowledgements-We
thank Carol Birchmore and Allison Smith for their kindness in making their horses available to us and John Orphan who helped design and constructed the apparatus. We thank also Dr Geoff Faulkner for conducting the ophthalmic examinations. Supported in part by a Dean’s grant from the Faculty of Social Science, University of Western Ontario.
