Visual attention affects temporal estimation in anticipatory motor actions
Welber Marinovic & Guy Wallis
Experimental Brain Research ISSN 0014-4819 Exp Brain Res DOI 10.1007/ s00221-011-2772-2
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Author's personal copy Exp Brain Res DOI 10.1007/s00221-011-2772-2
Visual attention affects temporal estimation in anticipatory motor actions Welber Marinovic • Guy Wallis
Received: 14 March 2011 / Accepted: 14 June 2011 Ó Springer-Verlag 2011
Abstract The production of accurate motor actions requires successful extraction of relevant information about the target of that action. By the same token, it also requires the successful exclusion of potentially distracting, irrelevant information. This study sought to determine the impact of transient visual distractions on performance in an anticipatory timing task, in particular the temporal and spatial relationship between distractor and target at which maximal distraction occurs. The results support the notion of a critical temporal and spatial window of distraction which provides insight into the visuomotor processes underlying distraction. Keywords Action Distractor Interception Motor preparation Time estimation Visual attention
Introduction Interactions with moving objects are commonplace in our daily activities (e.g. driving a car, hitting a tennis ball). These interactions usually occur in the presence of a multitude of sensorial stimuli. Some sources of sensorial stimuli are important to accurately guide our actions towards moving objects, such as visual information about
W. Marinovic G. Wallis Perception & Motor Systems Laboratory, School of Human Movement Studies, The University of Queensland, Brisbane, QLD, Australia W. Marinovic (&) Perception Lab, School of Psychology, The University of Queensland, Blair Drive, St Lucia, Brisbane, QLD 4072, Australia e-mail: [email protected]
the motion of a ball while playing tennis or when navigating around an obstacle (Tresilian et al. 2004; Cloete and Wallis 2009). Other sources of sensorial information, on the other hand, may be irrelevant to our goals and perhaps can be completely ignored. The accurate interception of a moving target depends on the preparation of elements of performance—such as amplitude and direction (Marinovic et al. 2008, 2009b)—as well as the precise estimation of the time at which descending motor commands must be issued (Tresilian and Houseman 2005; Tresilian and Plooy 2006; Marinovic et al. 2009a, c; Tresilian et al. 2009; Marinovic et al. 2010; Zago et al. 2010; Marinovic et al. 2011). Previous research suggests that the presence of multiple moving objects in the scene can affect time-to-arrival estimation of a moving target (Todd 1981; Lyon and Waag 1995; DeLucia and Novak 1997; Oberfeld and Hecht 2008; Baures et al. 2010). This observation seems to hold even if the participants know in advance which moving objects are irrelevant to the task (Lyon and Waag 1995; Oberfeld and Hecht 2008; Baures et al. 2011). That multiple moving objects can be distracting when one does not know the difference between target and distractors is not surprising given our limited capacity for dual tasking (Borst et al. 2010). But that moving visual distractors can affect temporal estimation processes even when these are irrelevant to the task is an interesting observation with important practical applications (e.g. drivers’ safety). This inability to selectively ignore irrelevant moving visual stimuli has been demonstrated thus far with tasks where the final displacement of the moving target was occluded (Lyon and Waag 1995; Oberfeld and Hecht 2008). Thus, the participants were required to make a prediction about the motion of the object during its final approach at the arrival location. According to some researchers (Tresilian 1995; DeLucia
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and Liddell 1998), this type of temporal estimation or motion extrapolation process is believed to involve more cognitive processing than other tasks in which time-toarrival can be monitored more directly using the dorsal visual stream (Goodale and Milner 1992; Milner and Goodale 2008). In line with this suggestion, Kerzel (2003) showed that visual attention—disrupted by visual distractors—is important for maintaining a mental extrapolation of the implied motion of a previously seen moving target. One might wonder in this case whether the increased use of cognitive resources to perform target motion extrapolation could have made the participants more susceptible to temporal errors when known moving distractors were present in the background. Yet another question that remains to be tackled concerns the type of visual distractor used in the experiments testing time-toarrival estimations. Most studies to date employed moving visual distractors. This approach seems sensible if one does not know which moving object is the target until late in the trial (DeLucia and Novak 1997) or if the hypothesis tested assumes that time-to-arrival estimation for the distractor can systematically bias time-to-arrival estimation for the target (Oberfeld and Hecht 2008). However, this type of visual interference does not allow us to evaluate whether the appearance of a transient stationary visual distractor in the scene can also affect time-to-arrival estimation and the motor response which depends on this process. Prior studies in which distracting visual stimuli were present during reaching actions suggest that the mere presence of a distractor can affect hand/arm trajectories towards static targets (Welsh et al. 1999; Welsh and Elliott 2004, 2005). In the studies reported here, we investigated the effects of transient stationary visual distractors on the temporal accuracy of interceptive actions when vision of the moving target was uninterrupted. Most models for the control of interceptive actions assume that descending motor commands start to be issued when a visually perceived variable containing information about time-to-arrival reaches a criterion value (Tyldesley and Whiting 1975; Lee 1976; Peper et al. 1994; Dessing et al. 2005; Tresilian 2005; Zago et al. 2009). Previous studies with anticipatory timing actions indicate that this criterion value occurs between 150 and 200 ms before response onset (Benguigui et al. 2003; Marinovic et al. 2009a, c, 2010; Vishton et al. 2010). Moreover, it has been recently shown that accurate estimates of the precise time of response onset can be made with only short observations of the moving target before it reaches the criterion value (Tresilian and Houseman 2005; Marinovic et al. 2009c). These results seem to suggest that there is a narrow critical time interval—about 200 ms before response onset—within which important processes take place to guarantee an
accurate time-to-arrival estimation. If transient visual distractors can affect time-to-arrival estimations during anticipatory timing actions, the 200 ms preceding response onset would be the interval within which we would expect the largest effect to occur. There is a growing body of evidence that attention can distort the perceived passage of time (Brown 1985; Brown and Stubbs 1992; Treisman et al. 1992; Macar et al. 1994; Brown 1995; Casini and Macar 1997; Casini and Macar 1999; Chaston and Kingstone 2004; Tse et al. 2004; Champagne and Fortin 2008; Buhusi and Meck 2009). Most models propose that time estimations rely on an internal clock or pacemaker containing a temporal oscillator and a counter that accumulates neural pulses occurring during the period to be estimated (Creelman 1962; Gibbon 1977; Treisman et al. 1990). The accuracy of the pacemaker-counter estimation depends on enough attentional neural resources being available during the duration of the interval to be judged. If attentional resources allocated to time an interval are divided with other processes, less resources will be available for processing temporal information (Kahneman 1973; Zakay and Block 1997). This typically leads to an underestimation of the duration of the interval to be judged—as the counter misses pulses if attention is diverted to another task—or less accurate estimations (Brown 1985). Thus, we expected that when presented in the scene, transient visual distractors would cause participants to initiate their anticipatory motor actions late and/or with greater variability. Since the critical time interval to initiate interceptive actions seems to occur around 200 ms prior to response onset, we expected larger effects to occur around this interval. To test these hypotheses, we asked the participants to initiate a simple abduction of the index finger when a moving target arrived at a predetermined location on a monitor screen (see Fig. 1b). In some trials, we randomly presented brief stationary visual distractors at different moments within the last 500 ms prior the expected time of response onset. The results showed a clear effect of transient visual distractors on response initiation accuracy and demonstrate that the time course of this effect also depends on the spatial position of the distractor.
Experiment 1 Participants. Six volunteers (2 men and 4 women, age range 22–33; mean = 28 years) participated in this experiment and all gave their written informed consent prior to commencement of the study, which was approved by the local Ethics Committee of the University of Queensland. They received a small financial compensation for their participation (AU$20).
Author's personal copy Exp Brain Res Fig. 1 Experimental setup and visual stimuli (not to scale). a The participant was seated in front of a 1900 CRT monitor which served to display the visual stimuli. b Schematic examples of the visual stimuli during trials with (left) and without (right) visual distractors
Task and apparatus Participants were seated in front of a monitor screen in a chair with support for the arms and hands as illustrated in Fig. 1a. The participants’ hands remained in a pronated position throughout the experiment. The participants were required to make a quick abduction of their right index finger against a torque transducer at the exact time they judged a moving red target (80 9 40 pixels, 1.8 9 0.9 degrees of visual angle (dva)) would make contact with a stationary green target (40 9 80 pixels, 0.9 9 1.9 dva) positioned at the right side of the monitor screen as shown in Fig. 1b. The moving target travelled at a constant velocity of 13.54 dva/s (595 pixels/s) and it took 1,440 ms to move from the left to the right side of a 1900 Sony Trinitron G420 monitor screen (85 Hz refresh rate, 1,024 9 768 resolution) located 0.9 metres away from the participants as shown in Fig. 1a. In most trials, the only visual stimuli to appear on the monitor screen were the moving red target and the stationary green target. In some trials, a stationary visual distractor flashed on the screen for an interval of 140 ms and it comprised two horizontally aligned red rectangles (40 9 80 pixels each, 0.9 9 1.8 dva) as shown in Fig. 1b. In Experiment 1, the visual distractor was always positioned close to the stationary green target (70 pixels or 1.6 dva away along the x-axis and measured from the objects’ centres) regardless of the position of the moving target on the screen. In all trials, the moment of contact between the moving and stationary targets was indicated by the latter changing from green to red. The moving target was always visible throughout its entire trajectory until it reached the stationary target at the right side of the monitor screen as shown in Fig. 1b. At the exact frame at which the moving target contacted the stationary target, a TTL pulse was sent through the parallel port to mark that event. When a visual distractor was
presented, a TTL pulse was sent through the parallel port in synchrony with its onset. The torque transducer data were time locked to the collection of the parallel port signals and sampled at 2,000 Hz. Visual stimuli and parallel port signals were generated with Cogent 2,000 Graphics (http:// www.vislab.ucl.ac.uk/cogent_2000.php) running in MATLAB 7.5. Procedures and design Participants were allowed to perform 40 practice trials to familiarize themselves with the task and apparatus. During these practice trials, no visual distractors were presented and feedback about the temporal error was provided after each trial. Prior to the experimental block of trials, the visual distractors were shown to the participants seven times (one presentation per interval), so that they were aware of the type of visual stimuli that could be presented at any given trial. During these familiarization trials with visual distractors, no response was required. For the experimental block, the participants were told to ignore the visual distractors and execute their actions as accurately as possible. The participants were informed about their temporal error after each trial except when a visual distractor was presented. The reason to give feedback in trials with no distractors was to maintain the participants motivated throughout the experiment and achieve an optimal performance. It should be noted that feedback given for trials with no distractors was also believed to be beneficial for performance in trials with distractors as feedback can be used to improve the programming of subsequent actions via offline processes (see Khan et al. 2003a, b). Since we did not know what pattern of results we would obtain, feedback was not provided when distractors were present in order to make participants unaware of potential systematic biases in their responses. The participants performed a total
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of 288 trials in the experimental block; on 14.6% of these, a distractor (distractor trials) was presented. The 85.4% remaining trials in which no distractors were presented served as control trials. The reason for the imbalance between the proportion of control trials and distractor trials was to avoid habituation to presence of objects appearing unexpectedly. In other words, we sought to maximize the effect of the visual distractor by keeping likelihood of occurrence relatively low. The visual distractors flashed on the monitor screen pseudorandomly at seven different times (490, 420, 350, 280, 210, 140 and 70 ms) before the moving target contacted the stationary target and disappeared after 140 ms of presentation.
proposal that the critical time to trigger anticipatory timing actions occurs between 200 to 150 ms prior to response onset (Benguigui et al. 2003; Marinovic et al. 2009a, c). The results of Experiment 1 indicated that transient visual distractors appearing close to the moment
Data reduction and analysis All data reduction was performed using custom software written using the LabVIEW application (version 7.1, National Instruments). The force data were digitally filtered by dual pass filtering through a second-order Butterworth filter with a 20 Hz cut-off. From these filtered time series, the moment of force onset was estimated using the algorithm recommended by Teasdale et al. (1993; their algorithm B). Constant temporal error (CTE), defined as the difference between force onset and the time the moving target arrived at the designed location (negative = early), and variable temporal error (VTE), defined as the standard deviation of the temporal error over a series of trials, were the dependent measures of interest. The mean constant and variable temporal errors were submitted to univariate one-way repeated measures ANOVAs. Departures from sphericity were verified through the Mauchley’s test of sphericity and when necessary the Huynh–Feldt’s method was used to correct the degrees of freedom. The differences between control (no-distractor trials) and distractor trials were further assessed through post hoc t-tests using the Bonferroni correction, P \ 0.05. Results Figure 2a displays the mean constant and variable temporal errors across all experimental conditions in Experiment 1. The repeated measures ANOVA on the constant temporal error showed no significant effect of distractor timing, F(5.8, 29.3) = 0.84, P = 0.277, g2p = 0.21. In contrast, the repeated measures analysis of variance on the variable temporal error detected a significant effect of distractor timing, F(4.3, 21.7) = 4.35, P = 0.016, g2p = 0.42. A posteriori comparisons between distractor and control conditions showed that the magnitude of the variable temporal error was greater when the distractor was presented at 210 ms to contact than in control trials as shown in Fig. 2a. This result seems to be consistent with the
Fig. 2 Constant temporal error (CTE) and variable temporal error (VTE). a Experiment 1, where distractor flashed in a fixed position close to the arrival location. b Experiment 2, where the distractor flashed in front of the moving target. c Experiment 3, where the distractor flashed behind the moving target. Error bars represent the ± SEM. * Indicate where testing conditions differed significantly (P \ 0.05) from controls (CTL)
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anticipatory actions are to be executed can significantly interfere with response onset. At this stage, it remains unclear whether the effect was due to the precise spatial offset between the moving target and visual distractor or the precise timing of the appearance of the distractor. In an attempt to further investigate this issue, in the second experiment, the spatial offset between moving target and distractor was kept equal to that observed in Experiment 1 at the 210 ms interval. That is, 2.9 dva (126 pixels) between the centre of the moving target and the centre of the distractor on the x-axis.
Experiment 2 Participants. Fourteen volunteers (9 men and 5 women, age range 19–33; mean = 25 years) participated in this experiment and all gave their written informed consent prior to commencement of the study, which was approved by the local Ethics Committee of the University of Queensland. They received a small financial compensation for their participation (AU$20). Four of the 14 participants in Experiment 2 had previously taken part in Experiment 1. Procedure The task, procedures, data reduction and analysis were identical to experiment 1 with the following exception: the position of the visual distractor was variable and depended on the position of the moving target on the monitor screen. The spatial offset between the centre of the moving target and the centre of the distractor was 2.9 dva (126 pixels) in the x-axis, with the visual distractor always leading the moving target.
Results Figure 2b displays the mean constant and variable temporal errors across all experimental conditions in Experiment 2. The repeated measures ANOVA on the constant temporal error showed a significant effect of distractor timing, F(7, 91) = 6.42, P \ 0.001, g2p = 0.33. The post hoc test comparing control trials and distractor trials indicated that response onset was significantly delayed when the distractors were presented at 350 and 280 ms prior to the time of arrival of the moving target at the contact location as shown in Fig. 2b. The repeated measures ANOVA on the variable temporal error also detected a significant effect of distractor timing, F(7, 91) = 10.26, P \ 0.001, g2p = 0.44. A posteriori comparisons between distractor and control conditions showed that the magnitude of the variable temporal error was greater when the distractor was
presented at 280 and 210 ms to contact than in control trials as shown in Fig. 2b. Keeping the spatial offset between distractor and moving target constant, resulted in a detectable effect on CTE (not observed in Experiment 1) and an effect on VTE (similar to that obtained in Experiment 1). Taken together, the results suggest that distraction takes place but that the effect does not exclusively depend on the timing of the visual distractor, but also on its spatial location in relation to the moving and stationary targets. Since the time course and magnitude of the effect observed in Experiment 2 seemed to be affected by the spatial location of the distractor, the purpose of the final experiment was to determine the role of position of the visual distractor relative to the moving target.
Experiment 3 Participants. Ten volunteers (7 men and 3 women, age range 22–35; mean = 28 years) participated in this experiment and all gave their written informed consent prior to commencement of the study, which was approved by the local Ethics Committee of the University of Queensland. They received a small financial compensation for their participation (AU$20). Four participants of the ten who took part in Experiment 3 also took part in Experiment 1 and 2. Procedure The task, procedures, data reduction and analysis were identical to experiment 2 with the following exception: the position of the visual distractor was always behind the moving target in the direction of motion. The spatial offset between the centre of the moving target and the centre of the distractor was 126 pixels or 2.9 dva in the x-axis, with the visual distractor always lagging the moving target. Results Figure 2c displays the mean constant and variable temporal errors across all experimental conditions in Experiment 3. The repeated measures analysis of variance on the constant temporal error found a significant effect of distractor timing, F(5.0, 45.5) = 6.05, P \ 0.001, g2p = 0.40. The post hoc test comparing control trials and distractor trials indicated that response onset was significantly late when the distractors were presented at 280 and 210 ms prior to the time of arrival of the moving target at the contact location. The repeated measures analysis of variance on the variable temporal error also revealed a significant effect of distractor timing, F(7, 63) = 2.59, P = 0.020, g2p = 0.22.
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A posteriori comparisons between distractor and control conditions showed that the magnitude of the variable temporal error was greater when the distractor was presented at 140 to contact than in control trials as shown in Fig. 2c. A qualitative comparison between the results obtained in Experiments 2 and 3 seems to suggest that our manipulation of the distractor position affected the time course of the effect. To confirm this observation, we directly compared the results obtained in Experiments 2 and 3. To this end, we performed two-way repeated measures ANOVAs with distractor timing as a within-subjects factor and Experiment as a between-subjects factor. In order to conduct these ANOVAs, however, we removed from the data set of Experiment 2 the means of the four participants that also participated in Experiment 3 (to avoid violating the assumption of independence of samples). These additional analyses showed that there were significant interactions between distractor timing and its spatial location (or Experiment) for both the constant temporal error (F(7, 126) = 2.22, P = 0.036, g2p = 0.11) and variable temporal error (F(7, 126) = 4.72, P \ 0.001, g2p = 0.21), indicating it is not only the time of distractor that matters but also its location. Overall, the results of Experiment 3 not only confirmed there is a reliable effect of transient visual distractors on the temporal accuracy of anticipatory actions but also indicate that the time course of the effect was affected by our manipulation of distractor position.
General discussion The main goals of the experiments reported here were to determine whether transient stationary visual distractors could interfere with the timing of response initiation in anticipatory actions and, if so, determine the time course of the effect. In relation to the first goal, the results clearly indicated that transient visual distractors can significantly affect the timing of response initiation. The fact that we detected significantly later response onsets in Experiment 2 and 3 in relation to control trials seems consistent with the idea that the duration of the interval to be judged was underestimated when attentional resources were captured by distractors in the scene (Brown 1985; Macar et al. 1994; Chaston and Kingstone 2004). This indicates that during anticipatory timing actions, even though time-to-arrival is determined precisely and directly by the moving target, participants must devote attentional resources to the passage of time. One could argue that this is so because the visuomotor delay—perceptual transmission time plus the motor command transmission time—must be taken into consideration when specifying the correct time to trigger the motor action (time when the perceptual variable
reaches the criterion value). Since this event cannot be specified as clearly as the moment in which the moving target touches the stationary target, more attentional resources must be devoted to accurately estimate time-toarrival than one might think. In regard to the second goal of our study, our results suggest that the time course of the effect spreads approximately from 140 to 350 ms prior to response onset and depends on the spatial location of the visual distractor. Since the critical time to trigger interceptive actions seems to occur between 150 and 200 ms prior to response onset, we expected that the effect would be more evident around this time. The fact that responses were later when the distractors were presented at 280 and 350 ms to arrival in Experiment 2 seems to suggest that there is a longer interval within which important time estimations must occur. It could be argued that perhaps the abrupt offset of the visual distractor was what caused the effect since the time offset for an onset at 350 occurred at 210 ms to timeto-arrival. This alternative, however, seems less plausible as abrupt object onsets tend to attract more attention than their offsets (Cole et al. 2003; Boot et al. 2005). A comparison between the time course of the effect in Experiments 2 and 3 suggests that the interference of the visual distractor depends not only on the time of its appearance but also on its spatial position. When the visual distractor led the moving target (Experiment 2), the effect began to show earlier on during the trial (350 ms to arrival). On the other hand, when the distractor lagged the moving target (Experiment 3), the interference occurred later during the trials. This shows that there was an optimal combination between time and space for distractors to interfere with time estimations. In a previous report, we suggested that interceptive actions are prepared in advance and centrally triggered by visual information specifying time-to-arrival about 150 to 200 ms prior to response onset (Marinovic et al. 2009c). The fact that visual distractors increased response initiation variability when presented 140 ms prior to response onset in experiment 3 indicates that the critical time window to trigger interceptive actions is likely to be closer to 150 ms than to 200 ms. In regard to visual information specifying time-to-arrival, one could imagine that our participants were not using the motion of the moving object to initiate their actions but perhaps using another cognitive strategy (e.g. counting the seconds after motion onset). The literature on this topic, however, is very clear in that data from studies where response initiation occurs via temporal estimation (due to an occlusion) show a much greater temporal variability than is observed in interceptive actions where the moving targets are visible (Tresilian 1995, 1999). In addition, in a recent paper of ours (Marinovic et al. 2011), using the same experimental task (but without distractors),
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we directly compared a condition in which the target was visible throughout its whole trajectory with a condition in which it systematically disappeared 500 ms prior to its arrival at the interception zone, and we found that temporal variability was larger, as expected, when the target was occluded. Therefore, we believe it is unlikely that participants ignored the moving object’s motion to initiate their actions. One could think that our results are not surprising, but there were reasons to believe that such a clear effect would be difficult to detect. In fast ball sports (e.g. baseball, cricket and tennis), only brief observations of the ball during flight are available to the players (Watts and Bahill 1990; Land and McLeod 2000). This means players must make accurate temporal estimations in the hundreds of millisecond range (Tresilian 2005). Estimation of short intervals is proposed to be supported by specialized timing areas such as the cerebellum (Hazeltine et al. 1997; Koch et al. 2007, 2009). Lewis and Miall (2003) suggest that timing in the hundreds of milliseconds range is automatic and for that reason does not rely on neural systems associated with attention and working memory. This would suggest that even if the distractor captured attention in our task, there would be potentially enough attentional resources to carry on the accurate estimation of short intervals (milliseconds range). Moreover, some studies indicate that visual attention is not easily diverted by distracting stimuli if it is already engaged somewhere else in the scene (Fischer and Breitmeyer 1987; Lavie and De Fockert 2005; Cosman and Vecera 2009). In this case, one would not expect to find an effect of visual distractors in our task if the participants were paying attention to the moving target which specified time-to-arrival information or at the arrival location itself as it occurs in some tasks (Land and McLeod 2000; Land 2006, 2009). Lastly, as discussed in the introduction, attentional resources are believed to be important for timing interceptive actions mainly in the absence of direct visual information about the moving target such as in occlusions (Tresilian 1995; DeLucia and Liddell 1998). Since our moving target specifying time-to-arrival was visible throughout its entire trajectory, one could expect that more attentional resources would be available in our task than in previous reports where the effects of visual distractors were demonstrated (Lyon and Waag 1995; Oberfeld and Hecht 2008). If any of these assumptions were correct, we would not be able to detect a reliable effect of visual distractors on anticipatory timing actions. Our results, therefore, are novel in that they clearly demonstrated that we are susceptible to errors even when all other stimuli, but the distractor, are predictable and the scene is optimized for successful performance. Our results reveal that in interceptive timing tasks, the effect of a distractor is highly dependent upon its precise spatial and
temporal relationship to the target. That is not to say that these are necessarily the only factors affecting timing behaviour. Carrozzo et al. (2010) have recently reported that the mere presence of an inanimate object in the scene delayed interceptive timing responses and that animate objects induced the opposite effect, consistent with a role for more high-level, cognitive factors.
Conclusion In summary, we have demonstrated that transient visual distractors can interfere with the timing of anticipatory motor actions when positioned within certain proximity in space and time to the interception. The pattern of results obtained was consistent with that expected if the interval to be judged was underestimated when attentional resources were captured by distractors in the scene. This highlights the importance of attention in anticipatory timing actions. The protocol developed in the present experiment represents an original approach upon which new findings regarding attention in motor actions can be investigated further. Acknowledgments We thank Dr. Paul E. Dux for the discussion of the results, Dr. David Lloyd for assistance with Fig. 1 and Alanna Cresp for assistance with data collection. We also appreciate the constructive criticism provided by Dr. Digby Elliott and two anonymous reviewers on an earlier version of this manuscript.
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