Order 1106099: migraine

Neuromagnetic Abnormality of Motor Cortical Activation and Phases of Headache Attacks in Childhood Migraine Jing Xiang1,2*, Xinyao deGrauw1, Abraham M. Korman1, Janelle R. Allen3, Hope L. O’Brien1,2,

Marielle A. Kabbouche1,2, Scott W. Powers3, Andrew D. Hershey1,2

1 Division of Neurology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America, 2 Department of Pediatrics, University of Cincinnati,

College of Medicine, Cincinnati, Ohio, United States of America, 3 Division of Behavioral Medicine and Clinical Psychology, Cincinnati Children’s Hospital Medical Center,

Cincinnati, Ohio, United States of America

Abstract

The cerebral cortex serves a primary role in the pathogenesis of migraine. This aberrant brain activation in migraine can be noninvasively detected with magnetoencephalography (MEG). The objective of this study was to investigate the differences in motor cortical activation between attacks (ictal) and pain free intervals (interictal) in children and adolescents with migraine using both low- and high-frequency neuromagnetic signals. Thirty subjects with an acute migraine and 30 subjects with a history of migraine, while pain free, were compared to age- and gender-matched controls using MEG. Motor cortical activation was elicited by a standardized, validated finger-tapping task. Low-frequency brain activation (1,50 Hz) was analyzed with waveform measurements and high-frequency oscillations (65–150 Hz) were analyzed with wavelet-based beamforming. MEG waveforms showed that the ictal latency of low-frequency brain activation was significantly delayed as compared with controls, while the interictal latency of brain activation was similar to that of controls. The ictal amplitude of low-frequency brain activation was significantly increased as compared with controls, while the interictal amplitude of brain activation was similar to that of controls. The ictal source power of high-frequency oscillations was significantly stronger than that of the controls, while the interictal source power of high-frequency oscillations was significantly weaker than that of controls. The results suggest that aberrant low-frequency brain activation in migraine during a headache attack returned to normal interictally. However, high-frequency oscillations changed from ictal hyper-activation to interictal hypo-activation. Noninvasive assessment of cortical abnormality in migraine with MEG opens a new window for developing novel therapeutic strategies for childhood migraine by maintaining a balanced cortical excitability.

Citation: Xiang J, deGrauw X, Korman AM, Allen JR, O’Brien HL, et al. (2013) Neuromagnetic Abnormality of Motor Cortical Activation and Phases of Headache Attacks in Childhood Migraine. PLoS ONE 8(12): e83669. doi:10.1371/journal.pone.0083669

Editor: Jay Pillai, Johns Hopkins School of Medicine, United States of America

Received April 19, 2013; Accepted November 6, 2013; Published December 27, 2013

Copyright: � 2013 Xiang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The project described was supported by Grant Number R21NS072817 from the National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

Introduction

Previous studies of migraine have suggested that not only can

untreated or ineffectively treated migraines become progressive,

but over the long-term, they may cause neurological changes

significant enough to be quantified with neuroimaging [1–6]. The

cerebral cortex serves a primary role in the pathogenesis of

migraine. There is accumulating evidence that adults with

migraine are associated with aberrant activation in the somato-

sensory, visual, and auditory cortices during attacks (ictal), as well

as, during the pain free period (interictal) [7–10].

The involvement of the motor cortex in hemiplegic migraine, a

small subset of migraine cases, is clinically significant [11–15].

With an alternate finger tapping task, psychomotor dysfunction

has also been found in typical migraine diagnosed according to

international headache society (IHS) criteria [16]. It seems that

motor coordination is also impaired in patients with migraine

during headache attacks [17]. Reports on non-familial migraine

with unilateral motor symptoms (MUMS) showed that a syndrome

of severe migraine with accompanying give-way weakness is

common in tertiary care headache centers [5]. Approximately,

58% of patients with MUMS reported persistent weakness

between headache attacks [5]. Functional magnetic resonance

imaging (fMRI) study of migraine has found that the supplemen-

tary motor area (SMA) is abnormal in migraine even at resting

state [18]. An increasing list of transcranial magnetic stimulation

(TMS) reports indicate that motor cortical dysfunction may play

an important role in the pathogenesis of attacks of migraine [19–

24]. Importantly, high-frequency repetitive TSM (rTMS) of the

motor cortex can normalize aberrant intracortical inhibition in

migraine [25]. Neurophysiologically, rTMS of the motor cortex

can also modulate pain-related evoked responses in migraine

patients [26]. Recent reports have also revealed that the spread of

abnormal ictal brain activation triggered by movements plays a

key role in the pathogenesis of pediatric migraine [27–29]. It

remains unclear whether these changes in motor cortical

activation persist during the headache free period.

The development of neuroimaging technologies, such as

magnetoencephalography (MEG) has made it possible to nonin-

vasively investigate the underlying neurophysiological mechanisms

of migraine [10,30,31]. It has been shown that neuromagnetic

brain activation is significantly increased in patients with migraine

[10,32,33]. Previous MEG studies of migraine typically focused on

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neuromagnetic waveforms in a low-frequency range, such as DC-

MEG signals [10,30,31]. Recent reports suggest that the brain

generates high-frequency oscillations (HFOs) or high-gamma

oscillations that can be detected and localized with newly

developed MEG methods such as wavelet-based beamforming

techniques [29,34]. The examination of HFOs has the potential to

provide key information about the cerebral mechanisms of

migraine, as HFOs are well-localized and can be quantified at

source space [29]. Currently, no reports specifically focus on

HFOs during interictal periods, or the correlations between HFOs

and the phases of headache attacks in pediatric migraine. HFOs

are important in the study of migraine for at least two reasons: (1)

recent reports showed that migraine is associated with cortical

hyper-excitability or hypo-excitability in various brain areas

[23,35–38]. HFOs, which can be well localized and quantified

at source space, can provide precise information about where and

to what degrees of alteration of cortical excitability is occurring in

migraine. (2) Transcranial magnetic stimulation (TMS)

[23,35,37,39,40] and other spatially targeted treatment (e.g.

transcranial direct current stimulation, tDCS) [41] can reduce

headache in migraine by normalizing focal cortical excitability.

HFOs may provide critical spatial information to guide spatially

targeted treatments for better clinical outcomes.

The aim of this study was to quantitatively determine if there

are any differences in low- and high-frequency brain signals during

ictal and interictal time periods using MEG. Since the pain of

many migraine sufferers worsens with physical activity [42,43] and

previous reports have confirmed that neuromagnetic signals in 65–

150 Hz (high-gamma oscillations) in motor cortex can be reliably

elicited by a finger tapping task [34,44,45], this study focused on

neuromagnetic high-gamma oscillations in the motor cortex.

MEG data were analyzed with the conventional waveform

measurement [46], as well as, a new wavelet based beamforming

technique [47]. The new technique enabled us to quantify

neuromagnetic high-gamma oscillations at source space [28],

while the conventional waveform measurements enabled us to

analyze low-frequency brain activation and compare our results

with previous reports typically focusing on MEG waveforms

[10,48].

Materials and Methods

Participants Sixty patients with migraine (migraine subjects) were recruited

from the Headache Center at Cincinnati Children’s Hospital

Medical Center (CCHMC). Twenty eight ictal subjects (20 girls, 8

boys; mean age 6SD: 15.062.1 years) and 28 interictal subjects

(20 girls, 8 boys; mean age 6SD: 15.362.3 years) were analyzed.

Of the 60 subjects, 4 subjects did not meet the inclusion and

exclusion criteria. Inclusion criteria were migraine without aura as

defined by the International Classification of Headache Disorders,

2nd Edition (ICHD-II) [49,50]; and no other neurological

disorder. Interictal subjects were recorded at least 3 days before

or after a migraine attack. Healthy controls were recruited to

match the patients for age and gender and met inclusion criteria of

being healthy without a history of neurological disorders,

migraine, or brain injury, and age-appropriate hearing, vision,

and hand movement. Exclusion criteria for all participants were:

(1) presence of an implant, such as cochlear implant devices, a

pacemaker or neuro-stimulator, devices containing electrical

circuitry, generating magnetic signals, or having other metal that

could produce visible magnetic noise in the MEG data; (2) inability

to remain still; (3) inability to cooperate with personnel operating

the MEG equipment. The research protocol, assent and consent

forms were formally reviewed and approved by the Institutional

Review Board (IRB) at CCHMC. The migraine subjects were pre-

screened by neurologists certified in headache medicine. If a

subject and parent/guardian met the criteria and were interested

in our MEG study, a researcher would explain the research

protocol and obtain written informed assent and consent from the

participant and her/his parents. Both the participant and her/his

parents were provided with a questionnaire that included an

assessment of headache (pain) severity on a scale of 0 to 10 (10

being the worst). The MEG recordings for ictal subjects were

performed prior to initiation of treatment. The MEG recordings

for interictal subjects were performed after confirming that the

subjects did not have migraine attacks for at least 3 days.

Motor Task All subjects performed a brisk index finger tapping task with

either the right or the left index finger immediately after hearing a

cue (500 Hz, square wave tone). Subjects were instructed to press a

response button with the index finger that was ipsilateral to the

tone presented, while keeping other body parts still [34]. Their

eyes were open and fixed to an arbitrary target during the

paradigm. A trigger was sent to the MEG system from the

response box when the button was pressed. The stimuli consisted

of 200 trials of square tones, 100 trials per ear, and were presented

randomly through a plastic tube and earphones. The inter-

stimulus interval of the sound cue was 0–1000 ms, which varied

from 0 to 1000 ms randomly. Stimulus presentation and response

recording were accomplished with BrainX software, which was

based on DirectX (Microsoft Corporation, Redmond, WA, USA)

[34].

MEG Recordings The MEG signals were recorded in a magnetically shielded

room (Vacuum-Schmelze, Hanau, Germany) using a whole-cortex

CTF 275-Channel MEG system (VSM MedTech Systems Inc.,

Coquitlam, BC, Canada). Before data acquisition began, electro-

magnetic coils were attached to the nasion, left and right pre-

auricular points of each participant. These three coils were

subsequently activated at different frequencies for measuring

participants’ head positions relative to the MEG sensors. The

sampling rate of the MEG recordings was 6000 Hz (very high-

frequency signals were analyzed in another study). An acquisition

window was set to 3000 milliseconds (ms) per trial, with 2000 ms

pre-trigger. Data were recorded with a noise cancellation of third

order gradients. Subjects were asked to remain still. If head

movement during a recording was beyond 5 mm, that dataset was

indicated as ‘‘bad’’ and an additional trial was recorded.

Magnetic Resonance Imaging (MRI) Scans Three-dimensional (3D) MRI was obtained using a 3 T Philips

Achieva (Philips Healthcare, 3000 Minuteman Road, Andover,

MA). Three fiduciary points were placed in identical locations to

the positions of the three coils used in the MEG recordings, with

the aid of digital photographs to allow for an accurate co-

registration of the two data sets. Subsequently, all anatomical

landmarks were made identifiable in the MRIs. Pediatric Brain

Templates developed by the Pediatric Neuroimaging Research

Consortium (PNRC) [51] and CCHMC MEG Center [34] were

also used for group comparison and visualization.

Waveform Analyses To analyze conventional low-frequency brain activity

[8,29,52,53], MEG waveforms were manually averaged using

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MEG Processor for identification of response components

(deflections). The averaged MEG data were preprocessed by

removing the DC offset based on the pre-trigger baseline as well as

linear trend. The triggers were elicited by pressing the response

button. An off-line high pass filter and low pass filter were applied

for viewing signals in 1–50 Hz. The latencies and amplitudes of

each recognizable peak were measured for each subject with a

customer-designed program, MEG Processor.

Wavelet-based Beamforming Analyses Magnetic sources were scanned with a newly developed

beamforming technique [47]. Each voxel in the source scan

utilized a sensor beam according to its lead field. Multiple local

spheres were used for magnetic forward computing. MEG

Processor was used to compute magnetic sources [45]. Before

doing beamforming analysis, a multiple local sphere head model

was created for each subject. Beamforming was applied to estimate

the cortical source power integrated over the time window for 65–

150 Hz frequency band in 5 mm steps. The time-window and

frequency band were determined by using our pilot data, as well

as, normative data from previous experiments [29,45]. The

choosing of 65–150 Hz also allowed us to avoid the power-line

noise around 60 Hz. The results were visualized using a Magnetic

Source Locator (MSL) software program [29,45].

Statistical Analyses MEG measurements were statistically analyzed with multiple

analyses of variance (ANOVA). The fixed factors were group

(interictal, ictal, and control groups) and age (categorized by

quartiles). The dependent variables were magnetic source power

and the latency and amplitude of waveforms. For multiple

comparisons, a Bonferroni multiple comparisons correction was

applied. The odds ratio of activity in brain areas among the

migraine and control groups was analyzed with Fisher’s exact tests.

The correlation between headache severity and MEG parameters

(latency, amplitude, and magnetic source power) were analyzed

with spearman correlation. Significance was accepted at the level

of p,0.05 for one test. If multiple testing were to be taken into

account then the significance level for any one of these tests were

reduced from 0.05 to 0.025 (two parameters) or 0.016 (three

parameters).

Results

1. Clinical Characteristics Twenty out of the 28 ictal subjects and 20 out of the 28

interictal subjects were girls (20/28, 71%). The gender ratio in the

ictal and interictal groups was 2.5 vs. 1.0. In the ictal group, 24

subjects had moderate to severe headache (24/28, 86%) and 22

subjects had bilateral headache attacks (22/28, 78%). The severity

(scale from 0 to 10) of headache attack’s range (mean 6SD) in the

migraine subjects during headache attacks was 6.862.7.

2. Low-frequency Waveforms The MEG waveforms in 1–50 Hz recorded from 24 out of the

28 ictal subjects and 24 out of the 28 interictal subjects showed at

least two responses (deflections), which were named as M1 and

M2. All the age- and gender-matched healthy controls had two

responses. Figure 1 shows representative waveforms from a subject

during a migraine attack (ictal), a subject between migraine attacks

(interictal), and a control. Since the waveforms were elicited by left

or right finger movements, there were two sets of waveforms for

each group of subjects. Both ictal and interictal MEG waveforms

had a larger variation in morphology among subjects in each

group than control MEG waveforms. The latencies and ampli-

tudes of interictal MEG waveforms were more similar to those of

the control waveforms than to those of the ictal MEG waveforms.

The quantitative measurements of the waveforms of all the three

groups of subjects are shown in Figure 2 and Figure 3. To be

consistent, in Figures 1–3, red indicates ictal data, blue indicates

interictal data, and green indicates control data.

ANOVA with repeated measures revealed that headache

attacks significantly affected the latencies of M1 and M2

(Figure 2), independent of age and gender (F = 7.94, p,0.001).

Pairwise comparisons found that there were significant latency

differences of M1 and M2 between ictal and control groups during

left (p,0.01; p,0.025) and right (p,0.01; p,0.01) finger

movements, respectively.

There were no latency differences of M1 and M2 between

interictal and control groups following left or right finger

movements (p.0.05). Compared with ictal group, the latencies

of M1 and M2 in interictal group were significantly shortened

during left (p,0.01; p,0.025) or right (p,0.025, p,0.025) finger

movements, respectively. In other words, the interictal latencies of

M1 and M2 were similar to the controls and were significantly

different from ictal latencies.

ANOVA with repeated measures revealed that headache

attacks significantly affected the amplitudes of M1 and M2

(Figure 3). The amplitude of M2 during left finger movement was

mostly affected (F = 4.86, p,0.025), independent of age and

gender. Pairwise comparisons revealed a significant amplitude

difference of M1 between ictal and control groups during left or

right finger movement (p,0.05). Though the latency of ictal M2

during right finger movement was longer than that of the control,

there was no statistical difference.

There were no amplitude differences of M1 and M2 between

interictal and control groups following left or right finger

movements (p.0.05). Compared with ictal group, the amplitudes

of M1 and M2 in interictal group were significantly decreased

during left or right finger movements (p,0.05). Thus, the interictal

amplitudes of M1 and M2 were similar to the controls and were

significantly different from ictal amplitudes.

3. High-gamma Oscillations The MEG source imaging data were analyzed in an effort to

determine the ictal and interictal spatial and spectral signatures of

aberrant high-gamma oscillations (Figure 4 and Figure 5). The

high-gamma oscillations were localized to the contralateral

primary motor cortex in 28 ictal subjects and 28 interictal

subjects. High-gamma oscillations in the 28 age- and gender-

matched controls were also localized to the contralateral primary

motor cortex. There was no significant difference among the three

groups in terms of source location (X, Y, and Z coordinates) in the

primary motor cortex (p.0.05). The MNI (Montreal Neurological

Institute) coordinates of the location of movement-elicited brain

activation are shown in Table 1. Though there were no statistical

differences of the coordinates of the location of movement-elicited

brain activation between the three groups of subjects, the ictal

groups tended to have a greater variation among subjects within

the group, which was indicated by a larger standard deviation.

High-gamma oscillations were identified in the supplement

motor area (SMA) in 7 interictal subjects (25%, 7/28), 24 ictal

subjects (86%, 24/28) and 6 healthy controls (23%, 6/26)

following left or right finger movements. Ictal subjects had

significantly higher odds of activation in the SMA (p,0.001) as

compared to either healthy controls or interictal subjects. There

was no significant difference between ictal subjects and healthy

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controls in terms of the activation in the SMA following either left

or right finger movements (p.0.05).

Analyses of neuromagnetic source power in the primary motor

cortex with ANOVA revealed that the strength of neuromagnetic

activation was significantly affected by the headache attack phases

(F = 6.792, p,0.01) following left or right finger movements

(F = 7.864, p,0.005), independent of age and gender.

Post-hoc pairwise comparisons indicated that the strength of

neuromagnetic activation in ictal subjects was significantly higher

than that of healthy controls following left or right finger

movements (p,0.025). The strength of neuromagnetic activation

in interictal subjects was significantly lower than that of healthy

controls following left or right finger movements (p,0.01). The

strength of neuromagnetic activation in interictal subjects was

significantly lower than that of ictal subjects following left or right

finger movements (p,0.001). Figure 6 shows the summary of

neuromagnetic source power elicited by finger movements in the

three groups of subjects.

4. Headache Severity and Neuromagnetic Brain Activity The correlations between the severity of headache attacks and

the latencies of M1 and M2 were 0.48 and 0.47 (p.0.025) for left

and 0.51 and 0.49 (p.0.025) for right finger movements. The

correlations between the severity of headache attacks and the

amplitudes of M1 and M2 were 0.54 and 0.46 (p.0.025) for left

and 0.52 and 0.42 (p.0.025) for right finger movements. The

correlations between the severity of headache attacks and the

source power of high-gamma oscillations in the primary motor

cortex were 0.68 (p,0.01) for left and 0.64 (p,0.01) for right

finger moments.

Discussion

The present study examined neuromagnetic activation in a low-

frequency range of 1–50 Hz and high-gamma activation in 65–

150 Hz during headache attack and pain free periods using

conventional measurements of waveforms, as well as, newly

developed source localization methods [8,29,33]. The frequency

band in which the MEG data were analyzed was determined with

several considerations and pilot data. The waveform analysis was

Figure 1. Movement-evoked magnetic waveforms from a subject during a migraine attack (‘‘Ictal’’), a subject between migraine attacks (‘‘Interictal’’), and a healthy control (‘‘Control’’). One waveform is from one sensor with highest amplitude of M1 among all sensors. Two neuromagnetic responses (‘‘M1’’ and ‘‘M2’’) following left or right finger movements are identifiable on each waveform in all the three subjects. The X-axis indicates latency; the Y-axis indicates amplitude. doi:10.1371/journal.pone.0083669.g001

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based on an averaging of multi-trial MEG data. Averaging keeps

time or phase-locked signals while minimizing time-variable

signals (such as random noise). Since low-frequency brain activity

change slowly with time and high-frequency brain activity changes

rapidly with time, averaging keeps low-frequency brain activity,

while minimizing high-frequency brain activity. The mathematical

reasoning is that a small natural variation in time among multiple

trials may significantly change the phase of high-frequency signals

but not the low-frequency signals. Therefore, averaging based

waveform analysis can only be used to analyze low-frequency

signals (1–50 Hz) in our movement-related studies. Beamformer,

on the other hand, was developed to analyze non-time-locked

signals, because it computes a covariance matrix of MEG data

without averaging the waveforms. For a given time-window, the

higher the number of oscillatory waveforms (higher frequency), the

more stable the covariance matrix will be. Consequently,

Figure 2. The latencies of the first two movement-evoked magnetic responses (‘‘M1’’ and ‘‘M2’’) during a migraine attack (‘‘Ictal’’), between attacks (‘‘Interictal’’), and healthy control (‘‘Control’’). Each bar represents the mean value and standard deviation (SD) of the corresponding latency. ‘‘**’’ indicates p,0.01; ‘‘*’’ indicates p,0.025. doi:10.1371/journal.pone.0083669.g002

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beamformer is suitable for analyzing rapid oscillatory activity, such

as high-gamma activity (65–150 Hz), because the time window of

movement-related brain activity is limited (,400 ms). We chose

1–50 Hz and 65–150 Hz, but not 40–100 Hz, because the power-

line noise in the USA is 60 Hz. MEG is sensitive to magnetic noise

generated by power-lines, therefore, our study avoided this noise.

Building on our previous study [34] and pilot data, we found 1–

50 Hz is suitable for waveform analysis and 65–150 Hz is suitable

for beamformer analysis.

The results have demonstrated that the latencies of neuromag-

netic responses evoked by finger tapping during the attacks, ictal

neuromagnetic responses, were significantly delayed as compared

with age- and gender-matched healthy controls. This observation

is consistent with previous reports on childhood migraine [28,29].

This is the first report showing that the latencies of ictal

neuromagnetic responses following finger movements were also

significantly delayed as compared with the latencies of interictal

neuromagnetic responses as well as controls. There were no

latency differences between interictal neuromagnetic responses

and controls. It seemed that the latencies of interictal neuromag-

netic responses were in a normal level as compared with controls.

These MEG results suggest that prolongations of brain responses

are associated with the headache attack phase and these

prolongations of brain responses do not persist within the pain

free period.

Figure 3. The amplitudes of the first two movement-evoked magnetic responses (‘‘M1’’ and ‘‘M2’’) during a migraine attack (‘‘Ictal’’), between attacks (‘‘Interictal’’), and healthy control (‘‘Control’’). Each bar represents the mean value and standard deviation (SD) of the corresponding amplitude. ‘‘*’’ indicates p,0.05; ‘‘**’’ indicates p,0.025. doi:10.1371/journal.pone.0083669.g003

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The amplitudes of ictal neuromagnetic responses following

finger movements were significantly increased as compared with

the amplitudes of interictal neuromagnetic responses, as well as,

with controls. This observation is slightly different from previous

reports on childhood migraine, which showed a trend of increased

amplitude during a headache attack (ictal) without statistical

significance [28,29]. This difference is likely due to the number of

subjects in the present study, which is larger than that within

previous reports [28,29], and due to improvements in MEG

analysis and procedures leading to better accuracy. MEG

waveforms filtered with our new MEG methods (see Figure 1)

are clearer, as compared with previous reports [28,29]. One of the

important findings of this study is that amplitudes of interictal

neuromagnetic responses were in a normal level as compared with

controls. It seems that aberrant ictal amplitudes returned to a

normal level interictally. This is the first report showing interictal

normalization of the amplitudes of neuromagnetic responses

related to finger-movements.

The cerebral mechanism of the aforementioned normalization

of neuromagnetic responses remains unclear. There is evidence

that neuromagnetic activation changes with the ictal-interictal

cycle of migraine [32]. It has been hypothesized that the dynamic

variation of cortical abnormality in migraineurs during headache

attack phase may reflect a change of serotonin transmission [54].

The ictal neuromagnetic alteration of motor cortex activation may

reflect a transient cortical dysfunction. Once the migraine attack

subsides, the functionality of the motor cortex may return to a level

that is close to normal. Thus, there are neurophysiological changes

associated with the subsidence of migraine headache attacks. We

postulate that ictal cerebral dysfunction during a migraine is

neurophysiologically reversible to a certain degree.

The measurements of neuromagnetic high-gamma oscillations

have shown that spectral power of motor cortical activation during

headache attack phase was significantly increased as compared to

controls, which is consistent with previous MEG studies [10,29].

Increased brain activation has been considered to be a result of

cortical hyperexcitability [7,55,56]. Although the underlying

mechanisms of increased activation in the primary motor cortex

remain unclear, cortical excitability is the target of many new

treatments [10]. MEG study of cortical excitability may play an

important role in developing better and more effective therapeutic

interventions for migraine in the future [57].

One of the most interesting findings is the decrease of

neuromagnetic high-gamma oscillations (or hypo-activation) inter-

ictally as compared with controls. Although there are reports on

interictal neuromagnetic activation in migraine [10,32], the

previous studies mainly focused on low-frequency brain waveforms

in adult migraine. This study specifically focused on high-gamma

oscillations in the motor cortex comparing ictal and interictal

neurophysiology. This MEG data demonstrated that spectral

power of interictal neuromagnetic high-gamma oscillations was

significantly lower than that of the ictal neuromagnetic high-

gamma oscillations and controls.

Figure 4. Magnetic source imaging (MSI) showing the locations of left finger movement-elicited high-gamma oscillations in a subject during a migraine attack (‘‘Ictal’’), a subject between attacks (‘‘Interictal’’), and a healthy control (‘‘Control’’). The primary motor cortex in the contralateral hemisphere is activated in all three subjects. The supplementary motor area is activated only during a migraine attack (green arrow). ‘‘R’’ indicates right; ‘‘L’’ indicates left. ‘‘A’’ indicates anterior; ‘‘P’’ indicates posterior. doi:10.1371/journal.pone.0083669.g004

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This observation is very interesting and important for several

reasons. First, the MEG results suggest that migraineurs, while

pain free, have distinct ‘‘neurophysiologically patterns’’, compared

to control subjects without a history of migraine. Second, pain free

periods are associated with unique aberrant brain activation,

which is different from ictal aberrant brain activation. Cortical

functionality in migraineurs changes from hyper-activation to

hypo-activation as migraine moves from the headache attack to

the pain free period. This neuromagnetic fluctuation of high-

gamma oscillations appears to serve as a very useful biomarker to

investigate the periodic nature of migraine using MEG as a

noninvasive tool.

The neurophysiological underpinnings of the fluctuation of

high-gamma oscillations comparing attack and pain free period

have rarely been studied with MEG. Previous reports have shown

that repetitive transcranial magnetic stimulation (rTMS) can

normalize habituation of the somatosensory system in migraine

patients [58,59]. It seems that dysfunctioning thalamo-cortical

loops may be responsible for the interictal habituation deficit in

migraine. It has also been found that about two-thirds (65%) of

patients affected by either migraine type present an increased

phosphene threshold in the interictal period, which suggests that

their visual cortex is hypoexcitable during headache free phase

[60]. A recent report using EEG has found that the amplitude of

interictal early presynaptic high-frequency oscillations in the

somatosensory system was significantly correlated to the clinical

evolution [7]. Noteworthy, there is accumulating evidence that

patients with migraine during pain free periods might be

Figure 5. Magnetic source imaging (MSI) showing the locations of right finger movement-elicited high-gamma oscillations during a migraine attack (‘‘Ictal’’), between attacks (‘‘Interictal’’), and a healthy control (‘‘Control’’). The primary motor cortex in the contralateral hemisphere is activated in all three subjects. The supplementary motor area is activated only during a migraine attack (green arrow). ‘‘R’’ indicates right; ‘‘L’’ indicates left. ‘‘A’’ indicates anterior; ‘‘P’’ indicates posterior. doi:10.1371/journal.pone.0083669.g005

Table 1. The MNI coordinates of the source locations of movement-elicited brain activation (in millimeters).

Moving Finger Location Ictal Interictal Control

Left M1 *

51.965.2 $ 49.864.6 48.263.8

(28/28)# 26.664.1 25.463.9 24.663.2

49.764.9 50.464.1 50.463.8

SMA *

1.968.1 1.765.6 1.464.9

(24/28) 1.566.3 1.665.8 1.865.2

51.267.6 52.766.4 53.366.6

Right M1 249.166.3 247.864.6 248.263.8

(28/28) 28.664.1 27.663.9 27.663.2

51.764.9 50.864.1 50.463.8

SMA 22.166.1 21.465.3 21.764.2

(24/28) 1.967.3 2.164.8 1.563.7

52.268.6 51.766.2 50.165.3

*M1: primary motor cortex; SMA: supplementary motor area. #

Number of subjects with activation/total number of tested subjects. $ Mean 6 Standard Deviation. The three numbers are the values of X, Y and Z

coordinates. doi:10.1371/journal.pone.0083669.t001

MEG Pattern of Childhood Migraine Phases

PLOS ONE | www.plosone.org 8 December 2013 | Volume 8 | Issue 12 | e83669

associated with cortical hypo-activation. The exact cerebral

mechanism of the fluctuation of high-gamma oscillations in

migraine remains unknown. Recent advances in neuroscience

suggest that synaptic specialization turns interneuron networks

into gamma frequency oscillators [61]. Specifically, the origin of

high-gamma oscillations may be generated by GABAergic cortical

interneurons. Consequently, the ictal hyper-activation and inter-

ictal hypo-activation may indicate an imbalance among excitatory

and inhibitory cortical circuits that could predispose migraineurs

to periodic headache attacks [7,61].

Based on previous reports on migraine [28,29,53], we

hypothesized that the source power of neuromagnetic high-

gamma oscillations changes with the phases of periodic headache

attack in childhood migraine. This study is clinically important for

at least two reasons. First, our MEG data were recorded from

children with migraine which might be unique as compared with

many previous reports focusing on adult migraine [10,32,48].

Second, recent reports [62–71] have shown that normalization of

cortical excitability may prevent and even cure migraine

headaches. If the location and type of cortical dysfunction

occurring during the phases of migraine attacks could be

noninvasively determined, all of the preventions and treatments

targeted at cortical dysfunction [39,72,73] – which currently show

great promise – could be specified, refined, and their outcomes

significantly improved in the future.

The results of MEG source localization have revealed that

neuromagnetic high-gamma oscillations are well-localized. The

present results are consistent with previous reports that show that

MEG provides excellent localization accuracy especially for

superficial sources [74,75]. Papadelis and colleagues have found

that the human high-frequency oscillations (HFOs) can be reliably

detected noninvasively. A superficial phantom’s source was

localized with an accuracy of 2–3 mm with MEG. In addition,

MEG sources can be linked with the cytoarchitectonic identity of

the underlying region [74]. This observation is important and

might be critical for developing spatially targeted treatments for

migraine. For example, high-frequency rTMS increase and low-

frequency rTMS decrease neural excitability of the stimulated

cortex [40,56,76]. If neuromagnetic high-gamma oscillations could

reliably reveal the location and types of cortical dysfunction

occurring during the phases of migraine attacks, all of the

preventions and treatments targeted at cortical excitability

[39,72,73] could be refined and optimized. Specifically, the

present study showed that the spectral power of neuromagnetic

high-gamma oscillations was increased in children with migraine,

during headache attack phase, while decreased in children with

Figure 6. The neuromagnetic source power elicited by finger movements during a migraine attack (‘‘Ictal’’), between attacks (‘‘Interictal’’), and healthy control (‘‘Control’’). Each bar represents the mean value and standard deviation (SD) of the corresponding neuromagnetic source power. ‘‘**’’ indicates p,0.01; ‘‘*’’ indicates p,0.025. doi:10.1371/journal.pone.0083669.g006

MEG Pattern of Childhood Migraine Phases

PLOS ONE | www.plosone.org 9 December 2013 | Volume 8 | Issue 12 | e83669

migraine, during headache free phase, in children with migraine.

Building on previous results [74,75] and the present data,

noninvasive stimulation (e.g. TMS) may be used to spatially

adjust cortical excitability during and between headache attacks,

so as to cure and prevent headache attacks for migraine patients.

Therefore, we consider the present study to lay an important

foundation for clinical management of migraine in the future.

In conclusion, the MEG results of the present study have

demonstrated that there was interictal normalization of motor

cortical activation in a low-frequency range (1–50 Hz). However,

the strength of interictal high-gamma oscillations (65–150 Hz) was

significantly lower than that of ictal high-gamma oscillations, as

well as, controls in the motor cortex. The ictal hyper-activation

and interictal hypo-activation may indicate an imbalance among

excitatory and inhibitory cortical circuits that could predispose

migraineurs to periodic migraine attacks.

Acknowledgments

We thank Ms. Susan LeCates, Ms. Polly Vaughan, Ms. Shannon White,

Ms. Judy Bush, Ms. Paula Manning, and Ms. Ann Segers for recruiting

participants. We thank Dr. Douglas Rose, Mr. Nat Hemasilpin, and Ms.

Hisako Fujiwara for helping with MEG recordings. We thank Dr. Hongtao

Chu, Dr. Milena Korostenskaja, and Ms. Yingying Wang for helping with

data analysis and management.

Author Contributions

Conceived and designed the experiments: ADH JX XD HLO MAK SWP.

Performed the experiments: JX XD AMK JRA. Analyzed the data: JX

AMK XD. Contributed reagents/materials/analysis tools: JX. Wrote the

paper: JX XD AMK JRA HLO MAK SWP ADH.

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