ORIGINAL ARTICLE
Task-and Phase-related Changes in Cortico-muscular Coherence
Yoshihisa Masakado1,2 and Jens Bo Nielsen2

Keio University Tsukigase Rehabilitation Center, Shizuoka, Japan
Department of Exercise and Sport Sciences & Department of Neuroscience and Pharmacology,
Panum Institute, University of Copenhagen, Denmark
1

2(Received for publication on September 4, 2007)(Revised for publication on November 7, 2007)(Accepted for publication on December 3, 2007)

Abstract: Cortico-muscular coherence was compared during ramp-and-hold isometric andquasi-isotonic contraction of the ankle joint in human subjects. EEG was recorded from theleg area of the motor cortex. EMG was recorded from the tibialis anterior (TA) muscle. The
subjects were requested to maintain a steady low level of dorsiflexion and at intervals of 10s to increase the contraction level within 1 s, maintain this level for 4 s and then decrease
the level of contraction again within another 1 s.
In seven subjects coherence in the 15-35 Hz frequency band was seen between EEG and
TA EMG during low-level tonic dorsiflexion. In all subjects coherence disappeared during
the ramp phase for both isometric and quasi-isotonic contraction. Coherence at other frequencies was also not observed in any of the subjects during the ramp phase. During thehold phase at the stronger level of contraction coherence reappeared quickly and had thesame size as at the low level of contraction. However, a significantly larger level of coherence was found during quasi-isotonic than during the isometric contraction.
This demonstrates that cortico-muscular coherence in the 15-35 Hz frequency band isphase- and task-related. The decrease in 15-35 Hz coherence during the ramp phase may berelated to event-related desynchronization of EEG activity. The larger level of coherence
during quasi-isotonic contraction may reflect a higher demand of precise control of the joint
position. It may also reflect a greater need for binding of functionally related cortical pyramidal tract neurons. (Keio J Med 57 (1) : 50－56, March 2008)
Key words: electroencephalography (EEG), electromyography (EMG), coherence, task, phase

Introduction

lateral hand and forearm muscles in monkeys and humans.1, 4-9 However, the functional significance of thiscorticomuscular coherence is unclear. Kilner et al foundthat coherence between the cortex and finger muscles
was larger when subjects had to squeeze a compliant object rather than a more rigid object.8,9 This suggests thatcorticomuscular coherence may be related to functionalparameters of the performed task. It may also play afunctional role in the activation of the muscles.10 Corticomuscular coherence established during prehensile actions has also been shown to vary in a task-dependent
manner. It was most prominent during the steady holdperiod of the precision grip task, but was abolished during digit movement.4, 8, 9 Coherence was shown to be

A number of recent reports have investigated the possible function of synchronous oscillatory synchrony within
the sensorimotor cortex of monkeys and humans. 1- 4
These oscillations can be detected in global measures ofcortical activity, including magnetoencephalography(MEG) and EEG in humans, and local field potential(LFP) in monkeys; the dominant characteristic frequencyof these oscillations is in the beta range of 15-30 Hz, andthey are thought to arise from the synchronous dischargeof large numbers of cortical neurones.
Cortical activity in the 15-30 Hz range has been shown
to be coherent with oscillatory EMG activity in contra-

Corresponding Author: Yoshihisa Masakado, MD Keio University Tsukigase Rehabilitation Center, 3802, Tsukigase, Izu-shi, Shizuoka 410-3293, Japan
Phone: 81-558-85-1701 Fax: 81-558-85-1810 E-mail address: masakado@sc.itc.keio.ac.jp50

Keio J Med 2008; 57 (1): 50－56

51

largest when a steady hold period immediately followed
movement, and covaried positively with the complianceof the object being gripped; it was smallest during isometric grip of a solid object.9 This raised the possibility
that 15－30 Hz cortico-muscular coherence may encode
the ‘motor set’ needed to maintain steady grip of compliant objects
To further investigate a potential functional role of corticomucular coherence the purpose of the present study
was to investigate whether corticomuscular coherenceshows task- and phase specificity for leg movement.
Materials and Methods
Subjects
Experiments were performed on 9 healthy right-handed
subjects aged 22-28 years, with approval from the local
ethics committee. All the subjects gave their informed
written consent to the experimental procedure. All experiments were performed according to the Helsinki declaration.
Experimental procedure

Fig. 1 Task Schematic of the task showing the force or angle
required to be exerted on the ankle by the subjects.
A Isometric and quasi-isotonic, ramp and hold contraction
B Slow ramp-and-hold quasi-isotonic contraction

The subjects were seated in an adjustable armchair.
Their right leg was semi-flexed in the hip (120°), theknee flexed to 40°, and the ankle in 10° plantar flexion.
The foot was mounted to a plate during all measurements. The plate was connected to a torque motor. During quasi-isotonic contraction, the foot was left free tomove and an electrical goniometer (SG150, Biometrics,UK) was placed over the right ankle joint for measurement of the position of the joint. “Quasi-isotonic” designates that the movement was performed without any external resistance.

(10%MVC or 10°) and then decrease the level of contraction again within another 1 s. For the slow quasi-isotonic contraction, the subjects were requested to dorsiflex the ankle joint slowly during 4s ( from 0° to 10°)and maintain the obtained level for 2 seconds. Each trial
was repeated 100 times for performing time-coherence
analysis. The torque level of the MVC for each subject
was determined prior to the experiment.

Tasks (Figure 1)

Data recording

At the beginning of the experiments, the subjects wererequested to maintain tonic isometric contraction for 200
seconds in order to measure coherence between the EEG
and EMG signals. If there were significant peaks foundin EEG-EMG coherence, then the subjects were requested
to perform either 1) isometric ramp and hold contraction,2) quasi-isotonic ramp and hold contraction or slow
quasi-isotonic contraction. The ramp and hold task wasdisplayed on the computer screen. To track the displayedtarget torque or angle, smooth isometric or quasi-isotonic
contraction was needed. In the ramp and hold task eachtrial lasted 10 seconds. With the aid of visual feedback of
the torque or the position of the joint, the subjects wererequested to maintain a steady low level of dorsiflexion(5%MVC or 0°) and at intervals of 10 s to increase thecontraction level within 1 s, maintain this level for 4 s

The EMG activity of the tibialis anterior muscle wasrecorded by bipolar surface electrodes (inter electrodedistance: 2 cm) placed in distal site and proximal site.
The amplified EMG signals were filtered (bandpass: 1
Hz to 1 kHz) and sampled at 2 kHz, then stored on a PC
for off-line analysis.
EEG was recorded by needle electrodes or surface
electrodes between Cz and 2cm anterior to Cz. The amplified EEG signals were filtered (bandpass: 1 Hz to 1
kHz) and sampled at 2 kHz, then also stored on a PC for
off-line analysis.
The torque or angle of the ankle joint was also recorded at 2 kHz for off-line analysis.

52

Masakado Y and Nielsen JB: Modulation of corticomuscular coherence

Analysis
Surface EMG records were full wave rectified, and estimated of the autospectra and coherence spectra between EEG and EMG signal were formed for the periodsof maintained tonic contraction.
For the ramp and hold task, the EMG, EEG, torque andposition were examined by eye; trials in which the subjects did not perform correctly were rejected. The onsetof the ramp phase of the contractions was determined byvisual inspection. This was used for subsequent coherence analysis for different segments of data in relation tothe onset of contraction. Time-coherence analysis wasthen performed to determine the modulation of coherence with task performance.
Coherence analysis
Coherence of EEG signal and EMG signal has been
described in detail in previous publications11-13 and will
only be described briefly here.
Coherence is an estimate of the correlation between thefrequency components of two spike trains, N1 and N2,
and may be written as
where λ is the frequency in Herz, ff(λ) represents the
cross-spectrum and f11(λ) and f2 2(λ) represent the autospectra of the two-component processes.
In the time domain, estimates of the cumulant density
function are used to characterize the correlation between
the signals. The cumulant density function, denoted by
qxy(u), is defined as the inverse Fourier transform of thecross spectrum
For two uncorrelated signals, the cumulant has an expected value of zero, deviations from this indicate a correlation between the two signals at a particular time lag,u. Rhythmic inputs will induce symmetrical oscillatorycomponents in the cumulant, the frequency and strengthof these components can be quantified from the corresponding coherence estimates. Cumulant density functions are analogous to cross-correlation functions often
used to quantify spike train data and have a similar interpretation.13
Time-frequency analysis was then performed to determine the modulation ofcoherence with task performance.
Any trends in the data associated with the ramp phasesof the task were first removed using linear regression
techniques. Power spectra and estimates of the coherence
between all of the EMG signals and the EEG were calculated over a sliding 1.28 sec time window with a 256
point Fast Fourier Transform;11 estimates from windows
with the same alignment to the task onset were averaged

Fig. 2 Coherence analysis during isometric tonic contraction
Single subject data for the isometric tonic contraction.
A. Power spectra of EMG recorded from the tibialis anterior
B. Power spectra for EEG
C. EEG-EMG coherence
D. Cross-correlation analysis

across trials. The time window was moved through thetask in 0.1 sec steps to generate a time-frequency map.
Differences between tasks were tested using paired t
tests on coherence estimates in the 15-30 Hz range inhigher holding phase of the task.
Results
Figure 2 shows representative results for a single subject performing tonic contractions. Figures 2A and B
show the power spectra of the TA EMG and the EEGfrom the leg area during tonic contractions lasting 200
seconds. Both spectra show distinct peaks between
10-12, and 18-25Hz. Figure 2C shows the coherence
spectrum between EEG and TA muscle EMG. There wasa single peak in the 15-30 Hz range centered around 20
Hz; this peak was statistically significant. Figure 2dshows the cross-correlation analysis. Seven subjects
from 9 subjects showed significant coherence during
tonic contractions for 200 seconds.

Keio J Med 2008; 57 (1): 50－56

53

Fig. 3 Time-coherence analysis during isometric ramp andhold contraction (from a single subject)

Fig. 4 Time-coherence analysis during ramp and hold quasiisotonic (from a single subject)

Figure 3 shows the results of time frequency of EMG
and EEG and time coherence during isometric ramp andhold contraction in a single subject. Both EEG and EMG
power changed in amplitude during the task. Both EEG
and EMG power in the 15-30Hz was great during thetwo hold periods of the task and for the EMG was reduced during the ramp. The below 10 Hz frequency signal in the EEG trace showed no obvious modulation during the task. The EMG power in the 15-30Hz frequency
band increased during the second hold phase and also
had a higher average frequency. Figures 3 and 4 show
time-frequency EEG-EMG coherence maps for the isometric and quasi-isotonic contractions, respectively. For
both types of contraction, coherence was confined to the
15-30 Hz range, despite the presence of power at higher
and lower frequencies. The coherence showed a marked
relationship with the phase of the movement. It was significant during both hold periods, but abolished during
the ramp phases. The amount of coherence was similar
during the strong contraction (hold phase at high torquelevel (Fig. 3), or at most dorsiflexed position (Fig. 4) as

during the weak contraction (hold phase at low torquelevel (Fig. 3) and least dorsiflexed position (Fig. 4).
Measurements were also made during a very slow
ramp movement without resistance (Fig 5). As can beseen, EEG-EMG coherence was absent when the muscle
was at rest, but appeared soon after the onset of the
movement and then slowly increased until a maximum
when the muscle was maximally activated. There were
no changes in the frequency band showing significant
coherence during the contraction. Figures 6a and b show
data from the same subject as in Figures 2 and 3. As canbe seen, the level of coherence in the 15-30 Hz range
was greater during 1 second of the upper hold phase of
the quasi-isotonic contraction than during the isometriccontraction. Figure 6c shows data from all 7 subjects
who showed significant coherence. In 5 of the 7 subjects
larger coherence was observed in the quasi-isotonic contraction than in the isometric contraction at the higher
level holding phase. For the group of subjects there wasa significantly higher level of coherence during the quasi-isotonic than during the isometric contraction (paired

54

Masakado Y and Nielsen JB: Modulation of corticomuscular coherence

Fig. 5 Time-coherence analysis during slow ramp and holdquasi-isotonic contraction (from a single subject)t-test: p = 0.015).
There are some differences in magnitude of coherence
between individual subjects, but the phase related changes of coherence in the quasi-isotonic or isometric contraction are basically same between subjects. Task related changes of coherence are described above.
Discussion

Fig. 6 The coherence data from mid hold phase in a single
subject.
A isometric
B quasi-isotonic
Left figure shows the coherence data analyses t the beginningof mid contraction. The right figure shows the coherence data
analyses 1 second after the left one.
C The level of coherence is higher in quasi-isotonic contraction
than isometric contraction.

In this study, we have shown that the 15-35 Hz coherence between the motor cortex and leg muscles is strongly modulated during leg movements. The cortico-muscular coherence was most pronounced during the steadyhold period of the task and mostly disappeared duringramp movements. This has similarly been reported forfinger muscles in monkey4 and in man.8 The decrease in
15-35 Hz coherence during the ramp phase may be related to event-related desynchronization and the increase in
the coherence during hold phase may be related to sychronization of EEG activity.14,1 5 Also the firing patternof cortico-motoneuronal (CM) cells during the ramp
phase a large part of the population of CM neurons might

not discharge within the specified frequency band.4
During the ramp phase of both fast and slow contractions, most corticospinal neurons increase their firing
rate as the force is increased, but some may show no
modulation and others may even decrease (possibly due
to recurrent inhibition) their firing rate.1 6 Since discharge of a large part of the population of CM cells at a
specific frequency is necessary in order to observe significant corticomuscular coherence at that frequency, it
is not surprising that no coherence was observed during
the ramp phase.
Recently Baker et al recorded long spike trains simul-

Keio J Med 2008; 57 (1): 50－56

taneously from multiple single neurons in the primary
motor cortex (M1) of two conscious macaque monkeys
performing a precision grip task.17 As a population, synchrony was greatest during the steady hold period in
striking contrast to the averaged cell firing rate, which
was maximal when the animal was moving the levers
into target. At the peak of population synchrony during
the hold period, about half of the synchronization waswithin 18-37 Hz frequency range. They concluded that
assemblies of neurons were synchronized during specificphases of a complex task with potentially important consequences for both information processing within M1
and for the impact of M1 commands on target motoneurones.
It is likely therefore that the changes in synchrony wehave observed during the task reflect changes in the underlying network state between ramp and hold phases.
The finding that synchrony is maximal during the holdphase agrees with the finding that 20- to 30-Hz oscillations in LFPs are confined to this period.4 Pfurtscheller
et al1 8 and Donoghue et al1 9 also reported that oscillations in motor cortical field potentials are strongest during steady holding.
We did not observe any significant coherence outside
the 15-35 Hz frequency range during either the hold or
ramp phases of any of the contractions. It should in particular be noted that significant coherence was not observed outside the 15-35 Hz frequency range even during
the slow quasi-isotonic contraction. This is in contrast to
several previous studies on finger and hand muscles.20-25
Vallbo et al2 0 observed 10Hz oscillation during slow
ramp finger movements and Kakuda et al2 1 reported
6-12 Hz coherence between motor units during the
movement phase of slow finger movements, which decreased during position holding. Thus they suggested
that the 6-12 Hz input is specific for movements and isnormally absent or much weaker during steady maintenance of position or force. During phasic movement execution, Feige et al2 2 found a low-frequency (2-14 Hz)
synchronization between cortical activity and muscle.
Conway et al also found low frequency coherence during rapid contractions.23 In pathological state, the 6-15
Hz coherence was found between cortex and EMG inphysiological tremor.2 4, 2 5 They conclude that cortical
networks are involved in the generation of physiologic
tremor. There is thus some evidence that coherence between cortex and muscle may be seen at frequencies
around 6-12 Hz especially during the movement phasefor both slow and fast finger and hand movements or temor, but we were unable to confirm that this was also thecase for leg muscles. It might be due to the task theyused. They use burst contraction as rapid as possible andthe coherence is established early in the movement but isshort lasting (~100 ms). Therefore the task in this study
was different from the studies as above.

55

The larger level of coherence during quasi-isotonic
contraction may reflect a higher demand of precise control of the joint position. The synchronous firing of neurons may be more effective in causing summation at processing. Thus common oscillatory activity may be morenecessary for quasi-isotonic contraction than isometriccontraction for the binding together of functionally related cortical elements. Between tasks, the control of thetorque and angle might be required especially for quasiisotonic contraction. Therefore the coherent activity
might reflect the combination of these two sources of theinformation. It may also reflect a greater need for binding of functionally related cortical pyramidal tract neurons in quasi-isotonic than in isometric contraction as agroup.
The results demonstrate a systematic relationship between coherence in the 15-30 Hz range and a specificparameter of the motor task. This relationship was only
observed in the degree of coherence between the cortex
and the muscles and was not present in the corresponding power spectra from either the MEG or EMG recordings. It is clear that the cortical activity, which is coherent with the leg muscles, represents something much
more than just an “idling rhythm”.2 6-2 8 It is possiblethat the modulation of coherent oscillatory activity signals and scales these important changes in motor state.
Control of both force and displacement is required forquasi-isotonic contraction; information related to bothparameters is represented in the primary motor cortex,29-32 and it is possible that coherent oscillatory activity reflects the appropriate combination of these twosources of information. The larger level of coherence
during quasi-isotonic contraction may reflect a higher
demand of precise control of the joint position.1-3 It may
also reflect a greater need for binding of functionally related cortical pyramidal tract neurons.
Acknowledgements
Supported by the Danish Research Council, the Elsass
Foundation, the Danish Society of Multiple Sclerosis,
The Henry Hansen Foundation and the Niels and DesireYdes Foundation
References
1. Murthy VN, Fetz EE: Coherent 25-Hz to 35-Hz oscillations in thesensorimotor cortex of awake behaving monkeys. Proc Natl Acad
Sci USA 1992; 89: 5670－74
2. Murthy VN, Fetz EE: Oscillatory activity in sensorimotor cortex
of awake monkeys: synchronization of local field potentials andrelation to behaviour. J Neurophysiol 1996a;76: 3349－67
3. Murthy VN, Fetz EE: Synchronization of neurons during local
field potential oscillations in sensorimotor cortex of awake monkeys. J Neurophysiol 1996b;76: 3968－82
4. Baker SN, Olivier E, Lemon RN: Coherent oscillations in monkey
motor cortex and hand muscle EMG show task-dependent modulation. J Physiol 1997;501:225－41
5. Conway BA, Halliday D, Farmer S, Shahani U, Maas P, Weir A,
Rosenberg J: Synchronization between motor cortex and spinal

56
motoneuronal pool during the performance of a maintained motor
task. J Physiol 1995; 489: 917－924
6. Salenius S, Portin K, Kajola M, Salmelin R, Hari R: Cortical control of human motoneuron firing during isometric contraction. J
Neurophysiol 1997;77:3401－05
7. Hari R, Salenius S: Rhythmical corticomotor communication.Neu
roreport 1999;10:R1-10
8. Kilner JM, Baker SN, Salenius S, Jousmaki V, Hari R, Lemon
RN: Task-dependent modulation of 15-30Hz coherence between
rectified EMGs from human hand and forearm muscles. J Physiol
1999;516:559－70
9. Kilner JM, Baker SN, Salenius S, Hari R, Lemon R: Human cortical muscle coherence is directly related to specific motor parameters. J Neurosci 2000;20:8838－45
10. Baker SN, Kilner JM, Pinches EM, Lemon RN: The role of synchrony and oscillations in the motor output. Exp Brain Res
1999;128:109－17
11. Rosenberg JR Amiad AM, Breeze P Brillinger DR Halliday DM:
The Fourier approach to the identification of the functional coupling between neural spike trains. Prog Biophys Mol Biol
1989;53:1－31
12. Farmer SF, Swash M, Ingram DA, Stephens JA: Changes in motor
unit synchronization following central nervous lesions in man. J
Physiol 1993;463: 83－105
13. Halliday DM, Rosenberg JR, Amjad AM, Breeze P, Conway BA,
Farmer SF: A framework for the analysis of mixed time series/
point process data--theory and application to the study of physiological tremor, single motor unit discharges and electromyograms.
Prog Biophys Mol Biol 1995;64: 237－78
14. Salmelin R, Hari R: Spatiotemporal characteristics of sensorimotor neuromagnetic rhythms related to thumb movement. Neuroscience. 1994;60:537－50
15. Pfurtscheller G, Lopes da Silva FH: Event-ralated EEG/MEG
synchronization and desynchronization: basic principles. Clin
Neurophysiol 1999;110: 1842－57
16. Porter R, Lemon RN: Corticospinal function and voluntary movement. Oxford: Oxford University Press, 1993
17. Baker SN, Spinks R, Jackson A, Lemon RN: Synchronization inmonkey motor cortex during a precision grip task. I. Task-dependent modulation in single-unit synchrony. J Neurophysiol
2001;85:869－85
18. Pfurtscheller G, Stancak A, Neuper C: Post-movement beta synchronization. A correlate of an idling motor area? Electroencephalogr Clin Neurophysiol 1996;98:281－293

Masakado Y and Nielsen JB: Modulation of corticomuscular coherence
19. Donoghue JP, Sanes JN, Hatsopoulos NG, Gaal G: Neural discharge and local field potential oscillations in primate motor cortex during voluntary movements. J Neurophysiol 1998;79:159－73
20. Vallbo AB and Wessberg J: Organization of motor output in slow
finger movements in man. J Physiol 1993;469: 673－91
21. Kakuda N, Nagaoka M, Wessberg J: Common modulation of motor unit pairs during slow wrist movement in man. J Physiol
1999;520:929－40
22. Feige B, Aertsen A, Kristeva-Feige R: Dynamic Synchronization
Between Multiple Cortical Motor Areas and Muscle Activity in
Phasic Voluntary Movements. J Neurophysiol 2000;84: 2622－29
23. Conway BA, Reid C, Halliday DM: Low frequency corlico-muscular coherence during voluntary rapid movements of the wrist
joint. Brain Topogr 2004;16:221－4
24. Raethjen J, Lindemann M, Dümpelmann M, Wenzelburger R,
Stolze H, Pfister G, Elger CE, Timmer J, Deuschl G: Corticomuscular coherence in the 6-15 Hz band: is the cortex involved in thegeneration of physiologic tremor? Exp Brain Res 2002;142:32－
40
25. Raethjen J, Govindan RB, Kopper F, Muthuraman M, Deuschl G.
Cortical involvement in the generation of essential tremor. J Neurophysiol 2007;97:3219－28
26. Adrian ED, Matthews BH. The Berger rhythm: potential changes
from the occipital lobes in man. Brain 1934;57:355－385
27. Buser P: Thalamocortical mechanisms underlying synchronised
EEG activity. In: Halliday AM, Butler SR, Paul R, eds, A textbookof clinical neurophysiology, Chichester, UK: Wiley, 1987;595－
621
28. Lopes da Silva F: Neural mechanisms underlying brain waves:from neural membranes to networks. Electroencephalogr Clin
Neurophysiol 1991;79:81－93
29. Wannier TMJ, Maier MA, Hepp-Reymond M: Contrasting properties of monkey somatosensory and motor cortex neurons activatedduring the control of force in precision grip. J Neurophysiol
1991;65:572－589
30. Picard N, Smith AM: Primary motor cortical activity related to theweight and texture of grasped objects in the monkey. J Neurophysiol 1992;68:1868－188
31. Hepp-Reymond M, Kirkpatrick-Tanner M, Gabernet L, Qi HX,
Weber B: Context-dependent force coding in motor and premotor
cortical areas. Exp Brain Res 1999;128:123－133
32. Kakei S, Hoffman DS, Strick P: Muscle and movement representations in the primary motor cortex. Science 1999;285:2136－2139