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OPEN

Modulation of sensorimotor
cortical oscillations in athleteswith yips
Tatsunori Watanabe1,2*, Kiyoshi Yoshioka3, Kojiro Matsushita4 & Shin Ishihara5
The yips, an involuntary movement impediment that affects performance in skilled athletes, iscommonly described as a form of task-specific focal dystonia or as a disorder lying on a continuumwith focal dystonia at one end (neurological) and chocking under pressure at the other (psychological).
However, its etiology has been remained to be elucidated. In order to understand sensorimotor
cortical activity associated with this movement disorder, we examined electroencephalographic
oscillations over the bilateral sensorimotor areas during a precision force task in athletes with yips,
and compared them with age-, sex-, and years of experience-matched controls. Alpha-band eventrelated desynchronization (ERD), that occurs during movement execution, was greater in athlete withyips as compared to controls when increasing force output to match a target but not when adjusting
the force at around the target. Event-related synchronization that occurs after movement termination
was also greater in athletes with yips. There was no significant difference in task performance between
groups. The enhanced ERD is suggested to be attributed to dysfunction of inhibitory system orincreased allocation of attention to the body part used during the task. Our findings indicate that
sensorimotor cortical oscillatory response is increased during movement initiation in athletes withyips.
Loss of motor skills in professional athletes can have consequences for their career. Even in experienced amateur
athletes, it could lead to deprivation of enjoyment of the skillful sport activity. The yips is one of those motor
phenomena that have a large impact on performance of athletes and was first defined as an involuntary movement affecting golfers with low handicaps during putting or c­ hipping1. With recent evidence showing the yips
in other ­sports2–4, however, it was redefined as “a psycho-neuromuscular impediment affecting the executionof fine motor skills during sporting performance”5,6, characterized by twitches, jerks, freezing, and tremors of aplanned movement. Although the yips has been reported to be observed in a relatively large number of golfers(17–48%)1,7,8 and has been apparent in athletes in other s­ ports2–4, its scientific research has been scarce so far.
The etiology of the yips is thought to be multifactorial and has been remained unclear. The most well-known
explanation is a continuum model proposed by Smith and ­colleagues7,9. In this model, the yips is placed on acontinuum between task-specific focal dystonia (neurological) and choking under pressure (psychological). The
task-specific focal dystonia is a movement disorder characterized by abnormal posturing and tremors during
motor ­tasks10, and well-recognized task-specific focal dystonia includes writer’s cramp and musician’s ­dystonia11.
Meanwhile, choking under pressure is defined as a perceived insufficiency in the individual resources to meetsituational demands occurring due to increased ­anxiety12. Athletes suffering from the yips are considered toreside somewhere on the ­continuum7,9, although the exact location is hardly determined. On the other hand,some other research argues that the yips is a task-specific form of focal dystonia that is worsened by psychological­elements13, or that psychological elements are triggering factors for the task-specific focal dystonia or the ­yips14.
Contradictory results in studies examining psychological profiles in athletes with y­ ips5,13,15–17 and the existenceof symptoms similar to task-specific focal dystonia (e.g., co-contraction) may support this a­ rgument15,18.
The pathophysiological mechanisms of task-specific focal dystonia are not completely understood, but oneof the most promising to explain it is dysfunction of inhibitory system as evidenced in several neurophysiological studies. For example, functional magnetic resonance imaging (fMRI) and positron emission tomography
studies have reported that focal dystonia was associated with hyperactivity of motor-related cortical a­ reas19–21.
1

Department of Sensorimotor Neuroscience, Graduate School of Biomedical and Health Sciences, Hiroshima
University, Hiroshima, Japan. 2Department of Physical Therapy, Nagoya University Graduate School of Medicine,
Nagoya, Japan. 3Institute for Research on Productive Aging, Kobe, Japan. 4Department of Mechanical Engineering,
Faculty of Engineering, Gifu University, Gifu, Japan. 5Havana Trainers Room, Tokyo, Japan. *email: twatan@
hiroshima-u.ac.jp
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NumberAgeSport

Years exp

Affected side

Affected movement

124

Baseball

12

Right

Throw

Years affected
5

2

20

Baseball

11

Right

Throw

7
16

3

35

Baseball

28

Right

Throw

4

33

Baseball

9

Right

Throw

5

5

30

Baseball

10

Right

Throw

2

6

30

Baseball

20

Right

Throw

11

7

25

Baseball

12

Right

Throw

10

8

21

Baseball

16

Right

Throw

6

9

19

Baseball

10

Right

Throw

2

10

21

Badminton

10

Right

Serve

3

Table 1.  Characteristics of athletes with yips.

Furthermore, in transcranial magnetic stimulation (TMS) studies, motor cortical excitability was increased, andshort intracortical inhibition was reduced in individuals with task-specific focal d­ ystonia22–26. The reduced inhibition has been proposed to impair surrounded inhibition, a mechanism whereby activations of task-irrelevantmuscles are actively inhibited during a motor t­ ask27. In contrast to these consistent brain imaging and TMS
studies’ outcomes, findings regarding cortical oscillatory activity have been equivocal. For instance, using aself-paced movement task, Deuschl and colleagues showed that movement-related cortical potential (MRCP)
preceding the movement was reduced over the central area in individuals with task-specific focal ­dystonia28.
Also, Toro and colleagues reported that event-related desynchronization (ERD) of 20–30 Hz band oscillations
over the central areas, which can reflect activation of the sensorimotor ­area29, was smaller just prior to and justafter the time of self-paced movement onset in focal dystonia ­group30. Similarly, beta-band oscillatory power
decrease was shown to be reduced during movements in individuals with task-specific focal d­ ystonia31. On theother hand, Yazawa and colleagues demonstrated that MRCP preceding a self-paced voluntary contraction was
greater over the ipsilateral central area in focal dystonia than control g­ roup32. Furthermore, Tseng and colleagues
showed that sensorimotor beta-band event-related synchronization (ERS) following a self-paced finger movement termination, which can reflect inhibition of the motor ­cortex33, was smaller in focal dystonia than control
group whereas beta-band ERD following the movement onset was not ­different34. Nevertheless, current evidence
suggests abnormal sensorimotor cortical activity in individuals with task-specific focal dystonia. However, it iscurrently unknown whether cortical oscillatory activity in athletes with yips is different from those without yips.
Accordingly, in this study we compared the ERD/ERS during a fine force control task between athletes withand without yips. We hypothesized that: (1) alpha/beta-band ERD would be exaggerated when attempting toprecisely control force in athletes with yips, (2) alpha/beta-band ERS following the termination of force control
would be diminished in athletes with yips, and (3) modulations in these oscillatory activities would be greater
when higher precision is required.

Methods
Subjects.

In this cross-sectional study, ten athletes with yips (mean age = 25.8 ± 5.8 years, all male) and tenage-, sex-, and years of experience-matched controls (mean age = 24.4 ± 5.1 years) participated in the experiment. The yips was defined as “an involuntary movement impeding athletic performance that had been proficient and automated through practice,” and its presence was confirmed by two of the authors (one sport trainer
and one physical therapist) who have more than 10 years of experience treating athletes with yips, as there
is no conclusive diagnostic ­test15. Characteristics of the participants are shown in Table 1. None of them wasunder treatment at the time of experiment. Exclusion criterion was a history of psychiatric and neurologicaldisorders other than the yips. All participants had normal or corrected-to-normal vision and were right-handed
by self-report. Each subject provided written informed consent prior to the study. This study was approved by
the ethics committee of Nagoya University and conducted in accordance with the Declaration of Helsinki, andfollowed STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) guidelines. Also,
this trial was registered with the University Hospital Medical Information Network Clinical Trials Registry as
UMIN000042062 (date of registration: 09/10/2020).

Experimental procedure. The subject sat on a chair in front of a table on which a PC monitor was set (eyeto monitor distance of 0.6 m) and was asked to lateral-pinch grip a force transducer (Tech Gihan, Kyoto, Japan)
using the thumb and index finger. The subjects with yips used the affected side, and the control subjects used theside that was used in playing his sport (right for all subjects).
Prior to an experimental task, we determined maximal voluntary isometric force (MVF). The subject gradually increased force over 3 s and kept maximum for 2–3 s. Verbal encouragement to make maximum effort wasprovided to the subject. The highest force over three contraction trials was adopted as the MVF.
The experimental task was similar to that in our previous ­study35. During the task, three horizontal parallelbars were displayed on the PC monitor (Fig. 1). One of them moved horizontally in real time according to thecontraction force produced by the subject (force bar). The other two bars, that were separated by the length of
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Figure 1.  Visual gain manipulation and schema of experimental setup and paradigm. The spatial amplitude ofvisual feedback was larger at higher visual gain (A). The subject produced force to place the blue bar between
two green bars as accurately and steadily as possible and stopped contraction when color of these bars turnedred (B). The bars were red for 5 s and green for 3 s. Event-related de/synchronization was computed using abaseline interval of − 1500 to − 500 ms with respect to force onset (C).
the smaller side of the bar, stayed at the same position (target bars). Color of these target bars changed between
green and red. The subject was asked to begin producing force as soon as the target bars turned green and toplace the blue force bar between two target bars as accurately and steadily as possible. He was required to stop
producing force as soon as the target bars turned red. The target bars were green for 3 s and red for 5 s, and thetarget force level was set at 15% MVF. A customized LabVIEW program (National Instruments, Austin, TX,
USA) was used to display the bars and collect 20 Hz low-pass filtered force data.
We adjusted the level of precision required in the task by manipulating visual gain (Fig. 1). It was done bychanging the height of the force fluctuation on the monitor, as the eye-to-monitor distance remained constant.
One could see small deviations from the target with the higher visual gain, requiring the higher precision. We
computed the visual angle using the following e­ quation35–40:
 h,visual angle = 2 tan−1dwhere h is half of the force fluctuation, and d is the eye-to-monitor distance. In this study we used visual gainsof 0.05° and 1.20°, because behavioral force parameters were shown to be mainly different between below andabove 1°41.
Each subject performed three blocks of 20 trials at each visual gain, and a sufficient rest was provided between
blocks.

Electroencephalography measurements. Electroencephalography (EEG) was recorded at a sampling

rate of 500 Hz using active electrodes (Polymate Mini AP108, Miyuki Giken, Tokyo, Japan). The electrodes wereplaced at C3 and C4 according to the international 10–20 system. The ground and reference electrodes werelocated at the forehead and left earlobe, respectively. During the experimental task, the subject was asked tokeep their eyes on the target bars and also to avoid unnecessary eye movements to reduce artifacts. The electrical
impedance was kept below 10 kΩ.

Data analysis. Data analysis was similar to that in our previous ­study35 and was completed in Matlab (Math-

Works, MA, USA). The force data were low-pass filtered at 15 Hz (4th-order Butterworth filter) and converted to
the rate of force change (N/s). The force onset and offset were defined as the first time point at which the rate offorce change (increase in force) reached above 10 N/s after the target bars turned green (start cue) and the firsttime point at which the rate of force change (decrease in force) reached below 10 N/s after the target bars turnedred (end cue), respectively. To include trials during which the task was performed as instructed and to remove
trials with accidental contraction during the rest period, we excluded following trials from the subsequent analysis: (1) trials with force onset below 100 ms or above 1000 ms, (2) trials with force offset below 100 ms or above
1000 ms, and (3) force generation (> 10 N/s) during a period of 4000 ms from 1000 to 5000 ms with respect tothe end cue. 46 trials (0.019%) were excluded from the following analysis.
We calculated mean force error (MFE) in percent MVF and coefficient of variation (CV) of force during thelast 1000 ms of the contraction period, considering the transition phase from the force onset to the time of theexerted force being stable around the target force l­ evel35.

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Figure 2.  Grand average event-related spectral perturbation at C3 electrode. Dashed vertical line presents
force onset. The color scale indicates the relative change from a baseline (− 1500 to − 500) in decibel (dB), with
red being positive values and blue negative values. The last column indicates the area of statistically significant
difference between groups, and the last row indicates the area of statistically significant difference between low
and high visual gains (p < 0.05 with FDR correction, shown in brown). The plot at the bottom right presents thestatistically significant interaction between group and visual gain. The red and blue squares indicate the force
increase phase and force control phase, respectively.
EEG data were analyzed using EEGLAB (http://​sccn.​ucsd.​edu/​eeglab/)42. They were first band-pass filtered
between 1 and 45 Hz and then divided into epochs. The epoch window was defined as − 2000 to 6000 ms withrespect to the force onset. We removed epochs contaminated with electrical activity exceeding ± 100 μV. Eventrelated spectral perturbation (ERSP) was computed between 3 and 45 Hz using Morlet wavelet transforms with
3 cycles at the lowest frequency and 9 cycles at the highest frequency. The values were normalized to a baseline,
which was defined as − 1500 to − 500 ms with respect to force onset, and expressed in decibel (dB) units.

Statistical analysis. The effects of group (yips vs. control) and visual gain (low vs. high) on ERD/ERS were
evaluated using a bootstrap method within ­EEGLAB43. This analysis was performed for C3 and C4 electrodes
separately. False discovery rate (FDR) correction was applied to correct for multiple c­ omparisons44. Behavioral
variables (MFE and CV) were analyzed with R (R Development Core Team). They were entered into a mixeddesign analysis of variance (ANOVA) to examine the effects of group and visual gain. The data were log-transformed when not normally distributed. A significant level was set at α < 0.05.

Results

Event‑related spectral perturbation. Grand average ERSP time–frequency plots at C3 and C4 electrodes are presented in Figs. 2 and 3, respectively. ERD is presented with negative values (blue) while ERS ispresented with positive values (red). At both electrodes, ERD can be observed in the alpha to beta range after
force onset, which was followed by ERS in the same range after force offset. The last column shows the area of
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Figure 3.  Grand average event-related spectral perturbation at C4 electrode. Dashed vertical line presents
force onset. The color scale indicates the relative change from a baseline (− 1500 to − 500) in decibel (dB), with
red being positive values and blue negative values. The last column indicates the area of statistically significant
difference between groups, and the last row indicates the area of statistically significant difference between low
and high visual gains (p < 0.05 with FDR correction, shown in brown). The plot at the bottom right presents thestatistically significant interaction between group and visual gain. The red and blue squares indicate the force
increase phase and force control phase, respectively.
significant differences in ERD/ERS between athletes with yips and controls (group effect). The last row shows thearea of significant differences in ERD/ERS between low and high visual gains (visual gain effect). Their interaction is presented at the bottom right. Comparison of ERSP at C3 electrode between groups revealed that the yips
group showed a significantly greater alpha-band ERD in the early phase of task during which force was increased
to match the target force level (force increase phase) at both low and high visual gain conditions. This difference
was mostly absent in the later phase during which force was controlled around the target force level (force control phase). Also, they showed a significantly greater ERS in alpha and/or beta bands after force offset at both low
and high visual gain conditions as compared to controls. When compared between two visual gains, beta-band
ERD during the force control phase and alpha/beta-band ERS following the force offset were significantly greaterat high than low visual gain in both groups. There was no significant interaction between group and visual gain.
Similar significant differences were present for data at C4 electrode.

Behavioral parameters. Figure 4 shows results of MFE and CV of force. A mixed-design ANOVA revealed
a main effect of task for the MFE (F(1,18) = 56.2, p < 0.001, η2 = 0.52) and also for the CV of force (F(1,18) = 9.7,
p = 0.01, η2 = 0.065). There was no significant main effect of group or interaction between group and visual gain.

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Figure 4.  Box plots of mean force error (MFE) and coefficient of variation (CV) of force. The median andinterquartile ranges are presented with whiskers representing the maximum and minimum values. Small circles
show outliners. The daggers indicate a significant main effect of visual gain.

Discussion

This study compared event-related sensorimotor cortical oscillatory activity during a precision force control
task between athletes with yips and age-, sex-, and years of experience-matched controls. We found that alphaband ERD over the ipsilateral and contralateral sensorimotor areas was greater during the force increase phase(movement initiation) in yips than control group, regardless of the precision level required in the task. There
was no apparent difference in ERD during the force control phase (controlling force around the target force
level). Furthermore, alpha/beta-band ERS following force offset was greater in yips than control group. Thesefindings suggest alteration of sensorimotor cortical oscillatory activity in a task requiring fine motor control inathletes with yips.
Alpha and beta-band ERD has been consistently reported to reflect increased activation of the sensorimotor
cortical areas during preparation or execution of m
­ ovements29,33,35,45. Furthermore, an increase in ERD was found
to reflect increased corticospinal excitability and reduced intracortical inhibition in a TMS ­study46. Thus, ourfinding of enhanced alpha-band ERD could indicate that sensorimotor cortical activity as well as corticospinal
excitability were increased while intracortical inhibition was reduced particularly when increasing force tomatch the target level force in athletes with yips. This is in line with previous brain imaging and TMS studies reporting increased motor cortical excitability and decreased intracortical inhibitory system in individuals
with task-specific focal d­ ystonia19–26. Particularly, Sohn and Hallett found an increase in amplitude of motorevoked potential recorded from the little finger muscle just after index finger movement onset (3–80 ms after
electromyographic onset) in individuals with focal hand d­ ystonia25. Also, intracortical inhibition was found to
be impaired during movement initiation. Specifically, in a rhythmic index finger flexion task, control subjects
showed a decrease in intracortical inhibition acting on the index finger and an increase in intracortical inhibition on the thumb muscle during the electromyographic burst; however, these modulations were not observedin individuals with focal hand d­ ystonia24. Moreover, in the following study that used a force control task with
the index finger, individuals with focal hand dystonia showed a reduced intracortical inhibition on the thumbmuscle during movement initiation but not during tonic ­contraction22. Hence, the increased ERD in athleteswith yips may be attributed to the reduced intracortical inhibition acting on task-irrelevant muscles. However,
it is currently unclear whether the yips is a pure form of task-specific focal dystonia, although some researchargues that it ­is13,14. Further studies are needed to better understand the neurophysiological mechanisms behindthe yips and whether or not it is on a spectrum of task-specific focal dystonia. In any case, the cortical oscillatory
response is enhanced during movement initiation in athletes with yips.
The important question to ask here is “why the difference in ERD was observed mainly in alpha band,” eventhough both alpha- and beta-band rhythms were desynchronized more or less similarly. One potential explanation is a relatively stronger association of the alpha-band oscillatory activity with motor cortical excitation andinhibition. Specifically, Sauseng and colleagues examined cortical oscillatory activity immediately before applying
a TMS pulse over the motor cortex and found that motor evoked potential was elicited more easily when alphaband power over the sensorimotor cortex was ­lower47. No such effect was observed for the other frequency bands(delta, theta, beta, or gamma). Also, alpha-band activity over the bilateral sensorimotor cortices was found toincrease when a planned movement was required to be ­suppressed48. Again, this effect was highly frequency-band
specific. It is, therefore, possible that the motor cortical alteration of athletes with yips was mainly reflected byalpha-band activity. Another possible explanation for this band specificity is voluntary attention to the body partthat is used during task performance, as a growing body of evidence shows that alpha-band activity decreases
in task-related cortical areas to facilitate sensory processing and increase in task-unrelated areas to suppress
distracting inputs. For instance, it is well-known and established that voluntary orientation of visuo-spatial attention is accompanied by a decrease in occipital alpha-band a­ ctivity49,50. In a similar manner, voluntarily orienting
attention to a body part has been reported to decrease alpha-band activity over the somatosensory ­areas51,52. It
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can, hence, be hypothesized that greater alpha-band ERD observed in the present study was ascribed to voluntaryorientation of attention to the index finger and thumb during the precision force control task, in order to facilitate
top-down control. This hypothesis further seems to be in line with reinvestment theory recently proposed to
explain the etiology of the ­yips16,17,53. In the course of motor skill learning, performance will become more andmore stable and turn into automatic control; however, when modifications of acquired motor skill are required
because of various intrinsic and extrinsic factors (e.g., injury and change in technic or equipment), s/he needs toprovoke reinvestment, an attempt to change the stable and automatic motor skill by consciously controlling own
movement with the use of explicit knowledge (i.e., breaking down the automatic motor skill into smaller chunks
as in the early learning stage)10,53,54: this attempt could result in a state where the acquired motor skill is vulnerable to disruption, and repeated attempts of unsuccessful performance can consolidate a deteriorated movement­control10,53. This theory is supported by results of a previous questionnaire study showing a tendency in athleteswith yips to consciously control their ­movements1. Yet, it is also possible that the athletes begin to consciously
control their movements to prevent an error after acquisition of the yips. Nevertheless, the increase in alpha-band
ERD could have been driven by a greater degree of conscious movement control by allocating the attention to
the body part used for the task. How reinvestment is involved in the yips appears to need further investigations.
In addition to the increased ERD, we found that post-movement ERS was greater in athletes with yips ascompared to controls. The post-movement ERS has been considered to reflect an active inhibition of the motor
cortex and its related networks following the termination of m
­ ovement55–57, and a previous study has reported
that the ERS tended to be greater after complex than simple m­ ovements58. Thus, although there was no difference in task performance between yips and control groups, the fine force control task could have been difficult
for athletes with yips, and they might have devoted the greater effort to the task, consequently resulting in thegreater post-movement ERS. However, we did not find a difference in the ERD during the force control phasebetween two groups, which contradicts previous studies’ finding of greater ERD in a more complex ­task35,58,59.
Moreover, because the purpose of this study was to examine the cortical oscillatory activity during a fine motortask, we did not adopt a motor task that induces the yips, in order to control the movement during the task(e.g., force and postural position), similar to previous studies on task-specific focal ­dystonia22,26,30,32. This could
underlie the insignificant difference in the task performance and have possibly obscured the potential differencein the cortical activity during the force control phase. The occurrence of the yips is highly movement specificand is dependent on the situation (e.g., competition), which makes it difficult to record neurophysiological data
during the affected movements while controlling for confounding factors (e.g., movement). This issue needs tobe resolved in future studies with technological progress to advance knowledge of the yips.
In regards to the effect of visual gain, we found that beta-band ERD/ERS was greater during high than low visual gain condition for both yips and control groups. At the higher visual gain, the subject can see force deviations
from a target more clearly, and this consequently forces the subject to control the force more precisely. Similar toprevious ­studies35,59, the increase in task demands most likely enhanced the motor cortical oscillatory response.
The yips has received considerable attention recently as famous professional athletes not only in golf but also
in other sports, such as baseball, basketball, and tennis, have confessed that they have suffered from the yips atsome point during their career. However, because clinical data are limited to few case ­studies60,61, evidence-based
treatment for the yips has not been established yet. Although further studies are necessary, our findings indicatethat athletes with yips may benefit from avoiding allocating too much attention to the affected movements andalso from learning such strategies. Real-time visual feedback of cortical activity may help the learning process.
In addition, non-invasive brain stimulation to modulate the intracortical inhibitory ­system62 may be applicableto the yips. Nonetheless, randomized clinical trials are essential for the valid assessment of treatments and thus
needed to improve the evidence regarding the treatment of the yips.
There are several limitations that should be acknowledged. First, we used only two electrodes to record EEG
over the sensorimotor areas. Recording and analysis of high-density EEG could have strengthened our discussion,
especially on the conscious top-down control of movements (e.g., frontal lobe). Second, only an affected hand
was examined in this study, and data during the task using a hand contralateral to the affected side may haveprovided additional information. Future studies need to clarify brain activity associated with the contralateral
hand movements. Third, although the occurrence of the yips is highly movement specific and is dependent on
the situation, recording of electromyogram may have clarified abnormal muscle activity during the task. Finally,
subjects of this study were baseball and badminton players; therefore, the findings may not be generalized togolfers or athletes in other sports (e.g., runners).
To sum up, our findings indicate alteration of sensorimotor cortical oscillations during precision force control
in athletes with yips. Especially, alpha-band ERD was greater in these individuals than controls when increasing force output to match a target but not when adjusting the force at around the target. The enhanced ERD issuggested to be attributed to dysfunction of inhibitory system or increased allocation of attention to the bodypart used during the task. Our findings provide new evidence that sensorimotor cortical oscillatory response isincreased particularly during movement initiation in athletes with yips.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding
author on reasonable request.
Received: 6 October 2020; Accepted: 5 May 2021

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References

1. McDaniel, K. D., Cummings, J. L. & Shain, S. The, “yips”: A focal dystonia of golfers. Neurology 39, 192–195 (1989).
2. Le Floch, A. et al. Table tennis dystonia. Mov. Disord. 25, 394–397. https://​doi.​org/​10.​1002/​mds.​22968 (2010).
3. Mayer, F., Topka, H., Boose, A., Horstmann, T. & Dickhuth, H. H. Bilateral segmental dystonia in a professional tennis player. Med.
Sci. Sports Exerc. 31, 1085–1087. https://​doi.​org/​10.​1097/​00005​768-​19990​8000-​00001 (1999).
4. Sitburana, O. & Ondo, W. G. Task-specific focal hand dystonia in a professional pistol-shooter. Clin. Neurol. Neurosurg. 110,
423–424. https://​doi.​org/​10.​1016/j.​cline​uro.​2007.​12.​012 (2008).
5. Clarke, P., Sheffield, D. & Akehurst, S. The yips in sport: A systematic review. Int. Rev. Sport Exerc. Psychol. 8, 156–184. https://​doi.​
org/​10.​1080/​17509​84x.​2015.​10520​88 (2015).
6. Smith, A. M. et al. A multidisciplinary study of the “yips” phenomenon in golf: An exploratory analysis. Sports Med. (Auckland,N.Z.) 30, 423–437 (2000).
7. Smith, A. M. et al. The “yips” in golf: A continuum between a focal dystonia and choking. Sports Med. (Auckland, N.Z.) 33, 13–31(2003).
8. Klampfl, M. K., Philippen, P. B. & Lobinger, B. H. Self-report vs. kinematic screening test: Prevalence, demographics, and sports
biography of yips-affected golfers. J. Sports Sci. 33, 655–664. https://​doi.​org/​10.​1080/​02640​414.​2014.​961026 (2015).
9. Stinear, C. M. et al. The yips in golf: Multimodal evidence for two subtypes. Med. Sci. Sports Exerc. 38, 1980–1989. https://​doi.​org/​
10.​1249/​01.​mss.​00002​33792.​93540.​10 (2006).
10. Sadnicka, A., Kornysheva, K., Rothwell, J. C. & Edwards, M. J. A unifying motor control framework for task-specific dystonia. Nat.
Rev. Neurol. 14, 116–124. https://​doi.​org/​10.​1038/​nrneu​rol.​2017.​146 (2018).
11. Furuya, S. & Hanakawa, T. The curse of motor expertise: Use-dependent focal dystonia as a manifestation of maladaptive changes
in body representation. Neurosci. Res. 104, 112–119. https://​doi.​org/​10.​1016/j.​neures.​2015.​12.​001 (2016).
12. Mesagno, C. & Beckmann, J. Choking under pressure: Theoretical models and interventions. Curr. Opin. Psychol. 16, 170–175.
https://​doi.​org/​10.​1016/j.​copsyc.​2017.​05.​015 (2017).
13. Sachdev, P. Golfers’ cramp: Clinical characteristics and evidence against it being an anxiety disorder. Mov. Disord. 7, 326–332.
https://​doi.​org/​10.​1002/​mds.​87007​0405 (1992).
14. Enders, L. et al. Musician’s dystonia and comorbid anxiety: Two sides of one coin?. Mov. Disord. 26, 539–542. https://​doi.​org/​10.​
1002/​mds.​23607 (2011).
15. Adler, C. H. et al. Are the yips a task-specific dystonia or “golfer’s cramp”?. Mov. Disord. 26, 1993–1996. https://​doi.​org/​10.​1002/​
mds.​23824 (2011).
16. Klampfl, M. K., Lobinger, B. H. & Raab, M. How to detect the yips in golf. Hum. Mov. Sci. 32, 1270–1287. https://d​ oi.o​ rg/1​ 0.1​ 016/j.​
humov.​2013.​04.​004 (2013).
17. Klämpfl, M. K., Lobinger, B. H. & Raab, M. Reinvestment—The cause of the yips?. PLoS ONE 8, e82470. https://​doi.​org/​10.​1371/​
journ​al.​pone.​00824​70 (2013).
18. Adler, C. H., Crews, D., Hentz, J. G., Smith, A. M. & Caviness, J. N. Abnormal co-contraction in yips-affected but not unaffected
golfers: Evidence for focal dystonia. Neurology 64, 1813–1814. https://​doi.​org/​10.​1212/​01.​Wnl.​00001​62024.​05514.​03 (2005).
19. Pujol, J. et al. Brain cortical activation during guitar-induced hand dystonia studied by functional MRI. Neuroimage 12, 257–267.
https://​doi.​org/​10.​1006/​nimg.​2000.​0615 (2000).
20. Haslinger, B., Altenmüller, E., Castrop, F., Zimmer, C. & Dresel, C. Sensorimotor overactivity as a pathophysiologic trait of embouchure dystonia. Neurology 74, 1790–1797. https://​doi.​org/​10.​1212/​WNL.​0b013​e3181​e0f784 (2010).
21. Lerner, A. et al. Regional cerebral blood flow correlates of the severity of writer’s cramp symptoms. Neuroimage 21, 904–913.
https://​doi.​org/​10.​1016/j.​neuro​image.​2003.​10.​019 (2004).
22. Beck, S. et al. Short intracortical and surround inhibition are selectively reduced during movement initiation in focal hand dystonia.
J. Neurosci. 28, 10363–10369. https://​doi.​org/​10.​1523/​jneur​osci.​3564-​08.​2008 (2008).
23. Beck, S., Schubert, M., Richardson, S. P. & Hallett, M. Surround inhibition depends on the force exerted and is abnormal in focal
hand dystonia. J. Appl. Physiol. (Bethesda, Md.: 1985) 107, 1513–1518. https://​doi.​org/​10.​1152/​jappl​physi​ol.​91580.​2008 (2009).
24. Stinear, C. M. & Byblow, W. D. Impaired modulation of intracortical inhibition in focal hand dystonia. Cereb. Cortex 14, 555–561.
https://​doi.​org/​10.​1093/​cercor/​bhh017 (2004).
25. Sohn, Y. H. & Hallett, M. Disturbed surround inhibition in focal hand dystonia. Ann. Neurol. 56, 595–599. https://d​ oi.o​ rg/1​ 0.1​ 002/​
ana.​20270 (2004).
26. Houdayer, E., Beck, S., Karabanov, A., Poston, B. & Hallett, M. The differential modulation of the ventral premotor–motor interaction during movement initiation is deficient in patients with focal hand dystonia. Eur. J. Neurosci. 35, 478–485. https://​doi.​org/​10.​1111/j.​1460-​9568.​2011.​07960.x (2012).
27. Beck, S. & Hallett, M. Surround inhibition in the motor system. Exp. Brain Res. 210, 165–172. https://​doi.​org/​10.​1007/​s00221-​
011-​2610-6 (2011).
28. Deuschl, G., Toro, C., Matsumoto, J. & Hallett, M. Movement-related cortical potentials in writer’s cramp. Ann. Neurol. 38, 862–868.
https://​doi.​org/​10.​1002/​ana.​41038​0606 (1995).
29. Pfurtscheller, G. & Lopes da Silva, F. H. Event-related EEG/MEG synchronization and desynchronization: Basic principles. Clin.
Neurophysiol. 110, 1842–1857. https://​doi.​org/​10.​1016/​s1388-​2457(99)​00141-8 (1999).
30. Toro, C., Deuschl, G. & Hallett, M. Movement-related electroencephalographic desynchronization in patients with hand cramps:
Evidence for motor cortical involvement in focal dystonia. Ann. Neurol. 47, 456–461 (2000).
31. Kristeva, R. et al. Electroencephalographic spectral power in writer’s cramp patients: Evidence for motor cortex malfunctioning
during the cramp. Neuroimage 27, 706–714. https://​doi.​org/​10.​1016/j.​neuro​image.​2005.​05.​004 (2005).
32. Yazawa, S. et al. Abnormal cortical processing of voluntary muscle relaxation in patients with focal hand dystonia studied by
movement-related potentials. Brain 122(Pt 7), 1357–1366. https://​doi.​org/​10.​1093/​brain/​122.7.​1357 (1999).
33. Salmelin, R., Hämäläinen, M., Kajola, M. & Hari, R. Functional segregation of movement-related rhythmic activity in the humanbrain. Neuroimage 2, 237–243. https://​doi.​org/​10.​1006/​nimg.​1995.​1031 (1995).
34. Tseng, Y. J., Chen, R. S., Hsu, W. Y., Hsiao, F. J. & Lin, Y. Y. Reduced motor cortex deactivation in individuals who suffer fromwriter’s cramp. PLoS ONE 9, e97561. https://​doi.​org/​10.​1371/​journ​al.​pone.​00975​61 (2014).
35. Watanabe, T., Mima, T., Shibata, S. & Kirimoto, H. Midfrontal theta as moderator between beta oscillations and precision control.
Neuroimage 235, 118022. https://​doi.​org/​10.​1016/j.​neuro​image.​2021.​118022 (2021).
36. Watanabe, T., Nojima, I., Mima, T., Sugiura, H. & Kirimoto, H. Magnification of visual feedback modulates corticomuscular andintermuscular coherences differently in young and elderly adults. Neuroimage 220, 117089. https://​doi.​org/​10.​1016/j.​neuro​image.​2020.​117089 (2020).
37. Watanabe, T., Nojima, I., Sugiura, H., Yacoubi, B. & Christou, E. A. Voluntary control of forward leaning posture relates to lowfrequency neural inputs to the medial gastrocnemius muscle. Gait Posture 68, 187–192. https://​doi.​org/​10.​1016/j.​gaitp​ost.​2018.​
11.​026 (2019).
38. Coombes, S. A., Corcos, D. M., Sprute, L. & Vaillancourt, D. E. Selective regions of the visuomotor system are related to gaininduced changes in force error. J. Neurophysiol. 103, 2114–2123. https://​doi.​org/​10.​1152/​jn.​00920.​2009 (2010).

Scientific Reports |Vol:.(1234567890)(2021) 11:10376 |https://doi.org/10.1038/s41598-021-89947-1

8

www.nature.com/scientificreports/
39. Watanabe, T., Saito, K., Ishida, K., Tanabe, S. & Nojima, I. Age-related declines in the ability to modulate common input to bilateraland unilateral plantar flexors during forward postural lean. Front. Hum. Neurosci. 12, 254. https://​doi.​org/​10.​3389/​fnhum.​2018.​
00254 (2018).
40. Watanabe, T., Saito, K., Ishida, K., Tanabe, S. & Nojima, I. Coordination of plantar flexor muscles during bipedal and unipedal
stances in young and elderly adults. Exp. Brain Res. 236, 1229–1239. https://​doi.​org/​10.​1007/​s00221-​018-​5217-3 (2018).
41. Vaillancourt, D. E., Haibach, P. S. & Newell, K. M. Visual angle is the critical variable mediating gain-related effects in manualcontrol. Exp. Brain Res. 173, 742–750. https://​doi.​org/​10.​1007/​s00221-​006-​0454-2 (2006).
42. Delorme, A. & Makeig, S. EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent
component analysis. J. Neurosci. Methods 134, 9–21. https://​doi.​org/​10.​1016/j.​jneum​eth.​2003.​10.​009 (2004).
43. Maris, E. & Oostenveld, R. Nonparametric statistical testing of EEG- and MEG-data. J. Neurosci. Methods 164, 177–190. https://​doi.​org/​10.​1016/j.​jneum​eth.​2007.​03.​024 (2007).
44. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat.
Soc. Ser. B Stat. Methodol. 57, 289–300. https://​doi.​org/​10.​1111/j.​2517-​6161.​1995.​tb020​31.x (1995).
45. Miller, K. J. et al. Spectral changes in cortical surface potentials during motor movement. J. Neurosci. 27, 2424–2432. https://​doi.​
org/​10.​1523/​jneur​osci.​3886-​06.​2007 (2007).
46. Takemi, M., Masakado, Y., Liu, M. & Ushiba, J. Event-related desynchronization reflects downregulation of intracortical inhibitionin human primary motor cortex. J. Neurophysiol. 110, 1158–1166. https://​doi.​org/​10.​1152/​jn.​01092.​2012 (2013).
47. Sauseng, P., Klimesch, W., Gerloff, C. & Hummel, F. C. Spontaneous locally restricted EEG alpha activity determines corticalexcitability in the motor cortex. Neuropsychologia 47, 284–288. https://​doi.​org/​10.​1016/j.​neuro​psych​ologia.​2008.​07.​021 (2009).
48. Sauseng, P., Gerloff, C. & Hummel, F. C. Two brakes are better than one: The neural bases of inhibitory control of motor memory
traces. Neuroimage 65, 52–58. https://​doi.​org/​10.​1016/j.​neuro​image.​2012.​09.​048 (2013).
49. Thut, G., Nietzel, A., Brandt, S. A. & Pascual-Leone, A. Alpha-band electroencephalographic activity over occipital cortex indexes
visuospatial attention bias and predicts visual target detection. J. Neurosci. 26, 9494–9502. https://​doi.​org/​10.​1523/​jneur​osci.​0875-​
06.​2006 (2006).
50. Worden, M. S., Foxe, J. J., Wang, N. & Simpson, G. V. Anticipatory biasing of visuospatial attention indexed by retinotopicallyspecific alpha-band electroencephalography increases over occipital cortex. J. Neurosci. 20, Rc63. https://​doi.​org/​10.​1523/​JNEUR​
OSCI.​20-​06-​j0002.​2000 (2000).
51. Haegens, S., Luther, L. & Jensen, O. Somatosensory anticipatory alpha activity increases to suppress distracting input. J. Cogn.
Neurosci. 24, 677–685. https://​doi.​org/​10.​1162/​jocn_a_​00164 (2012).
52. Jones, S. R. et al. Cued spatial attention drives functionally relevant modulation of the mu rhythm in primary somatosensory
cortex. J. Neurosci. 30, 13760–13765. https://​doi.​org/​10.​1523/​jneur​osci.​2969-​10.​2010 (2010).
53. Sadnicka, A. et al. Task-specific dystonia: Pathophysiology and management. J. Neurol. Neurosurg. Psychiatry 87, 968–974. https://​doi.​org/​10.​1136/​jnnp-​2015-​311298 (2016).
54. Masters, R. S. & Maxwell, J. P. In Skill Acquisition in Sport: Research, Theory and Practice (eds Williams, A. M. & Hodges, N. J.)
207–228 (Routledge, 2008).
55. Alegre, M., Alvarez-Gerriko, I., Valencia, M., Iriarte, J. & Artieda, J. Oscillatory changes related to the forced termination of amovement. Clin. Neurophysiol. 119, 290–300. https://​doi.​org/​10.​1016/j.​clinph.​2007.​10.​017 (2008).
56. Solis-Escalante, T., Müller-Putz, G. R., Pfurtscheller, G. & Neuper, C. Cue-induced beta rebound during withholding of overt andcovert foot movement. Clin. Neurophysiol. 123, 1182–1190. https://​doi.​org/​10.​1016/j.​clinph.​2012.​01.​013 (2012).
57. Pfurtscheller, G., Stancák, A. Jr. & Neuper, C. Post-movement beta synchronization. A correlate of an idling motor area?. Electroencephalogr. Clin. Neurophysiol. 98, 281–293. https://​doi.​org/​10.​1016/​0013-​4694(95)​00258-8 (1996).
58. Heinrichs-Graham, E. & Wilson, T. W. Coding complexity in the human motor circuit. Hum. Brain Mapp. 36, 5155–5167. https://​doi.​org/​10.​1002/​hbm.​23000 (2015).
59. Chung, J. W., Ofori, E., Misra, G., Hess, C. W. & Vaillancourt, D. E. Beta-band activity and connectivity in sensorimotor and parietal
cortex are important for accurate motor performance. Neuroimage 144, 164–173. https://​doi.​org/​10.​1016/j.​neuro​image.​2016.​10.​008 (2017).
60. Asahi, T., Taira, T., Ikeda, K., Yamamoto, J. & Sato, S. Improvement of table tennis dystonia by stereotactic ventro-oral thalamotomy:
A case report. World Neurosurg. 99(810), e811-810.e814. https://​doi.​org/​10.​1016/j.​wneu.​2016.​12.​117 (2017).
61. Dhungana, S. & Jankovic, J. Yips and other movement disorders in golfers. Mov. Disord. 28, 576–581. https://d​ oi.o​ rg/1​ 0.1​ 002/m​ ds.​
25442 (2013).
62. Bocci, T. et al. Spinal direct current stimulation modulates short intracortical inhibition. Neuromodulation 18, 686–693. https://​doi.​org/​10.​1111/​ner.​12298 (2015).

Acknowledgements

We would like to thank study participants for their willingness and time devoted to the study and Yips Lab. Japanfor its support and cooperation during the experiment. This study was supported by Mizuno Sports Promotion
Foundation and partially by Japan Society for the Promotion of Science (20K19708).

Author contributions

T.W. designed the study, acquired, analyzed, and interpreted the data, and wrote the original draft. K.Y. acquired,analyzed, and interpreted the data. K.M. acquired and analyzed the data. S.I. acquired, analyzed, and interpreted
the data. All authors reviewed and approved the final manuscript.

Competing interests

The authors declare no competing interests.

Additional information

Correspondence and requests for materials should be addressed to T.W.
Reprints and permissions information is available at www.nature.com/reprints.
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