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Independence of reaction time and response force control during isometric leg extension Tamami Fukushia; Tatsuyuki Ohtsukia a Laboratory of Human Movement, Department of Physical Education, Nara Women's University, Kitauoya-nishimachi, Nara City, Nara, Japan

To cite this Article Fukushi, Tamami and Ohtsuki, Tatsuyuki(2004) 'Independence of reaction time and response force

control during isometric leg extension', Journal of Sports Sciences, 22: 4, 373 — 382 To link to this Article: DOI: 10.1080/02640410310001641601 URL: http://dx.doi.org/10.1080/02640410310001641601

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Journal of Sports Sciences, 2004, 22, 373–382

Independence of reaction time and response force control during isometric leg extension TAMAMI FUKUSHI* and TATSUYUKI OHTSUKI{ Laboratory of Human Movement, Department of Physical Education, Nara Women’s University, Kitauoya-nishimachi, Nara City, Nara 630-8506, Japan

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Accepted 1 October 2003

In this study, we examined the relative control of reaction time and force in responses of the lower limb. Fourteen female participants (age 21.2+1.0 years, height 1.62+0.05 m, body mass 54.1+6.1 kg; mean+s) were instructed to exert their maximal isometric one-leg extension force as quickly as possible in response to an auditory stimulus presented after one of 13 foreperiod durations, ranging from 0.5 to 10.0 s. In the ‘irregular condition’ each foreperiod was presented in random order, while in the ‘regular condition’ each foreperiod was repeated consecutively. A significant interactive effect of foreperiod duration and regularity on reaction time was observed (P 5 0.001 in two-way ANOVA with repeated measures). In the irregular condition the shorter foreperiod induced a longer reaction time, while in the regular condition the shorter foreperiod induced a shorter reaction time. Peak amplitude of isometric force was affected only by the regularity of foreperiod and there was a significant variation of changes in peak force across participants; nine participants were shown to significantly increase peak force for the regular condition (P 5 0.001), three to decrease it (P 5 0.05) and two showed no difference. These results indicate the independence of reaction time and response force control in the lower limb motor system. Variation of changes in peak force across participants may be due to the different attention to the bipolar nature of the task requirements such as maximal force and maximal speed. Keywords: auditory signal, isometric force, reaction time, sprint start, timing.

Introduction It is important to understand the neural system controlling movement timing and movement parameters, including muscle force, during limb movements. Such movements are used in daily motor control behaviour and sport performance (Ivry, 1996; Sakai et al., 2000). For example, movement timing and movement parameters are important for the execution of sprint start performance, since a quick response to the starting gun and an efficient, powerful push-off force to accelerate the runner’s body are required simultaneously (Mero et al., 1983; Buckolz and Vigars, 1987; Mero, 1988; Young et al., 1995; Harland and Steele, 1997; Collet, 1999). Previous studies of sprint start training have focused on biomechanics (Mendoza and *Address all correspondence to Tamami Fukushi, Brain Sciences Center 11B, University of Minnesota, VAMC, One Veterans Drive, Minneapolis, MN 55417, USA. e-mail: [email protected] { Present address: Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguroku, Tokyo 153-8902, Japan.

Shollhorn, 1993; Delecluse, 1997; Blazevich and Jenkins, 2002) and neuromuscular physiology (Harridge et al., 1998; Ross and Leveritt, 2001; Ross et al., 2001), with little attention being paid to neuropsychological aspects of such training. It would be important and helpful to understand the basic neuropsychological nature of the timing and force control function in the human motor system for further development of skilled performance of the sprint start and similar types of motor behaviour. In recent studies of forelimb movements, researchers have reported that timing and force production are controlled independently (Mattes et al., 1997; Mattes and Urlich, 1997; Urlich et al., 1998; Inui and Ichihara, 2001a,b). Neurological studies have also indicated that time adjustment and detailed execution of the motor response are represented in different brain structures during hand and finger movements (Ivry et al., 1988; Ivry and Keele, 1989). These results support the functional independence of timing and force control in the forelimb motor system. Nevertheless, it is unclear whether this is true for the lower limb motor system.

Journal of Sports Sciences ISSN 0264-0414 print/ISSN 1466-447X online # 2004 Taylor & Francis Ltd DOI: 10.1080/02640410310001641601

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374 The main aim of this study was to clarify the functional characteristics of lower limb motor systems controlling timing and force production in an auditory-guided motor task. Another issue related to sprint start performance is the ability to predict the time of the starting pistol, which is usually assessed by reaction time (Walker and Hayden, 1933; Buckolz and Vigars, 1987; Hamon et al., 1989; Collet, 1999). In the sprint start, there is a period between the ‘get set’ warning and the starting pistol, which is termed the ‘foreperiod’ by psychologists. If the duration of the foreperiod is kept constant, the runner can easily predict the time of the ‘go’ signal such that reaction time is shorter (Botwinick and Thompson, 1966; Bertelson and Tisseyere, 1968; Mattes et al., 1997) and the response force is reduced (Mattes et al., 1997; Mattes and Ulrich, 1997). Although both the duration and regularity of the foreperiod are important to achieve quicker and stronger responses during the sprint start, few studies have approached this problem using reaction time (Walker and Hayden, 1933; Buckolz and Vigars, 1987; Hamon et al., 1989; Collet, 1999). For a detailed understanding of the nature of the time adjustment function of the lower limb motor system, which enables us to develop a more efficient sprint start performance, a more controlled experimental design in which the reaction time and response force can be measured under various foreperiod conditions is needed. The second aim of this study was to compare the effects of duration and regularity of foreperiod on response force with those on reaction time during a lower limb motor task. To obtain basic information on the neural control of lower limb movement, which is useful for a comparison with previous studies on upper limb motor control, we used participants who were not elite athletes.

Fukushi and Ohtsuki (1990, 1995). We used isometric leg extension in the current task, because force production under conditions in which movement kinematics are variable from trial to trial and from participant to participant might involve complicated force–velocity and force–length relations. The participant was seated on a horizontal table with her trunk fixed vertically, and her right foot was on a foot-plate with knee and ankle angles fixed at 1208 and 908, respectively. Although the angle between the trunk and the lower limb and the direction of force application were different from the actual sprint starting posture, these angular positions were considered more efficient for exerting isometric force, allowing the participant to perform the task repetitively for a long time (Nakamura et al., 1985; Marcora and Miller, 2000). The left lower limb was relaxed and extended forward on the chair. The footplate was connected to the chair by a load cell (1269F Takei, Japan) and a chain. One end of the chain was

Force amp.

Methods

EMG amp.

Data recorder

Participants Fourteen female university students without any known neurological disorders provided informed consent to participate in the study (age 21.2+1.0 years, height 1.62+0.05 m, body mass 54.1+6.1 kg; mean+s). The menstrual cycle stage of the participants was not controlled for in the current study. The experimental protocol was approved by the Ethical Advisory Committee of the University of Tokyo. Experimental apparatus The apparatus used in the current experiment (Fig. 1) has been described in detail by Seki and Ohtsuki

PC

Polygraph

Speaker

Time regulator

Auditory stimuli (300Hz pure tone)

Load cell Fixation point

Fig. 1. Schematic representation of the experimental apparatus and participant’s posture.

375

Neuropsychological approach to reaction time and response force control hooked on the foot-plate so that the participant could not apply muscle force to the transducer by dorsiflexion or plantar-flexion of the ankle. If these types of ankle motion were to occur, the foot-plate would be rotated and the participant’s foot would slip off it. To keep the head stationary, the participant was instructed to fixate her eyes on the centre of the cross on a screen in front of her during performance of the task.

were amplified, digitized and stored in a personal computer (PC9001-DA NEC, Japan) with 1 ms resolution (1000 Hz) for off-line analyses. Figure 2 shows the time course of force curve and EMG activity for three muscles in one trial. The peak magnitude of isometric force (peak force) was determined as the highest point on the force curve. Measurement of reaction time (RT)

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Behavioural task In the present study, an ‘auditory-guided’ isometric leg-extension task was employed with a 2 6 13 repeated-measures design. An auditory warning signal (a brief tone of 100 ms duration) was first given to the participant. After one of the 13 foreperiod durations (0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 and 10.0 s), a ‘go’ signal (a tone of 300 ms duration) was presented. We used a time regulator (Sanwa, Japan) to control the time course of the auditory stimuli. The participant was instructed to apply isometric leg extension force as quickly and strongly as possible to the foot-plate in response to the ‘go’ signal. During the experimental session, the participant was not given any knowledge of the behavioural results. To assess the effects of duration and regularity of foreperiod on the reaction time and response force, we used two conditions. In the ‘irregular condition’, each foreperiod was given once in a random order so that 13 trials of different foreperiods constituted one block, and five consecutive blocks were performed by each participant. In the ‘regular condition’, each foreperiod was given seven times consecutively to construct one block, and the order of foreperiods was randomized. Thus, in the irregular condition participants could not predict the onset time of the response stimulus, while they could in the regular condition. Each condition was repeated once and the order of conditions was randomized for every participant. The participants were instructed explicitly about the regularity, but not the duration, of the foreperiod. Measurement of isometric force and EMG Isometric force applied to the foot-plate was recorded by the load cell, and electromyograms (EMGs) were recorded from three muscles (vastus medialis, tibialis anterior and gastrocnemius lateralis) using bipolar surface electrodes (5 mm diameter, 30 mm interelectrode distance) to monitor muscle activity throughout the experimental session. These muscles are recruited during the sprint start (Mero and Komi, 1990; Guissard et al., 1992). The force and EMG data

The latency between the onset of the ‘go’ signal and the onset of the isometric force curve was defined as the Force-RT. The onset of the isometric force was determined as the first time point of the period during which the force increased continuously over five successive time points. This latency can be divided into premotor and motor components (Botwinick and Thompson, 1966; Haagh et al., 1987; Kawabe, 1987). In previous studies, the premotor component was determined as the period from stimulus onset to the onset of EMG activation in the prime mover muscle, and the motor component was determined as the period from the onset of EMG activation to movement initiation. EMG onset, which was equivalent to the premotor component, was determined from the full-wave rectified EMG of the vastus medialis by the same procedure as the force onset detection. Then we calculated electromechanical delay by subtracting EMG-RT from Force-RT. Data analysis Two-way analysis of variance (ANOVA) with repeated measures (factors: task condition and foreperiod duration, P 50.05) was applied to the Force-RT, EMGRT, electromechanical delay and peak force for each

Isometric force

100 N

Gastrocnemius lateralis

0.1 mV

Tibialis anterior

0.1 mV

Vastus medialis

0.1 mV

500 ms

Fig. 2. An example force curve and EMG activities during an experimental trial. All events were aligned at the onset of the response stimulus.

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participant or across participants. All statistical analyses were performed using the Statcel 1.0 statistical software package (OMS, Japan). We analysed the data from the last five trials in the regular condition to eliminate the after-effect of the preceding foreperiod duration.

Results

There was no significant difference between Force-RT and EMG-RT, since the electromechanical delay, which ranged from 42 to 47 ms, was relatively constant. No statistically significant effects of foreperiod duration or task condition on the electromechanical delay were found for any of the participants. Therefore, we describe the EMG-RT data. Mean EMG-RT across all participants is shown in Fig. 3. The EMG-RT differed between the regular and irregular conditions for the shorter foreperiod durations (0.5–2.5 s). For

300 250 RT (ms)

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Effects of task condition and foreperiod duration on reaction time

200 150 100 0

2

6 8 4 Foreperiod duration (s)

10

Fig. 3. Mean and standard error of EMG-RT across all participants. &, regular condition; &, irregular condition.

these foreperiods, the mean value in the regular condition was obviously shorter. For the longer foreperiods, the mean reaction times were similar across the two conditions. Analysis of variance revealed a significant interaction effect between task condition and foreperiod duration (F12,156 = 9.8, P 50.001). Effects of task condition and foreperiod duration on peak force Overall, peak force was affected by the task condition. However, the effect of the task condition was not as strong as that observed on EMG-RT, and the difference in peak force varied substantially among individual participants. Table 1 shows mean peak force in the two task conditions for each classification of participants. The participants were classified into the following three groups based on the significance of the main effect of task condition and the sign of the difference: Type I (n = 9, irregular 5regular), Type II (n = 3, irregular 4 regular) and Type III (n = 2, no statistical difference between the two conditions). We re-examined the effect of foreperiod duration on peak force for each group. Figures 4a, 5a and 6a show typical examples of isometric force–time courses for a short (0.5 s) and a long (8.0 s) foreperiod from Type I, II and III participants (participants 5, 4 and 14, respectively). For the short foreperiod in the regular condition, all participants initiated the fast ramp force earlier than in the irregular condition. Participant 5 (Fig. 4) exerted a greater force in the regular condition than in the irregular condition regardless of foreperiod duration, whereas participant 4 exerted a greater force in the irregular condition only (Fig. 5). Participant 14 exerted consistent force across the two conditions (Fig. 6). Figure 4b shows mean peak force across the nine Type I participants. Peak force was significantly greater in the regular condition than in the irregular condition (F1,8 = 29.0, P 50.001). However, foreperiod duration

Table 1. Peak force across 13 foreperiod durations for each condition for each participant and the classification of participants (mean+s) Peak force (N) Participants Type I (n = 9) Type II (n = 3) Type III (n = 2) Overall (n = 14)

EMG-RT (ms)

Irregular condition

Regular condition

Irregular condition

Regular condition

734.4+433.2 1038.4+679.1 1207.3+207.9 867.1+509.2

875.4+455.1*** 875.4+620.2* 1213.5+184.2 923.7+483.7*

208.4+65.3 255.9+94.5 179.3+48.7 214.4+74.5

187.4+78.1§§§ 225.2+85.7§§§ 166.0+42.3*** 192.4+78.0§§§

Note: *P 5 0.05, ***P 5 0.001 for main effect of condition and §P 5 0.05, §§§P 5 0.001 for an interaction effect between condition and the duration of the foreperiod. The mean values were obtained from the samples of 65 trials (5 trials multiplied by 13 foreperiod durations) multiplied by the number of participants of each type for each condition.

377

Peak force (N)

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Neuropsychological approach to reaction time and response force control

Foreperiod duration (s) Fig. 4. (a) Examples of force trajectories exerted by participant 5 for foreperiod durations of 0.5 s and 8.0 s. (b) Mean and standard error of peak force in the nine participants grouped into Type I.

did not affect peak force (F12,96 = 0.3, non-significant). Similarly, the average peak force across the three Type II participants (Fig. 5b) and across the two Type III participants (Fig. 6b) showed no foreperiod durationdependent changes (F12,24 = 0.2, non-significant for Type II; F12,12 = 1.0, non-significant for Type III). No significant interaction of task condition and foreperiod duration was observed for peak force in any participant. In addition, we re-examined the effects of task condition and foreperiod duration on reaction time for each type of participant separately and the results were almost the same as for the pooled data (Table 1).

Discussion The results of the present study can be summarized as follows. First, reaction time showed an interaction between the regularity and the duration of the foreperiod. Second, the effect of regularity of foreperiod on peak force was found for most participants, but it

was not in the same direction for all participants. Finally, foreperiod duration did not influence peak force in any participants. These results suggest that the reaction time and response force associated with leg movement are processed independently in the lower limb motor system during a simple reaction time task with auditory guidance. We discuss three points associated with these findings below. Effects of duration and regularity of foreperiod on timing control Previous psychological experiments have demonstrated the significant effects of regularity and duration of foreperiod on reaction time during forelimb movements, with reaction time usually shorter under a regular condition (Botwinick and Thompson, 1966; Bertelson and Tisseyere, 1968; Ohtsuki and Kawabe, 1983; Mattes et al., 1997; Mattes and Urlich, 1997). For example, Botwinick and Thompson (1966), using a finger keypress task

Fukushi and Ohtsuki

Peak force (N)

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378

Foreperiod duration (s) Fig. 5. (a) Examples of force trajectories exerted by participant 4 for foreperiod durations of 0.5 s and 8.0 s. (b) Mean and standard error of peak force in the three participants grouped into Type II.

in response to an auditory stimulus with four different foreperiods (0.5, 3.0, 6.0 and 15.0 s), reported that reaction time was always shorter in the regular than the irregular condition regardless of foreperiod duration. In contrast, our results showed that the regularity and duration of the foreperiod significantly interacted with each other, which suggests that the predictability of the ‘go’ signal can facilitate the initiation of a lower limb motor response but the response also depends on foreperiod duration. The discrepancy between our findings and those of past studies may have derived from the difference in task performance (exertion of maximal isometric force vs keypress), experimental limb (leg vs hand/finger) and/or foreperiod duration. For real sprint starts, Walker and Hayden (1933) examined the optimal time for holding sprinters between the ‘get set’ command and starting gun in a short-distance race. They reported that 1.4–1.6 s seemed to be the optimum duration, which is comparable with the 1.5 s foreperiod in our study. In the irregular condition in the present study, a shorter

reaction time was usually observed with a foreperiod of more than 3 s; in the regular condition, reaction time was significantly shorter than in the irregular condition with foreperiods of 1.0–1.5 s (Fig. 3). Previous results and those of the present study suggest that humans may require between 1 and 3 s to complete the ‘preparatory set’ for a quick response to an auditory stimulus during leg movement, and the repetition of such short foreperiod durations can facilitate this preparatory process. Effects of duration and regularity of foreperiod on response force The present results demonstrate that the regularity of the foreperiod, which means the timing of the response signal is predictable, affects the magnitude of response force exerted by isometric leg muscle contractions. That there was no effect of foreperiod duration on response force is in line with the results of Mattes and Urlich (1997) and Mattes et al. (1997), who examined the effects of foreperiod on index finger

379

Peak force (N)

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Neuropsychological approach to reaction time and response force control

Foreperiod duration (s) Fig. 6. (a) Examples of force trajectories exerted by participant 14 for foreperiod durations of 0.5 s and 8.0 s. (b) Mean and standard error of peak force in the three participants grouped into Type III.

flexion force in response to an auditory stimulus. These researchers showed that predictability of the time of the response signal usually induced a smaller response force, while in the current study only three Type II participants decreased response force in the regular foreperiod condition. Mattes et al. (1997) explained their observations by recourse to Na¨a¨ta¨nen’s motor readiness model (Na¨a¨ta¨nen, 1971). This model proposes that a higher response probability induces a faster but weaker response, since the higher predictability of response provides a higher level of motor readiness and this readiness requires only a small increment of activation to trigger the response. Our results suggest that Na¨a¨ta¨nen’s motor readiness model may not be directly applicable for the timing and force control of the lower limb motor system under the current experimental conditions. Our participants were required to exert force as quickly as possible using maximal effort, whereas the studies of Mattes and Urlich (1997) and Mattes et al. (1997) did not require maximal effort. This suggests that the exertion

required modifies the level of motor readiness, regardless of foreperiod. In the present study, we noted three different types of participants in relation to peak force, although the manipulation of foreperiod and the instructions for the motor task were identical across participants. It is possible that attention to the instructions related to response effort differed among participants. Gordon and Ghez (1987) examined the changes in magnitude of force exerted under different instructions (‘as brief as possible’ vs ‘as accurate as possible’) and reported that different instructions concerning the strategy of forceexertion induced different time courses of the force curve. In our experiment, participants were required to perform isometric leg extension ‘as quickly and as strongly as possible’. Since most participants showed a similar interaction effect between regularity and duration of foreperiod on reaction time, the relative amount of attention – conscious or unconscious – to the force and speed aspects of the effort possibly caused the different directions of change in peak force. Those who

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paid most attention to ‘as strongly as possible’ in the stimulus-predictable condition would have belonged to Type I, and those who concentrated on the ‘quickness’ aspect would have constituted Type II. This latter special effort of Type II might have been peculiar to the slow reactors who showed longer reaction times than other types of participants, as shown in Table 1. We need to count such cognitive effects in the real situation of sprint start performance, during which attention, allocation of concentration for the race, or mental pressure may affect the motor response and the internal process of motor preparation (Buckolz and Vigars, 1987; Collet, 1999). Using trained athletes and more manipulated behavioural requirements will be of benefit in future studies of this issue. Representation of timing and response parameters of motor behaviour in brain structures A previous study of force–time relationships in sprint start performance reported that take-off force and the time required to reach 2.5 m from the start position were negatively correlated (Young et al., 1995). Consistently, psychological studies have reported covariation between reaction time and response force under reaction time task paradigms (Nagasaki et al., 1983; Haagh et al., 1987). Kawabe (1987; Kawabe-Himeno, 1993), who studied visually guided elbow flexion movement resisting an external load, demonstrated that the predictability of the forthcoming load (heavy or light) affected reaction time differently according to foreperiod duration. These results appear to suggest that the timing and response force might be controlled by a common single process or by an interaction of the respective processes. On the other hand, recent psychological findings have emphasized the functional segregation between

timing and response force control processes in the human motor system even though they still did interact (Ivry 1986; Mattes and Urlich, 1997; Mattes et al., 1997; Urlich et al., 1998). Our results are in line with these recent concepts, and extend them to lower limb motor control. Neurological studies support these recent behavioural findings (for a review, see Ivry, 1996). Studies using cerebellar patients have reported that timing of motor initiation is represented in the lateral part of the cerebellum, whereas response parameter and selected motor responses are represented in the medial part (Ivry et al., 1988; Ivry and Keele, 1989; Ivry, 1996). At the cortical level, the right cerebral hemisphere prefrontal–inferior parietal network appears to play a role in timing control (Harrington et al., 1998), and premotor cortex and the supplementary motor area are considered to play a role in time adjustment during sequential motor tasks (Halsband et al., 1993). Imaging studies using positron emission tomography (PET) or functional magnetic resonance imaging (MRI) further emphasize the independence of timing and parametric control of movement. The timing and execution details of motor responses are represented by different cortical and subcortical structures (Table 2). In addition, Sakai et al. (2000) reported that the premotor cortex appears to integrate the timing and response selection of finger tapping during a choice reaction time task. Anatomically, the cortical areas indicated in Table 2 have parallel and segregated pathways involving the cerebellum and basal ganglia via thalamo-cortical circuits and both pathways are thought to play critical roles in motor control (Jueptner and Weiller, 1998; Middleton and Strick, 2000). The problem remaining is whether the time adjustment and movement parameters are processed in parallel or series in these brain structures (Sakai et al., 2000). Our findings do not discriminate

Table 2. Brain structures associated with timing and parametric control of movement as indicated by PET and MRI studies Brain region

Timing

Response details

Cerebral cortex

Supplementary motor area (SMA) (Rao et al., 1997)

SMA and primary motor cortex (MI) (Dettmers et al., 1995; Sakai et al., 2000) Sensorimotor cortex (Rao et al., 1997)

Sensory association areas and ventrolateral prefrontal cortex (Penhune et al., 1998) Cerebellum

Posterior lobe (Sakai et al., 2000) Lateral cerebellar cortex and cerebellar vermis (Jueptner et al., 1995; Penhune et al., 1998)

Anterior lobe (Sakai et al., 2000) Dorsal dentate nucleus (Rao et al., 1997) Inferior cerebellar cortex (Jueptner et al., 1995)

Basal ganglia

Putamen (Rao et al., 1997)

Globus pallidus (Penhune et al., 1998)

Thalamus

Ventrolateral thalamus (Rao et al., 1997)

Neuropsychological approach to reaction time and response force control between these two models of information processing even though we clearly demonstrated the segregation of these two processes. Further investigations are required to verify the order of information processing of time adjustment and parametric control of motor responses, and hence provide new insights into effective training for the speed and power aspects of sport performance, including the sprint start.

Acknowledgement We thank R.D. Seidler for helpful comments on an earlier draft of the manuscript.

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