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Exp Brain Res (2008) 190:239–249
DOI 10.1007/s00221-008-1467-9RESEARCH ARTICLE
Response preparation changes following practice of an asymmetrical bimanual movement
Dana Maslovat · Anthony N. Carlsen · Ryu Ishimoto · Romeo Chua · Ian M. Franks
Received: 1 April 2008 / Accepted: 8 June 2008 / Published online: 1 July 2008© Springer-Verlag 2008
Abstract The purpose of the current study was to exam-ine the eVects of practice on the advance preparation of anasymmetrical bimanual movement. Participants performed170 trials of a discrete bimanual aiming movement wherethe right arm moved twice the amplitude of the left, inresponse to an auditory “go” signal. During three of the Wrstand last ten trials, the “go” signal was replaced with a star-tle (124 dB) stimulus, which is thought to trigger a preparedmovement. Startle and non-startle (control) trials from earlyand late practice were compared on various kinematic andEMG measures. Results indicated that it is possible to pre-program a bimanual asymmetrical movement, and thatadvance preparation of movement amplitude changes withpractice. Evidence was also provided that the diVerentamplitude movements were performed using similar EMGtiming between limbs, while adjusting the relative ratio ofEMG amplitude. Furthermore, learning of the taskappeared to be related to the ability to prepare the correctasymmetrical EMG amplitudes rather than changing thetiming of the EMG pattern.
Keywords Response preparation · Programming · Practice · Bimanual · Startle
Introduction
The examination of how practice aVects skill acquisitionhas provided valuable insight into what factors aVect learn-ing; however these experiments are often limited in theirevaluation of what is actually learned by the participants.Assessing changes in internal processes that lead to theimprovements in the capability to produce a skill can proveto be challenging. One way to explore these internalchanges associated with learning is to examine how prac-tice aVects the diVerent stages of information processing(i.e., stimulus identiWcation, response selection, responseprogramming). It has been hypothesized that these process-ing stages develop independently with practice, dependingon the type of task and experience of the performer (Ver-wey 1999). It would be expected that during practice of asimple reaction time task (where only one movement alter-native is performed in response to a stimulus) participantscould bypass response selection and primarily focus onresponse programming (Schmidt and Lee 2005, p. 69–74).Response programming is the process by which theresponse to the stimulus (i.e., the “program”, Young andSchmidt 1991; Schmidt et al. 1997) is prepared prior to ini-tiation. In a simple reaction time task, because the requiredresponse is known in advance, response preparation mayoccur prior to the “go” stimulus (Klapp 1996). Thus, in thecontext of learning, improvement in performance of a taskin a simple reaction time paradigm may be due to a moreaccurate response being pre-programmed. The purpose ofthe current study was to examine the eVects of practice onthe advance preparation of a movement.
A number of diVerent methodologies have beenemployed to examine response preparation and its changeswith practice. One avenue has examined reaction timechanges with practice of a multiple component movement
D. Maslovat · A. N. Carlsen · R. Ishimoto · R. Chua · I. M. Franks (&)School of Human Kinetics, War Memorial Gymnasium, University of British Columbia, 210-6081 University Boulevard, Vancouver, BC, Canada, V6T 1Z1e-mail: [email protected]
D. Maslovate-mail: [email protected]
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240 Exp Brain Res (2008) 190:239–249
(Fischman and Lim 1991; Klapp 1995). These studiesreported a decrease in reaction time with practice, whichthe authors attributed to a change in response preparationwhereby a multiple segment movement could be pre-pro-grammed as a single chunk. Another avenue has examinedpractice-related changes to the initial, ballistic portion of arapid aiming movement (Abrams and Pratt 1993; Pratt andAbrams 1996; Khan et al. 1998). These studies showed animprovement in the primary sub-movement, which is con-sidered to be pre-programmed and initiated without modiW-cations.
The methodology we chose for this experiment involvedthe implementation of a startling acoustic stimulus (SAS),which has been used to examine movement preparation.During a simple reaction time task, replacing the auditory“go” signal with a loud (>124 dB) startling stimulus hasbeen shown to elicit the required action at a much shorterlatency, with kinematics and EMG conWgurations largelyunchanged (Valls-Solé et al. 1995, 1999; Siegmund et al.2001; Carlsen et al. 2003, 2004a,b, 2007; Cressman et al.2006; MacKinnon et al. 2007). Due to dramatic shorteningof premotor reaction times (<60 ms), it has been hypothe-sized that the startle can act as a trigger for a pre-pro-grammed response, bypassing the usual voluntarycommand (Valls-Solé et al. 1999; Carlsen et al. 2004b).This hypothesis has been supported by a number of studiesshowing that startle eVects are distinct from and larger thanstimulus intensity eVects (Carlsen et al. 2007), and onlyoccur when the participant has prepared the response inadvance (Valls-Solé et al. 1999; Carlsen et al. 2004a; Roth-well 2006).
The startle paradigm has provided valuable informationregarding when advance movement preparation occurs.Previous studies have shown that pre-programming maynot occur when there is uncertainty with regards to themovement being produced, such as during a choice (Carl-sen et al 2004a) or discrimination reaction time task (Carl-sen et al. 2008a). However, advance knowledge of the to-be-performed task does not guarantee the movement can befully pre-programmed. Movements involving multiple sub-components are thought to require a sequencing componentwhich can only be completed following the “go” stimulus(Klapp 1995, 1996). Indeed, recent evidence has shown thata multiple component unimanual movement is not triggeredby a startling stimulus (Carlsen et al. 2008b). Thus the useof a SAS can act as a probe for what is pre-programmed, asfully prepared movements would be expected to be trig-gered at a shorter latency when compared to control trials(with similar movement characteristics). Furthermore, thestartle paradigm can be used as a valuable tool to examinepreparation changes during the learning process, and deter-mine if practice related changes are due to a change in pre-programming.
The task we chose was a bimanual asymmetrical move-ment, whereby each limb moved simultaneously to a targetof diVerent amplitude. While there is evidence that this typeof task can be performed without extensive training (e.g.,Kelso et al. 1979; Marteniuk and MacKenzie 1980; Mar-teniuk et al. 1984; Fowler et al. 1991; Sherwood 1991;Sherwood and Nishimura 1992; Heuer and Klein 2005,2006), it has also been shown that participants becomemore accurate with practice (Sherwood 1990, 1994; seealso Gottlieb et al. 1988). Furthermore, target-directed armmovements produce a consistent and characteristic tripha-sic EMG activation pattern (Gottlieb et al. 1989b; Latashand Gottlieb 1991) that can be prepared prior to the “go”stimulus (Wadman et al. 1979). Although advance prepara-tion has not speciWcally been examined for this type of task,it has been suggested that amplitude can be individuallypre-programmed for bimanual movements (Schmidt et al.1979; Heuer 1986, 1993). Additionally, bimanually asym-metrical movements are typically performed with a similarstart and endpoint in time (Kelso et al. 1979), therefore nosequencing should be required. Thus we predicted that thisparticular asymmetrical bimanual movement would betreated as a single component movement and fully preparedin advance of the “go” stimulus. This was investigated bycomparing control trials to those where the “go” signal wasreplaced with a SAS, to determine if the startling stimulustriggered a movement with similar characteristics at ashorter latency. We also predicted that performance of themovement would improve with practice, and we could attri-bute these improvements to changes in response prepara-tion. This was explored by comparing control and startletrials prior to, and following a number of practice trials. Ifpractice-related changes resulted in a modiWcation of thepre-programmed features (i.e., muscle activation pattern),we would expect that any diVerences in performance forcontrol trials would also be present in the startle trials.
Method
Participants
Thirteen right-handed volunteers with no obvious upperbody abnormalities or sensory or motor dysfunctions par-ticipated in the study after giving informed consent. How-ever, only data from ten right-handed volunteers (six males,four females; age 23 § 3 years) were employed in the Wnalanalysis. Three participants did not show activation in thesternocleidmastoid muscle during any startle trials (whichis thought to be the most reliable indicator of a startleresponse), and thus were excluded from the analysis (seeCarlsen et al. 2003, 2004a, 2007 for more detail regardingthe exclusion criteria for participants). All participants were
123
Exp Brain Res (2008) 190:239–249 241
naïve to the hypothesis under investigation and this studywas conducted in accordance with ethical guidelines estab-lished by the University of British Columbia.
Task and instructions
Participants sat in a height-adjustable chair in front of a 17-inch color monitor (VGA 640 £ 480 pixels, 60 Hz refresh)resting on a table. Attached to the table on each side of themonitor were lightweight manipulanda that participantsused to perform horizontal Xexion-extension movementsabout the elbow joint. Participants’ arms and hands weresecured with velcro straps to the manipulanda with theelbow joint aligned with the axis of rotation and the handspronated. The home position was a point where the elbowjoint approximated 90° for each limb and was deWned as 0°.In response to an auditory “go” signal, the participants wereasked to rapidly extend the right and left limb to targets onthe table located at 20° (right limb) and 10° (left limb)respectively.
Participants were instructed to look straight ahead at themonitor and respond by making a movement “as fast and asaccurately as possible” from the starting position and tostop at the Wnal targets. No augmented feedback was pro-vided during the trial; however following each trial termi-nal feedback was provided for 5 s on the monitor thatincluded reaction time (RT, in ms), movement time (MT, inms), and movement error (root mean squared error orRMSE, in degree). To further promote performanceimprovements during the acquisition period (see proceduresection below), terminal feedback was also providedregarding details of how the movement was performed.This was presented via Lissajous feedback superimposedover the correct movement template. Lissajous feedbackmerges the two limb movements into a single two-dimen-sional orthogonal movement. SpeciWcally, movements ofthe right manipulandum produce horizontal movements ofthe cursor on the screen while movements of the left manip-ulandum produce vertical movements of the cursor on thescreen. Thus the Lissajous template resulted in a straightline with a slope of one-half of the screen. At the end ofeach trial, participants were allowed to examine the Wnalposition of their hands, relative to the targets. To encouragefast and accurate responses, a monetary bonus was oVeredfor fast RT, MT and low RMSE scores.
Experimental design
All trials began with a warning tone consisting of a shortbeep (82 § 2 dB, 100 ms, 100 Hz), followed by a randomvariable fore period of 2–4 s, then by the imperative “go”signal. The “go” signal could either consist of a controlstimulus (82 § 2 dB, 100 ms, 1,000 Hz) or startling stimu-
lus (124 § 2 dB, 40 ms, 1,000 Hz, <1 ms rise time). Allauditory signals were generated by a computer program andwere ampliWed and presented via a loudspeaker placeddirectly behind the head of the participant. The acousticstimulus intensities were measured using a sound levelmeter (Cirrus Research model CR:252B) at a distance of 30cm from the loudspeaker (approximately the distance to theears of the participant). Testing consisted of three phases:pre-testing (10 trials), acquisition (6 blocks of 25 trials),and post-testing (10 trials). During both pre-test and post-test conditions, three of the ten trials included a startling“go” stimulus. These trials were presented in a pseudo-ran-dom order. The Wrst trial was always a control trial, andstartle trials were never presented consecutively.
Recording equipment
Surface EMG data were collected from the muscle belliesof the following superWcial muscles: right and left lateralhead of the triceps brachii (TRI—agonist), right and leftlong head of the biceps brachii (BIC—antagonist), and leftsternocleidomastoid (SCM—startle indicator) using pream-pliWed bipolar Ag/AgCl surface electrodes connected viashielded cabling to an external ampliWer system (Therapeu-tics Unlimited Inc. Model 544). Recording sites were pre-pared and cleansed in order to decrease electricalimpedance. The electrodes were oriented parallel to themuscle Wbers, and then attached using double sided adhe-sive strips. A grounding electrode was placed on the partic-ipant’s left lateral malleolus. Arm angular displacementwas measured using optical encoders (Dynapar, E20-2500-130) attached to the central axis of the manipulanda. Ana-log data were digitized in real time (LabMaster PGH) andall data were collected at a rate of 1,000 Hz and stored foroZine analysis. A custom computer program initiated datacollection 100 ms before the presentation of the “go” signaland terminated data collection 1,000 ms following the “go”signal.
Data reduction
Movement onset was deWned as the Wrst point when veloc-ity reached and remained above 0 m/s following the “go”stimulus. Final position was deWned as the Wrst point atwhich angular velocity fell below 8°/s and remained belowthis value for 100 ms. To calculate velocity, displacementdata were passed through a digital, fourth order Butterworthlowpass Wlter (cutoV frequency of 10 Hz), and then diVer-entiated. Surface EMG burst onsets were deWned as thepoint at which the EMG Wrst began a sustained rise abovebaseline levels. The location of this point was determinedby Wrst displaying the EMG pattern with a superimposedline indicating the point at which activity increased to more
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242 Exp Brain Res (2008) 190:239–249
than 2 standard deviations above baseline (mean of 100 msof EMG activity preceding the go signal). Onset was thenveriWed by visually locating and manually adjusting theonset mark to the point at which the activity Wrst increased.This method allowed for correction of errors due to thestrictness of the algorithm. EMG oVsets were marked in asimilar fashion, with the activity between EMG onset andEMG oVset being deWned as the duration of a muscle burst.Startle trials in which no detectable startle response (SCMactivity) was observed were discarded (total of 3 of 60 tri-als; see Carlsen et al. 2003, 2004b, 2007 for a more detaileddiscussion regarding the use of various startle indicators).
Dependent measures and statistical analyses
Kinematic dependent measures included MT, velocity ratioto peak velocity, and endpoint error (as a percentage oftotal movement distance). MT was deWned as the diVerencein time between movement onset and Wnal position. Veloc-ity ratio was calculated as the mean ratio of left arm to rightarm velocity between movement onset and peak velocity,which typically occurred at approximately 100 ms (M =106.5 ms, SD = 7.5 ms). This time frame was chosen toreXect the initial portion of the movement which sensoryinformation is expected to have minimal inXuence. As thetarget displacement of the left limb was half that of the rightlimb, we expected this ratio value to approach 0.5 withpractice. Finally we examined absolute error of the Wnalendpoint position for each limb as a measure of movementaccuracy. We expressed this error score as a percentage ofthe target movement amplitude. For example, a 5° error fora 10° movement would represent a 50% movement errorand a 5° error for a 20° movement would represent a 25%error. Endpoint error and MT were analyzed via a 2 time(pre-test, post-test) £ 2 type (control, startle) £ 2 arm (left,right) repeated measures analysis of variance (ANOVA).Velocity ratio was analyzed via a 2 time (pre-test, post-test)£ 2 type (control, startle) repeated measures ANOVA.
Previous work involving bimanual movements withasymmetrical amplitudes has shown that the kinematic pro-Wles of the two limbs are relatively consistent with regardsto their temporal structure (e.g., reaction time, MT, peakvelocity, peak acceleration); however the force productionis diVerent (Kelso et al. 1979; although see also Marteniukand MacKenzie 1980; Marteniuk et al. 1984; Fowler et al.1991). To examine the synchrony of the kinematic proWles,we calculated a correlation coeYcient between the velocityproWles of the two limbs from movement onset to move-ment endpoint for each trial.
To compare EMG patterns, burst onsets and durationswere calculated. The onset of the Wrst agonist burst (AG1,TRI) was measured from the time of the “go” stimulus andrepresented premotor reaction time (PMT). Onset of the
antagonist (ANT, BIC) and second agonist burst (AG2,TRI), were calculated as the time from the onset of theAG1, as this allowed for determination of the relative tim-ing of the triphasic EMG pattern. To quantify activationamplitude of the Wrst agonist burst we integrated the recti-Wed raw EMG trace (normalized to the mean peak of con-trol trial values for each participant) for the Wrst 30 ms ofthe AG1 burst (Q30, Corcos et al. 1989; Gottlieb et al.1989a; Khan et al. 1999). The Q30 measure represents theinitial slope of the agonist burst and is minimally aVectedby feedback, thus providing insight into pre-programmedagonist EMG activity. Muscle onsets, burst durations andQ30 values were analyzed independently via a 2 time (pre-test, post-test) £ 2 type (control, startle) £ 2 arm (left,right) repeated measures ANOVA.
The alpha level for the entire experiment was set at 0.05.Partial eta squared (�p
2) values are reported as a measure ofeVect size. SigniWcant results for the repeated measuresANOVAs were examined via Tukey’s honestly signiWcantdiVerence (HSD) test and simple eVects tests to determinethe locus of the diVerences.
Results
A summary of the results for all dependent measures,including mean and standard deviations, are provided inTable 1. Figure 1 shows limb displacement and EMG data(rectiWed and smoothed by 20-point averaging) for a repre-sentative post-test control trial (top) and startle trial (bot-tom). During control trials, participants performedtemporally symmetrical movements to the targets of diVer-ent distances. Although each limb moved a diVerent dis-placement, the timing of the triphasic EMG burstsremained relatively consistent between arms but the rela-tive EMG burst amplitudes were greater for the right arm.During startle trials, participants still produced a temporallysynchronous movement to diVerent distances; howeverthey typically overshot both targets. Although EMG activ-ity began at a much shorter latency for startle trials, thetemporal pattern was similar to control trials as the EMGtiming between limbs remained similar with dissimilarburst amplitudes.
Kinematics
Although participants were able to produce asymmetricalmovement amplitudes during the pre-test, they did improvetheir performance with practice. This was shown by a sig-niWcant main eVect for time in the velocity ratio betweenthe limbs [F(1, 9) = 12.66, P = 0.006, �p
2 = 0.58]. In thepost-test, both limbs moved closer to the required value of0.5 (M = 0.67), as compared to the pre-test (M = 0.81). The
123
Exp Brain Res (2008) 190:239–249 243
Tab
le1
Exp
erim
enta
l res
ults
for
eac
h st
imul
us ty
pe, a
rm a
nd te
stin
g co
ndit
ion,
sho
win
g m
eans
and
sta
ndar
d de
viat
ions
(br
acke
ted)
Not
e th
at v
eloc
ity r
atio
and
cor
rela
tion
coeY
cien
ts o
nly
have
one
val
ue f
or b
oth
limbs
AG
1 in
itial
ago
nist
bur
st (
tric
eps)
, AN
T a
ntag
onis
t bur
st (
bice
ps),
AG
2 se
cond
ago
nist
bur
st (
tric
eps)
Var
iabl
eC
ontr
ol c
ondi
tion
Sta
rtle
con
diti
on
Lef
t arm
Rig
ht a
rmL
eft a
rmR
ight
arm
Pre
-tes
tPo
st-t
est
Pre-
test
Post
-tes
tP
re-t
est
Pos
t-te
stPr
e-te
stPo
st-t
est
Mov
emen
t tim
e (m
s)41
9.9
(59.
1)34
5.4
(48.
7)44
6.5
(52.
8)39
1.4
(41.
9)45
9.2
(104
.6)
396.
5 (4
8.0)
427.
6 (7
2.2)
449.
6 (8
4.8)
Vel
ocit
y ra
tio0.
74 (
0.15
)0.
64 (
0.16
)–
–0.
88 (
0.20
)0.
70 (
0.15
)–
–
End
poin
t err
or (
%)
35.3
(21
.4)
17.7
(7.
5)14
.3 (
6.3)
10.0
(3.
3)50
.7 (
39.8
)22
.2 (
13.3
)17
.4 (
10.6
)13
.2 (
10.4
)
Cor
rela
tion
coeY
cien
t be
twee
n lim
bs0.
9126
(0.
156)
0.93
59 (
0.08
0)–
–0.
9276
(0.
071)
0.95
35 (
0.05
3)–
–
AG
1 on
set (
ms)
188.
9 (5
2.7)
172.
5 (4
9.1)
190.
7 (4
8.1)
171.
8 (4
7.4)
98.8
(22
.1)
94.7
(18
.7)
98.7
(16
.9)
94.4
(18
.3)
AG
1 to
AN
T o
nset
(m
s)76
.4 (
25.5
)59
.0 (
19.2
)90
.2 (
31.4
)78
.7 (
25.1
)64
.0 (
33.4
)64
.1 (
28.9
)81
.5 (
29.3
)70
.2 (
22.6
)
AG
1 to
AG
2 on
set (
ms)
168.
1 (4
0.6)
151.
1 (2
8.5)
183.
9 (4
1.8)
154.
6 (2
9.2)
154.
9 (4
2.0)
153.
2 (4
3.8)
166.
2 (4
8.1)
144.
5 (2
3.9)
AG
1 du
rati
on (
ms)
96.6
(22
.5)
93.0
(24
.4)
99.1
(14
.0)
95.3
(17
.8)
100.
5 (4
0.2)
100.
9 (4
2.9)
98.4
(33
.4)
91.9
(20
.8)
AN
T d
urat
ion
(ms)
95.6
(21
.3)
120.
4 (2
3.6)
97.3
(21
.4)
104.
2 (2
4.1)
106.
8 (4
4.6)
109.
5 (3
0.4)
92.7
(24
.0)
101.
9 (2
8.9)
AG
2 du
rati
on (
ms)
81.1
(18
.0)
91.2
(18
.3)
75.3
(18
.0)
83.0
(24
.3)
89.8
(35
.0)
82.8
(26
.5)
89.3
(15
.3)
90.5
(25
.5)
Q30
(%
peak
£ m
s)34
2.0
(158
.7)
474.
7 (2
39.4
)52
6.5
(248
.4)
620.
4 (2
43.9
)86
1.7
(366
.1)
891.
0 (2
89.8
)10
80.9
(47
2.1)
1174
.6 (
351.
9)
123
244 Exp Brain Res (2008) 190:239–249
lack of a main eVect for type of stimulus (P = 0.111) pro-vided evidence that there was no signiWcant diVerencebetween the velocity ratio for control and startle trials. Thisresult supports our prediction that the movement would beprepared in advance as the SAS triggered a similar move-ment to that produced in control trials. Furthermore, thelack of time £ type interaction (P = 0.297) conWrmed thatboth control and startle trials showed a similar improve-ment in velocity ratio following practice. This result sup-ports our prediction that practice-related changes could beattributed to an improvement in response preparation, as theresponse triggered by the SAS was more accurate followingthe acquisition period.
In addition to becoming more accurate with respect tothe relative velocity of the limbs, participants alsodecreased the duration of the movement. MT showed amain eVect for time [F(1, 9) = 19.13, P = 0.002, �p
2 = 0.68]due to signiWcantly faster movements (M = 396 ms) follow-ing practice as compared to pre-test trials (M = 438 ms).The eVects of practice were also seen in endpoint error, asthere was a main eVect for time [F(1, 9) = 5.49, P = 0.044,
�p2 = 0.38], arm [F(1, 9) = 16.15, P = 0.003, �p
2 = 0.64],and a signiWcant arm £ time interaction [F(1, 9) = 5.13, P =0.050, �p
2 = 0.36]. This interaction was examined by sepa-rately analyzing the left and right arm data. This analysisrevealed a signiWcant time eVect for the left arm (P = 0.038)due to a relatively large decrease in error from pre-test (M =43.0%) to post test (M = 19.9%), but no signiWcant timeeVect for the right arm (P = 0.261) due to a relatively smalldecrease in error for the right arm from pre-test (M =15.9%) to post-test (M = 11.6%). Thus the change in per-formance during acquisition appeared to be due to reducingthe error of the smaller movement of the non-dominantarm, while the larger movement of the dominant arm stayedfairly constant. There was also a main eVect in endpointerror for type of stimulus [F(1, 9) = 6.73, P = 0.029, �p
2 =0.43], with control trials having less overall error (M =19.3%) when compared to startle trials (M = 25.9%).
As expected, all three kinematic variables improved withpractice. To determine when improvement occurred and ifparticipants reached a performance asymptote, we per-formed a post hoc examination of performance during theacquisition period. This was done by analyzing participantmeans for velocity ratio and endpoint error during non-star-tle trials for the pre-test, the six acquisition blocks and thepost-test. Velocity ratio means were subjected to an 8Block (pre-test, acquisition block 1–6, post-test) repeatedmeasures ANOVA, while endpoint error means were sub-jected to an 8 Block (pre-test, acquisition block 1–6, post-test) £ 2 arm (left, right) repeated measures ANOVA.Results of the endpoint analysis conWrmed a signiWcanthand £ block interaction eVect (P = 0.005) which aTukey’s HSD test determined was due to a signiWcantdiVerence for the left hand between the pre-test and allother blocks (with no signiWcant diVerence occurring afterthe Wrst acquisition block). Results of the velocity ratioanalysis did not produce a signiWcant block eVect (P =0.157), however a similar trend occurred whereby the larg-est improvement in performance occurred between the pre-test and Wrst acquisition block. Thus, the majority of perfor-mance improvements appeared to occur within the Wrst 25trials, with little change in performance during the rest ofthe acquisition period. Endpoint error for the left and rightarm for control trials during acquisition, and startle andcontrol trials during pre- and post-testing is shown inFig. 2.
In support of previous results (e.g., Kelso et al. 1979),kinematic variables showed a high degree of synchrony.SpeciWcally, correlation coeYcients of movement velocitywere above 0.90 for all conditions (Table 1). Howeverthese numbers may be somewhat deceptive, given that themovement would require some degree of coordinationbetween the kinematics of the two limbs. To contrast trialswith a high and low correlation coeYcient, Fig. 3 shows
Fig. 1 Limb displacement and EMG data for a representative control(top) and startle (bottom) trial, following acquisition. Note the tempo-ral consistency of EMG activity in both control and startle trials, eventhough the limbs are moving to diVerent amplitude targets. Also notestartle trials are performed with a shortened latency and increasedmovement amplitude
-40
-30
-20
-10
0
10
20
30
40
0 50 100 150 200 250 300 350 400
Time (ms)
Dis
pla
cem
ent
(deg
)R
igh
tA
rmL
eft
Arm
CONTROL
-40
-30
-20
-10
0
10
20
30
40
0 50 100 150 200 250 300 350 400Time (ms)
Dis
pla
cem
ent
(deg
)R
igh
tA
rmL
eft
Arm
STARTLE
Agonist EMG
Agonist EMG
Agonist EMG
Agonist EMG
Antagonist EMG
Antagonist EMG
Antagonist EMG
Antagonist EMG
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Exp Brain Res (2008) 190:239–249 245
kinematic data (displacement, velocity, and accelerationversus time), from one participant, of two consecutive post-test control trials. The left panel (a) depicts one trial with a
low velocity correlation between limbs (r = 0.6245),whereas the right panel (b) shows a high correlation (r =0.9678). Notice for panel (a) that the peak velocity for theleft arm occurs earlier than the right arm, as compared topanel (b) when they occur almost simultaneously.
EMG
The collection of EMG allowed us to determine how partici-pants achieved limb movements of diVerent amplitudes(Fig. 1). We expected participants would either alter the tim-ing pattern of the triphasic burst, or change the relativeEMG amplitude between the arms. EMG boxplots, showingthe triphasic burst for both limbs during control and startletrials (collapsed by time), are shown in Fig. 4, as well as theSCM burst for startle trials. Overall our results support thehypothesis that asymmetrical movement amplitudes wereachieved by adjusting the ratio of EMG amplitude whilekeeping the timing invariant between the limbs. During star-tle trials EMG latencies were decreased; however the tripha-sic pattern and amplitude diVerences between the limbsfollowed the same pattern as the control trials.
Fig. 2 Mean (SEM) endpoint error as a percentage of total movement,during pre-test, acquisition (ACQ) and post-test startle and control tri-als, separated by arm. Note the signiWcant arm by time interactionwhereby the left arm decreases error with practice more than the rightarm
0
10
20
30
40
50
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70
Pre-Tes
t
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)
ACQ(2
)
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)
ACQ(4
)
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)
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est
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t
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ACQ(3
)
ACQ(4
)
ACQ(5
)
ACQ(6
)
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est
En
dp
oin
t E
rro
r (%
)
Control
Startle
Left Arm Right Arm
Fig. 3 Kinematic proWles showing displacement (top), velocity (middle), and accelera-tion (bottom), of the two limbs for single trials. Left panel (a) shows a movement with low velocity correlation (r = 0.6245) while right panel (b) shows a movement with high velocity correlation (r = 0.9678)
-30
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Left Arm
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Left Arm
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Time (ms)
Left Arm
Right Arm
Left Arm
Right Arm
Left Arm
100 150 200 250 300 350
Time (ms)
Right Arm
Left Arm
Right Arm
Dis
pla
cem
ent
(deg
)V
elo
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/s)
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atio
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eg/s
/s)
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123
246 Exp Brain Res (2008) 190:239–249
Analysis of AG1 onset conWrmed a main eVect for typeof stimulus [F(1, 9) = 52.47, P < 0.001, �p
2 = 0.85],whereby startle trials exhibited a signiWcantly shorter PMT(M = 99 ms) when compared to control trials (M = 179 ms).Although PMT did decrease with practice (pre-test M = 143ms, post-test M = 133ms), this result was not statisticallysigniWcant as there was no main eVect for time (P = 0.260).This was not unexpected as the entire movement was likelyprepared in advance both prior to, and following practice.Although changes in reaction time have been shown withpractice (e.g., Fischman and Lim 1991), this result is typi-cally found for a multiple component movement that can-not be initially fully pre-programmed (see Klapp 1995,1996 for a more detailed description).
The pattern of EMG activity produced was investigatedby examining the relative onset of the ANT and AG2 burst,and the three muscle burst durations. Analysis of ANTonset revealed a main eVect for arm [F(1, 9) = 6.46, P =0.032, �p
2 = 0.42], with the onset of the right arm ANToccurring later (M = 80 ms) than that of the left arm (M =66 ms). Analysis of the AG2 onset revealed a main eVectfor time [F(1, 9) = 5.51, P = 0.044, �p
2 = 0.38], with theonset of AG2 occurring earlier in post-testing (M = 151 ms)when compared to pre-testing (M = 168 ms). This eVectlikely contributed to the decrease in MT with practice, asearlier AG2 activity would result in the limb stopping at thetarget sooner. The analysis of duration for all three musclebursts showed no main eVect for time (AG1, P = 0.210; ANT,P = 0.210; AG2, P = 0.690), type (AG1, P = 0.826; ANT, P =0.801; AG2, P = 0.220), or arm (AG1, P = 0.785; ANT, P =0.151; AG2, P = 0.721), nor any signiWcant interactioneVects. The analysis of the Q30 scores showed a signiWcant
eVect for arm [F(1, 9) = 27.52, P = 0.001, �p2 = 0.75], and
stimulus type [F(1, 9) = 26.94, P = 0.001, �p2 = 0.75]. This
was due to signiWcantly greater EMG activity for the rightAG1 (M = 851%peak £ ms) versus the left (M = 642%peak£ ms), and greater activity during startle trials (M =1002%peak £ ms) versus control trials (M = 491%peak £ms). Thus while the timing pattern of the triphasic burstremained similar between the limbs, increased EMG activ-ity for the limb moving the greater distance allowed theparticipants to move the diVerent amplitudes.
Discussion
The purpose of this experiment was to examine the eVectsof practice on the preparation of an asymmetrical bimanualmovement. Our results supported the hypothesis that thismovement could be prepared in advance both prior to andfollowing practice, as illustrated by similar movement pro-duction during startle and control conditions. Not only wasthere no signiWcant diVerence between conditions forvelocity ratio, the timing of the triphasic EMG pattern(including both durations and relative onset timings) alsoremained essentially unchanged between control and startletrials. The only signiWcant eVect of startle on the performedmovement was an increase in endpoint error (from 19.3 to25.8%) and Q30 values (from 491%peak £ ms to1002%peak £ ms). Previous research has shown increasedpeak movement amplitude and increased peak EMG ampli-tudes associated with startle trials (e.g., Carlsen et al.2004a), which the authors attributed to increased neuralactivation associated with the increased stimulus intensity.This explanation seems likely for the current experiment asthe diVerence in endpoint error and agonist EMG amplitudebetween control and startle trials was consistent for bothlimbs, before and after practice (Table 1).
Although pre-programming of the required movementwas possible before and after the acquisition period, we wereinterested in whether the prepared response changed withpractice. Our results indicate that participants did improve atthe task, as shown by a decrease in MT, a more accuratevelocity ratio, and lower endpoint error. The post hoc analy-sis of the acquisition data conWrmed that the majority ofimprovement occurred within the Wrst block of 25 acquisitiontrials (Fig. 2). While MT and velocity ratio changed withpractice, these changes were also reXected in startle trials,conWrming that both types of trials improved following prac-tice. Furthermore, the change in velocity ratio conWrmed thatpractice aVected the Wrst 100 ms of the movement, a timeframe which is thought to be minimally inXuenced by sen-sory feedback. Thus, as we predicted, the practice-relatedchanges appeared to be due to a change in pre-programming,resulting in a more accurately prepared movement.
Fig. 4 Plots of triphasic EMG conWgurations during startle and con-trol trials, collapsed by time. Boxes represent EMG burst durationswith mean (SEM) onsets and oVsets with respect to time. AG1 repre-sents the initial agonist (triceps) burst, ANT represents the antagonist(biceps), AG2 represents the second agonist burst, and SCM representsthe startle indicator (sternocleidomastoid). Note the consistency of thetriphasic burst pattern between limbs (left and right) and conditions(control and startle)
0 50 100 150 200 250 300 350 400 450
Time (ms)
Right A G1 Right A G2
Right A NT
LeftAG1 LeftAG2
LeftANT
CONTROL
Right A G1 Right A G2
RightANT
LeftAG1 LeftAG2
LeftANT
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123
Exp Brain Res (2008) 190:239–249 247
The arm by time interaction for endpoint error providedinsight as to how the improvements in performanceoccurred. Participants decreased the error of the non-domi-nant arm moving the smaller distance (Fig. 2), which isconsistent with previous work investigating how asymmet-rical bimanual movements change with practice. Poor per-formance early in acquisition has been attributed toassimilation eVects, whereby errors in performance are dueto neural crosstalk between the motor commands of the twolimbs (Marteniuk et al. 1984; Sherwood 1990, 1991, 1994;Sherwood and Nishimura 1992; Spijkers and Heuer 1995;Spijkers et al. 1997; Heuer et al. 1998). Assimilation eVectsare more pronounced for the shorter movement as thecrosstalk interaction is from a larger amplitude movement,resulting in larger errors. With practice these eVects arethought to be either decreased or eliminated, allowing theparticipant to more accurately perform the asymmetricalmovement (Marteniuk et al. 1984; Sherwood 1990, 1994).
The use of a SAS allowed us to probe preparationchanges with practice; however it is necessary to ensure thestartling stimulus acted as a trigger for the prepared move-ment. While the temporal movement characteristicsremained unchanged for startle trials, response latencieswere much reduced. SpeciWcally, startle trials resulted in aPMT of 99 ms, compared to 179 ms during control trials,which is consistent with previous work involving a SASwith a targeted upper limb movement (e.g., Carlsen et al.2003, 2004a; Kumru and Valls-Solé 2006). Although short-ened reaction times occur with a more intense stimulus(Piéron 1920), it has been shown that the use of a SAS canresult in a further decrease in reaction time, which isthought to be due to triggering a pre-programmed represen-tation of the movement (Valls-Solé et al. 1999; Carlsenet al. 2004b). The presence of SCM activity prior to themovement, as observed in the current experiment (Fig. 4),appears to be the most reliable indicator that the participanthas indeed been startled (Carlsen et al. 2007). Thus webelieve that the SAS acted as a trigger and released the pre-programmed movement, conWrming the movement wasindeed prepared in advance of the “go” stimulus.
The design of the current experiment allowed investiga-tion into how movement preparation occurs for an asymmet-rical bimanual movement. The previous work by Kelso et al.(1979) led to the observation that when two movements ofasymmetrical amplitude are combined, the temporal structureof the limbs became synchronous, while the force productionvaried. Our results support this Wnding as the temporal struc-ture of both kinematic (Fig. 3) and EMG (Fig. 4) datashowed remarkable invariance between the limbs. This tem-poral invariance in EMG pattern between the limbs was alsomaintained in startle trials, suggesting this pattern was pre-pared in advance. However, EMG amplitudes of the initialagonist burst diVered between the limbs allowing the partici-
pants to make movements of diVerent distances. Theseresults suggest that to perform a bimanual movement ofdiVerent amplitudes, we prepare and execute motor com-mands for the two limbs with a similar timing structure butdiVerent muscle activation levels. This is in contrast to uni-manual limb movements where changes in amplitude areassociated with changes in timing of the triphasic EMG pat-tern (Wadman et al. 1979; Carlsen et al. 2004b). Therefore itappears that it is the coupling of the limbs that causes a simi-lar EMG timing structure for both limbs to be pre-pro-grammed. This is in line with previous bimanual researchshowing that diVerent movement amplitudes can easily bespeciWed between the limbs but producing movements withdiVerent durations is more diYcult (Schmidt et al. 1979;Heuer 1986, 1993; Spijkers et al. 1994).
In addition to examining how movement preparationoccurs in a bimanual movement, we also determined howpreparation changed with practice. The improvement inperforming the task appeared to result from pre-program-ming a more accurate ratio of left to right limb amplitude,rather than a change in the timing of the triphasic muscleactivity. This again can be contrasted to improvements inunimanual targeted movements where changes occur in thetiming pattern of muscle activations (Gabriel and Boucher1998, 2000; Liang et al. 2008). This suggests that duringpractice of a bimanual movement, it may be easier to mod-ify the relative EMG activation level rather than timing pat-tern to adjust the movement amplitude of one of the limbs.
In conclusion, the results from this study support thenotion that we can prepare in advance an asymmetricalbimanual movement, and that this response preparationchanges with practice. Results also indicate that this move-ment is performed using similar EMG timing betweenlimbs, while adjusting the relative ratio of EMG amplitude.Furthermore, learning of the task appears to be related tothe ability to produce the correct asymmetrical EMG ampli-tudes, rather than changing the timing of the triphasic pat-tern. By investigating the practice-related changes incertain aspects of information processing, we believe wecan begin to gain insight into what is learned during acqui-sition of this particular skill. The current results provideadditional support that skill acquisition can result fromchanges in the process of advance response preparation.
Acknowledgements A Natural Sciences and Engineering ResearchCouncil of Canada grant was awarded to Ian M. Franks. We would alsolike to recognize Paul Nagelkerke for his technical support.
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