Prevention of coordinated eye movements and steering impairs driving performance

Transcription

1 Exp Brain Res (2005) 163: DOI /s RESEARCH ARTICLE D. E. Marple-Horvat Æ M. Chattington Æ M. Anglesea D. G. Ashford Æ M. Wilson Æ D. Keil Prevention of coordinated eye movements and steering impairs driving performance Received: 1 July 2004 / Accepted: 9 November 2004 / Published online: 20 April 2005 Ó Springer-Verlag 2005 Abstract When approaching a bend in the road, a driver looks across to the inside kerb before turning the steering wheel. Eye movements and steering are tightly linked, with the eyes leading, which means that the oculomotor controller can assist the neural centres controlling steering. This optimum coordination is observed for all drivers; but despite being the preferred solution to the motor-control problem of successfully steering along a winding road, the question remains as to how crucial such coordinated eye and steering movements are for driving performance. Twenty subjects repeatedly drove a simulated stage of the World Rally Championship, aiming to complete the course in the fastest possible time. For the first six repetitions they used the usual coordination of eye movements and steering; for drives 7 12 they were instructed to fixate on a small spot in the centre of the screen (centre gaze). Prevention of coordination in this way impaired their performance (drives 6 and 7 compared), dramatically increasing their time taken to complete the course, equivalent to slipping 19 places down the leader board in the actual rally stage. This indicates that the usual pattern of eye movements correlated with steering is crucial for driving performance. Further experiments are suggested to reveal whether any attentional demand associated with keeping the eyes still contributes to the loss in performance. Keywords Eye movements Æ Steering Æ Driving Æ Performance Æ Impaired D. E. Marple-Horvat (&) Æ M. Chattington M. Anglesea Æ D. G. Ashford Æ M. Wilson Æ D. Keil Institute for Biophysical and Clinical Research into Human Movement (IRM), Manchester Metropolitan University, Hassall Road, Alsager, Cheshire, ST7 2HL, UK d.e.marple-horvat@mmu.ac.uk Tel.: Fax: Introduction Driving is a classic example of visually guided behaviour in which the eyes move in relation to, and just before, another action (see Herman et al. 1981; Hollands and Marple-Horvat 2001; Land and Hayhoe 2001 for other examples). In diverse situations the degree of coordination between eye movements and other actions, and their relative timing, largely determines performance (Miall and Reckess 2002). Individuals who are unable to move their eyes appropriately in relation to their actions, making eye movements of the wrong size or at the wrong time, perform badly (Van Donkelaar and Lee 1994; Crowdy et al. 2000; Marple-Horvat and Crowdy 2004). Persuasively, such individuals improve their performance if they first improve their eye movements (Crowdy et al. 2002). Driving on the open road involves the continuous action of steering, and it is therefore possible to define the relationship between a driver s eye movements and the movement of the steering wheel in terms of the degree of coordination or linkage between the two, and their relative timing. When approaching a bend in the road, a driver looks across to the inside of the curve before turning the steering wheel (Land and Lee 1994). Eye movements and steering are tightly linked, with the eyes leading by half a second or more. Because all drivers do this without specific instruction, it seems reasonable to conclude that this behaviour represents optimum coordination, and the preferred solution by the CNS of the motor-control problem of successfully steering along a winding road. Such tangent point steering has identifiable benefits in terms of acquiring visual information to guide steering (Land and Lee 1994; Land and Horwood 1995; Land 1998). Equally, with eye movements leading (as in so many other situations) it probably reflects a general principle of brain function and motor control. Because the eyes lead, the oculomotor controller can assist the neural centres controlling steering. Such a suggestion fits

2 412 well with current frameworks for understanding coordinated movement (involving different parts of the body) and the role of the cerebellum, where such coordination is probably established (Miall et al. 2000; Miall and Reckess 2002). Despite being the preferred solution to the motor control problem of steering along a winding road, the question remains as to how crucial such coordinated eye and steering movements are for driving performance. Deliberate disturbance of a universally adopted driving strategy in a real vehicle on the road, though informative in this respect, clearly involves risks. We, and others (e.g. Wilkie and Wann 2003), have therefore used a simulated driving paradigm to assess the effect on performance. We asked subjects to repeatedly drive a simulated stage of the World Rally Championship, aiming to complete the course in the fastest possible time. Initially they adopted (without instruction or suggestion) the usual coordination of eye movements and steering. Subsequently, they were instructed to drive whilst looking straight ahead at a spot placed in the centre of the screen. Prevention of any eye movements, and so of coordination, in this way dramatically increased the time taken to complete the course. This indicates that the usual pattern of eye movements correlated with steering is crucial for driving performance; disruption of coordination impairs driving ability. Methods Subjects Twenty subjects took part, 10 males and 10 females (age 20.9±1.7 years, mean±sd). All were qualified drivers with a clean UK driving licence and had no corrected vision. Local ethical committee approval and written informed consent were obtained before testing. Driving task The driving task was taken from the Colin McRae Rally 2 simulation, a driving environment simplified by the absence of other vehicles and pedestrians. Subjects were seated in a driving simulator incorporating a 42 inch (diagonal) plasma screen, force feedback steering wheel, accelerator and brake pedals and a rally car seat. Each subject was asked to repeatedly drive the same set course (France, Stage 1), aiming to complete the course in the fastest possible time. The route involved a large number of turns (47) and each subject drove under two different conditions. Under the first condition (control trials 1 6) they negotiated the course six times successively and were given no advice on their driving; they were allowed to adopt their own driving style and racing strategy. In the second condition (test trials 7 12) their eye movements were restricted. A small (4 4 mm) white spot was placed in the centre of the screen and subjects were instructed to keep their gaze fixed on the spot while driving. Under the test condition, therefore, subjects were denied eye movements and looked straight ahead (centre gaze). They negotiated six successive test drives. Again, no other advice was given regarding driving style or racing strategy. Data acquisition During driving, the subject s eye movements were monitored at 60 Hz using an ASL 5000 pan and tilt eye tracker (Applied Science Laboratories, Bedford, Massachusetts, USA) mounted at dashboard height. Analogue signals representing horizontal and vertical components of any eye movements (calibrated to 1 accuracy using nine equally spaced calibration points covering the full area of the plasma screen) were digitised on-line at 200 Hz using a CED 1401 A/D converter (Cambridge Electronic Design, Cambridge, UK) for subsequent computer-based analysis using Spike 2 software. The two signals were also fed to the ASL eye tracker control unit which generated on a small monitor visible only to the experimenters crosshairs representing the horizontal and vertical coordinates of gaze superimposed on the subject s view of the road through the windscreen; this scene plus gaze output was recorded on videotape. Care was taken to make sure that none of the monitor screens showing the tracked eye, analogue data, or scene view with crosshairs were visible to the subject. A potentiometer placed inside the steering column to measure steering wheel rotation yielded an analogue signal that was digitised at 200 Hz alongside the eye movement signals for subsequent analysis. Analysis Signals representing the horizontal component of eye movements and steering wheel rotation were analysed within the CED Spike 2 environment. Cross-correlation of the two signals over the time taken to complete a drive (typically 4 5 min) yielded a cross-correlogram, the peak of which identified the correlation coefficient (r) which is a measure of the covariation of the two signals. Calculation of (r 2 100) gave the percentage variance in steering wheel movement attributable to covariation with horizontal eye movement. These statistics were used first to define the usual degree of coordination between eye movements and steering during control trials, and second to ensure that in test trials subjects followed the instruction to keep their gaze fixed straight ahead as best as they were able. True centre gaze maintained accurately without interruption throughout a complete drive, which necessitated many turns of the steering wheel to negotiate the course, would result in a correlation coefficient of zero, i.e. no coordination (or covariation). Because all subjects experienced difficulty

3 413 maintaining centre gaze in test runs, we also computed frequency distributions of horizontal gaze component for each drive, and calculated mean and SD values as an additional measure of how successfully subjects followed the instruction to look straight ahead. The rally car seat and headrest were a snug fit, and subjects (who were observed directly from diagonally behind at all times while driving) made very little in the way of head and torso movements. With the head still, eye movements equate to gaze movements. Together with the controlled lighting within the simulator, this provided ideal conditions for eye tracking, and the pantilt eye tracker coped very well with any small head movements that did occur. On rare occasions when the eye was briefly lost (mainly due to force feedback steering wheel vibration if the car strayed off the road) drop-out occurred in the horizontal eye movement trace. This was removed by manual interpolation before cross correlation. Typically, a 240-s record of a complete drive required interpolation of only a few seconds in total (5.8±3.4 s, mean±sd). The horizontal and vertical eye movement signals provided by the ASL 5000 were therefore very reliable, and the gaze cross-hairs superimposed on the scene of the road ahead very accurate and stable. This was particularly evident at the start of each control drive, when the subject s gaze travelled sequentially down through the traffic lights waiting for the go signal. Because subjects were trying to complete the course as quickly as possible, racing against the clock, completion time was taken as the primary measure of performance. The number of crashes that halted the car was also recorded as a general indicator of performance (catastrophic or complete loss of control) and racing strategy; for further details, see Results, below. Further analysis of variance was conducted using Statistica (Statsoft, USA). A 2 group (male, female) 4 trial (1, 6, 7, 12) mixed design ANOVA with repeated measures on the last factor was performed. Of particular interest was any increase in completion time between trials and any differential effects of gender s (control 1) to s (control 6), a reduction of 14%. Under test conditions the same trend was seen, but there was less improvement overall, 22.1 s (8%). Mean completion time for the last drive under restricted eye movements (test 12) was longer at s than for the last drive under control conditions (control 6), s. Variation in completion times around the mean value for a particular trial was a measure of consistency of performance across all 20 subjects. The largest standard error of the mean was obtained for the first trial in which subjects were forbidden to move their eyes (test 7); the smallest was obtained for the last trial under control conditions (control 6), when subjects exhibited their usual, preferred coordination and had enjoyed the most practice. Figure 1 (bottom) presents male and female data separately. A repeated measures mixed factorial ANO- VA (2 4) analysis of completion times confirmed there was a main effect of group (F (1,18) =26.962, P<0.001) with men having a lower mean finishing time over the four trials analysed (trials 1, 6, 7 and 12). Mean finishing Results Eighteen of the 20 participants (90%) took longer to complete the course when eye movements were first restricted; on average, completion time increased by 30.3 s from s to 280 s, which is a 12% increase (test 7 v control 6; Fig. 1, top). One male subject s time was hardly affected, and one went 10 s faster in the first test drive than the last control. The biggest increase in completion time was 76.9 s (for a female subject). Within the block of trials under a particular condition, practice by repetition improved performance; there was a clear trend for time taken to reduce progressively from the first to the last trial. Under control conditions, mean time taken reduced by 38.2 s from Fig. 1 The effect of eye movements and practice on completion time. Top: mean completion times are shown ±s.e.m. bars for repeated driving of the same course with eye movements permitted (control, drives 1 6) then forbidden (test, drives 7 12). N=20 subjects. Bottom: male and female completion times (N=10 in each case) shown separately

4 414 time was s for men and s for women, a difference of 33.2 s (P<0.05). There was also a main effect of trial (F (3,54) =24.336, P<0.001). Tukey s HSD post-hoc analysis of the trial effect indicated a significant difference (P<0.001) between drive trials 1 and 6, indicating there was a learning effect. A significant difference (P<0.001) was also visible between drives 6 and 7, brought about by the change in the task requirement. There was also a significant difference (P<0.001) between drives 7 and 12 showing that after the drivers were instructed to look straight ahead they did subsequently improve their performance. Finally, there was also a significant interaction effect between trial and group (F (3,53) =2.805, P<0.05). Subsequent Tukey s HSD post-hoc analysis indicated that this interaction effect occurred at trial 7 (P<0.01), where the female drivers were significantly more negatively affected by the change in task requirements. Analysis of subjects eye movements and steering revealed that these were highly coordinated in the first six drives (controls 1 6). This was immediately evident in the live video feed showing the view of the road with gaze crosshairs superimposed. When approaching a bend in the road, all subjects looked across to the inside kerb (or grass verge) before turning the steering wheel, and gaze remained fixed on this tangent point until they were emerging from the bend. Figure 2, top left and right, are typical video still frames showing gaze fixed on the left and right road margins whilst approaching left and right hand bends, respectively. Figure 3 (top) illustrates, under control conditions, eye movements and steering for a 30 s epoch of driving, which included negotiating several bends in the road. The horizontal component of gaze and steering wheel rotation show a high degree of covariation; eye movements and steering are tightly coordinated, with the eyes leading (see, for example, at turning points highlighted by cursors). Vertical eye movements (not shown) were minimal in size and frequency, and were not correlated with steering. By contrast, Fig. 2, bottom left and right, are video frames obtained at the same two bends in the road, for the same driver, but in a test drive when the subject was following instructions and maintaining centre gaze (no eye movements). Gaze is clearly displaced away from the inner road margin. Figure 3 (bottom) confirms that for a 30 s epoch of driving under test conditions, and for a similar stretch of road, this subject kept gaze centred with a high degree of success, and only few and small departures left and right (compare with usual eye movements (top) on the same scale). Figure 4 shows the frequency distributions of horizontal gaze for the same individual under control and test conditions (control 6 and test 7, respectively). Gaze ranged over about ±15 degrees (99% of distribution within this range) around a near-zero mean under control conditions (Fig. 4, left). When instructed to fixate centrally, gaze was within ±2 degrees of centre 96% of the time (Fig. 4, right). Fig. 2 Video frames showing gaze superimposed on the view of the road. Top: gaze crosshairs (in red for visibility) fixed on the left and right (inside) road margins on approach to left and right-hand bends, when driving with eye movements permitted. Bottom: gaze crosshairs fixed on the centre of the scene on approach to the same bends, but with eye movements forbidden (centre gaze)

5 415 Fig. 3 Eye movements and steering during control and test drives. Top: horizontal component of eye movements (above) and steering wheel rotation (below) exhibiting the typical pattern of coordination when eye movements were permitted. Bottom: eye movements (above) and steering (below) in a test drive, when eye movements were forbidden Figure 5 shows that in the absence of any instruction about where to look, for all subjects there was a high degree of correlation between their eye movements and steering (control drives 1 6). With practice, there was a slight increase in correlation to a value of 0.75, identical for male and female drivers. This means that 56% (r 2 100) of the variation in steering wheel position (left right rotations) is attributable to covariation with horizontal (left right) eye movements. Only 44% of the variation in steering wheel position is independent of eye movements. In the absence of any instruction, and with the benefit of practice in the previous five drives, the coordination between eye movements and steering in drive 6 was the subject s preferred and optimum coordination. Eye movements led steering, but there was no relationship between the precise time lead adopted by an individual (defined by the peak of the cross correlogram) and their completion time; subjects who were faster overall did not look to the inside kerb earlier (r 2 =0.050, gradient of regression line not significantly different from zero). In the first test drive (drive 7), subjects obeyed the instruction to fixate gaze on the centre spot on the screen, which dramatically reduced the correlation between any remaining eye movements and steering. The correlation coefficient of 0.34 represents 12% covariation, or 88% independent variation. In subsequent drives, all subjects showed some occasional (or episodic) tendency to revert to their usual pattern of coordination, but correlation remained low, with r circa 0.4, representing 16% covariation. Beyond the manipulation of eye movements, either allowed or not, subjects were free to pursue their own driving strategy. The number of crashes in each drive was noted because visual inspection suggested, first, that the number of crashes in a drive might well affect completion time, and, second, that there might be a different approach to crashing, which represents brief complete loss of control, between genders. Crashes were always a failure to steer around a bend in the road (there were no other cars or obstacles); i.e. drivers went off the road to the right hand side on left hand bends and went off to the left hand side on right hand bends.

6 416 Fig. 4 Frequency distributions of horizontal gaze component. Left: under control conditions, gaze distributed circa 20 left and right of centre. Right: under test conditions, gaze centred with few, small deviations Fig. 5 Correlation between eye movements and steering for drives under control and test conditions. Cross correlation of the horizontal gaze and steering signals across a complete drive yielded a correlation coefficient, r. Values of r were higher in drives 1 6, when eye movements were permitted (no instructions given), and lower in drives 7 12 when eye movements were forbidden (subjects instructed to fix their gaze on the centre of the screen) Under control conditions there was a relationship between number of crashes and completion time; regression analysis yielded r 2 =0.189 (P<0.05), or 19% of the variation in completion time could be explained by the number of crashes (Fig. 6, top). Under test conditions, there was no relationship, r 2 =0.007 (P>0.05). Male and female drivers did not crash with significantly different frequency under control conditions (Fig. 6, bottom). On average (across all six control drives) drivers crashed three times in each drive (males 3.40, females 3.17). Males did not significantly change their frequency of crashing under test conditions, but females did, reducing to twice on average (2.25) per drive. When eye movements were denied, females crashed less frequently than males (unpaired t-test, P<0.05), and less frequently than they had under control conditions (paired t-test, P<0.05). Having identified that drivers took longer to complete the course when constrained to look straight ahead, analysis of their steering was undertaken to identify any differences between steering under normal (drive 6) and constrained (drive 7) conditions which might underlie the drop in performance. A frequency distribution was generated for each driver showing how much of the time in drive 6 the wheel was turned by different amounts. The twenty individual distributions were then averaged to produce a single average distribution which reflects the way drivers steered in their most practised, last attempt under normal conditions, with eye movements (Fig. 7, top). A corresponding plot was generated for their first drive without eye movements (Fig. 7, centre). The difference between the two (test control) shows any difference in steering that accompanied the difference in eye movements (Fig. 7, bottom). The difference distribution shows that when drivers were constrained to look straight ahead they spent more time steering straight ahead or nearly so. The central peak in the distribution is higher under test conditions than control, producing a central peak in the difference distribution. Similarly, the difference plot shows that the steering wheel spent more time turned by small amounts away from centre when the driver looked straight ahead, 7.8% more of the total drive time, about 20 s, within the range 45 degrees to +25 degrees (area under the difference plot within these boundaries). Correspondingly, the wheel was turned further away from centre less of the time, shown by the deficits in the difference plot flanking the central surplus. Statistical comparison of corresponding pairs of bins in the control and test drive

7 417 Fig. 6 Number of crashes, and effect on drive completion times. Top: regression analysis of completion time against number of crashes under control (blue) and test (red) conditions (N=20 subjects). Bottom: number of crashes under control and test conditions shown separately for male and female drivers distributions identified all significantly different bins in the difference plot, and these are colour coded red (paired t-test, P<0.05). Discussion Prevention of eye movements impairs driving performance Since Land and Lee (1994) first demonstrated that eye movements and steering are highly coordinated when driving, the question has remained as to how crucial this preferred coordination is for performance, and how much driving would be impaired if the usual coordination was disrupted. There are obvious safety issues raised by any such intervention while a person is actually driving, but this study provides clear evidence, in a driving simulation, that the effect is dramatic. Subjects racing against the clock in a well-practised simulated stage of the World Rally Championship (France, stage 1) took, on average, 30 s longer to complete the stage, an Fig. 7 Differences in steering when eye movements were or were not made. Frequency distribution shows the percentage of drive time for which the wheel was turned by different amounts away from centre (driving straight ahead). Top: steering when horizontal eye movements coordinated with steering were made. Centre: steering when driver looked straight ahead. Bottom: difference between steering under the two conditions. Bins that are significantly different are in red. Note: there was an offset error of between 5 and 10 in steering wheel calibration so that the peak in the distributions appears in bin 10 to 5 increase of 12%, when eye movements were denied, abolishing the usual pattern of coordination. This impairment of driving performance is dramatic; comparison with actual race times from the stage (in the World Rally Championship of 2003) reveals that such an increase in time taken to complete the course is

8 418 equivalent to slipping 19 places down the leader board in the actual rally stage. This therefore shows that the usual pattern of eye movements correlated with steering is not just a preference, but is crucial for driving performance. There are good reasons why this should be so. Land and co-workers (Land and Lee 1994; Land and Horwood 1995; Land 1998) have provided a framework for understanding why tangent point steering might be the best way for the visuomotor control system to acquire the visual information it requires when driving along a winding open road. But two other possible explanations (i.e. other than the absence of coordinated eye movements) merit discussion at this point. Subjects did report that effort was required to keep gaze fixed on the centre spot. This could represent a motor control effort incurred by the necessity to override the usual oculomotor control signal driving the eyes left and right to tangent points during normal driving; or, it could represent attentional effort in keeping looking straight ahead. Whilst prevention of coordinated eye movements was the direct intervention in test drives, it might have the consequence of placing an additional attentional demand on the driver, which itself might in part explain the impaired driving performance. The presence or absence of eye movements under the two driving conditions is the demonstrable primary difference, but it is important to note in terms of underlying mechanisms that any difference in attentional load as a secondary consequence of what the eyes are doing might contribute to the observed impairment and should be assessed in future experiments by deliberately manipulating attentional load, but without manipulating eye movements. Unfortunately, previous studies which manipulated attention (Lamble et al. 1999; Summala 1999) by requiring subjects to look at and process in-car displays of course also manipulated drivers eye movements which were not measured and are therefore inconclusive. Experiments manipulating attention by using auditory distractants, and in which eye movements are measured, are therefore planned for the future. The task we have used was deliberately stripped of attentional demands (other vehicles, pedestrians, junctions, road signs, lane discipline) other than those related to steering successfully at speed. As a consequence, we do not think that subjects were at or close to their attentional limits which itself makes it unlikely that attention is a main explanation of the impaired performance in the current study when the eyes did not coordinate with steering. Our conclusion remains, therefore, that it is the appropriateness of what the eyes are doing that determines performance (i.e. are they coordinated with steering or not in this case). A second possibility that might explain the drop in performance is that when fixating artificially, gaze is displaced by up to 20 degrees from the point on the road that would normally be fixated. Summala (1999) has shown that an aspect of driving performance deteriorates at eccentricities of 23 to 38 degrees, so displacement of the eye from the tangent point could itself be the reason for the reduced performance. Figure 4 does indeed show that when fixating centrally, gaze could be displaced by almost 20 from the point on the road that would normally be fixated. However, such large departures could only arise very rarely and briefly. In the example shown, departures greater than 15 would only arise for less than 1% of the total drive time (because 99% of the distribution in Fig. 4 (left) lies within ±15 degrees of centre) or about 2.8 s (from Fig. 1, drive 7). We are not convinced that a circumstance arising only for 2.8 s in total can explain an increase in drive time of seconds (Fig. 1). Our experiment is, therefore, very different from Summala s, which involved 23 or 38-degree vertical eccentricities (forced looking downwards) for much of the time to look at an in-car display, so also requiring repeated vergence, accommodation and pupil size changes, and deliberate cognitive loading to respond to a numeric display. Our experiment is in a real sense the opposite of Summala s, because in our study drivers were forced to look straight ahead down the road, whereas in Summala s they were forced to look away. Those studies do not therefore account for the impairment seen in our experiments as arising from gaze displacement rather than lack of coordinated eye movement. We therefore consider that neither of the alternatives presented above can provide the main explanation for the observed impairment, so remain convinced that it is the absence of eye movements coordinated with steering that is the crucial factor. Wilkie and Wann (2003) made a parallel finding when they compared simulated driving with eye movements denied or permitted. Even during short (10-s) drives at constant low to moderate speed (29 km h 1 ), steering performance as measured by deviation of trajectory from the centre of the road was best when subjects were allowed to move their eyes to sample naturally the road ahead, and worst when they were made to look straight ahead (no eye movements). A lack of eye movements implies absence both of the usual outgoing oculomotor control signal (and any efference copy of the same), and of sensory feedback on eye eccentricity from muscle spindles, either of which might provide information useful for the control of steering. Perhaps the most compelling evidence that the oculomotor controller invariably influences the CNS controller for steering comes from the twin observations that in normal circumstances as the eyes look left and right (at the tangent point ahead) steering follows left and right; and when the eyes are restricted to looking straight ahead, steering tends more to straight ahead (Fig. 7), in drives exhibiting loss of performance (completion time). Such a link between good or bad eye movements and good or bad other body movements in relation to visual targets has previously been demonstrated in walking subjects (see below). In a general sense, it seems that where the eyes lead, other movements tend to follow.

9 419 In different driving environments, other competing requirements (than simply steering) might impinge upon eye movements and gaze distribution. Thus, at very high speed (formula 1 racing), head movements are related to steering (Land and Tatler 2001). This might reflect the necessity to keep the resultant force vector, due to gravity acting vertically on the head mass and centrifugal force acting horizontally, aligned through the axis of the neck vertebrae, perhaps to avoid neck muscle fatigue or horizontal shear forces on the brain in the cranium. At very low speed, in a cluttered urban environment, driving and steering become intermittent, with the necessity to sample many other features than the road ahead, such as other vehicles, traffic signals and pedestrians. On a winding open road, however, steering and driving involve a simple, well established, continuous pattern of eye steering coordination. The analysis provided by Land of the observed coordination of eye movements and steering in terms of acquiring visual information most appropriate or useful for steering emphasises sensory or perceptual aspects: what visual information is required. We stress here that there are additional reasons underlying the observed coordination that relate more to the way in which the brain solves problems involving coordinated movements under visual guidance in general. Thus, a strategy in which the eyes move with a time or phase lead over other body movements provides for the oculomotor controller to assist the neural centres controlling, for example, voluntary limb movements (van Donkelaar and Lee 1994; Crowdy et al. 2000; Miall and Reckess 2002). Such an influence is demonstrable in patients who have been able to improve their limb movements by improving their eye movements (Crowdy et al. 2002), is probably established within the cerebellum, which is known to be crucial for motor coordination (Miall et al. 2000), and is evident in tight, relatively invariant, timing relationships (Hollands and Marple-Horvat 2001). Current and future work aims to establish whether disruption of eye movements and steering by pharmacological agents (such as alcohol) or fatigue in a driving simulation and driving on the road leads to impairment of performance (Cooper 2004), and, conversely, whether improving eye movements can improve driving performance. Gender differences in a simulated driving task Male drivers were faster at each stage than their female counterparts. The immediate effect on completion time when eye movements were denied was qualitatively similar; both groups suffered an increase in time taken, performance was impaired. But the effect on females was significantly larger, an increase of 41.7 s (16%) which was more than double the effect on males, who suffered an increase of 18.8 s (7%) on average. However, although females initially suffered a greater loss in performance (in test 7), they subsequently improved by four times more than males. By the last drive (test 12) their times had reduced by 36 s on average; males, by comparison, improved much less, by a modest 8.1 s. These differences seem, at least in part, to arise from a different approach or attitude to the simulated racing task. Males seemed to adopt a more aggressive, attacking style of driving, which they were less prepared to modify or abandon when they found themselves in the unusual and difficult conditions of being forbidden to move their eyes. Thus, under test conditions, males crashed as frequently as under control conditions (and as females under control conditions); but females moderated their driving, reducing the number of crashes by 29% at the expense of a greater slowing overall (greater increase in completion time). These differences in performance and attitude may well reflect a male/female difference in gaming strategy. We think this a more likely explanation than difference in driving experience, because male and female subjects covered a similar narrow age range, and most had held a full driving licence for a similar length of time, 2 3 years. It is by no means clear that the same difference would exist, or to the same extent, in a real driving situation, although a greater willingness to modify driving style and drive more slowly in difficult situations might underlie gender differences in crash statistics and insurance costs that favour female drivers. Another factor might explain the smaller immediate effect on male completion times when eye movements were forbidden. If males were less successful in following the instruction to look straight ahead and not move their eyes, making small eye movements, but in the right direction and appropriately timed to assist steering, more often than females, then this might explain why their performance was less impaired. Comparison of frequency distributions and ranking of SD values of horizontal gaze in the first test drive did reveal that the worst (biggest) three SD values were from males. Apart from this, however, male and female SD values covered an overlapping range; among the best ten values, six were from males. Furthermore, regression analysis of completion time on gaze SD value for male drivers in the first test run revealed that only 12% of the variation in completion time could be explained by variation in gaze SD (completion time reducing with increasing eye movements). We conclude, therefore, that only a small part of the observed gender difference could arise from different male/female success rates in not moving the eyes. Acknowledgements Mark Chattington was supported by an IRM PhD studentship, and Damian Keil by an IRM research fellowship. Steve Gilbey and Darryl Knights provided expert technical assistance, including building the driving simulator and providing data acquisition and analysis programs.

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