www.elsevier.com/locate/cogbrainres

Cognitive Brain Research 20 (2004) 273–280

Research report

Effects of motor imagery on finger force responses to transcranial

magnetic stimulation

Sheng Li*, Mark L. Latash, Vladimir M. Zatsiorsky

Department of Kinesiology, Pennsylvania State University, University Park, PA 16802, USA

Accepted 11 March 2004

Available online 27 April 2004

Abstract

The purpose of this study was to investigate whether characteristics of finger interaction seen in voluntary finger force production tasks

could also be observed during motor imagery. Transcranial magnetic stimulation (TMS) was applied over the contralateral M1 hand area. Three

conditions were tested in eight young healthy volunteers: At rest, during motor imagery of maximal force production by the index finger (ImIn),

and during motor imagery of maximal force production by all four fingers simultaneously (ImAll). We obtained measures of motor threshold

(MT), motor-evoked potentials (MEP) from the contralateral flexor digitorium superficialis, and TMS-induced forces from individual fingers.

Increased MEP and decreased MT during motor imagery tasks suggested enhanced excitability of structures involved in the generation of

TMS-induced responses. TMS-induced forces were larger during motor imagery tasks than at rest. This effect was present, albeit significantly

smaller, in the middle, ring, and little fingers during ImIn as compared to ImAll. This finding has been interpreted as a correlate of the

phenomenon of unintended finger force production (enslaving). The motor imagery effect on finger forces evoked by TMS was significantly

larger during ImIn (4% MVC) than during ImAll (2.8% MVC) tasks, corresponding to the phenomenon of force deficit. These results provide

direct evidence of the neural origin of the main phenomena of finger interaction. Furthermore, the similarities between characteristics of finger

interaction during motor imagery and during voluntary movement suggest the involvement of similar neural structures (including M1).

D 2004 Elsevier B.V. All rights reserved.

Theme: Motor systems and sensorimotor integration

Topic: Control of posture and movement

Keywords: Motor imagery; Transcranial magnetic stimulation; Finger; Enslaving; Deficit

1. Introduction However, there has been some controversy in the litera-

Motor imagery, i.e., imagining doing a certain movement

without executing them, has been an object of several

research papers [8,12–14,18,19,34,45,46,48–50]. Repeated

evidence in the literature shows that motor imagery shares

features involved in the actual movement, such as involve-

ments of common neural structures [1,3,8], kinematic con-

straints [43], temporal properties [9,43], effects on motor

performances [52], the role in skill acquisition [33] and in

motor recovery after stroke [31,51].

0926-6410/$ - see front matter D 2004 Elsevier B.V. All rights reserved.

doi:10.1016/j.cogbrainres.2004.03.003

* Corresponding author. Sensory Motor Performance Program, Reha-

bilitation Institute of Chicago, Northwestern University, 345 E. Superior St.

Room 1406, Chicago, IL 60611, USA. Tel.: +1-312-238-2227; fax: +1-312-

238-2208.

E-mail address: shengli@northwestern.edu (S. Li).

ture regarding the involvement of the primary motor cortex

(M1) during motor imagery. On one hand, evidence of the

M1 involvement in motor imagery includes reports on focal

enhancement of corticospinal excitability during the appli-

cation of transcranial magnetic stimulation (TMS) over M1

[12,13,15,19] and increased M1 activity revealed in fMRI

experiments [30,36,38]. We use the term ‘‘corticospinal

excitability’’ to refer to the excitability of all the structures

involved in the generation of finger responses to TMS; these

responses may be mediated by the corticospinal tract as well

as by other descending pathways [35]. On the other hand, the

conclusion on an M1 involvement in motor imagery has not

been supported by other neuroimaging studies [10,16,32,47].

Due to its unique and complex peripheral anatomy and

representations in M1, the human hand is an appealing object

to study the physiology of motor imagery. In particular,

S. Li et al. / Cognitive Brain Research 20 (2004) 273–280274

cortical control of the distal hand muscles in monkeys is the

most direct of any of the muscles of the extremities [37].

Finger representations in M1 are highly interconnected [42].

Convergence and divergence of des-cending pathways as

well as widespread finger representations lead to an exten-

sive activity in the cortical network, even during a single-

finger movement [41]. A few characteristics of finger inter-

action during multi-finger voluntary force production have

been attributed to this complex organization—unfortunately,

without a direct proof of the hypothesis [4,23,26,29]. When a

finger produces force, other uninstructed fingers also pro-

duce forces. The phenomenon, named enslaving, has been

repeatedly observed during voluntary contraction tasks at

maximal [20,21,25,54], moderate [44], and low levels

[20,21]. Another characteristic is force deficit: a finger

produces less peak force during a multi-finger task than

during its single-finger maximal voluntary contraction

(MVC) task [24]. Enslaving and force deficit have been

interpreted as reflecting both the peripheral design of the

hand muscles and their neural control [53].

Within this study, we accept a hypothesis that motor

imagery and actual movements involve common neural

structures, including M1. In particular, if phenomena of

force deficit and enslaving are predominantly defined by

neural factors the phenomena are expected to be revealed in

responses of fingers to TMS applied over the contralateral

M1 area during motor imagery. Specifically, motor imagery

of an action by a finger should be reflected in TMS-induced

responses of other fingers (cf. enslaving) and larger effects

on TMS-induced finger responses during motor imagery of

a one-finger MVC than during imagery of a four-finger

MVC (cf. force deficit). Alternatively, if these phenomena

are crucially dependent on the peripheral factors, such as the

presence of multi-digit muscles and connective tissue inter-

digit connections, they are not expected to be reflected in

modulation of TMS-induced finger force responses during

motor imagery.

2. Materials and methods

2.1. Subjects

Eight healthy volunteers, all males, participated in the

experiments. All of them were right-handed according to

their preferential use of the right hand during writing and

eating. The age of the subjects was 27F 4 (meanF S.D.)

years. Their weight was 80.3F 15.5 kg, and their height was

1.79F 0.11 m. All the subjects gave informed consent

according to the procedures approved by the Office for

Regulatory Compliance of the Pennsylvania State University.

2.2. Apparatus

During testing, the subject was seated in a chair in front of

a testing table. Two upper limbs were symmetrical with

respect to the body midline with the upper arms at approx-

imately 45j of abduction in the frontal plane and 45j of

flexion in the sagittal plane, elbow joints at approximately

135j of flexion. The right hand and fingers were positioned

and stabilized into a suspension device for force measure-

ment using four unidirectional piezoelectric force sensors

(208A03, PCB Piezotronics, Depew, NY) (cf. Ref. [23]). The

resolution of sensors was 2.714 mN/byte. In the suspension

device, the sensors were each connected in series with wire

cables that were suspended by swivel attachments from slots

in the top plate of the inverted U-shaped frame. The rubber-

coated loops, located at the bottom of each wire, were placed

in the middle of the distal phalanxes. Due to the employed

experimental procedure, all four-finger forces were parallel.

A hand-fixation device was located at the bottom of the

frame and used to stabilise the palm of the hand and to ensure

a constant hand configuration throughout the experiment

(the wrist was fixed at approximately 20j of extension and

the fingers were positioned so that there was also approxi-

mately 20j of flexion at the metacarpophalangeal joints).

The left forearm and hand rested on the testing table at the

same height as the right forearm.

2.3. EMG recordings

Bipolar electromyographic (EMG) recordings from the

flexor digitorum superficialis (FDS) of the right forearm

were obtained from pairs of disposable surface electrodes

placed over the muscle belly. The diameter of each

electrode was 1 cm, the distance between the centres of

two electrodes within a pair was 3 cm. The EMG signals

were amplified, high pass filtered at 10 Hz and low pass

filtered at 500 Hz. The signal from the right forearm was

displayed on-line on the monitor. EMG signals were set

at a high gain (25 AV per division) to ensure complete

EMG silence during the experiment.

2.4. Magnetic stimulation of the brain

The method and procedures of application of TMS was

the same as previously described (cf. Ref. [7]). Briefly, focal

TMS was performed with a figure-of-8-shaped stimulation

coil (mean diameter of each wing 45 mm) connected to a

Magstim 200 magnetic stimulator with the maximal mag-

netic field strength of 2.2 Tesla (Magstim, UK). A tight

elastic cap was placed on the subject’s head. A grid of 1�1

cm was marked on the left side of the scalp, with its centre

positioned 2 cm to the left of Cz. The intersection of the

coils was placed tangentially to the center of the grid with

the handle pointing backward and laterally at a 45j angle

away from the midline. In this way, the current induced in

the neural tissue was directed approximately perpendicular

to the line of the central sulcus in a direction parallel to the

mid-line between the two coils and therefore optimal for

activating the corticospinal pathways transsynaptically [2].

First, the stimulus intensity was set at 60% of the stimulator

S. Li et al. / Cognitive Brain Res

output, and an optimal position for eliciting the largest

increment in the total force of all fingers that was stable

in three consecutive trials was found by moving the coil

over the scalp in steps of 1 cm. The optimal position was

then marked with a pen to ensure constant positioning of the

coil throughout the experiment. Keeping the coil at the

optimal location, the intensity of the stimulation was slowly

decreased until the motor threshold (MT) was found. The

MT was defined as the lowest stimulus capable of evoking

at least three of six motor-evoked potentials (MEPs) with

the amplitude of at least 50 AV for both the rest condition

and the conditions of motor imagery (see below). The coil

position and orientation was ensured with double-sided

adhesive tape; besides, at all times, the coil position was

stabilized by an experimenter.

A Gateway 450 MHz computer was used for data

acquisition and processing. All signals were sampled at

1000 Hz by a 16-bit A/D board using LabView software

(National Instrument).

2.5. Procedures

During the experiment, the instruction for motor imag-

ery was to mentally press down with the intended finger(s)

as hard as possible (MVCI). Subjects were asked to

practice this mental task for a few minutes prior to testing

to ensure that they are able to keep the EMG silent during

motor imagery. EMG silence was defined as the absence of

any background activity at the sensitivity of 25 AV per

division. Three experimental conditions were investigated:

(1) Rest: the absence of motor imagery; (2) ImIn: motor

imagery of MVCI by the right index finger only; (3)

ImAll: motor imagery of MVCI by all four fingers of the

right hand simultaneously. At the end of the experiment,

subjects were asked to produce MVCs at the fingertips

using the index finger only and using all four fingers

simultaneously. The highest peak value from three trials

was considered as MVC forces for the index finger and

four-finger tasks, respectively.

The subject was asked to start to imagine pressing

finger down as hard as possible after a verbal command

and sustain this condition until a TMS stimulus was

delivered (unexpectedly, within 3 s). Then the subject

was instructed to relax. Due to the employed high resolu-

tion of EMG/force sensing systems, deviation of EMG and

force signals from the background levels due to the

slightest movement of individual fingers was able to be

detected by the sensing systems during the experiment.

Such trials, if happened, were discarded by the experi-

menter to ensure motor imagery tasks purely imagined.

The stimulation intensity was the same for the rest and

motor imagery conditions at 150% of the resting MT

(rMT), on average 60.9% of the stimulator output. The

order of conditions was randomized. Five trials were

conducted for each condition. The interval between two

consecutive trials was approximately 15 s.

2.6. Data processing

Changes in individual and combined finger forces

were used as the main indices to evaluate the effects

of TMS and motor imagery, while EMG signals were

used to monitor the background activity during motor

imagery tasks and to quantify changes in the cortico-

spinal excitability.

Two parameters were calculated from the measured

finger forces—TMS-induced force increments (DF) and

changes in DF due to the motor imagery (DFIMAG). The

former index (DF) for a finger was defined as the

difference between its force at the time of peak force

response to TMS of all fingers and its background force,

defined as the mean force from � 100 ms to the moment

of TMS application (t0 = 0 ms). This index was also

calculated for all four fingers, DFTOTAL=SDFi (i = I, M,

R, and L—the index, middle, ring, and little fingers,

respectively), for the index finger (DFINDEX), and for

the three other fingers DFMRL=SDFi (i =M, R, and L).

To quantify effects of motor imagery on DF indices

during different motor imagery tasks, DF at rest was

subtracted from DF during a motor imagery test resulting

in a DFIMAG index. DF was expressed in absolute units

(N). DFIMAG was expressed in percent with respect to the

peak force value (MVC) observed in its corresponding

voluntary task. The normalized DFIMAG was used to

compare the motor imagery effect for different imagery

tasks. The latency of TMS-induced force responses was

defined as the time interval between the application of the

stimulation and the time when the total force exceeded

two standard deviations (S.D.) of its background value,

i.e., the weight of fingers (offset to zeros).

The EMG signal was rectified and low-pass filtered at

100 Hz using a second-order, zero-lag Butterworth filter.

The background EMG (EMGBG) was defined as the mean

rectified, filtered EMG calculated from � 100 ms to the

moment of TMS application. The MEP latency was

computed as the time it took the baseline EMG to increase

by 2 S.D. The size of the MEP was defined as the

difference between the peak EMG in the rectified signal

and EMGBG. The MEP size was expressed in arbitrary

units (AU). Both the force and EMG indices were aver-

aged across five trials for each condition. Other data

processing techniques were similar to those described

earlier [7].

2.7. Statistics

The data in the text are presented as means while figures

show means and standard error bars. Repeated-measures

ANOVAs were used with a factor CONDITION (three

levels, Rest, ImIn, and ImAll). Whenever necessary, post

hoc Tukey’s honest significant difference tests were used to

compare the various levels of the factors. Paired Student’s t-

test was also used.

earch 20 (2004) 273–280 275

Fig. 1. Typical traces of individual and combined forces induced by focal

TMS application on the contralateral motor cortex from one subject. Note

that (1) in the ImIn test, there is a larger DF of the intended finger as

compared to the rest condition. (2) In the ImAll test, there is a larger DF of

the total force than for the ImIn tests. (3) DF of the unintended M, R, L

fingers (ImIn task) increases when these fingers become the intended

fingers (ImAll task). Rest: absence of motor imagery; ImIn: motor imagery

of maximal force production of index finger only; ImAll: motor imagery of

maximal force production of four finger simultaneously.

S. Li et al. / Cognitive Brain Research 20 (2004) 273–280276

3. Results

A single TMS stimulus produced a sequence of mechan-

ical and EMG effects. It was followed, after a short delay, by

a burst of activity (MEPs) in the FDS muscle, frequently

followed by a silent period. The silent period was not

analyzed in the current study. The latency of the MEP

ranged in different subjects from 11.8 to 17 ms with the

average value of 14.7 ms. Following a suggestion by an

anonymous reviewer, we re-analyzed the data without the

100-Hz filter. The results showed the FDS MEP latency in

the range between 11 and 19.3 ms (mean = 15.7 ms) for the

rest condition across the eight subjects, i.e., about 1 ms

longer than the values obtained from analysis with the filter.

This latency is comparable to the MEP latency in extensor

digitorum communis (12.2 to 18.4 ms, mean = 15.2 ms) at

rest reported in an earlier study [11]. Changes in finger force

were seen about 14 ms after the beginning of the MEP. They

were typically seen in all four fingers of the hand.

3.1. Motor imagery effects on EMG responses

During motor imagery trials, a decrease in the motor

threshold (MT) was observed accompanied by an increase

in the MEP amplitude. At rest, the motor threshold (MT)

was, on average, 40.8% of the stimulator output. It was

significantly lower during both ImIn (36.6%) and ImAll

(37.4%) conditions as supported by the one-way ANOVA

(F[2,14] = 24.49, p < 0.001). MT did not differ between the

ImIn and ImAll tasks. These data are presented in Table 1.

At the same stimulus intensity of 150% of resting MT, the

MEP magnitude was significantly lower at Rest (7.7, in

arbitrary units, AU) than in the ImIn tasks (13.8 AU) and in

the ImAll tasks (16.4 AU) (F[2,14] = 11.78, p< 0.001). No

difference was found between the two imagery conditions,

i.e., the described effects did not depend on whether the

subject imagined pressing with the index finger only (ImIn)

or with all four fingers of the hand (ImAll).

3.2. Motor imagery effect on finger force responses

As mentioned earlier, the application of TMS induced an

increase in the forces of all four fingers. Fig. 1 illustrates

typical traces of TMS-induced force increments (DF) during

different conditions from a representative subject. Note that,

(1) in the ImIn test, there is a larger DF of the intended

Table 1

Motor threshold (MT) and motor-evoked potentials (MEPs)

Rest ImIn ImAll

MT (%) 40.8F 2.0 36.6F 2.5 37.4F 2.0

MEP (AU) 7.7F 0.9 13.8F 2.6 16.4F 2.6

MT was recorded as the percentage of the stimulator output; MEP was

recorded from the flexor digitorum superficialis (FDS) during different

conditions and was expressed in arbitrary unit (AU). Standard errors are

presented.

finger (DFINDEX) as compared to the rest condition. (2) In

the ImAll test, there is a larger DF of the total force

(DFTOTAL) than for the ImIn tests. (3) DF of the unintended

M, R, L fingers (ImIn task) increases when these fingers

become the intended fingers (ImAll task).

Fig. 2A shows the DF of the total force and of the index

finger averaged across subjects during different conditions.

The mean DFTOTAL was the lowest at rest (2.4 N), higher

during ImIn (4.4 N), and the highest during ImAll (5.8 N).

DFTOTAL was significantly larger during motor imagery

tasks than at rest (F[2,14] = 4.16, p < 0.001). The difference

between DFTOTAL in ImAll and in ImIn was just at the

boundary of statistical significance ( p= 0.059). DFINDEX

was larger for imagery tasks than at rest; the mean DFINDEX

was 0.7, 1.9, 1.5 N for Rest, ImIn, ImAll tasks, respectively.

According to a one-way ANOVA (F[2,14] = 7.92, p < 0.005)

and post hoc tests, DFINDEX for the ImIn and ImAll tasks

were larger than that at rest, while no difference was found

between the motor imagery tasks.

The amount of force increment reflecting the motor

imagery effect (DFIMAG) showed a different pattern from

Fig. 3. The individual and combined (DFMRL) TMS-induced force

increments in middle, ring and little fingers, averaged across trials and

subjects, are shown. DFMRL is the difference between two lines shown in

S. Li et al. / Cognitive Brain Research 20 (2004) 273–280 277

DF (Fig. 2B). In absolute units, DFIMAG was smaller for

ImAll tasks (2.1 N) than for ImIn tasks (3.4 N), according to

paired t-tests (t[7] = 2.37, p < 0.05). To compare the motor

imagery effect on finger force responses during different

tasks, DFIMAG was normalized to corresponding MVC

values. DFIMAG of the total force was larger for ImIn tasks

than for ImAll tasks. DFIMAG for ImIn tasks ranged from

1.2% to 10.3% MVC with the average of 4% MVC, while

for ImAll tasks it ranged from 0.2% to 6% MVC with the

average of 2.8% MVC. Paired t-tests confirmed that this

difference (on average 30%) was statistically significant

(t[7] = 3.67, p < 0.01).

To investigate whether enslaving effects exist during

motor imagery, comparisons between TMS-induced force

increments in the unintended fingers at rest and during motor

imagery tasks were performed. The combined force pro-

duced by unintended fingers (DFMRL) was significantly

larger during ImIn tasks (2.6 N) than that at rest (1.6 N)

(see Fig. 3). However, when these fingers became the

intended fingers in ImAll tasks, DFMRL increased signifi-

Fig. 2. (A) TMS-induced force increment (DF) in the index finger and total

forces, averaged across trials and subjects, are shown. DF was larger for

motor imagery tasks than at rest. (B) The motor imagery component

(DFIMAG) of DF of the total force was larger for the ImAll task than for the

ImIn task. Note that DFIMAG was computed by subtracting DF at rest and

normalizing to corresponding MVCs. I: index finger; TOT: all fingers.

Standard error bars are shown.

Fig. 2A. DFMRL in ImIn tasks was larger than at rest, but smaller than in

ImAll tasks. Motor imagery showed strong effects in the middle and ring

fingers, but not in the little finger. Standard error bars are shown.

cantly (4.3 N). These differences were confirmed by a one-

way ANOVA (F[2,14] = 9.82, p< 0.005) and post hoc tests.

Further paired t-tests were used to compare DF for each

unintended finger at rest and in ImIn tasks separately and

showed significant effects on DFMIDDLE and DFRING (0.4 vs.

0.8 N and 0.4 vs. 1.0 N, for the Rest and ImIn, respectively;

p < 0.05), but not on DFLITTLE (0.8 vs. 0.9 N for the Rest and

ImIn, respectively).

4. Discussion

Motor imagery in our experiments was associated with a

decrease in the threshold for TMS-induced responses and an

increase in the MEP amplitude. These observations agree

well with previous reports on an enhanced corticospinal

excitability during motor imagery [12,13]. Our experiment

used two sets of measures to quantify effects of motor

imagery on TMS-induced responses in EMG and force.

The more traditional EMG measures, as used in the previous

TMS studies of motor imagery [12–14,19,34,45,46,48–50],

showed effects of motor imagery but failed to reveal differ-

ences between the imagery conditions. This may partly be

due to the fact that the surface EMG signal effectively

averaged signals over several compartments of the FDS

muscle with possible effects from the deep flexor, FDP [6].

Recording the EMG signals from only one muscle is a

limitation of our study. However, as mentioned, placing the

electrodes over the FDS typically allows to record signals

from both FDS and FDP. The tendons of these muscles

attach at the middle and distal phalanges and make them

prime movers during force production at the fingertips.

S. Li et al. / Cognitive Brain Research 20 (2004) 273–280278

Hence, we view monitoring the lack of the EMG activity at

a high gain (25 AV per division) during motor imagery in

addition to controlling the lack of background forces of the

fingers during the experiment as practically adequate.

4.1. Comparisons with data from actual finger force

production

Finger interactions during one- (index) and four-finger

MVC tasks have been extensively studied earlier and

phenomena of enslaving and force deficit have been de-

scribed and quantified [4,5,22–29,53,54]. Patterns of TMS-

induced finger force responses during motor imagery

showed effects of finger interaction similar to those early

described during voluntary force production. In particular,

during motor imagery of MVC by the index finger, TMS-

induced responses were higher in the other three fingers

(middle, ring, and little) than at rest (Fig. 3) (enslaving).

When these fingers become explicitly involved, in the ImAll

condition, their response increased even more suggesting a

graded involvement of neural structures responsible for

finger force production [37,39,40] depending whether a

finger is instructed or not instructed to produce imagined

force. Another feature of enslaving described in voluntary

force production tasks [53] is that it is larger for neighboring

fingers. Our results of significant effects of motor imagery

in the ImIn condition on the TMS-induced responses in the

middle and ring fingers, but not in the little finger, illustrate

this feature of enslaving for motor imagery. Furthermore,

these results are consistent with those during actual finger

production reported in a recent paper [7]. This paper, in

particular, showed an inverted U-shaped dependence of the

TMS-induced force responses on the background finger

forces over the whole range of finger forces up to the

MVC. Peak finger force responses to the TMS were seen

at about 50% of the MVC. Graded increments in the TMS-

induced force responses in the middle, ring and little fingers

across the Rest, ImIn and ImAll tasks could be viewed as

reflecting the rising part of the inverted U-shaped relation.

Force deficit (FD), was quantified in earlier studies as the

difference between the sum of peak forces of individual

fingers during a multi-finger task and the sum of their

MVCs in one-finger tasks [25]. FD measures an inability

to produce maximal force by a finger during a multi-finger

MVC task; it was interpreted as a consequence of a limit to

the total central neural drive (ceiling hypothesis) [25].

However, direct evidence of a neural origin of the force

deficit phenomenon has been lacking.

In the present study, the motor imagery effect on finger

responses was quantified using DFIMAG. After subtracting

TMS-induced force increment at rest, the remaining com-

ponent reflects the motor imagery effect on finger force

responses induced by TMS. Normalized to i ts

corresponding MVC to make the data comparable despite

the different numbers of intended fingers during the ImIn

and ImAll tasks, DFIMAG could then be used to compare the

relative effects of motor imagery on one-finger and four-

finger tasks. The DFIMAG index was significantly higher

during the one-finger (ImIn, 4%) tasks than during four-

finger (ImAll, 2.8%) tasks. This result implies that the effect

of motor imagery, per unit of force in MVC tasks, is lower

during the ImAll task than during the ImIn task. This result

could be interpreted as a correlate of the phenomenon of

force deficit during voluntary force production tasks. Note

that the relative amount of ‘‘imagery deficit’’ was about

30%, which is close to typical force deficit values described

earlier [25,29].

4.2. Movement-specific effect

Observation of enslaving effects during motor imagery

supports an earlier hypothesis that enslaving is of a central

origin [4,23,26]. On the other hand, this result seems to be

in contrast to movement-specific effects of motor imagery

[12,13], which imply that humans are able to specifically

facilitate an intended movement. For example, Facchini et

al. [12] showed no facilitatory effect on the MEP in the first

dorsal interosseus during motor imagery of thumb abduction

on the same side.

It is possible, however, that the observation of enslaving

effects of motor imagery in our study is associated with the

unique and complex organization of finger representations

in the primary motor cortex. Previous studies have shown

that finger representations are highly interconnected, and

that activation is distributed throughout the M1 hand area

whenever any finger movement is made [17,37,39,40].

Furthermore, due to the diverging effect of output projec-

tions from finger representations, activation of one finger

representation could project onto adjacent fingers [40,42].

Indeed, the observation of enslaving effects supports move-

ment-specific effects of motor imagery. Combined effects

on middle, ring and little fingers (DFMRL) were larger in

ImAll tasks when these fingers were explicitly involved

(Fig. 3). This result means that motor imagery of a move-

ment specifically affects effectors that would be involved in

actual execution of the movement (cf. Refs. [12,13]).

To conclude, the results illustrate similarities in charac-

teristics of finger interactions, such as enslaving and force

deficit, during motor imagery and voluntary action. They

provide direct evidence of the neural origin of the main

phenomena of finger interactions and suggest the involve-

ment of similar neural structures (including M1) in volun-

tary action and motor imagery.

Acknowledgements

The authors thank Desmond Oathes and Jared Bruce for

assistance in data acquisition. The studywas in part supported

by NIH grants NS-35032, AG-018751 and AR-048563. S. Li

was supported by a NIDRR training grant H133P990006.

We thank the anonymous reviewers for useful comments.

S. Li et al. / Cognitive Brain Research 20 (2004) 273–280 279

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