Exp Brain Res (2001) 141:242–249 DOI 10.1007/s002210100872

R E S E A R C H A RT I C L E

Kenichiro Miura · Kazuyo Suehiro Miyuki Yamamoto · Yasushi Kodaka · Kenji Kawano

Initiation of smooth pursuit in humans Dependence on target saliency Received: 3 August 2000 / Accepted: 27 July 2001 / Published online: 3 October 2001 © Springer-Verlag 2001

Abstract We examined the influence of target saliency on the initiation of smooth pursuit. The eye movements of five human subjects were recorded with the scleral search-coil technique. A video-projection system was used to create a pursuit target, consisting of a cluster of 14 red or green dots (0.5° squares) extending randomly over a 3°×3° region, and a surrounding background, consisting of stationary, random dots of the same size and density extending over an area 70°×40°. When the dots in the background and the target were of the same color, the target was indistinguishable from the background until it started to move. On the other hand, when the colors were different, the target was salient, even when stationary. We measured the changes in eye position over the 70-ms interval starting 70 ms after the onset of target motion (initial tracking response). When the target moved toward the fovea (centripetal motion), the initial tracking responses developed earlier when the dots in the target and background were of different color than when the two sets of dots were of the same color. However, in order to see this effect of target salience, it was critical that the colors be different before the onset of motion, but not afterwards. When the target moved away from the fovea (centrifugal motion), the initial tracking responses were independent of whether the colors of the target and the background were the same or different. K. Miura · Y. Kodaka (✉) · K. Kawano CREST, Japan Science and Technology Corporation e-mail: [email protected] Tel.: +81-298-615847, Fax: +81-298-615849 K. Suehiro · Y. Kodaka · K. Kawano Neuroscience Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan M. Yamamoto Institute of Basic Medical Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8575, Japan Present address: K. Miura, Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA

Our data indicate that the initiation of tracking responses is very sensitive to the saliency of the target before the onset of target motion when that motion is toward the fovea. Keywords Eye movements · Smooth pursuit · Target saliency · Attention · Human

Introduction Primates utilize the so-called smooth pursuit system to track moving objects with their eyes (Lisberger et al. 1987; Keller and Heinen 1991; Ilg 1997). This system allows humans to keep the retinal image of the object within or near the fovea, facilitating good vision of the tracked object. In everyday life, we commonly track objects that move across a stationary textured background, and a number of studies have shown that such backgrounds influence tracking performance (Collewijn and Tamminga 1984; Keller and Khan 1986; Kimmig et al. 1992; Masson et al. 1995; Mormann and Thier 1995; Niemann and Hoffmann 1997). In particular, stationary textured backgrounds have been shown to reduce the initial eye acceleration that monkeys can achieve when attempting to track a target that suddenly starts to move (Keller and Khan 1986; Kimmig et al. 1992; Mormann and Thier 1995). A similar reduction has also been observed in humans, although the reduction was smaller than in monkeys (Masson et al. 1995; Niemann and Hoffmann 1997). One effect of stationary textured backgrounds is to reduce the target’s saliency, though the mere existence of stationary texture elements nearby is sufficient to attenuate initial tracking responses (Kimmig et al. 1992). In the present study, we have examined the effect of manipulating the saliency of the target on smooth pursuit initiation by using targets consisting of elements that either matched the background (nonsalient) or differed from the background in color (salient). Our data indicate that the target’s saliency can influence smooth pursuit initia-

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tion when the target moves toward the fovea, but not when the target moves away from the fovea. Moreover, our results indicate that these effects depend on the saliency of the target before it starts to move.

Materials and methods Subjects Eye movements were recorded in five subjects (subjects A–E, four men and one woman) ranging from 28 to 50 years old. Subjects A, B, and C were authors and the remaining two subjects were na and unaware of the experimental design. Each subject had normal or corrected-to-normal vision, normal visual fields, and clinically normal eye movements. The experiments were performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki. All subjects gave their informed consent prior to their inclusion in the study. Visual stimuli and behavioral paradigms During the experiments, the subject sat on a chair with their eyes near the center of an 80-cm-diameter field coil system (EnzanshiKogyo). The subject’s head was supported by chin and forehead rests so that the eyes were 52 cm from a translucent tangent screen (90×90°). All the visual stimuli were generated by a Silicon Graphics Octane workstation and were back-projected onto a translucent screen with a video projector (Electrohome, Marquee 8110). The spatial resolution was 1,280×1,024 pixels (~0.1°/ pixel), with a display-refresh rate of 72 Hz. The track target consisted of a cluster of 14 red or green dots (0.5° squares, 4.52 cd/m2) randomly distributed over a 3×3° region, and was surrounded by a background consisting of stationary, randomly distributed dots of the same size, luminance, and density extending over an area 70×40° (luminance, less than 0.02 cd/m2; density, ~1.5 dots/1° squares). All the dots in the background were the same color (red or green). When the dots in the target and background were the same color, the target was indistinguishable from the background until it started moving. On the other hand, when the colors were different, the target was salient, even when stationary. One experimental situation used two kinds of visual stimuli: In one stimulus, the dots in the target and background were of a different color throughout the trial (Fig. 1a) and, in the other, their colors were the same throughout the trial (Fig. 1b). For three subjects, we recorded eye movements using all of the possible stimulus combinations: 2 target colors × 2 background colors × 2 directions × 7 initial target positions. For the remaining two subjects, the number of combinations was reduced by half by using only green targets: 1 target color × 2 background colors × 2 directions × 7 initial target positions. (Note that the data from the three subjects obtained for all of the visual conditions showed no systematic differences depending on the color of the target.) At the beginning of each trial, the target cluster of dots was centered 0°, 3°, 6°, or 12° right or left of the center of the screen. The subject was required to fixate a yellow spot (0.8°×0.8°) projected at the center of the screen for 1.5–2.0 s. Then the fixation spot disappeared and the target started to move horizontally (leftward or rightward) at 30°/s. After the target had moved for 500 ms, the projected images were replaced by a dark, homogeneous image (less than 0.02 cd/m2), signaling the end of the trial. The subjects were required to track the moving target as best they could. Before starting each recording session, the subjects were informed that if there were dots whose color differed from the surrounding dots those dots would be the pursuit target. The other experimental situation had two additional visual conditions (Fig. 1c, d). In one, the dots in the target and background were of a different color until 14 ms before the onset of target motion (one frame), at which time the color of the target

Fig. 1a–d Schematic diagram of the visual stimuli used in the experiments. Representative stimulus configurations at three different time points are shown for the visual conditions used. Left: Visual display while the subject was fixating the central dot. Middle: Visual display during the frame where the first moving stimuli were presented. Right: Visual display while the subject was tracking the target. a Visual condition in which the dots in the target and background were different colors throughout the trial. b Visual condition in which the colors were the same throughout the trial. c Visual condition in which the colors were different until 14 ms before the onset of target motion and the colors were the same while it was moving. d Visual condition in which the colors were the same until 14 ms before the onset of target motion and the colors were different while it was moving

dots changed to that of the background (Fig. 1c). In the other, the dots in the target and background were of the same color until 14 ms before the onset of target motion, at which time the color of the target dots changed (Fig. 1d). In these experimental situations, we recorded the smooth pursuit eye movements of three subjects. The time course and sequence of events during each trial were the same as in the first experiment. In each trial, the region centered either 0° or 3° right or left of the center of the screen was selected as the initial target position. Eye movement recordings and data analysis The presentation of the stimuli and the acquisition, display, and storage of data were controlled by the REX system (Hays et al. 1982) running on a PC (Gateway, P5-150). Eye movements were measured with the electromagnetic search-coil technique (Fuchs and Robinson 1966). Each subject wore an eye coil (Collewijn et al. 1975). The coil was placed in the right eye following application of 1–2 drops of anesthetic (oxybuprocain hydrochloride) and wearing time was limited to 40 min. Viewing was always binocular. The signal from this coil was calibrated by having the subject fixate targets at the center of the screen or 10 up, down, left, or right of the center. Voltage signals encoding the horizontal and vertical components of the eye position were low-pass filtered with R-C circuitry (170 Hz, –3 dB) and digitized to a resolution of 12 bits, sampling at 1 kHz. A digital output channel on the DIO board of the PC running REX was connected to a parallel port of

244 the workstation that generated the visual stimulus to permit triggering of the target motion. The actual onset of target motion was slightly delayed from the trigger signal. To help determine the exact time of onset and the duration of the target motion, the workstation generated a rectangular image 20° below the lower edge of the visual stimulus on the screen while the target was moving. This image was sensed with a photocell (Hamamatsu, S2281) whose output was monitored by the PC running REX, together with eye position. Note that the part of the screen where the rectangular images were projected was covered with a black sheet, hiding the images from the subject. All data were stored and transferred to a PC (Dell XPS D333) for analysis using an interactive computer program based on MATLAB (Mathworks). First, eye position data were smoothed with a digital low-pass filter (33 points, 30 Hz, –3 dB). Then, eye velocity was obtained by two-point backward differentiation of the eye position data. Signals encoding eye acceleration were also obtained by two-point backward differentiation of the eye velocity data, in order to identify saccades using velocity and acceleration criteria (eye velocity of more than 50°/s; eye acceleration of more than 1,000°/s per second). The eye movement data were aligned on the onset of target motion (the time at which the first motion frame was presented) and sorted according to the stimulus conditions. First, the mean eye velocity temporal profile was computed for each of the different stimulus conditions, after excluding the data that contained any saccades during the 130-ms period following the onset of target motion. Then, the time of response onset was determined from the mean eye velocity profiles, using the method of Kimmig et al. (1992). Briefly, we first determined the mean eye speed (± SD) over the 100-ms time period beginning 50 ms before the onset of target motion (preresponse baseline). We then determined the earliest time at which the response exceeded the preresponse baseline by 3 SDs. Finally, we computed the change in eye position over the 70-ms interval starting 70 ms after the onset of target motion (initial tracking response). Note that the shortest onset latency estimated from the mean velocity profiles was 70 ms, so that this initial tracking response provided an estimate of the initial openloop response. Trials were excluded from the analysis if they contained saccades of less than 140 ms after stimulus onset, using the criteria described above. After this exclusion, for each stimulus condition, data were available for at least 14 trials and generally more than 20 trials, and these were used to compute the mean eye velocity profiles for each stimulus condition. The statistical significance of the differences between measurements was assessed with the Wilcoxon rank-sum test or Wilcoxon sign test.

Results The raw smooth pursuit responses (n=30) when subject A tracked a green target moving leftward at 30°/s against a background consisting of red dots on a dark plane are shown in Fig. 2a as eye position and in Fig. 2b as eye velocity. At the beginning of each trial, the target dots occupied a 3°×3° region centered 3° right of the initial fixation point. In most trials, the eye velocity increased smoothly until ≈180ms after stimulus onset, and then catch-up saccades occurred. After the catch-up saccades, the eye velocity was generally close to the target velocity. Figure 2c shows the mean eye velocity for these 30 responses as a thick continuous line, with 1 SD shown as a thick dashed line. Also shown in Fig. 2c is the mean velocity (thin line) with 1 SD (thin dashed line) when the subject tracked the same green target moving against a background of green dots. In these sample data, it is clear that the eye velocity during the initiation of

Fig. 2a–c Smooth pursuit responses to multiple presentations of a green target (a cluster of 14 green dots) moving leftward at 30°/s against a background consisting of red dots. a Superimposed horizontal eye position traces (n=30). b Superimposed horizontal eye velocity traces computed from the traces in a. In each velocity trace, data points within the interval of catch-up saccades were deleted. c Mean eye velocity (thick continuous line) with 1 SD (thick dashed line) computed from the traces in b. Only the data points for which we could average more than ten values after deleting the excursions due to catch-up saccades are shown. It also shows the mean eye velocity traces (thin continuous line) with 1 SD (thin dashed line) when the subject pursued a green target moving against a green background. In a–c, upward deflections of the traces indicate leftward eye movements

smooth pursuit was larger when the colors of the dots in the target and background were different than when the colors were the same, though no such difference was apparent during the maintenance period of smooth pursuit. Centrifugal versus centripetal tracking This dependence of initial smooth pursuit on the color contrast between the dots in the target and background was only apparent when target motion was directed toward the fovea. Figure 3a, b shows sample pursuit responses of subject D when the subject pursued a green target moving leftward against red (thick lines) and green (thin lines) background dots. When the target

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Fig. 4 Group mean of initial tracking responses. Closed circles and open circles indicate the responses observed when the dots in the target and background were different colors and when the colors were the same, respectively. Data points are group means of the normalized responses and error bars are 1 SD (16 cases: 2 target colors × 2 directions × 3 subjects + 1 target color × 2 directions × 2 subjects). Points to the right of zero represent responses when the target moved toward the fovea

Fig. 3a–c Initial tracking responses when subject D tracked a green target moving leftward at 30°/s. a Mean eye velocity traces when the target started to move from the region centered 3° left of the initial fixation point against red (thick line) and green (thin line) backgrounds. b Mean eye velocity traces when the target started to move from the region centered 3° right of the initial fixation point against red (thick line) and green (thin line) backgrounds. c Initial tracking response as a function of the initial target position. The initial target position was plotted as positive when the center of the target regions was right of the fixation point. In a–c, upward deflections indicate leftward eye movement

started to move from the region centered 3° left of the fixation point (centrifugal motion; Fig. 3a), the mean eye velocity profiles were similar, irrespective of the color of the dots in the background. On the other hand, when the target started to move from the region centered 3° right of the fixation point (centripetal motion; Fig. 3b), the mean eye velocity 90 ms after the onset of target motion was larger when the dots in the background were red (thick line) than when they were green (thin line). The same trend was already seen in Fig. 2. Figure 3c shows a plot of the initial tracking responses, quantified as indicated in Materials and methods, when subject D tracked a green target moving leftward against red (closed circles) and green (open circles) backgrounds as a function of the initial position of the target. When the target started to move from the regions centered 3°, 6°, and 12° right of the fixation point, i.e., target motion was centripetal, the initial tracking responses were larger when the dots in the background were red than when they were green. The differences were statistically significant (Wilcoxon rank sum test, P<0.01). On the other hand, when the target started to move from the regions centered 3°, 6°, and 12° left of the fixation point, i.e., target motion was centrifugal, the responses were quite similar, irrespective of the color of the background dots, and the differences were not statistically significant. When the

target started to move from the center of the screen (0°), the initial tracking response was larger when the background dots were red than when they were green. However, the difference between the responses was not statistically significant. In sum, for subject D, the initial tracking responses to a centripetally moving target were larger when the color of the dots in the target and background were different from when the color was the same. Similar effects of color contrast were often observed in all five subjects studied. Thus, for the 16 cases studied (2 target colors × 2 directions × 3 subjects + 1 target color × 2 directions × 2 subjects), statistically significant differences were found in 15, 16, and 12 cases when the target started to move from the regions centered 3°, 6°, and 12°, respectively (Wilcoxon rank sum test, P<0.01). On the other hand, when the track target moved centrifugally, initial tracking responses were similar irrespective of the differences in colors of dots in the target and background or somewhat smaller when the colors of the target and the background were different than when the colors were the same. Statistically significant differences were found only in single cases when the target started to move from the region centered at 3°, 6°, and 12° (Wilcoxon rank sum test, P<0.01). When the target started to move from the region centered at 0°, initial tracking responses were similar or larger when the dots in the target and background were of different color than when they were the same. Statistically significant differences were found in four cases (Wilcoxon rank sum test, P<0.01). There were no systematic dependencies on color per se, i.e., whether dots were red or green. Figure 4 shows the group mean of the normalized initial tracking responses (with 1 SD) as a function of the initial position of the target. The normalized responses were computed by dividing the individual mean responses by the mean responses to motion of a target that was the same color as the background and started at 0°. When the target started to move from the regions cen-

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Fig. 5a–c Representative mean eye acceleration (top) and mean eye velocity profiles (bottom). a Mean eye acceleration and mean eye velocity profiles when subject D tracked the green target starting to move centripetally from 3° right or left of the initial fixation point. Responses to leftward target motion are shown in gray and to rightward target motion in black; thin lines indicating that the dots in the target and the background had the same color and the thick lines indicating that they had different colors. The mean acceleration profiles shown were smoothed with a cubic spline to reduce the effects of noise. Upward deflections indicate leftward eye movement. b Mean eye acceleration and mean eye velocity profiles when subject A tracked the green target starting to move centripetally from 3° right or left from the initial fixation point. c Mean eye acceleration and mean eye velocity profiles when subject E tracked the red target starting to move centripetally from 3° right or left from the initial fixation point. In b and c, other conventions as in a

tered 12°, 6°, 3°, or 0°, the responses were larger when the dots in the target and background were different colors (closed circles) than when they were the same (open circles). The differences were statistically significant (Wilcoxon sign test for initial target position of 0°, Wilcoxon rank sum test for all others; P<0.01, n=16). On the other hand, when the target started to move from the regions centered –12°, –6°, or –3°, the responses were somewhat smaller when the dots in the target and background were different colors (closed circles) than when they were the same (open circles). However, these differences were not statistically significant. The above analysis showed that the initiation of smooth pursuit was sensitive to the color contrast between the dots in the target and the background when the target motion was centripetal. However, our response measure was time-locked to the stimulus and so did not indicate whether the effects were due to changes in the latency of response onset and/or the initial eye acceleration. Careful scrutiny of the mean response profiles uncovered some cases in which the latency appeared to be

affected but, unfortunately, the initial tracking responses were often weak and irregular, rendering the usual latency algorithms unusable. Figure 5 shows representative mean eye acceleration (top panels) and velocity (bottom panels) profiles of our three subjects when they tracked a target that started to move centripetally from 3° right or left of the initial fixation point. Responses to leftward target motion are shown in gray and responses to rightward target motion in black; thin lines indicating that the dots in the target and the background had the same color and the thick lines indicating that they had different colors. The mean acceleration profiles shown in this figure were smoothed with a cubic spline to reduce the effects of noise. Typically, mean eye acceleration started to increase about 70 ms after the onset of target motion, showing an initial peak 20–30 ms later and, following a dip that varied considerably in extent, increased once more, often steeply. For the data illustrated in Fig. 5a (subject D), the major effect of changing the color contrast of the dots in the target and background when target motion was leftward seems to be on the latency of response onset. However, this effect is less clear in the rightward pursuit of the same subject and is also not evident in the initial pursuit responses of the other subjects. These latter mean profiles could mean that changing the color contrast of the dots in the target and background often did not cause a simple shift of the latency distribution. Unfortunately, the irregularity and low signal-tonoise of the earliest components in the raw data do not permit us to examine this issue further.

Dependence on color contrast before and after the onset of target motion The above data indicate that, when the target moved toward the fovea (centripetal motion), the initial tracking

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Fig. 6a–c Initial tracking responses when subject B tracked the pursuit target moving against a green background under four visual conditions. a Mean eye velocity traces when the target color changed from red to green before motion onset (Different-same condition, thick continuous line); when the color changed from green to red before motion onset (Same-different condition, thin continuous line); when the color remained red throughout the trial (Different-different condition, thick dashed line); and when the color remained green throughout the trial (Same-same condition, thin dashed line). Upward deflection of the trace indicates leftward eye movement. b Initial tracking responses (with SE) calculated from the data shown in a. c Distribution of indices under the Different-same (closed circles) and Same-different (open circles) conditions. Each bin has a width of 0.2

responses developed earlier when the dots in the target and background were of different color than when the two sets of dots were of the same color. The data in Fig. 6, however, indicate that in order to see this effect of color contrast it was critical that the colors be different before the onset of motion but not afterwards. Figure 6a, b shows sample data for subject B when the subject

tracked a target that started moving leftward at 30°/s from the region centered 3° right of the initial fixation point against a background of green dots. When the dots in the target started out red but changed to green to match the color of the background dots, 14 ms before motion onset (Different-same condition, thick continuous line), the response to target motion was similar to that when the color was red throughout a trial (Differentdifferent condition, thick dashed line). Furthermore, when the dots in the target started out green, matching the color of the background dots, but then changed to red 14 ms before motion onset (Same-different condition, thin continuous line), the response was similar to that when the color was green throughout the trial (Samesame condition, thin dashed line). To quantify these effects of changing the color of the target, we computed an index, defined as (x–RSS)/ (RDD–RSS), where RDD and RSS denote the responses to target motion under the Different-different and Samesame conditions, respectively, and x was the response under the Different-same or Same-different conditions. When x equals RDD, (RDD+RSS)/2, or RSS, the index becomes 1, 0.5, and 0, respectively. For the data shown in Fig. 6a, b, the index was 1.11 under the Different-same condition and –0.08 under the Same-different condition. Figure 6c shows the distribution of the index under the Different-same (closed circles) and Same-different (open circles) conditions for 12 cases (2 background colors × 2 directions × 3 subjects). The mean index (± SD) under the Same-different condition was –0.02±0.10 (n=12), indicating that the responses to target motion under the Same-different condition are similar to the responses under the Same-same condition. On the other hand, the mean index (± SD) under the Different-same condition was 1.07±0.23 (n=12). This indicates that the responses to target motion under the Different-same condition are similar to the responses under the Different-different condition, and that the response to centripetal target motion is sensitive to the difference in the colors of the target and background 14 ms or more before the onset of target motion.

Discussion In this study, we examined the effect of target saliency on smooth pursuit initiation using a cluster of 14 dots as the pursuit target. The size, shape, and density of the dots in the target were always identical to those of the dots in the background, so that when the dots also shared the same color, the pursuit target blended completely with the background, and subjects could not distinguish the target unless it moved. On the other hand, when the dots in the target and background were different colors, the subjects could easily distinguish the target before it began to move. When the dots in the target and background were of different color, the initial tracking responses to centripetal target motion developed earlier than when the colors were the same, provided that the

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color contrast was present before the target began to move. The responses to centrifugal target motion showed no such dependence on color contrast. We also found a significant difference in the group mean of the responses when the target motion started from the center, perhaps because the target dots were scattered over a 3°×3° area and so included some that underwent centripetal motion. Centripetal bias When the dots in the target and background were of different color prior to motion onset, centripetal target motion resulted in higher initial tracking responses than centrifugal target motion (Figs. 3c, 4): centripetal bias. On the other hand, such asymmetry was not found when the colors were the same prior to target motion. The observed centripetal bias might be a consequence of the mechanism by which the target’s saliency before the onset of target motion improves the pursuit of centripetally moving targets. Previous studies have found a similar centripetal bias in the initial pursuit of humans (Tychsen and Lisberger 1986) and monkeys (Lisberger and Westbrook 1985). Effects on latency and/or initial eye acceleration? In this study, we used the change in eye position during the 70-ms interval starting 70 ms after the onset of target motion as our measure of the initial tracking response. This raises the issue of whether the effects of color contrast that we have reported were due to changes in latency and/or the initial eye acceleration. In our preliminary analyses (not shown), we attempted to measure the response latency on individual trials using some objective methods often used in quantitative studies of smooth pursuit (Carl and Gellman 1987; Krauzlis and Miles 1996). However, the latency estimates were variable, depending on the methods used. Also, direct visual inspection of the initial velocity and acceleration response profiles indicated that these methods often yielded poor estimates of latency, in large part because the initial response profiles were often irregular (see Fig. 5) and very small resulting in low signal-to-noise. Perusal of the mean response profiles, such as those in Fig. 5, generally showed little evidence of simple shifts of the latency distribution. Because the latency of the mean profiles is generally determined by the shortest latency on a trialby-trial basis, this implies that the shortest latency has little dependence on the target saliency. However, it is still unclear whether the effect of target saliency on our initial tracking response measure is due to effects on the initial acceleration (metrics) and/or the variance of the latency (trigger mechanism). Even in the case in which a clear latency change is evident in the mean profiles, such as in Fig. 5a, it is quite possible that the latency change was secondary to changes in the response magnitude, the apparent changes in latency resulting from an “iceberg

effect” in which raising or lowering the incrementing responses uncovers more or less of the earliest component. Further systematic experiments are needed to clarify this point. Comparison with previous studies Using the deviation of the eye acceleration profiles for leftward and rightward pursuit to mark the onset of pursuit (cf. Tanaka and Lisberger 2000) suggests that the latency in our experiments was ≈70 ms. Such short latencies are more in line with ocular following responses than the voluntary tracking of a small spot (Carl and Gellman 1987; Gellman et al. 1990), perhaps because we used a target consisting of a cluster of dots. This suggests that the earliest components of our responses might share its mechanism with the ocular following responses. Previous studies of the effects of stationary textured backgrounds on the initiation of smooth pursuit reported reductions in the magnitude of the initial eye acceleration but no changes in the latency of onset of the tracking (Keller and Khan 1986; Kimmig et al. 1992). However, in the study of Kimmig et al., the background influenced only the tracking of centrifugal motion (Kimmig et al. 1992) and did not seem to depend on target salience, because initial tracking was even attenuated by texture 30° from the target. It is possible that the saliency phenomenon which we have described could account for the finding of Krauzlis and Lisberger (1994), who demonstrated that, when monkeys tracked a small spot moving centripetally on a dark background, the early phase of eye acceleration during smooth pursuit initiation was modulated by the motion onset delay, which was the period during which the target spot was visible before it started to move. They showed that, when the motion onset delay was more than 100 ms, the initial eye acceleration showed separable early and late components, but if the delay was 0 ms then the early component was absent. In terms of target saliency, the visual conditions when the motion onset delay was 300 ms resembled those in our experiments when the target was salient before motion onset (Different-different), a situation in which the earliest phase of pursuit was present (Fig. 6a). In contrast, the visual conditions when the motion-onset delay was 0 ms resembled those in our experiments when the target was not salient before motion onset (Same-different), a situation in which the earliest phase of pursuit was much reduced or even absent (Fig. 6a). As already pointed out, our experiments indicate that it was the target saliency prior to the onset of motion that was critical, so that the earliest phase of eye acceleration was also present in the Different-same condition but small or absent in the Same-same condition (Fig. 6a). The similarity between our finding and those of Krauzlis and Lisberger suggests to us that our two studies share a common mechanism.

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Attentional effects? The attention of the subjects might also have been a factor in our experiments. When the dots in the target and background were of a different color, the target was salient and clearly visible even when stationary. Hence, when the colors were different before the target started to move, it is possible that the subjects directed their attention to the target before the onset of target motion. There is evidence that MT and MST provide the visual motion signals for pursuit (Dursteler and Wurtz 1988; Komatsu and Wurtz 1988; Kawano et al. 1994) and that the activity of some neurons in these areas is modulated by the subject’s attention: Treue and Maunsell (1999) demonstrated that the responses of some neurons in areas MT and MST to a stimulus inside their receptive field were larger when the subject’s attention was directed inside the receptive field than when their attention was directed elsewhere. If the activity of the neurons in MT/MST contributing to pursuit were modulated by the subject’s attention, then the tracking responses to the motion of an attended target would be expected to be larger than to the motion of an unattended target. It remains to be explained why the effects of target saliency were apparent only with centripetal target motion. Acknowledgements We are deeply grateful to Dr. F.A. Miles for his valuable suggestions on the manuscript. We thank K. Hashimoto for technical assistance, and Y. Yaguchi and S. Inoue for secretarial assistance. This research was supported by grants from Core Research for Evolutional Science and Technology (CREST) of the Japan Science and Technology Corporation.

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