Effective Connectivity of Cortical Sensorimotor Networks During Finger Movement Tasks: A Simultaneous fNIRS, fMRI, EEG Study.

Recently, interest has been growing to understand the underlying dynamic directional relationship between simultaneously activated regions of the brain during motor task performance. Such directionality analysis (or effective connectivity analysis), based on non-invasive electrophysiological (electroencephalography-EEG) and hemodynamic (functional near infrared spectroscopy-fNIRS; and functional magnetic resonance imaging-fMRI) neuroimaging modalities can provide an estimate of the motor task-related information flow from one brain region to another. Since EEG, fNIRS and fMRI modalities achieve different spatial and temporal resolutions of motor-task related activation in the brain, the aim of this study was to determine the effective connectivity of cortico-cortical sensorimotor networks during finger movement tasks measured by each neuroimaging modality. Nine healthy subjects performed right hand finger movement tasks of different complexity (simple finger tapping-FT, simple finger sequence-SFS, and complex finger sequence-CFS). We focused our observations on three cortical regions of interest (ROIs), namely the contralateral sensorimotor cortex (SMC), the contralateral premotor cortex (PMC) and the contralateral dorsolateral prefrontal cortex (DLPFC). We estimated the effective connectivity between these ROIs using conditional Granger causality (GC) analysis determined from the time series signals measured by fMRI (blood oxygenation level-dependent-BOLD), fNIRS (oxygenated-O2Hb and deoxygenated-HHb hemoglobin), and EEG (scalp and source level analysis) neuroimaging modalities. The effective connectivity analysis showed significant bi-directional information flow between the SMC, PMC, and DLPFC as determined by the EEG (scalp and source), fMRI (BOLD) and fNIRS (O2Hb and HHb) modalities for all three motor tasks. However the source level EEG GC values were significantly greater than the other modalities. In addition, only the source level EEG showed a significantly greater forward than backward information flow between the ROIs. This simultaneous fMRI, fNIRS and EEG study has shown through independent GC analysis of the respective time series that a bi-directional effective connectivity occurs within a cortico-cortical sensorimotor network (SMC, PMC and DLPFC) during finger movement tasks.

Oscillating central motor networks in pathological tremors and voluntary movements. What makes the difference?

Parkinsonian tremor (PD), essential tremor (ET) and voluntarily mimicked tremor represent fundamentally different motor phenomena, yet, magnetoencephalographic and imaging data suggest their origin in the same motor centers of the brain. Using EEG-EMG coherence and coherent source analysis we found a different pattern of corticomuscular delays, time courses and central representations for the basic and double tremor frequencies typical for PD suggesting a wider range defective oscillatory activity. For the basic tremor frequency similar central representations in primary sensorimotor, prefrontal/premotor and diencephalic (e.g. thalamic) areas were reproduced for all three tremors. But renormalized partial directed coherence of the spatially filtered (source) signals revealed a mainly unidirectional flow of information from the diencephalon to cortex in voluntary tremor, e.g. a thalamocortical relay, as opposed to a bidirectional subcortico-cortical flow in PD and ET promoting uncontrollable, e.g. thalamocortical, loop oscillations. Our results help to understand why pathological tremors although originating from the physiological motor network are not under voluntary control and they may contribute to the solution of the puzzle why high frequency thalamic stimulation has a selective effect on pathological tremor leaving voluntary movement performance almost unaltered.

Cortical representation of different motor rhythms during bimanual movements.

The cortical control of bimanual and unimanual movements involves complex facilitatory and inhibitory interhemispheric interactions. We analysed the part of the cortical network directly related to the motor output by corticomuscular (64 channel EEG-EMG) and cortico-cortical (EEG-EEG) coherence and delays at the frequency of a voluntarily maintained unimanual and bimanual rhythm and in the 15-30-Hz band during isometric contractions. Voluntary rhythms of each hand showed coherence with lateral cortical areas in both hemispheres and occasionally in the frontal midline region (60-80 % of the recordings and 10-30 %, respectively). They were always coherent between both hands, and this coherence was positively correlated with the interhemispheric coherence (p < 0.01). Unilateral movements were represented mainly in the contralateral cortex (60-80 vs. 10-30 % ipsilateral, p < 0.01). Ipsilateral coherence was more common in left-hand movements, paralleled by more left-right muscle coherence. Partial corticomuscular coherence most often disappeared (p < 0.05) when the contralateral cortex was the predictor, indicating a mainly indirect connection of ipsilateral/frontomesial representations with the muscle via contralateral cortex. Interhemispheric delays had a bimodal distribution (1-10 and 15-30 ms) indicating direct and subcortical routes. Corticomuscular delays (mainly 12-25 ms) indicated fast corticospinal projections and musculocortical feedback. The 15-30-Hz corticomuscular coherence during isometric contractions (60-70 % of recordings) was strictly contralaterally represented without any peripheral left-right coherence. Thus, bilateral cortical areas generate voluntary unimanual and bimanual rhythmic movements. Interhemispheric interactions as detected by EEG-EEG coherence contribute to bimanual synchronization. This is distinct from the unilateral cortical representation of the 15-30-Hz motor rhythm during isometric movements.

Deep brain stimulation of the posterior hypothalamic area in intractable short-lasting unilateral neuralgiform headache with conjunctival injection and tearing (SUNCT).

BACKGROUND: SUNCT (short-lasting unilateral neuralgiform headache with conjunctival injection and tearing) is a rare syndrome characterized by the sudden onset of excruciating unilateral periorbital pain that is accompanied by conjunctival injection and lacrimation or further autonomic signs. Similar to patients with chronic cluster headache, Leone and Lyons showed a beneficial effect of deep brain stimulation of the posterior hypothalamic region in two patients with a chronic SUNCT. CASE: Here, we present the case of a man with a chronic SUNCT responding to deep brain stimulation of the posterior hypothalamic area. CONCLUSION: This case supports the idea of a central origin of SUNCT and shows that deep brain stimulation of the hypothalamic region can be effective in the treatment of the chronic form of this rare disorder.

Differentiating phase shift and delay in narrow band coherent signals.

OBJECTIVE: Differentiating between a fixed activation pattern (phase shift) and conduction time (time delay) in rhythmic signals has important physiological implications but is methodologically difficult. METHODS: Delay was estimated by the maximising coherence method and phase spectra calculated between (i) a narrow band-pass filtered AR2 process and its delayed copy for different phase shifts, (ii) the surface EMGs from two antagonistic forearm muscles with reciprocal alternating activity, and (iii) EEG and EMG data from 11 recordings in five Parkinsonian tremor patients. RESULTS: Estimated delays between the versions of the AR2 process resembled the real delay and were not significantly biased by the phase-shifts. The reciprocal alternating pattern of muscle activation was shown to be a pure phase-shift without any time delay. The phase between tremor-coherent cortical electrodes and EMG showed opposite signs and differed by 3pi/4-pi between the antagonistic muscles. Bidirectional delays between contralateral cortex and EMG did not differ between the antagonists and were in keeping with fast corticospinal transmission and feedback to the cortex for both muscles. CONCLUSIONS: Phase shifts and delays reflect different mechanisms in tremor related oscillatory interactions. SIGNIFICANCE: The maximising coherence method can differentiate between them.

[Tremor]. / Tremor.

Tremor is one of the most frequent neurological signs. The correct clinical classification is mainly clinical. The most frequent primarily neurological tremor is essential tremor (prevalence 2 to 5%). It presents in most cases as a more or less symmetrical postural and kinetic tremor. In about 60% of cases an autosomal-dominant inheritance is found. Tremor may manifest not only in the hands but also in the head and voice. In about 60 to 70% of the patients alcohol may improve the tremor. Parkinsonian tremor is normally a tremor at rest and it starts asymmetrically. The legs and the face are frequently involved. Cerebellar tremor is intentional. Orthostatic tremor, which has a high frequency, mainly manifests in the legs and gives rise to postural instability. Dystonic tremor is an action tremor of the affected region of the body. Drug therapy, which is purely symptomatic, mostly depends on clinical manifestation. Postural and action tremors respond to non selective betablockers (propranolol), primidone, some antiepileptics (gabapentin, toparimate) and benzodiazepines. Classical rest tremors are improved by dopaminergic substances (levodopa, dopamine agonists) or anticholinergics. Dystonic tremor may successfully be treated by injections of botulinum toxin. Orthostatic tremor responds to gabapentin or benzodiazepines in some of the patients. In severely handicapped patients with refractory tremors the implantation of thalamic stimulation electrodes may be considered. This treatment may be very successful, however, its inherent risks have to be taken into account.

Comparison of imaging modalities and source-localization algorithms in locating the induced activity during deep brain stimulation of the STN.

One of the most commonly used therapy to treat patients with Parkinson's disease (PD) is deep brain stimulation (DBS) of the subthalamic nucleus (STN). Identifying the most optimal target area for the placement of the DBS electrodes have become one of the intensive research area. In this study, the first aim is to investigate the capabilities of different source-analysis techniques in detecting deep sources located at the sub-cortical level and validating it using the a-priori information about the location of the source, that is, the STN. Secondly, we aim at an investigation of whether EEG or MEG is best suited in mapping the DBS-induced brain activity. To do this, simultaneous EEG and MEG measurement were used to record the DBS-induced electromagnetic potentials and fields. The boundary-element method (BEM) have been used to solve the forward problem. The position of the DBS electrodes was then estimated using the dipole (moving, rotating, and fixed MUSIC), and current-density-reconstruction (CDR) (minimum-norm and sLORETA) approaches. The source-localization results from the dipole approaches demonstrated that the fixed MUSIC algorithm best localizes deep focal sources, whereas the moving dipole detects not only the region of interest but also neighboring regions that are affected by stimulating the STN. The results from the CDR approaches validated the capability of sLORETA in detecting the STN compared to minimum-norm. Moreover, the source-localization results using the EEG modality outperformed that of the MEG by locating the DBS-induced activity in the STN.

Voxel seed coherent source analysis on transient global amnesia patients.

Transient global amnesia (TGA) is a rare neurological disorder with a sudden, temporary episode of memory loss which usually occurs in old age. The episodic loss of memory becomes normal after a stipulated time of approximately 24 hours. The precise pathology is not yet completely understood. Moreover, there is no proper neuroimaging method to assess this condition. In this study, the EEG was measured at two time points one with the occurrence of the episode (acute) and the second time point after the patient returns to the normal memory condition (follow-up). The aim of the study was to look at the pathological network involved during the acute phase and the follow up phase in these patients for the five frequency bands, namely, delta, theta, alpha, beta, and gamma. The method used for the source analyses was a beamforming approach called dynamic imaging of coherent sources in the frequency domain. The seed voxel was the lesion area taken from the anatomical MRI of each patient. The cortical and subcortical network comprised of the caudate and cerebellum in case of the delta band frequency. Two temporal sources in case of the theta band. Temporal, medial frontal, parietal, putamen, and thalamus sources were found in case of the alpha band. Prefrontal, parietal, and thalamus sources were found in case of the beta band. Temporal and thalamus in case of the gamma band frequency. All these sources were involved in the acute phase. Moreover, in the follow-up phase the motor area, in all frequency bands except gamma band, was additionally active followed by parietal and occipital regions in alpha and gamma frequencies. The differences involved in the network of sources between the two phases gives us better understanding of this neurological disorder.

Comparison of EEG and MEG in source localization of induced human gamma-band oscillations during visual stimulus.

High frequency gamma oscillations are indications of information processing in cortical neuronal networks. Recently, non-invasive detection of these oscillations have become one of the main research areas in magnetoencephalography (MEG) and electroencephalography (EEG) studies. The aim of this study, which is a continuation of our previous MEG study, is to compare the capability of the two modalities (EEG and MEG) in localizing the source of the induced gamma activity due to a visual stimulus, using a spatial filtering technique known as dynamic imaging of coherent sources (DICS). To do this, the brain activity was recorded using simultaneous MEG and EEG measurement and the data were analyzed with respect to time, frequency, and location of the strongest response. The spherical head modeling technique, such as, the three-shell concentric spheres and an overlapping sphere (local sphere) have been used as a forward model to calculate the external electromagnetic potentials and fields recorded by the EEG and MEG, respectively. Our results from the time-frequency analysis, at the sensor level, revealed that the parieto-occipital electrodes and sensors from both modalities showed a clear and sustained gamma-band activity throughout the post-stimulus duration and that both modalities showed similar strongest gamma-band peaks. It was difficult to interpret the spatial pattern of the gamma-band oscillatory response on the scalp, at the sensor level, for both modalities. However, the source analysis result revealed that MEG3 sensor type, which measure the derivative along the longitude, showed the source more focally and close to the visual cortex (cuneus) as compared to that of the EEG.

Effects of bilateral subthalamic nucleus stimulation on parkinsonian gait.

Gait analysis was carried out to assess the effects of L-dopa and bilateral subthalamic nucleus stimulation on gait velocity, cadence, stride length, and gait kinematics in nine patients with PD. Substantial effects of bilateral subthalamic nucleus stimulation on gait, with an increase in gait velocity and stride length comparable to that of a suprathreshold L-dopa dose, were found. Interestingly, stride length was more improved by L-dopa and cadence more by subthalamic nucleus stimulation. In two patients with freezing during the "on" period, subthalamic nucleus stimulation failed to reduce this symptom effectively.

Delay estimation for cortico-peripheral relations.

In neurophysiology, time delays between concurrently measured time series are usually estimated from the slope of a straight line fitted to the phase spectrum. We point out that this estimate is valid only in the case in which, one signal is a mere time-delayed copy of the other one. We present a procedure for delay estimation that applies to a much wider class of systems with nontrivial phase spectrum like for example lowpass filters. The procedure is based on the Hilbert transform relation between the phase of a linear system and its log gain. The Hilbert transform relation is nonlocal in frequency space, a fact that limits its applicability to experimental data. We explore these limits, and demonstrate that the method is applicable to neurophysiological time series. We present the successful application of the Hilbert transform behavior method to concurrently recorded epicortical brain activity and peripheral tremor. We point out and explain physiologically unreasonable delay estimates given by the traditional method. Finally, we discuss the assumptions underlying the applicability of the Hilbert transform method in the neuroscience context.

The pathophysiology of parkinsonian tremor: a review.

Parkinsonian tremor is most likely due to oscillating neuronal activity within the CNS. Summarizing all the available evidence, peripheral factors only play a minor role in the generation, maintenance and modulation of PD tremor. Recent studies have shown that not a single but multiple oscillators are responsible. The most likely candidate producing these oscillations is the basal ganglia loop and its topographic organization might be responsible for the separation into different oscillators which, nevertheless, usually produce the same frequency. The neuronal mechanisms underlying these oscillations are not yet clear, but three hypotheses would be compatible with the presently available data from animal models and data recorded in patients. The first is a cortico-subthalamo-pallido-thalamic loop, the second is a pacemaker consisting of the external pallidum and the subthalamic nucleus, and the third is abnormal synchronization due to unknown mechanisms within the whole striato-pallido-thalamic pathway leading to a loss of segregation. Assuming the oscillator within the basal ganglia pathway, the mechanism of stereotactic surgery might be a desynchronization of the activity of the basal ganglia-thalamo-cortical or the cerebello-thalamo-cortical pathway.

Determinants of physiologic tremor in a large normal population.

OBJECTIVES: It has been well established that peripheral mechanical resonant factors as well as central mechanisms may play a role in the generation of physiological tremor (PT). Furthermore it has been postulated that subject's attributes like age and sex might influence PT. The present study was designed to quantify these influences on PT in a large normal population. METHODS: Physiological hand and finger tremors were measured in a group of 117 normal subjects between 20 and 94 years of age using accelerometry and surface EMG recordings from the forearm flexor and extensor muscles. The hand tremor was measured in a postural position with and without weight, and the finger tremor was recorded with the arm outstretched, forearm supported and hand supported. Hand volume and grip force were measured in each subject. RESULTS: Hand tremor frequency (mean 7.7 Hz) was reduced significantly by added inertia (mean 5.2 Hz) and it was negatively correlated with hand volume while there was no correlation with grip force. Finger tremor showed, subject to the arm position, maximally 3 and at least two distinct frequency bands (1-4, 6-11 and 15-30 Hz) reflecting the resonance frequencies of the whole arm, the hand and the finger, respectively. A significant EMG peak was found in 50-80% of the recordings. This EMG synchronization gave rise to a corresponding accelerometer peak or a significant EMG-EMG coherence in about one-third of the population indicating a central component of PT because its frequency was unaffected by mechanical changes in the periphery. We did not find a significant influence of age on the tremor frequency, while the sex of the subjects slightly but significantly changed the frequency range of hand tremor. Multiple partial correlations revealed, however, that the only direct influence on hand tremor frequency is the hand volume indicating that the influence of sex on hand tremor frequency is an indirect effect produced by the significantly larger hands of male subjects. CONCLUSIONS: In conclusion, the main determinants of PT are the mechanical properties of the oscillating limb. Apart from the dominating peripheral resonance mechanism we found indications of an additional central component of PT in about one-third of the normal population. There was no age dependence of tremor frequency and it was shown that the influence of the subjects' sex on tremor frequency only represents an indirect mechanical effect.

Tremor analysis in two normal cohorts.

OBJECTIVE: Quantitative tremor analyses using almost identical methods were compared between two independent large normal cohorts, to separate robust measures that may readily be used diagnostically from more critical ones needing lab-specific normalization. METHODS: Hand accelerometry and surface EMG from forearm flexors and extensors were recorded with (500 and 1000 g) and without weight loading under postural conditions in 117 and 67 normal volunteers in two different specialty centers for movement disorders in Germany. RESULTS: Tremor amplitude (total power) and frequency fell within a similar range but differed significantly. A significant reduction of tremor frequency under 1000 g weight load (>1 Hz), and a lack of rhythmic EMG activity at the tremor frequency in around 85-90% of the recordings were robust findings in both centers. CONCLUSIONS: The differences in frequency and total power indicate that these measures critically depend on the details of the recording conditions being slightly different between the two centers. Thus each lab needs to establish its own normative data. We estimate that at least 25 normal subjects have to be recorded to obtain normal values. The reduction of tremor frequency under load and lacking tremor-related EMG activity were well reproducible allowing a differentiation of physiological from low amplitude pathological tremor. SIGNIFICANCE: This study provides a framework for more standardized tremor analyses in clinical neurophysiology.

Coherent source and connectivity analysis on simultaneously measured EEG and MEG data during isometric contraction.

The most well-known non-invasive electric and magnetic field measurement modalities are the electroencephalography (EEG) and magnetoencephalography (MEG). The first aim of the study was to implement the recently developed realistic head model which uses an integrative approach for both the modalities. The second aim of this study was to find the network of coherent sources and the modes of interactions within this network during isometric contraction (ISC) at (15-30 Hz) in healthy subjects. The third aim was to test the effective connectivity revealed by both the modalities analyzing them separately and combined. The Welch periodogram method was used to estimate the coherence spectrum between the EEG and the electromyography (EMG) signals followed by the realistic head modelling and source analysis method dynamic imaging of coherent sources (DICS) to find the network of coherent sources at the individual peak frequency within the beta band in healthy subjects. The last step was to identify the effective connectivity between the identified sources using the renormalized partial directed coherence method. The cortical and sub-cortical network comprised of the primary sensory motor cortex (PSMC), secondary motor area (SMA), and the cerebellum (C). The cortical and sub-cortical network responsible for the isometric contraction was similar in both the modalities when analysing them separately and combined. The SNR was not significantly different between the two modalities separately and combined. However, the coherence values were significantly higher in the combined modality in comparison to each of the modality separately. The effective connectivity analysis revealed plausible additional connections in the combined modality analysis.

Impact of head modeling and sensor types in localizing human gamma-band oscillations.

An effective mechanism in neuronal communication is oscillatory neuronal synchronization. The neuronal gamma-band (30-100 Hz) synchronization is associated with attention which is induced by a certain visual stimuli. Numerous studies have shown that the gamma-band activity is observed in the visual cortex. However, impact of different head modeling techniques and sensor types to localize gamma-band activity have not yet been reported. To do this, the brain activity was recorded using 306 magnetoencephalography (MEG) sensors, consisting of 102 magnetometers and 102 pairs of planar gradiometers (one measuring the derivative of the magnetic field along the latitude and the other along the longitude), and the data were analyzed with respect to time, frequency, and location of the strongest response. The spherical head models with a single-shell and overlapping spheres (local sphere) have been used as a forward model for calculating the external magnetic fields generated from the gamma-band activity. For each sensor type, the subject-specific frequency range of the gamma-band activity was obtained from the spectral analysis. The identified frequency range of interest with the highest gamma-band activity is then localized using a spatial-filtering technique known as dynamic imaging of coherent sources (DICS). The source analysis for all the subjects revealed that the gradiometer sensors which measure the derivative along the longitude, showed sources close to the visual cortex (cuneus) as compared to the other gradiometer sensors which measure the derivative along the latitude. However, using the magnetometer sensors, it was not possible to localize the sources in the region of interest. When comparing the two head models, the local-sphere model helps in localizing the source more focally as compared to the single-shell head model.

The cortical and sub-cortical network of sensory evoked response in healthy subjects.

The aim of this study was to find the cortical and sub-cortical network responsible for the sensory evoked coherence in healthy subjects during electrical stimulation of right median nerve at wrist. The multitaper method was used to estimate the power and coherence spectrum followed by the source analysis method dynamic imaging of coherent sources (DICS) to find the highest coherent source for the basic frequency 3 Hz and the complete cortical and sub-cortical network responsible for the sensory evoked coherence in healthy subjects. The highest coherent source for the basic frequency was in the posterior parietal cortex for all the subjects. The cortical and sub-cortical network comprised of the primary sensory motor cortex (SI), secondary sensory motor cortex (SII), frontal cortex and medial pulvinar nucleus in the thalamus. The cortical and sub-cortical network responsible for the sensory evoked coherence was found successfully with a 64-channel EEG system. The sensory evoked coherence is involved with a thalamo-cortical network in healthy subjects.

Discrimination of Parkinsonian tremor from essential tremor using statistical signal characterization of the spectrum of accelerometer signal.

A new technique for discrimination of Parkinson tremor from essential tremor is presented in this paper. This technique is based on Statistical Signal Characterization (SSC) of the spectrum of the accelerometer signal. The data has been recorded for diagnostic purposes in the Department of Neurology of the University of Kiel, Germany. Two sets of data are used. The training set, which consists of 21 essential-tremor (ET) subjects and 19 Parkinson-disease (PD) subjects, is used to obtain the threshold value of the classification factor differentiating between the two subjects. The test data set, which consists of 20 ET and 20 PD subjects, is used to test the technique and evaluate its performance. Three of twelve newly derived SSC parameters show good discrimination results. Specific results of those three parameters on training data and test data are shown in detail. A linear combination of the effects of those parameters on the discrimination results is also included. A total discrimination accuracy of 90% is obtained.

Cortico-muscular coherence on artifact corrected EEG-EMG data recorded with a MRI scanner.

Simultaneous recording of electroencephalogram (EEG) and electromyogram (EMG) with magnetic resonance imaging (MRI) provides great potential for studying human brain activity with high temporal and spatial resolution. But, due to the MRI, the recorded signals are contaminated with artifacts. The correction of these artifacts is important to use these signals for further spectral analysis. The coherence can reveal the cortical representation of peripheral muscle signal in particular motor tasks, e.g. finger movements. The artifact correction of these signals was done by two different algorithms the Brain vision analyzer (BVA) and the Matlab FMRIB plug-in for EEGLAB. The Welch periodogram method was used for estimating the cortico-muscular coherence. Our analysis revealed coherence with a frequency of 5Hz in the contralateral side of the brain. The entropy is estimated for the calculated coherence to get the distribution of coherence in the scalp. The significance of the paper is to identify the optimal algorithm to rectify the MR artifacts and as a first step to use both these signals EEG and EMG in conjunction with MRI for further studies.

Dipole source analysis for readiness potential and field using simultaneously measured EEG and MEG signals.

Various source localization techniques have indicated the generators of each identifiable component of movement-related cortical potentials, since the discovery of the surface negative potential prior to self-paced movement by Kornhuber and Decke. Readiness potentials and fields preceding self-paced finger movements were recorded simultaneously using multichannel electroencephalography (EEG) and magnetoencephalography (MEG) from five healthy subjects. The cortical areas involved in this paradigm are the supplementary motor area (SMA) (bilateral), pre-SMA (bilateral), and contralateral motor area of the moving finger. This hypothesis is tested in this paper using the dipole source analysis independently for only EEG, only MEG, and both combined. To localize the sources, the forward problem is first solved by using the boundary-element method for realistic head models and by using a locally-fitted-sphere approach for spherical head models consisting of a set of connected volumes, typically representing the scalp, skull, and brain. In the source reconstruction it is to be expected that EEG predominantly localizes radially oriented sources while MEG localizes tangential sources at the desired region of the cortex. The effect of MEG on EEG is also observed when analyzing both combined data. When comparing the two head models, the spherical and the realistic head models showed similar results. The significant points for this study are comparing the source analysis between the two modalities (EEG and MEG) so as to assure that EEG is sensitive to mostly radially orientated sources while MEG is only sensitive to only tangential sources, and comparing the spherical and individual head models.