Human Movement Science 29 (2010) 542–555
Contents lists available at ScienceDirect
Human Movement Science journal homepage: www.elsevier.com/locate/humov
How changing the focus of attention affects performance, kinematics, and electromyography in dart throwing q Keith R. Lohse a,*, David E. Sherwood b, Alice F. Healy a a b
Department of Psychology and Neuroscience, University of Colorado, Muenzinger Building, 345 UCB, Boulder, CO 80309, USA Department of Integrative Physiology, University of Colorado, Muenzinger Building, 345 UCB, Boulder, CO 80309, USA
a r t i c l e
i n f o
Article history: Available online 11 June 2010 PsycINFO classification: 2330 2343 2346 Keywords: Focus of attention Motor control Human performance
a b s t r a c t Research has found an advantage for an external focus of attention in motor control and learning; instructing subjects to focus on the effects of their actions, rather than on body movements, can improve performance during training and retention testing. Previous research has mostly concentrated on movement outcomes, not on the quality of the movement itself. Thus, this study combined surface electromyography (EMG) with motion analysis and outcome measures in a dart throwing task, making this the first study that includes a comprehensive analysis of changes in motor performance as a function of attentional focus. An external focus of attention led to better performance (less absolute error), decreased preparation time between throws, and reduced EMG activity in the triceps brachii. There was also some evidence of increased variability for kinematic measures of the shoulder joint under an external focus relative to an internal focus. These results suggest improved movement economy with an external focus of attention. Ó 2010 Elsevier B.V. All rights reserved.
1. Introduction If attention is not properly directed or attentional limits are exceeded, salient information in the environment will be missed, which can degrade performance or result in outright failure (Wickens & McCarley, 2008). In a demanding performance environment, performers (e.g., surgeons, pilots) need to have empirically sound training and be able to implement strategies that optimize performance and
q
This work was supported in part by Army Research Office Grant W911NF-05-1-0153 to the University of Colorado. * Corresponding author. Tel.: +1 2082417861. E-mail address:
[email protected] (K.R. Lohse).
0167-9457/$ - see front matter Ó 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.humov.2010.05.001
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
543
maintain these optimal levels of performance. Thus, correctly focusing attention during learning and during performance is critical, especially when the pressure to perform increases. A common example of misdirected attention hurting performance is ‘‘choking”. Choking is a decrement in performance that occurs when attention shifts as a function of increased pressure to perform (Baumeister, 1984; Lewis & Linder, 1997; Pijpers, Oudejans, & Bakker, 2005). Beilock and Carr (2001) investigated this phenomenon in a series of descriptive studies and experiments. Initially, Beilock and Carr interviewed expert and novice golfers about their experiences with putting. Experts had less detailed and fewer recollections of shots made, suggesting that experts do not think as explicitly about their actions as novices do. Instead, this finding suggests that experts operate with more implicit procedural knowledge, which may allow them to perform at a high level but is not conducive to explicit recollection. Based on this observation, Beilock and Carr experimentally manipulated training conditions by having subjects train a golf putting skill with either a concurrent secondary alphabetic arithmetic task (where attention was essentially ‘‘distracted” from putting) or with increased self-consciousness. Subjects were oriented toward high self-consciousness by being videotaped while putting and told that their movements would be later evaluated by an expert. In a post test that maintained training conditions for all subjects, subjects were told that if they could increase their performance by 20% they would receive $5 (increasing the pressure to perform). Subjects who had received high selfconsciousness training suffered no negative changes in performance in the post test (i.e., no choking), but performance began to worsen for subjects who had received dual-task training. The fact that self focused training ameliorated the performance decrement of choking suggests that ‘‘choking” is at least partially a shift to internally focused attention whereby the performer attempts to consciously (explicitly) control the component movements of the skill. It is also important to note that the inoculating effect of self-conscious training only appeared once the skill had been highly practiced and thus was more proceduralized; interrupting training early to administer the high pressure test led to no difference between the self-conscious and dual-task groups. This effect was replicated by Wan and Huon (2005), where novice musicians were first taught a basic rhythm and then practiced under single task conditions (simply practicing to reproduce the rhythm), under dual-task conditions (reproducing the rhythm while listening to a second piece of music), or under high self-consciousness conditions (where subjects were videotaped and told to focus on how they were performing). In accordance with the conclusion that choking occurs as a result of explicit monitoring, some research implies that performers should be taught motor skills implicitly, because attending to procedural skills erodes performance (Masters, 2000; Masters, Polman, & Hammond, 1993; Maxwell, Masters, & Eves, 2000). This position is similar to the five-step model of athletic performance proposed by Singer (1985). Singer proposed five general phases (from preparation to execution) for successful motor performance. First (1) is a readying stage, in which the performer thinks about positive performance outcomes and expectations. Then (2) is an imaging phase, in which the performer mentally envisions successful performance of the task. The next phase of mental preparation is more narrow, and Singer suggests that the performer should (3) focus on a single, highly relevant dimension of the task before (4) executing the movement. During execution, cognitive demands are different from the mental preparation phases, and Singer suggests it is advantageous to the performer not to think about possible outcomes or about the action itself. In the final phase (5), available feedback, both intrinsic and extrinsic, needs to be analyzed to correct errors and improve performance. Willingham’s (1998, 1999) Control Based Learning Theory of motor control (COBALT) offers a neurological explanation of why shifting attention in order to explicitly control proceduralized skills hurts performance and leads to choking. COBALT proposes several stages of neurological representation and motor control. First, a performer selects which objects in the environment need to change (goal selection). Then perceptual motor areas in parietal cortex and premotor cortex select the most appropriate movement targets to achieve these goals. After the spatial targets are selected, they must be properly sequenced, a function associated with the supplementary motor area (SMA). When subjects are instructed to complete a complex series of finger movements, both the SMA and primary motor cortex (PMC) are active, but when instructed to imagine performing the sequence only the SMA is active (Roland, Larsen, Lassen, & Skinhoj, 1980). Finally, the abstract sequence of movements is represented in an egocentric spatial code and must be translated into a pattern of muscular activation. These stages of processing can operate in either an explicit or implicit control mode, except for the translation of
544
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
egocentric representation to muscle activation, which is always an implicit process. Implicit control modes allow for the automatic selection of spatial targets and automatic sequencing of movements based on practice and experience. Explicit control allows the performer to consciously select spatial targets and consciously sequence their movements. Thus, a shift to explicit control processes in later stages of motor learning could degrade performance because actions would change from rapid, automatic to slower, conscious selection of spatial targets and movement sequences. Interestingly, this issue of timing has not been examined in research on the focus of attention. It is plausible that an external focus of attention might minimize conscious control thus requiring a shorter preparation time (but not shorter execution time) compared to an internal focus that is associated with greater conscious control. The current study addresses this question with separate analyses of preparation time and execution time as a function of focus of attention. Thus, both Singers’ (1985) model of performance and Willingham’s (1998) model of motor control predict better performance when attention is not internally directed to the mechanics of a performers’ actions (i.e., when motor control processes are allowed to run implicitly with minimal conscious control). This prediction is well supported experimentally. The advantage of externally focused attention during learning and performance has been shown for a variety of athletic skills. For example, it has been found in a ski simulator (Wulf, Höß, & Prinz, 1998; Wulf & Weigelt, 1997), in tennis strokes (Maddox, Wulf, & Wright, 1999; Wulf, McNevin, Fuchs, Ritter, & Toole, 2000), in the accuracy of golf shots (Wulf, Lauterbach, & Toole, 1999; Wulf & Su, 2007), in soccer kicking accuracy (Wulf, Wächter, & Wortmann, 2003), and even in the more fundamental skill of a stationary vertical jump (Wulf, Zachry, Granados, & Dufek, 2007). It is important to note that many of these tasks used novice performers as subjects. Previous research has shown that novices should focus on a single relevant task dimension to improve performance, whereas experts can focus on more dimensions simultaneously (Masters, 2000; Singer, 1988), but a more accurate interpretation is perhaps that attention of novices should be directed to a single external dimension of the task and not an internal dimension such as limb position. One task that has reliably shown a performance advantage for externally focused attention is dynamic balance. Dynamic balance (usually measured by having subjects stand on a pendulous stabilometer platform) is a skill most people master early in life, but as a result of aging or injury commonly needs to be retrained by physical therapists. In their second experiment, Wulf et al. (1998) demonstrated the advantages of an external focus in learning dynamic balance. In this experiment, subjects stood on a stabilometer and maintained balance by keeping the platform in a horizontal position. To direct the focus of attention subjects were told to focus on their feet (internal focus group) or on markers placed in front of their feet on the platform (external focus group) and, depending on the condition, keep either their feet or the markers level. On two consecutive days, subjects completed practice trials while being reminded of how they should focus their attention on alternating trials. On the third consecutive day, subjects were given a retention test, but no instructions on how to focus attention. During this retention test subjects who practiced with an external focus of attention showed significantly better performance than internally focused subjects, measured by root mean squared error (RMSE) of platform movement. Wulf and Shea (1999) replicated these results in a stabilometer task, but also manipulated the feedback subjects received about their performance. Feedback was provided concurrently to the task on a computer screen that illustrated deviations of the platform. Internally focused subjects were told that the feedback represented their feet, whereas externally focused subjects were told that the feedback represented the platform. Both feedback and external focus of attention were found to facilitate learning, as demonstrated on a retention test without feedback or attentional instructions. Similarly, Wulf, Shea, and Park (2001) demonstrated an advantage for externally focused attention in a stabilometer task, but also used self-report measures to assess subjects’ preferences for external and internal focus if they were given the choice during practice. After a day of training with both foci in separate blocks of trials, subjects were allowed to shift their attention freely, and in a post test had to report how they were focusing their attention. Most subjects reported that they adopted an external focus of attention. By keeping the markers very close to the feet in the stabilometer task, researchers have controlled for the spatial focus of attention, making the critical difference between the two conditions a conceptual difference between the subjects’ own body and the platform of the stabilometer, when the actual
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
545
spatial difference is a matter of millimeters. A few studies have manipulated the spatial distance of attentional foci and generally found an advantage for extending the focus of attention well beyond the body. One study looked at placing different markers along the platform of the stabilometer, with markers either under the feet (near-external), at the fulcrum of the platform (inside far-external), or at the edges of the platform (outside far-external). These three external focus groups were compared to each other as well as to an internal focus group. As predicted, the external focus groups all had significantly smaller RMSE during retention testing than the internal focus group. Interestingly, the two farexternal focus groups also outperformed the near-external focus group, indicating that increasing the distance of external focus can enhance learning, although the two far-external focus groups were not different from each other (McNevin, Shea, & Wulf, 2003). Similar to the findings of McNevin and colleagues, Park, Shea, McNevin, and Wulf (2000) found an advantage for increasing the distance of external focus in a stabilometer task (see also Bell & Hardy, 2008). Rather than using near- versus far-external foci on the stabilometer platform, however, Park et al. placed markers on 1 m rods that extended out from the platform in front of the subjects’ feet. Again, this far-external focus resulted in smaller RMSE during retention than a near-external focus, and both external focus groups out performed internally focused subjects. But how exactly does attentional focus confer an advantage? Previous research has very clearly and empirically demonstrated the advantage of externally focusing attention during dynamic balance tasks (Park et al., 2000; Shea & Wulf, 1999; Totsika & Wulf, 2003; Wulf et al., 1998, 2000) as well as more athletic endeavors (Maddox et al., 1999; Wulf & Su, 2007; Wulf & Weigelt, 1997; Wulf et al., 1998) and even therapeutic settings (Fasoli, Trombly, Tickle-Degnen, & Verfaellie, 2002; Landers, Wulf, Wallman, & Guadagnoli, 2005; Wulf, Landers, Lewthwaite, & Töllner, 2009). Yet all of these previous studies have focused on the outcomes of movement (e.g., distance of a ball from the target or motion of the stabilometer platform) rather than on the quality of the movement itself. Thus in the current experiment, we include a comprehensive analysis of changes in motor performance that occur with a shift in attentional focus by using not only behavioral measures of performance but also detailed electrophysiological measures and biomechanical measures. A few previous studies have incorporated EMGs as a measure of attention and performance. These studies have replicated behavioral findings that externally focused attention improves performance but also found a general reduction in EMG activity when subjects adopt an external focus of attention. Vance, Wulf, Töllner, McNevin, and Mercer (2004) recorded EMG activity of the agonist (biceps brachii) and antagonist (triceps brachii) muscles in the biceps curl under different attentional foci. Vance et al. found significantly reduced integrated EMG activity (iEMG) when subjects adopted an external focus of attention compared to when subjects adopted an internal focus of attention, in both the biceps and triceps muscles. By using an integrated fast Fourier transform of the raw EMG data, Vance et al. were also able to calculate the mean power frequency (MPF) of contractions. In early repetitions, an external focus of attention led to smaller MPF than an internal focus of attention, suggesting that externally focusing attention improves movement economy at the level of muscle fiber recruitment. Zachry, Wulf, Mercer, and Bezodis (2005) also used surface EMG to study how attentional focus affects the neuro-muscular system while shooting free-throws with a basketball. In this experiment, subjects were instructed to focus either on the motion of their wrist (internal focus) or the rear-center of a basketball hoop (external focus). Free-throw accuracy was greater in the external focus condition and, congruent with the results of Vance et al. (2004), there was reduced EMG activity in the biceps and triceps brachii during the shooting motion when subjects adopted an external focus of attention. Increased EMG activity in both the biceps and the triceps suggests increased muscle stiffness that might hamper fine motor control. Although the current study used dart throwing (see also Marchant, Clough, & Crawshaw, 2007) instead of dynamic balance or bicep curls, based on the results of Vance et al. (2004) and Zachry et al. (2005), we anticipated a similar advantage in behavioral measures of accuracy and reduced EMG activity in the biceps and triceps brachii when subjects used an external, rather than internal, focus of attention. Further, we hypothesized that reduced muscle stiffness (i.e., reduced EMG activity) in the external focus condition would also lead to increased variability in the joint kinematics. Thus, we predicted an increase in kinematic variability with an external focus of attention, but based on COBALT (Willingham, 1998) as a model, it seemed unlikely that shifting from an external to an
546
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
internal focus of attention would produce qualitatively different movements as represented by the other kinematic variables. However, we did predict an increase in preparation time between trials with an internal rather than external focus, because greater explicit control is theoretically being exerted on the perceptual-integration and sequencing processes during internal focus. 2. Method 2.1. Participants Data were collected from 12 participants, three of whom were left handed and nine of whom were right handed (identified first by having subjects’ sign a letter of informed consent and later by self report). Participants always threw with their dominant hand. Participants were recruited through introductory psychology classes and participated in the experiment to fulfill course credit requirements. 2.2. Apparati and measurements A commercially available competition bristle dart board was set to a regulation height (1.73 m off the ground) and distance (2.37 m from the throwing line). Participants threw regulation steel tip darts that weighed 22 g. Error was measured as the linear distance from the center of the dartboard (bullseye) to the dart, and served as the behavioral measurement of performance. For the EMG recording, the throwing arm was fitted with pairs of circular EMG electrodes (Ag/AgCl electrodes) on the surface of the skin on the mid-line belly of the biceps (antagonist muscle) and the mid-line long head of the triceps brachii (agonist muscle). Electrodes had a 1-cm diameter and were placed approximately 1 cm apart. The surface of the skin was prepared using an alcohol wipe with a mild abrasive, and EMG electrodes were coated with conductive gel then affixed using adhesive collars. A GB Instruments GMT 312Ò multimeter measured the resistance between EMG electrodes; if the resistance was greater than 100 Os, the area was cleaned again and the electrodes were reattached. An electrical common for each electrode pair was attached to the ear lobe. EMG data were collected using BiopacÒ MP100 hardware at 1000 Hz sampling rate and analyzed using Biopac AcqKnowledge software. The raw EMG signal was converted to RMSE, which some research suggests is a more accurate index of physiological changes than measures of raw amplitude (Basmajian & De Luca, 1985; De Luca, 1997) and was used in previous studies on the focus of attention (Zachry et al., 2005). The EMG signal was time-locked to the video data so that the moment of release for each trial was noted. In our analyses we were interested in EMG activity from the onset of activity to the moment of release. The moment of release was extracted from video data and the time of onset was estimated as the earliest continuously rising deviation above baseline for the triceps muscle (i.e., a deviation that rose and then fell back to baseline was not considered an onset). From the onset–release interval we analyzed the time of onset (release time–onset time), peak activation (in V), and the integral of the signal (iEMG, which represents both temporal and spatial components of the EMG signal). We also calculated mean power frequency (MPF) to replicate the findings of Vance et al. (2004), but because dart throwing uses dynamic contractions, considerable reservations must be taken in interpreting the frequency components of the EMG signal, which are very sensitive to morphological properties of the muscle and the relative relationship of EMG electrodes to the neuro-muscular system (Farina, 2006; Farina, Merletti, & Enoka, 2004; Merletti, Rainoldi, & Farina, 2001). MPF was computed by selecting the onset–release area of the raw EMG signal and computing a Fast Fourier Transform (FFT), which was windowed using a Hamming function. The FFT was then squared and integrated. From this integrated waveform, the frequency (Hz) corresponding to the mean power (V) between 1 and 250 Hz was selected as the MPF. A Canon Z950 MiniDV (30 frame per second capture rate) camera was placed perpendicular to the line of the throw to capture participants’ movement in the sagittal plane. Participants were asked to limit their throwing as much as possible to flexion and extension of the arm and wrist in the sagittal plane (i.e., no ‘‘side-arming” the throw). Two participants (in different counterbalancing orders) failed to follow this instruction satisfactorily, and as a result their data were omitted from the kinematic
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
547
analysis. Video data were captured and analyzed using Dartfish ConnectProÒ motion analysis software. The kinematic variables of interest included shoulder angle, elbow flexion, throwing time, and angular velocity of the dart. Shoulder angle and elbow flexion were measured at two critical times in the throwing motion: at the moment of retraction (point of maximum elbow flexion) and at the moment of release. To measure these variables, anatomical markers were placed at the acromion process, the lateral epicondyle, and styloid process of the throwing arm (see Fig. 1). Angular velocity of the throw (in degrees per second) was calculated by subtracting elbow flexion at retraction from flexion at the moment of release and dividing by throwing time. Preparation time, defined as the time between throws (from the moment of release in trial n to maximal flexion in trial n + 1), was also
Fig. 1. Kinematic measures of interest at retraction, defined as the moment of maximum elbow flexion (top). Kinematic measures of interest at release, defined as the moment the dart has clearly left the hand (bottom).
548
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
extracted from the video and served as a combined measure of feedback integration from the previous trial and preparation for the next trial. 2.3. Design The experiment was divided into three phases, and during each phase participants completed seven blocks of three dart throws. Participants received 2 min of rest between phases, in which they were allowed to sit, and some rest between blocks (while error was being measured) but remained standing. The first phase (acquisition phase) of the experiment familiarized participants with the experiment and no explicit instructions on how to focus attention were given, although in all phases, participants were instructed that they should throw the dart as accurately and consistently as they could to the center of the board. Phases 2 and 3 were counterbalanced between participants with internal focus and external focus instructions given by the experimenter, ‘‘Visually focus on the bulls-eye. . . mentally focus on the [movement of your arm/flight of the dart]. When you’re off target think about how you can correct the mistake by changing the [motion of your arm/flight of the dart]. Each time you throw, focus on [your arm/the dart] and think about [how you are moving/how it should fly].” Between each block, participants were reminded, ‘‘Focus on the [motion of your arm/flight of the dart] while being as accurate as possible.” Thus, there are within-subject variables of phase (1st, 2nd, and 3rd), block (seven blocks per phase), trial (three trials per block), and attentional focus condition (internal, external) and one between-subjects variable of order (internal then external or external then internal) for the dependent variables of behavioral performance measures, EMG measures, and kinematic measures. Phase was only initially analyzed for accuracy to assess participants’ improvement across phases of the experiment regardless of focus condition. In all subsequent analyses, Order Condition Block Trial mixed factorial ANOVAs were conducted for each dependent variable. Condition replaced phase as a factor, because the only counterbalanced conditions were the internal and external focus conditions (balanced between the second and third phases). Acquisition, in which no explicit attentional focus instructions were given, was confounded with order because it was always the first phase, invalidating comparisons between the acquisition phase and internal/external phases. All significant effects are reported in the results section, as well as some non-significant effects that are germane to the experimental hypotheses. All unreported main effects and interactions were nonsignificant in the mixed factorial ANOVA for that dependent variable (p > .05). 3. Results 3.1. Behavioral performance measures Overall, participants’ absolute error from the center of the target was 8.06 cm. Accuracy improved across blocks and error reduced from 10.41 cm in Block 1 to 8.01 cm in Block 7, F(6, 60) = 4.90, g2p = .33, p < .001; see Fig. 2a. The main effect of phase was not significant, F(2, 20) = 1.89, g2p = .15, p = .18, although error declined from the first phase (8.66 cm) to the second phase (7.63 cm) and third phase (7.89 cm). Restricting the analysis to only the internal and external focus phases, participants had significantly less error when externally focused than when internally focused, F(1, 10) = 4.79, g2p = .32, p = .026 (by a directional test; t(10 = 2.19); see Fig. 2b. In this restricted analysis the effect of block was still significant, F(6, 60) = 2.89, g2p = .22, p = .015, however the interaction of block and condition was not, F(6, 60) = 1.56, g2p = .17, p = .139, suggesting that the improvement from Block 1 to Block 7 was comparable for the internal and external focus conditions. The between-subjects variable of order was not significant, F(1, 10) = 1.16, g2p = .10, p = .307, and did not significantly interact with any of the within-subject variables. In terms of preparation time, participants averaged 2.98 s between throws. Preparation time significantly increased across blocks, from 2.60 s in Block 1 to 3.03 s in Block 7, F(6, 60) = 3.57, g2p = .26, p = .004. Restricting the analysis to only the internal and external focus phases, participants took less preparation time during external focus than during internal focus, F(1, 10) = 5.11, g2p = .33, p = .047; see Fig. 3a. In this restricted analysis the effect of block was still significant, F(6, 60) = 2.44, g2p = .19,
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
549
Fig. 2. (a) Absolute error as a function of block. (b) Absolute error as a function of attentional focus condition. Bars show between-subjects standard error.
p = .035, and participants’ preparation time increased from Block 1 (2.69 s) to Block 7 (3.15 s). The interaction of condition and block was not significant, F(6, 60) = 1.47, g2p = .128, p = .202. 3.2. EMG measures Integrated EMG activity (iEMG) was calculated for the onset-to-release interval for both the triceps (agonist) and biceps (antagonist) muscles. There was significantly less iEMG activity in the triceps muscle during external focus than during internal focus, F(1, 10) = 5.54, g2p = .35, p = .040. A similar pattern was found for iEMG in the biceps, where activity during external focus was less than during internal focus, but this difference was not significant, F(1, 10) = 1.86, g2p = .14, p = .200; see Fig. 4a. We also calculated an index of co-contraction by taking the ratio of iEMG in the agonist divided by iEMG of the antagonist; there was no difference in the iEMG ratio between attentional focus conditions, external = 4.71 and internal = 5.41, F(1, 10) < 1. No difference in the contraction ratio suggests no difference in co-contraction between internal and external focus conditions. However, decreased iEMG activity in the external focus condition can be interpreted as improved movement economy and reduced muscle stiffness because less activity (i.e., energy) is required and produces a more accurate result than the internal focus condition. Peak amplitude of the RMSE rectified EMG in the tricep was also significantly less during external focus than during internal focus, F(1, 10) = 6.32, g2p = .38, p = .031. Again, a similar pattern for peak amplitude was found in the biceps, where activity during external focus was less than during internal focus, but this difference was not significant, F(1, 10) < 1; see Fig. 4b.
550
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
Fig. 3. (a) Preparation time as a function of attentional focus condition. (b) Throw time as a function of attentional focus condition. Bars show between-subjects standard error.
EMG onset was computed from the RMSE rectified EMG and measured from the onset of activation in agonist muscle to the time of release. During external focus, onset time was significantly shorter than during internal focus, F(1, 10) = 8.22, g2p = .45, p = .017; see Fig. 4c. MPF was computed from an FFT of the raw EMG signal and restricted to frequencies between 1 and 250 Hz. There was no significant difference in MPF between the internal and external focus conditions, F(1, 10) < 1; see Fig. 5a. Also, contrary to the results of Vance et al. (2004), there was no significant interaction of condition and block, F(6, 60) = 1.55, g2p = .14, p = .179, such that the difference between early and late blocks was the same for external focus and internal focus conditions; see Fig. 5b. 3.3. Kinematic measures Throwing time (from maximum elbow flexion to the point of release) was not significantly different between external focus and internal focus, F(1, 10) < 1; see Fig. 3b. Interestingly, there was a significant effect of trial, such that Trial 1 (0.202 s) was slower than Trial 2 (0.183 s) and Trial 3 (.186 s), F(2, 22) = 13.040, g2p = .54, p < .001, indicating that participants moved faster as a block progressed. Although the difference between blocks was not significant, participants’ throwing time also reduced from Block 1 (.201 s) to Block 7 (.183 s), F(6, 60) = 1.92, g2p = .14, p = .090. There was also no difference in the standard deviation of throwing time between conditions, F(1, 10) < 1.
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
551
Fig. 4. (a) iEMG activity in the agonist (triceps) and antagonist (biceps) muscles as a function of attentional focus condition. (b) Peak EMG activity in the agonist and antagonist muscles as a function of attentional focus condition. (c) Time from the moment of release to the onset of EMG activity in the agonist muscle as a function of attentional focus condition. Bars show betweensubjects standard error.
Angular velocity was computed by examining the difference between maximum elbow flexion and the degree of elbow flexion at release divided by throwing time. Similar to the results from throwing
552
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
Fig. 5. (a) MPF as a function of attentional focus condition. (b) MPF as a function of attentional focus (external or internal) and block. Bars show between-subjects standard error.
time, there was no significant difference in angular velocity between external focus (409.7°/s) and internal focus (395.6°/s), F(1, 8) < 1. There were no effects of trial or block on angular velocity, respectively, F(2, 16) = 1.03, g2p = .11, p = .378 and F(6, 48) < 1. There was also no difference in the standard deviation of angular velocity between conditions, F(1, 9) < 1. Joint angles at the shoulder and elbow were measured at the moment of retraction (maximum elbow flexion) and at the moment of release. During retraction, participants had an average shoulder angle of 69.72°, there was no significant difference in shoulder angle between external and internal focus, F(1, 9) = 1.14, g2p = .11, p = .313, and no difference in the standard deviation of shoulder angle, F(1, 9) < 1. During retraction, participants had an average elbow flexion angle of 46.07°; there was no significant difference in elbow flexion between external and internal focus, F(1, 9) < 1, and no difference in the standard deviation of elbow flexion, F(1, 9) < 1. At the point of release, participants had an average shoulder angle of 80.12°, and there was no significant difference in shoulder angle between external and internal focus, F(1, 9) < 1. However, the standard deviation in shoulder angle during extension was greater during external (2.29°) than internal focus (1.90°), F(1, 9) = 6.71, g2p = .42, p = .029. At the point of release, participants had an average elbow extension angle of 114.33°, there was no significant difference in elbow extension between external and internal focus, F(1, 9) < 1, and no difference in the standard deviation of elbow angle, F(1, 9) < 1.
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
553
Additionally, all kinematic measurements were used as predictor variables of accuracy in a linear regression within each participant. Although occasionally an individual predictor was significant, the omnibus test including all six predictors was only significant for one participant. Averaging across participants the omnibus ANOVA was F(6, 56) = 1.49, g2p = .11, p = .195. Thus, accuracy does not seem to be tied to a particular kinematic measurement or set of measurements.
4. Discussion Improved accuracy in dart throwing during an external relative to internal focus of attention is consistent with previous research that has demonstrated improved performance in dynamic balance tasks (McNevin et al., 2003; Wulf & Shea, 1999), athletic performance (Maddox et al., 1999; Wulf & Su, 2007; Wulf et al., 2000), and rehabilitation (Landers et al., 2005). Reduced iEMG activity in the agonist muscle for external relative to internal focus of attention is also consistent with previous findings (Zachry et al., 2005). Similar to the interpretation made by Zachry et al., we believe that the reduced iEMG activity and improved performance that result from an external focus of attention can be interpreted as improved neuro-muscular efficiency. Essentially, less muscular activation coincides with an improved movement outcome. Thus an external focus of attention leads not only to more accurate performance in dart throwing, but also to more economic movement. Importantly, we have the added dimension of kinematics to examine whether movement economy is improved. Although a more detailed assessment of the movement kinematics is needed (e.g., we made no measurement of wrist or hand movements, which can tremendously affect the outcome of the throw), we can see that movement time, angular velocity, and joint angles in the elbow and shoulder do not seem to change as a function of attention. However, variability of shoulder movement at the moment of release was greater during external than internal focus (other kinematic variability measures also showed this difference, but none were significant). Although these results are somewhat tentative, increased variability during an external focus of attention would be similar to ‘‘functional variability” that is characteristic of expert performance (Müller & Loosch, 1999). Similar functional variability has been found in long jumping for stride length (Lee, Lishman, & Thompson, 1982) as well as for center-mass position and angle of take-off (Voigt, 1933). In these studies the variability in the final result is considerably smaller than the variability of its components, suggesting that the function of variability in movement control is to preserve the planned outcome or effect. This suggestion is congruent with Bernstein’s (1967) hypothesis that the goal of the task serves as an invariant property in the regulation of movement and agrees with Wulf and Prinz’s (2001) conclusion that adopting an external focus of attention may facilitate compensatory variability during movement to preserve the movement effect, whereas focusing on the movements themselves may reduce movement variability (e.g., through increased muscle stiffness) but at the expense of the movement outcome. It is also important to note that the iEMG represents both the spatial and temporal dimensions of the EMG signal, and those dimension are represented separately (albeit less completely) in measures of peak amplitude and EMG onset. Simply knowing that a difference existed in iEMG activity would not allow us to discriminate between low levels of activation that have a very early onset and high levels of activation that have a late onset. However, by combining the iEMG with peak amplitude and onset measures we can see that the difference in iEMG activity between the internal and external focus conditions is attributable to both early onset (the internal focus condition has a longer onset time in the agonist muscle) and increased magnitude of activity (the internal focus condition resulted in larger peak amplitudes than external focus). Fig. 4 also shows a proportional increase in iEMG in the antagonist muscle of the biceps during an internal focus of attention (although this difference was not significant). This concurrent increase in agonist and antagonist iEMG is evidence of increased muscle stiffness and decreased efficiency with an internal focus, and thus we can conclude that an external focus of attention improves intermuscular co-ordination by reducing muscle stiffness, which is consistent with the finding of increased movement variability. Beyond the magnitude of activation in a particular muscle, the frequency characteristics of the contraction also need to be considered. Smaller MPF during the external focus attention found by Vance et al. (2004) is indicative of less muscular recruitment, because of the incremental nature of muscle
554
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
contraction (i.e., ‘‘the size principle” of muscular contraction; Olsen, Carpenter, & Henneman, 1968). However we failed to replicate this we found in a dart throwing task, instead finding very similar MPF with internal and external focus. Both of these conclusions must be treated with caution, however, because these studies (this study and that by Vance et al.) used dynamic contractions. During dynamic contractions muscle morphology, relative location of the electrodes to the innervation zone, and relative depth of active motor units are changing, so it becomes impossible to make definitive statements about what physiological changes the MPF represents (Farina, 2006). To understand the implications of change in MPF that results from a shift in attentional focus, isometric contractions will need to be examined so that muscle morphology remains constant through the contraction. We aim to address this question in future studies (Lohse, Sherwood, & Healy, 2010). In sum, the present study succeeded in replicating previous behavioral results but went further by adding new electrophysiological and biomechanical dimensions that help to explain exactly how changing the focus of attention improves performance. Notably, an external focus of attention leads to improved movement economy through reduced activity of the agonist and antagonist muscles, but also increases the functional variability of the movement. As research on the focus of attention continues to demonstrate, even subtle differences in the structure of a task (in this case, subtle changes in the wording of the instructions) can have profound effects on motor behavior and the underlying physiology. Practitioners and instructors need to be aware that shifting one’s focus of attention affects performance and should develop effective strategies to keep the performer’s attention focused externally on the goals of the task. Growing evidence suggests that internally focusing on one’s own movements constrains the motor system and leads to movements that are not only less accurate, but also less efficient at the neuro-muscular level. An intriguing new finding of the present study was the increased preparation time during an internal focus of attention. Our measure of preparation time confirmed the initial prediction that preparation time would be decreased with an external focus of attention and is consistent with neuropsychological theories of motor learning and control (Willingham, 1998), but it is not clear what this decrease in preparation time represents (at either a theoretical or physiological level), and more detailed analyses of preparation time offer a promising direction for future experiments. References Basmajian, J. V., & De Luca, C. J. (1985). Muscles alive: Their functions as revealed by electromyography (5th ed.). Baltimore: Williams & Wilkins. Baumeister, R. F. (1984). Choking under pressure: Self-consciousness and paradoxical effects of incentives on skillful performance. Journal of Personality and Social Psychology, 16, 361–383. Beilock, S. L., & Carr, T. H. (2001). On the fragility of skilled performance: What governs choking under pressure. Journal of Experimental Psychology: General, 130, 701–725. Bell, J. J., & Hardy, J. (2008). Effects of attentional focus on skilled performance in golf. Journal of Applied Sport Psychology, 21, 163–177. Bernstein, N. A. (1967). The co-ordination and regulation of movements. Oxford: Pergamon. De Luca, C. J. (1997). The use of surface electromyography in biomechanics. Journal of Applied Biomechanics, 13, 135–163. Farina, D. (2006). The interpretation of the surface electromyogram in dynamic contractions. Exercise and Sport Sciences Reviews, 35, 121–127. Farina, D., Merletti, R., & Enoka, R. M. (2004). The extraction of neural strategies from the surface EMG. Journal of Applied Physiology, 96, 1486–1495. Fasoli, S. E., Trombly, C. A., Tickle-Degnen, L., & Verfaellie, M. H. (2002). Effect of instructions on functional reach in persons with and without cerebrovascular accident. American Journal of Occupational Therapy, 56, 380–390. Landers, M., Wulf, G., Wallman, H., & Guadagnoli, M. A. (2005). An external focus of attention attenuates balance impairment in Parkinson’s disease. Physiotherapy, 91, 152–185. Lee, D. N., Lishman, J. R., & Thompson, J. A. (1982). Regulation of gait in long jumping. Journal of Experimental Psychology: Human perception and performance, 8, 448–459. Lewis, B. P., & Linder, D. E. (1997). Thinking about choking? Attentional processes and paradoxical performance. Personality and Social Psychology Bulletin, 23, 937–944. Lohse, K. R., Sherwood, D. E., & Healy, A. F. (2010). How changing the focus of attention affects performance, kinematics, and electromyography. Paper presented at the North American Society for the Psychology of Sport and Physical Activity, Tucson, AZ. Maddox, M. D., Wulf, G., & Wright, D. L. (1999). The effects of internal versus external focus of attention on the learning of a tennis stroke. Journal of Exercise Psychology, 21, S78. Marchant, D. C., Clough, P. J., & Crawshaw, M. (2007). The effects of attentional focusing strategies on novice dart throwing performance and their task experiences. International Journal of Sport and Exercise Psychology, 5, 291–303. Masters, R. S. W. (2000). Theoretical aspects of implicit learning in sport. International Journal of Sport Psychology, 31, 530–541.
K.R. Lohse et al. / Human Movement Science 29 (2010) 542–555
555
Masters, R. S. W., Polman, R. C. J., & Hammond, N. V. (1993). ‘‘Reinvestment”: A dimension of personality implicated in skill breakdown under pressure. Personality and Individual Differences, 14, 655–666. Maxwell, J. P., Masters, R. S. W., & Eves, F. F. (2000). From novice to know-how: A longitudinal study of implicit motor learning. Journal of Sports Sciences, 18, 111–120. McNevin, N. H., Shea, C. H., & Wulf, G. (2003). Increasing the distance of an external focus of attention enhances learning. Psychological Research, 67, 22–29. Merletti, R., Rainoldi, A., & Farina, D. (2001). Surface electromyography for noninvasive characterization of muscle. Exercise and Sport Science Reviews, 29, 20–25. Müller, H., & Loosch, E. (1999). Functional variability and an equifinal path of movement during targeted throwing. Journal of Human Movement Studies, 36, 103–126. Olsen, C. B., Carpenter, D. O., & Henneman, E. (1968). Orderly recruitment of muscle action potentials. Archives of Neurology, 19, 591–597. Park, J. H., Shea, C. H., McNevin, N. H., & Wulf, G. (2000). Attentional focus and the control of dynamic balance. Journal of Sport and Exercise Psychology, 22, S85. Pijpers, J. J., Oudejans, R. R., & Bakker, F. C. (2005). Anxiety induced changes in movement behavior during the execution of a complex whole body task. Quarterly Journal of Experimental Psychology, 58, 421–445. Roland, P. E., Larsen, B., Lassen, N. A., & Skinhoj, E. (1980). Supplementary motor area and other cortical areas in the organization of voluntary movements in man. Journal of Neurophysiology, 43, 118–126. Shea, C. H., & Wulf, G. (1999). Enhancing motor learning through external-focus instructions and feedback. Human Movement Science, 18, 553–571. Singer, R. N. (1985). Sport performance: A five step mental approach. Journal of Physical Education and Recreation, 57, 82–84. Singer, R. N. (1988). Strategies and metastrategies in learning and performing self-paced athletic skills. Sport Psychologist, 2, 49–68. Totsika, V., & Wulf, G. (2003). The influence of external and internal foci of attention on transfer to novel situations and skills. Research Quarterly Exercise and Sport, 74, 220–225. Vance, J., Wulf, G., Töllner, T., McNevin, N. H., & Mercer, J. (2004). EMG activity as a function of the performers’ focus of attention. Journal of Motor Behavior, 36, 450–459. Voigt, E. (1933). Über den Aufbau von Bewegungsgestalten [About the organization of movement ‘‘Gestalts”]. Neue Psychologische Studien, 12, 1–45. Wan, C. Y., & Huon, G. F. (2005). Performance degradation under pressure in music: An examination of attentional processes. Psychology of Music, 33, 155–172. Wickens, C. D., & McCarley, J. S. (2008). Applied attention theory. Boca Raton, FL: CRC Press. Willingham, D. B. (1998). A neurophysiological theory of motor skill learning. Psychological Review, 105, 558–584. Willingham, D. B. (1999). The neural basis of motor skill learning. Current Directions in Psychological Science, 8, 177–182. Wulf, G., Höß, M., & Prinz, W. (1998). Instructions for motor learning: Differential effects of internal versus external focus of attention. Journal of Motor Behavior, 30, 169–179. Wulf, G., Landers, M., Lewthwaite, R., & Töllner, T. (2009). External focus instructions reduce postural instability in individuals with Parkinson disease. Physical Therapy, 89, 162–168. Wulf, G., Lauterbach, B., & Toole, T. (1999). Learning advantages of an external focus in golf. Research Quarterly for Exercise and Sport, 70, 120–126. Wulf, G., McNevin, N. H., Fuchs, T., Ritter, F., & Toole, T. (2000). Attentional focus in complex motor skill learning. Research Quarterly for Exercise and Sport, 71, 229–239. Wulf, G., & Prinz, W. (2001). Directing attention to movement effects enhances learning: A review. Psychonomic Bulletin & Review, 8, 648–660. Wulf, G., & Shea, C. H. (1999). Enhancing motor learning through external-focus instructions and feedback. Human Movement Science, 18, 553–571. Wulf, G., Shea, C. H., & Park, J. H. (2001). Attention in motor skill learning: Preferences for and advantages of an external focus. Research Quarterly for Exercise and Sport, 72, 335–344. Wulf, G., & Su, J. (2007). External focus of attention enhances golf shot accuracy in beginners and experts. Research Quarterly for Exercise and Sport, 78, 384–389. Wulf, G., Wächter, S., & Wortmann, S. (2003). Attentional focus in motor skill learning: Do females benefit from an external focus. Women in Sport and Physical Activity Journal, 12, 37–52. Wulf, G., & Weigelt, C. (1997). Instructions about physical principles in learning a complex motor skill: To tell or not to tell. . .. Research Quarterly for Exercise and Sport, 68, 362–367. Wulf, G., Zachry, T., Granados, C., & Dufek, J. S. (2007). Increases in jump-and-reach height through an external focus of attention. International Journal of Sport Science and Coaching, 2, 275–282. Zachry, T., Wulf, G., Mercer, J., & Bezodis, N. (2005). Increased movement accuracy and reduced EMG activity as a result of adopting an external focus of attention. Brain Research Bulletin, 67, 304–309.
