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Cerebral Cortex January 2010;20:34--45doi:10.1093/cercor/bhp075 Advance Access publication May 11, 2009

Functional Neuroanatomy of Mirroringduring a Unimanual Force Generation Task

B. Sehm1,2 , M.A. Perez1 , B. Xu1 , J. Hidler3 and L.G. Cohen 1

1 Human Cortical Physiology Section and StrokeNeurorehabilitation, National Institute of NeurologicalDisorders and Stroke, National Institutes of Health, Bethesda,MD 20892, USA, 2 Department of Neurology, University of Greifswald, D-17487 Greifswald, Germany and 3 Department of Biomedical Engineering, Catholic University, Washington DC

20064, USA B. Sehm and M.A. Perez contributed equally to this work.

Performance of a unimanual motor task often induces involuntary mirror electromyographic (EMG) activity in the opposite, resting hand.In spite of the ubiquitous presence of mirroring, little is knownregarding the underlying cortical contributions. Here, we usedfunctional magnetic resonance imaging (fMRI) to study brain regionsactivated in association with parametric increases in right isometricwristexion force (10%, 20%, 30%, and70%) in 12 healthy volunteers.During scanning, EMG activity was recorded bilaterally from exorcarpi radialis (FCR), extensor carpi radialis (ECR), biceps brachii (BB),

and triceps brachii (TB). Mirror EMG was observed in left FCR during20%, 30%, and 70% of force. Left ECR, BB, and TB showedmirror EMGonly at 70% of force. Increasing force was associated with a linearincrease of blood-oxygen-level--dependent (BOLD) signal in bilateralprimary motor cortex (M1), supplementary motor area (SMA), caudalcingulate, and cerebellum. Mirroring in the left FCR correlated withactivity in bilateral M1, SMA, and the cerebellum. Overall, our resultssuggest that activity in these regions might reect sensorimotorprocesses operating in associationwithmirroring and suggest cautionwhen interpreting fMRI activity in studies that involve unilateral forcegeneration tasks in the absence of simultaneous bilateral EMG/ kinematics measurements.

Keywords: caudal cingulate, fMRI, mirror EMG, primary motor cortex,supplementary motor area

During unimanual motor tasks, muscle activity may not berestricted to the contracting arm, but has also been reported inthe contralateral resting arm, referred to as mirror electromyo-graphic (EMG) activity (Mayston et al. 1999; Leocani et al. 2000;Hoy et al. 2004; Carson 2005; Giovannelli et al. 2006; Cincotta and Ziemann 2008). Mirror EMG activity has been reportedduring performance of simple (Uttner et al. 2007; Ottavianiet al. 2008) and complex (Armatas et al. 1994; Cincotta et al.2006) motor tasks as well as during strong unimanual voluntary contractions (Muellbacher et al. 2000; Zijdewind et al. 2006) in

healthy individuals and in patients with motor disorders.Previous studies demonstrated a possible role for the primary motor cortex (M1) ipsilateral to a voluntary contrac-tion in the generation of mirror EMG activity (Mayston et al.1999; Hoy et al. 2004, Carson 2005, Zijdewind et al. 2006). Accordingly, functional magnetic resonance imaging (fMRI)studies have shown an increase in activity in M1 ipsilateral toa contracting arm during strong unimanual force generation(Dettmers et al. 1995; Thickbroom et al. 1998; Dai et al. 2001; van Duinen et al. 2008), when mirror EMG activity has beenreported. Furthermore, studies in patients with movementdisorders have demonstrated a decrease in intracortical in-hibition in the M1 ipsilateral to the moving arm in the presenceof mirror EMG activity (Cincotta et al. 2006; Cincotta and

Ziemann 2008) supporting the view that mirroring is related tofunctional changes in corticospinal projections originating inthe M1 ipsilateral. Although these studies characterizeddetailed physiological and blood-oxygen-level--dependent(BOLD) changes in ipsilateral M1 (Dettmers et al. 1995; Thickbroom et al. 1998; Dai et al. 2001), others have evaluatedsimultaneously changes in BOLD signal and EMG activity (Postet al. 2008), suggesting that simultaneous recording of BOLDsignal and EMG would be necessary to identify the possible

involvement of brain regions other than M1 in mirroring. To address this issue, we used fMRI to study brain regions

activated during performance of a parametric unimanual forcegenerationtaskwithsimultaneousEMGrecordingsfrom8 musclesin both arms.Wechose this combined fMRI/EMGdesign tobeableto relate accurately activation in different cortical areas engagedin force generation with mirror EMG activity. The main nding of our study was that during performance of a unimanual forcegeneration task, in addition to M1 ipsilateral to the active hand,mirroringcorrelatedwithincreasedactivity in thecontralateralM1and the medial premotor structures including SMA and thecerebellum.

Methods

Subjects Fifteen healthy volunteers (6 women, 9 male; 29 9.5 years) participatedin the study. All subjects gave their informed consent to the experimental procedure, which was approved by the National Institutes of NeurologicalDisorders and Stroke (NINDS) ethics committee. The study was performed in accordance with the Declaration of Helsinki. All the subjects were right handed as tested by the Edinburgh handedness inventory (Oldeld 1971). All subjects participated in a single session carried out inthe MRI scanner. In this session, subjects performed 10%, 20%, 30%, and70% of their maximal right wrist isometric exion force in a pseudo-randomized order with their right arm. Two subjects were excluded fromdata analysis because of excessive head movement ( > 5 mm) and 1 for notrespecting the behavioral instructions during scanning. The other subjectsshowed no signicant movements during the different levels of right wrist

exion force ( > 2 mm; range 0.1--2.6 mm, mean = 0.84 0.67 mm). Therefore, data from 12 subjects were included in the analysis.

Motor Task and Procedures During testing, subjects lay in the MRI scanner. A custom 6-axis load cell(35-E15A; Woodland, CA) was attached to the right arm to measure wristexion force (Fig. 1 A ). Custom software was written to acquire signalsfrom the load cell and to display visual feedback (Fig. 1 B ) correspondingto rest, 10%, 20%, 30%, and 70% of each subject maximal right wristexion force in real-time (Matlab R14SP3, Mathworks, Natick, MA; Hidleret al. 2006). Subjects were instructed to respond to the GO (target) signal presented on a computer monitor by moving a cursor to a target boxlocated at different distances according to their maximal right wristexion force (i.e., larger distances at larger levels of force generation) andto maintain the cursor in the target box for 2 s by performing isometric

Published by Oxford University Press 2009.

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right wrist exion force (Fig. 1 B ). The visual target was displayed ona rear-projection screen using a color liquid crystal display (LCD) projector. Thesubject viewed thedisplay througha mirrorxed to thetopofthe head coil.Theinstructionfor the subjectwas When you seethe GOsignal bend the right wrist. The maximal right wrist exion force wasmeasured 3 times at the beginning of each session and the measurements were averaged. Theexperiment was conducted in an event-relateddesignusing all force conditions (10%, 20%, 30%, and 70%). The gap betweenmovements was 6 and 14s. The stimulus-onset-asynchrony between trials was jittered with an average of 9 s (range = 6--14 s). Subjects performed 2experimental runs. Each run consisted of 64 trials with 16 trials for eachforce level. EMG measurements (see below EMG recordings and analysis) were acquiredfrombotharmsat rest andduring 10%,20%,30%,and70% of maximalright wrist exion force (Fig. 1 C ). During testing, the left arm wasoriented parallel to the trunk and supported from theforearm to the radialside of thehand withcushions. It is important to consider that duringforce

generation in thelyingposition, stabilization ofthe trunkmightbe achieved by contracting the other extremityor other segments of thesame arm. Tominimize this possibility, the segments proximal to the wrist weresupported by 4 padded adjustable bumpers. The contact point of the bumpers along theforearm andthewidthof thebumpers were adjusted toaccommodate forearms of different subjects. The conguration of the bumpers secured form closure, which prevented the forearm from rotat-ing and also minimized the forces generated at the hand and wrist from propagating up the arm and trunk (Hidler et al. 2006).

EMG Recordings and Analysis EMGrecordings were acquiredusing the BrainAmp MR Plus recorder andsoftware (Brainproducts GmbH, Munich, Germany; van Duinen et al.2005).Surfaceelectrodes were positioned bilaterallyon theskinoverlyingthe exor carpis radialis (FCR), extensor carpi radialis (ECR), biceps brachii (BB), and triceps brachii (TB) muscles in a bipolar montage

(interelectrodedistance,2 cm).To avoid EMGmovementartifact,the EMGleads were secured with adhesive tapes on the electrodes and cohesive bandages around the arms. The EMG signals were ltered (band-pass, 10--400 Hz), sampled at 5 kHz, and stored on a PC for off-line analysis. Brain Vision Analyzer software was used to remove scanner artifacts accordingto the method described by Allen et al. (2000). After the scanner artifact was removed, EMG data (ASCII format) were imported into Spike2(Cambridge Electronic Design, Cambridge, UK) for further analysis. EMGsignals were rectied, and the mean EMG activity was obtained, trial-by-trial, from all recordingmuscles. The onset of each EMG burst wasdenedas the time point when the mean EMG activity exceeded the baselineactivity (BL) by 3 standard deviations (SD) of the baseline (BL 3SD). Theoffset of each EMG burst was dened as the time point when the EMGsignal fellbelowthisvalue.EMG data were expressed as percentof baseline(BL) EMG. A total of 32 trials (trials from 2 fMRI runs combined) percondition were averaged. Kolmogorov--Smirnov and Mauchlys tests were

initially used to characterize the distribution and sphericity of data,respectively.Repeated measures analysisof variance(ANOVA RM ) wasusedto determine the effect of FORCE (Baseline, 10%, 20%, 30%, and 70%) oneachmuscle EMG. Tukey posthoc testwas usedfor multiple comparisons(SigmaStat, Version 2.03, Systat Software Inc., San Jose, CA). To assess the presenceof mirror EMGactivity,we tested the effect of FORCE (Baseline,10%,20%,30%,and 70%)on EMGactivity on eachmuscle. Signicancewasset at P < 0.05. Variance is expressed as mean SD.

fMRI Data Acquisition and Analysis The fMRI scans were performed using a GE 3-T scanner (GE Medical, Waukesha, WI) with an 8-channel receiving head coil. The functionalimages were acquired in 2 separated runs (274 volumes each) usinga T2*-weighted interleaved echo-planar imaging (EPI) sequence coveringthe whole brain (TR = 2 s, TE = 30 ms, ip angle = 90 , NEX = 1, eld of

Figure 1. Experimental setup. ( A) Schematics of the experimental setup. Subjects lay in the MRI scanner with their right arm attached to a custom device during performandifferent levels of right wrist exion force. ( B) Diagram showing the visual display presented to all subjects during testing. The black vertical line in the center shows the that subjects were instructed to move by performing right isometric wrist exion force over the manipulandum. The GO signal (dark gray box located to the left of thwas also the target to where subjects had to move the cursor, maintaining it in position for 2 s. The distance between cursor and target related to the magnitude of force reto accomplish each task, normalized to the maximal wrist exion force determined in each participant. (C) Traces showing force and EMG recordings after MRI artifact correctiin the right FCR (primary mover) on a representative subject. Note the randomized presentation of the force trials during testing.

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view = 220 3 220, number of slices = 32, slice thickness = 4 mm, gap = 0,and matrix size = 64 3 64). T1-weighted structural images with 1 3 1 3 4-mm resolution were also acquired for each subject.

fMRI data preprocessing and analysis were performed with SPM2 andSPM5 (for second level group analysis) software (the Wellcome De- partment of Imaging Neuroscience, University College London, London,UK). The rst 5 volumes (scans) of images were automatically discarded priorto data processing. Allimages ofeach time series(i.e., a scan run) wererst slice-time correctedand then realignedto therstimageof therstrun

with a 6-parameter rigid-body transformation for each subject. Resultingspatially realigned images were normalized to the template MNI brain. Therefore, thecoordinates usedto report the locationsof activation areallin the MNI space. The image volumes were subsequently spatially smoothed (FWHM = 8 mm 3 ) andhigh-pass ltered with a cut-off frequency of 1/128 s to remove low frequency drift. Statistical analyses were carriedout with the SPM2 and SPM5 software using the general linear model(Friston etal.1995;Turneretal.1998). TheSPM matrixmodeledan implicit baseline thatincludedtheresting baselinebetween trialsin thefMRIdesign.

Forthe rstlevel xed-effectsanalysis,statisticalcontrasts( t -tests) of MR signals for each level of force (10%, 20%, 30%, and 70%) relative to the baseline were performed for each individual subject. Anatomical identi-cation was carefully performed by superimposing activation foci on theMNI brain and on the normalized structural T1-weighted images of eachsubject. The resulting contrast images were usedas input for the random-effects analysis at the group level using SPM5. Task-related changes inBOLD signal between and across force levels were examined using 1-sample t -testsoverthe voxelsin thewholebrain.A voxelis consideredto besignicantly different from the baseline or in a contrast if it survived theFalse Discovery Rate (FDR) correction for multiple comparisons at thethreshold of P < 0.05 or otherwise specied. To characterize changes inBOLD signal across conditions as the force level increased, a linear trendanalysis was also performed at the second level group analysis. The trendanalysis was done using the output of a within-subject ANOVA in SPM5 by assigning linear weightsto the force condition (using a Flexible Factorialdesignwith force levelasa within-subjectfactor).Thepurpose of thelineartrend analysis was to identify cortical regions that showed a signicantlinear increase in BOLD signal withincreasing levels of force. Theactivatedareas were dened with a probabilistic cytoarchitectonic map (Eickhoff et al. 2005). We used the atlas of Schmahmann et al. (1999) for a specicneuroanatomical differentiation of cerebellar activations and the nomen-

clature of Larsell and Jansen (1972) to label cerebellar lobules. The SPManatomy toolbox (Eickhoff et al. 2005) was used to estimate cytoarchitec-tonic probabilities when possible. In order to evaluate the relationship between EMG activity and BOLD signal, Pearson correlation analysis was performedbetween mean EMGsignals andthe activity of thepeak voxelof the areas showing a signicant linear increase across force levels depictedin Figure 3 using SPM5. In addition, we performed multiple regressionanalyses of BOLD signal change at the group level using 2 regressors: 1)right FCR EMG and 2) left FCR EMG. The 2 EMG regressors wereorthogonalized to the mean EMG of the 2 muscles (i.e., the constant) in 2regression models using the Gram--Schimdt orthogonalization algorithm. With the orthogonalized regressors, the 2 models accounted for (i.e.,subtracted) the mean effect of force/task from the EMG regressors andallowed estimation of BOLD signal change uniquely associated with theright and the left FCR EMG across force levels (vanDuinen at al. 2008; vanRootselaar et al. 2008). In model 1, right FCREMG was entered as the rst

regressor and left FCR as the second regressor. This model providesestimate for the BOLD signal change associated with the right FCR and of the variance of the activation uniquely associated with the left FCR. Inmodel 2, left FCR EMG was entered as the rst regressor and right FCR asthe second regressor. This model provides estimate for the BOLD signalchange associated with the left FCR and of the variance of the activationuniquelyassociated withthe right FCR. Allsignicant correlations survivedthe threshold of P = 0.05 (FDR corrected).

Results

EMG Activity in the Right Arm Figure 2 (upper traces) illustrates the right FCR EMG activity recorded in a single subject during 10%, 20%, 30%, and 70% of

force. The group data are shown in Figure 2 A --D . We founda signicant effect of FORCE on EMG activity (% of baseline)in all muscles tested in the right arm (FCR, F (4,44) = 76.9,P < 0.001, Fig. 2A ; ECR,F (4,44) = 22.0, P < 0.001, Fig. 2B ; BB,F (4,44) = 16.9, P < 0.001, Fig. 2C ; TB,F (4,28) = 34.1, P < 0.001,Fig. 2D ). In the right FCR, EMG activity was increased at 70%(P < 0.001), 30% ( P < 0.001), 20% ( P < 0.001), and 10%(P = 0.036) of force compared with baseline. In the right ECR,EMG activity was increased at 70% ( P < 0.001), 30% ( P < 0.01),and 20% (P < 0.02) of force compared with baseline. In theright BB, increased EMG activity was observed at 70% ( P