ritva paetau - biac.duke.edu · ritva paetau department of child neurology, hospital for children...

Developmental Science 5:3 (2002), pp 361–370

© Blackwell Publishers Ltd. 2002, 108 Cowley Road, Oxford OX4 1JF, UK and 350 Main Street, Malden, MA 02148, USA.

Blackwell Publishers LtdMagnetoencephalography in pediatric neuroimaging

Ritva PaetauDepartment of Child Neurology, Hospital for Children and Adolescents, University of Helsinki; Brain Research Unit, Helsinki University of Technology; BioMag Laboratory; Helsinki University Central Hospital, Finland

Abstract

Neural currents give rise to electroencephalogram (EEG) and magnetoencephalogram (MEG). MEG has selective sensitivityto tangential currents (from fissural cortex), and less distorted signals compared with EEG. A major goal of MEG is to determinethe location and timing of cortical generators for event-related responses, spontaneous brain oscillations or epileptiform activity.MEG provides a spatial accuracy of a few mm under optimal conditions, combined with an excellent submillisecond temporalresolution, which together enable spatiotemporal tracking of distributed neural activities, e.g. during cognitive tasks or epilepticdischarges. While the present focus of pediatric MEG is on tailored epilepsy surgery, the complete noninvasiveness of MEGalso provides unlimited possibilities to study the brain functions of healthy and developmentally deviant children.

Introduction

Magnetoencephalography (MEG) detects weak extra-cranial magnetic fields, and allows determination oftheir intracranial sources. Magnetic source imaging(MSI) means procedures which combine the MEGsources with anatomical magnetic resonance imaging(MRI). The term MEG is used in the present paper tocover both MEG and MSI.

After the first recordings of human magnetic alpharhythm (Cohen, 1968), MEG technology and its appli-cations to neuroscience and clinical research have pro-gressed at an accelerating rate during the past 20 years.Several excellent reviews are available on various aspectsof the MEG method (e.g. Williamson & Kaufman, 1981;Weinberg, Stroink & Katila, 1985; Hari & Ilmoniemi,1986; Sato, Balish & Muratore, 1991; Hämäläinen, Hari,Ilmoniemi, Knuutila & Lounasmaa, 1993; Gallen, Hir-schkoff & Buchanan, 1995; Lewine & Orrison Jr., 1995;Hari, 1998; Forss, Nakasato, Ebersole, Nagamine &Salmelin, 2000; Otsubo & Snead, 2001). At present, overone hundred MEG installations worldwide contributeto our knowledge about the function and developmentof the human brain. Most MEG studies have beenconducted with adult subjects, but some MEG dataalready exist on children. Pediatric MEG studies havemainly focused on epilepsy surgery (Paetau, Hämäläinen,Hari, Kajola, Karhu, Larsen, Lindahl & Salonen, 1994;Chuang, Otsubo, Hwang, Orrison & Lewine, 1995;Minassian, Otsubo, Weiss, Elliott, Rutka & Snead, 1999),on rolandic epilepsy (Kubota, Oka, Kin & Sakakihara,1996; Minami, Gondo, Yamamoto, Yanai, Tasaki & Ueda,

1996; Kamada, Moller, Saguer, Kassubek, Kaltenhauser,Kober, Uberall, Lauffer, Wenzel & Vieth, 1998; Kubota,Takeshita, Sakakihara & Yangisawa, 2000), on the Landau-Kleffner syndrome and related disorders (Paetau, Kajola,Korkman, Hämäläinen, Granström & Hari, 1991; Paetau,1994; Lewine, Andrews, Chez, Patil, Devinsky, Smith, Kan-ner, Davis, Funke, Jones, Chong, Provencal, Weisend, Lee &Orrison, 1999; Paetau, Granström, Blomstedt, Jousmäki,Korkman & Liukkonen, 1999; Sobel, Aung, Otsubo &Smith, 2000), on sensory cortex properties in progressivemyoclonus epilepsies (Karhu, Hari, Paetau, Kajola &Mervaala, 1994; Lauronen, 2001; Forss, Silen & Kar-jalainen, 2001), and on dyslexia (Heim, Eulitz,Kaufmann, Fuchter, Pantev, Lamprecht-Dinnesen, Matulat,Scheer, Borstel & Elbert, 2000; Simos, Breier, Fletcher,Bergman & Papanicolaou, 2000). This article will brieflyreview the basic principles of MEG and give some exam-ples of the present use of MEG in children.

Basic principles of MEG

A moving electric charge is always associated with anelectric field and a concomitant magnetic field surround-ing the axis of movement (Figure 1a). Electroencephalo-gram (EEG) and MEG signals are believed to reflectsynchronous postsynaptic currents in thousands of par-allel apical dendrites. Despite being ultimately due to thesame primary currents, EEG and MEG signals differ atsome important points. First, only tangential currents,parallel to the head surface, give rise to an extracranialmagnetic field. Because the apical dendrites typically run

Address for correspondence: Hospital for Children and Adolescents, P.O. Box 280, FIN-00029 HUS, Finland; e-mail: [email protected]

362 Ritva Paetau

© Blackwell Publishers Ltd. 2002

perpendicular to the cortex surface, MEG signals mainlyarise in fissure walls (Figure 1b). The EEG signals, onthe other hand, are dominated by radial currents, whilethe tangential ones may require signal averaging to bedetected. This complementary sensitivity to currentorientation warrants combined use of EEG and MEGwhenever possible. Second, inhomogeneous tissue con-ductivity of the human head tends to spread out theEEG signal, but does not alter the magnetic fields.

Therefore, tumors, cysts, calcified lesions and skulldefects cause less distortion on MEG than EEG signals(van der Broek, Reinders, Donderwinkel & Peters, 1998).Third, signal attenuation in EEG is caused by poorlyconducting tissue, while the magnetic field fades offproportionally to the second power of the distance fromthe source. Infants and persons with small heads shouldpreferably be studied with systems composed of twopart-head devices adjustable according to the head sizeor with specially designed baby devices. Fourth, differentpractical problems hamper data acquisition. MEG sen-sors are in a rigid helmet and the head has to be keptimmobile with respect to the helmet. Long-term record-ings or recordings of major motor seizures are so far notpossible with MEG, but continuous monitoring of thehead position may offer relief to some of the movementproblems. Finally, MEG and EEG have partly differingartifact profiles: MEG is less sensitive to muscle artifactsthan EEG. On the other hand, magnetic materials mov-ing with respiration (traces from craniotomy drills, someshunt materials, tooth braces, cochlear implants, etc.)may cause serious artifacts or even destroy the MEG data.

Instrumentation

The brain’s magnetic fields are extremely weak (on theorder of 10−15 Tesla) and need to be heavily amplified,while much stronger environmental magnetic noise frompower lines or electronic equipment must be suppressed.MEG measurements are carried out in magneticallyshielded rooms, using sensitive superconducting quan-tum interference devices (SQUIDs) (Zimmermann, Thiene& Harding, 1970). The MEG sensors consist of a fluxtransformer coupled to a SQUID, which amplifies theweak extracranial magnetic field and transforms it intovoltage. The sensors are immersed in liquid helium andattached on a concave bottom of a container, where theytypically lie at a distance of 3–4 cm from the cortex.

A flux transformer may be planar, and gives thelargest signal at the sharpest field gradient right abovea local brain current, or axial giving maximum signalsat both the field extremes. At present, several companiesmanufacture whole-head devices with 64–306 sensors forclinical and experimental work. The present examplescome from experiments with a planar 122-SQUID gradi-ometer, Neuromag-122™, and a planar-axial 306-SQUIDdevice Vectorview, 4-D Neuroimaging, Helsinki, Finland.

Data acquisition

During the experiments, the subject is sitting or lyingwith his /her head inside a sensor helmet as close to the

Figure 1 Physical basis of MEG signals. (a) The intracellular current I in the apical dendrite of a pyramidal cell is associated with a surrounding magnetic field B. (b) In the brain, pyramidal cells typically are perpendicular to cortex surface, and may be radial (white arrows), oblique or tangential (dark arrows) to the scalp. Only the tangential currents and the tangential component of oblique currents contribute to the extracranial magnetic field, which can be detected by sensitive SQUID magnetometers. (c) Dipolar magnetic field pattern viewed from above. B in indicates the magnetic flux into the head and B out the flux out from the head. An equivalent current dipole (ECD; the thick black arrow) represents the concerted action of all fissural dipoles. Its orientation is parallel to the isofield lines and it is located underneath the steepest gradient halfway between the in- and out-flowing flux. Its depth determines the distance between the two extremes, and its strength is proportional to the number of active pyramidal cells.

Magnetoencephalography 363


sensors as possible. Head movements are minimized byusing videotape films, visual stimuli, neck collars or headfixating bite bars.

The exact head position within the helmet is oftendetermined with three or four coils pasted around thehead. Prior to data acquisition, the position of thesecoils is sensed with a 3-D digitizer within an individualhead coordinate system based on three fiducial points:the left and right preauricular points and the nasion.Brief magnetic signals from the coils allow determina-tion of the head position within the helmet. For lateralignment of MEG and MRI data, the fiducial pointsare identified on the subject’s MRI slices.

EEG, electromyogram (EMG), electro-oculogram,electrocardiogram, finger movements, voice phono-grams, etc. can be monitored during MEG acquisition,provided that nonmagnetic materials are used inside theshielded room.

Evoked responses to auditory, somatosensory or vis-ual stimuli require little cooperation and are routinelyrecorded in the context of presurgical mapping even in youngchildren. Typically, more than one hundred evokedresponses have to be averaged during 4–8 minutes inschool-age children until a satisfactory signal-to-noiseratio is achieved. The youngest children often have large-amplitude background activity and require more averagesand longer recordings. Auditory experiments take evenlonger, because the common target signal, the magneticauditory evoked 100-ms response, N100m – labeledaccording to event-related potential (ERP) terminology(Taylor & Baldeweg, this issue) – can only be detectedat long interstimulus intervals in young children (Paetau,Ahonen, Salonen & Sams, 1995; Rojas, Walker, Sheeder,Teale & Reite, 1998). The same is true for a number ofother long-latency responses.

Mismatch negativity (MMN) is a long-latency audi-tory evoked vertex-negative potential to infrequent devi-ants in a sequence of homogeneous standard stimulipeaking at 200–400 ms in adults and children. Its mag-netic counterpart, the mismatch field (MMF), is generatedby the auditory cortex, and has been widely studied inhealthy adults (Hari, Hämäläinen, Ilmoniemi, Kaukoranta,Reinikainen, Salminen, Alho, Näätänen & Sams, 1984;Sams, Kaukoranta, Hämäläinen & Näätänen, 1991; Levänen,Hari, McEvoy & Sams, 1993; Näätänen, Lehtokoski, Lennes,Cheour, Huotilainen, Iivonen, Vainio, Alku, Ilmoniemi,Luuk, Allik, Sinkkonen & Alho, 1997; Vihla, Lounasmaa& Salmelin, 2000). Recording responses to hundreds ofrare deviant stimuli also means long sessions, but theinteresting potential of MMN in early language dis-crimination (Cheour, Ceponiene, Lehtokoski, Luuk, Allik,Alho & Näätänen, 1998) warrants developmental MEGstudies in babies and young children.

Brain–muscle interaction can be studied using MEG-EMG coherence analysis, an important new method foridentification of the motor cortex (Salenius, Portin,Kajola, Salmelin & Hari, 1997; Mäkelä, Kirveskari,Seppä, Hämäläinen, Forss, Avikainen, Salonen, Salenius,Kovala, Randell, Jääskeläinen & Hari, 2001). It requiresa few minutes of weak voluntary isometric musclecontraction, and can be successfully recorded fromschool-age children.

Data analysis

The MEG data are displayed as traces, similar to tradi-tional EEG signals allowing epileptiform spikes, evokedresponse components and other graphoelements to beeasily recognized (Figures 2a, 2b). The same data areconcomitantly displayed as time-varying magnetic field

Figure 2 Source analysis of epileptiform spikes. (a) A nose-up top view from a planar 122-SQUID display. The 600-ms epoch shows epileptiform spikes with two local amplitude maximae, enlarged in (b). Traces and concomitant field patterns (c) are screened for dipolar field patterns, occurring here at 304 and 330 ms. Dipolar fields are modeled with a single equivalent current dipole (ECD; white and black arrows). ECD activity over time (d) shows a consistent activity pattern, with right-hemisphere activity (R) leading the left-hemisphere activity (L) by 25 ms during repeated spikes (superimposed). The two ECDs together explain 80–40% of the overall field variance (Goodness-of-fit %) during spikes. (e) Dipole locations (boxes) and orientations (tails) in the upper bank of sylvian fissure.

364 Ritva Paetau


patterns (Figure 2c). The goal of data analysis is todetermine which brain currents underlie a particular spikeor evoked response, i.e. to solve the ‘inverse problem’.Unfortunately, an infinite number of current distributionsmay result in exactly the same field pattern, and there isno unique solution to the inverse problem (Sarvas, 1987).To rule out false possibilities, the brain and the braincurrents have to be appropriately modeled and furtherconstraints are needed to rule out unphysiological oranatomically impossible solutions.

A single dipole model provides a good first approxi-mation of local brain activity. After screening the mag-netic field patterns, dipolar fields (Figures 1c & 2c–e) areexplained with an equivalent current dipole (ECD)found by a least-squares search. The single dipole fitis repeated at short intervals (e.g. 1 ms) to explore thestability of the solution, and to find the time pointwhen the largest dipole moment coincides with the leastconfidence volume and the largest goodness-of-fit valueor the best correlation coefficient. An ideal ECD shouldexplain most of the field variance, and it should main-tain an anatomically stable location over a few ms. Suchan ECD represents the mean current location and orien-tation in an active area. The single dipole model is onlyvalid if the active area is small. Extended corticalsources with several parallel ECDs will be misinterpretedby the single dipole algorithm as one giant, deeplysituated source. Simultaneous currents of differentorientations and locations often suit multi-dipole analysis(Mosher, Lewis & Leahy, 1992). If the sources overlap

only partly in time, the single dipole model may beadequate at a particular time point. The effects ofthat dipole can be removed from the analysis by a signal-space projection procedure (Uusitalo & Ilmoniemi,1997) and a new single dipole may be fitted to the resid-ual field. Finally, all dipoles together are used to explainthe data. Complex source patterns (e.g. in the visualcortex) may be best visualized by using minimum cur-rent estimate-based maps instead of dipoles (Uutela,Hämäläinen & Somersalo, 1999).

Examples of pediatric MEG

Presurgical mapping of epileptic and eloquent cortex

Tailored epilepsy surgery is one of the major rationalesfor MEG recordings. In temporal-lobe epilepsy (foranatomical terms, see Figure 3), MEG identifies correctlyhalf of the sources, but only 20–50% of mesial temporallobe foci (Brockhaus, Lehnertz, Wienbruch, Kowalik,Burr, Elbert, Hoke & Elger, 1996; Knowlton, Laxer,Aminoff, Roberts, Wong & Rowley, 1997), and 50–70%of the lateral temporal-lobe foci (Smith, Schwartz, Gal-len, Orrison, Lewine, Murro, King & Park, 1995;Wheless, Willmore, Breier, Kataki, Smith, King, Meador,Park, Loring, Clifton, Baumgartner, Thomas, Constan-tinou & Papanicolau, 1999). Deep orbitofrontal epilepticactivity, expectedly, is poorly identified by MEG, butextratemporal convexial foci are detected in 44–92% ofpatients (Paetau et al., 1994; Smith, Gallen & Schwartz,1994; Smith et al., 1995; Brockhaus et al., 1996; Knowltonet al., 1997; Wheless et al., 1999) and the highest percent-age comes from children with normal MRI (Minassianet al., 1999).

For good surgery outcome, all epileptogenic cortexshould be removed and lesions of eloquent cortex, i.e. ofthe primary sensorimotor and language areas should beavoided as far as possible. Somatosensory evoked fields(SEFs) to electric or tactile stimulation are equally reliableas cortical stimulation to identify the somatotopicallyorganized primary sensory cortex in the central sulcus(Sutherling, Crandall, Engel, Darcey, Cahan & Barth,1988; Smith, Gallen & Schwartz, 1994; Minassian et al.,1999; Mäkelä et al., 2001). Abnormal low-frequencyactivity may occasionally contaminate the averagedresponse and increase the localization error. The erroris proportional to the signal-to-noise ratio, and increasesin young subjects with large-amplitude backgroundactivity. In epilepsy patients, the distance betweenSEF sources from two successive recordings of the sameindividual was larger in the age group 4–8 years than12–16 years (16 ± 3 mm vs 4 ± 1 mm).

Figure 3 Schematic brain viewed from the left. Only the lateral temporal cortex is visible. The mesial temporal cortex lines the inner surface of the temporal lobe. Perisylvian cortex encompasses the shaded temporal, frontal and parietal banks of the sylvian fissure.



Localization of the primary motor cortex by MEG-EMG coherence has proved successful in patients withbrain tumors (Mäkelä et al., 2001) and with epilepsy(Paetau, unpublished observations). Figure 4 showspresurgery MEG data from a girl with drug-resistantepilepsy and cortical dysplacia in left frontal lobe.Her interictal MEG spikes originated at the anterior andposterior borders of the dysplastic sulcus. MEG local-ized the primary motor and sensory cortices 1.5 cmposterior to the dysplastic area. The lesion was removedwith no resultant paresis and >90% reduction ofseizures.

Language-related cortex should not be lesioned bybrain surgery. While critical language functions most com-monly reside in the left hemisphere, right-hemispherelanguage dominance or bilateral language representationoccasionally occur in epilepsy surgery patients. For theintracarotid amobarbital procedure or the Wada test(Wada & Rasmussen, 1960), a short-acting barbiturate isinjected to one hemisphere at a time. The neural functionsof the injected side are paralyzed for a few minutes,during which contralateral hemisphere language functionscan be selectively tested. Wada test is the goldenstandard for presurgery assessment of language domi-nance, while cortical stimulation mapping is thestandard to identify subhemispheric language areas,

which may have large individual variations (Ojemann,Ojemann, Lettich & Berger, 1989). Papanicolaou, Simos,Breier, Zouridakis, Willmore, Wheless, Constantinou,Maggio and Gormley (1999) reported a word recogni-tion task for noninvasive lateralization and localizationof language cortex using MEG. The subjects listened orread abstract English nouns, and they had to indicate ifa noun had been presented earlier during the session.Evoked magnetic responses to memorized words wereaveraged. A single dipole analysis over a time window of150–700 ms poststimulus showed approximately twiceas many good dipoles (correlation coefficient ≥0.9) inthe left than in the right hemisphere. This empirical cri-terion for language lateralization was recently reportedto match the Wada test (Breier, Simos, Zoudriakis,Wheless, Willmore, Constantinou, Maggio & Papanico-laou, 1999) and cortical stimulation mapping in patientswith tumors or epilepsy (Simos, Papanicolaou, Breier,Wheless, Constantinou, Gormley & Maggio, 1999). Theword recognition paradigm, however, failed to activatethe left temporoparietal cortex in dyslexic children(Simos, Breier, Fletcher, Bergman & Papanicolaou, 2000),whose language dominance might remain ambiguousby the number of left- vs right-hemisphere dipoles.

Salmelin, Hari, Lounasmaa and Sams (1994) foundthat overt picture naming activates several brain areas of

Figure 4 Presurgical mapping of epileptic generators and sensorimotor cortex. Brain sources of magnetic spikes (white squares), of auditory and somatosensory evoked activity (white circles in auditory cortex and primary somatosensory cortex, SI), and of EMG-coherent motor activity (black circles in primary motor cortex, MI). Dotted lines indicate a deep dysgenetic sulcus.

366 Ritva Paetau


healthy adults in a sequential manner, beginning in theoccipital visual areas, progressing bilaterally to the tem-poral and frontal lobes. Pediatric epilepsy patients andhealthy children from five years up show similar naming-related activity patterns, but also individual variations.Figure 5 compares the results of presurgical MEG andof cortical stimulation mapping during a picture namingtest. The suprasylvian cortex, the posterior superiortemporal sulcus, the supramarginal cortex, and the ante-rior tip of the temporal lobe were repeatedly activated inthe left hemisphere. According to cortical stimulation,the suprasylvian MEG sources were associated withmotor responses from the mouth area, while stimulationof the superior temporal sulcus elicited dysnomia. OtherMEG sources were not covered by the electrode grid andnot tested. This example shows that language-relatedMEG sources were correctly localized, but a namingtask cannot separate the sources of specific languageprocesses such as motor planning, articulation or semanticcomprehension, and more sophisticated task paradigmsmust be developed before the noninvasive languagelocalization by MEG can substitute the invasivemethods.

MEG in acquired epileptiform regression syndromes

Acquired epileptic regression syndromes are disablingchildhood disorders, where a previously healthy childdeteriorates over a week to months. The children may ormay not show overt seizures, but their EEG usually dis-plays almost continuous epileptiform spike-and-waveactivity, especially during sleep. In acquired epilepticaphasia or the Landau-Kleffner syndrome, LK (Landau& Kleffner, 1957), the regression affects receptive languageand/or auditory perception. Epileptiform spike-and-wave discharges appear during the first few weeks, and

have been proposed to be causally related to cognitivedisability. Some LK children develop giant auditory N100mresponses with similar auditory cortex sources andreactivity as the normal N100m, but with morphologyand amplitude identical to the patient’s epileptic spikes(Paetau, 1994). LK patients’ verbal auditory agnosiacan, therefore, be understood as local epilepsy of theauditory cortex, activated by sounds!

Spontaneous language recovery in LK syndrome isdisappointing. More than two-thirds of the LK patientsremain permanently and often severely disabled (Deonna,Peter & Ziegler, 1989). Morrell, Whisler, Smith, Hoeppner,Pierre-Louis, Kanner, Buelow, Ristanovic, Bergen, Chezand Hasegawa (1995) have shown that selected LKpatients greatly benefit from epilepsy surgery or mayeven be cured, provided that the epileptic activity isentirely paced by a restricted area in one hemisphere.

MEG alone or combined with EEG has proved usefulin identifying the sources of epileptic activity in LK, aswell as in childhood epileptic autistic regression dis-orders. Despite widespread spike-and-wave discharges,the sources have consistently been in rather restrictedareas, usually in the intra- and perisylvian cortex (Paetauet al., 1991; Paetau, 1994; Morrell et al., 1995; Lewineet al., 1999; Paetau, Granström, Blomstedt, Jousmäki,Korkman & Liukkonen, 1999). Occasionally also nonsylviansources may be found (Sobel et al., 2000).

Several brain areas may become active during thecourse of a single spike-and-wave complex, and accuratetiming between these generators is crucial to findingthe pacemaker. Multi-dipole analysis of spike-and-wavedischarges (Figure 6) identified a single intrasylvianpacemaker with monosynaptic connections to the samehemisphere in one LK patient (A). In another patient(B) one right sylvian source paced both ipsilateral andcontralateral activity. Such single-pacemaker patientswould benefit from surgical lesions (multiple subpialtranssections, MST) applied to the pacemaker area. PatientA underwent MST on her right auditory cortex, and herauditory perception of environmental sounds improvedessentially over the next 3 months. Patient C with bilat-eral, independent, sylvian-paced circuits and independ-ent local spikes was not recommended for surgery.

For children with epileptic regression disorders andwidespread discharges, coregistered MEG and EEGprovides at present the most efficient way to identifypossible surgery candidates.

Conclusions

MEG and EEG are fundamentally different comparedto functional magnetic resonance imaging (fMRI),

Figure 5 Language-related MEG activity compared to cortical stimulation mapping of the left hemisphere. MEG sources are shown in white and stimulation sites in black symbols. Open and black symbols indicate the subdural grid placement.



positron emission tomography (PET) or other anatomicalimaging methods, where the spatial resolution is basedon voxel size. The 3-D sources of electromagnetic dataare based on mathematical models, and adequacy of themodel is of critical importance for correct solution. Withthe precaution, the spatial resolution of MEG is gener-ally good, ranging from a few mm on the superficialfissures to a few cm in the basal temporal and frontalareas (Tarkiainen, Hämäläinen & Salmelin, 1996; Leahy,Mosher, Spencer, Huang & Lewine, 1998), which is oftensufficient for practical decisions. Even though the exactlocation of MEG sources should be confirmed by elec-trocorticography (ECoG) before surgical lesioning, awhole-head MEG effectively identifies the brain areas tobe sampled by ECoG. This is of particular importancein patients without structural brain lesions, in whomlocalization of the epileptic area is entirely based on itselectrophysiological and metabolic properties.

The most important advantage of MEG and EEGover any present functional imaging modality is theirsubmillisecond temporal resolution. At present, MEGprovides the most efficient single tool for real-time track-

ing of distributed brain activities during a number ofcognitive tasks (Salmelin et al., 1994; Helenius, Salmelin,Service & Conolly, 1998) or epileptic discharges (Hari,Ahonen, Forss, Granström, Hämäläinen, Kajola, Knuu-tila, Lounasmaa, Mäkelä, Paetau, Salmelin & Simola,1993; Paetau et al., 1999).

So far, MEG technology has been most widely usedwithin basic neuroscience in an attempt to reveal corticalactivation dynamics in a multitude of tasks of the work-ing human brain. The complete noninvasiveness ofMEG enables detailed and repeated studies in healthysubjects, children, as well as neurological and psychiatricpatients. Technical improvements, such as infant-sizehelmets, effective movement correction algorithms, andfast new subroutines for data analysis are constantlydeveloped to better meet the clinical demands.

In patient work, MEG is routinely used for mappingthe central sulcus, but with an increasing number ofMEG-compatible experimental setups being standard-ized, the technique ultimately bears potential for tailoredassessment of specific neural circuitries and cognitiveprocesses. Finally, combining imaging modalities withcomplementary weak and strong sides provides the mostreliable individual brain model for both scientificresearch and medical care.

Acknowledgements

Financially supported by Helsinki University CentralHospital subsidy TYH1334 and by grants from Arvo andLea Ylppö Foundation and Finska Läkaresällskapet.I thank professor Riitta Hari for comments on themanuscript.

References

Breier, J., Simos, P., Zoudriakis, G., Wheless, J., Willmore, L.,Constantinou, J., Maggio, W., & Papanicolaou, A. (1999).Language dominance determined by magnetic source imag-ing. A comparison with the Wada procedure. Neurology, 53,938–945.

Brockhaus, A., Lehnertz, K., Wienbruch, C., Kowalik, A.,Burr, W., Elbert, T., Hoke, M., & Elger, C. (1996). Pos-sibilities and limitations of magnetic source imaging ofmethohexital-induced epileptiform patterns in temporal lobeepilepsy patients. Electroencephalography and Clinical Neuro-physiology, 102, 423–436.

Cheour, M., Ceponiene, R., Lehtokoski, A., Luuk, A., Allik, J.,Alho, K., & Näätänen, R. (1998). Development of language-specific phoneme representations in the infant brain. NatureNeuroscience, 1, 351–353.

Chuang, S., Otsubo, H., Hwang, P., Orrison, W.J., & Lewine, J.(1995). Pediatric magnetic source imaging. In J. Kucharczyk,

Figure 6 Spatiotemporal activity patterns during epileptic spikes in three patients with Landau-Kleffner syndrome. Each patient’s spikes were modeled with the number of ECDs necessary to explain the signal. To explore cortical spread patterns, the set of ECDs was aligned after peak activity of each independent ECD in turn (shaded). Superimposed traces represent the ECD solution for several unaveraged spikes. Modified from Paetau et al. (1999).

368 Ritva Paetau


M. Moseley, T. Roberts & W. Orrison (Eds.), Functional neu-roimaging. Neuroimaging clinics of North America (pp. 575–596). Philadelphia: Saunders.

Cohen, D. (1968). Magnetoencephalography: evidence of mag-netic field produced by alpha-rhythm currents. Science, 161,784–786.

Deonna, T., Peter, C., & Ziegler, A.-L. (1989). Adult follow-upof the acquired aphasia-epilepsy syndrome. Report of 7cases. Neuropediatrics, 20, 132–138.

Forss, N., Nakasato, N., Ebersole, J., Nagamine, T., &Salmelin, R. (2000). Clinical use of magnetoencephalogra-phy. In Z. Ambler, S. Nevsimalova, Z. Kadanka & P. Rossini(Eds.), Clinical neurophysiology at the beginning of the 21stcentury (pp. 287–297). Amsterdam: Elsevier Science B.V.

Forss, N., Silen, T., & Karjalainen, T. (2001). Lack of activa-tion of human secondary somatosensory cortex in Unverricht-Lundborg type of progressive myoclonus epilepsy. Annalsof Neurology, 49, 90–97.

Gallen, C., Hirschkoff, E., & Buchanan, D. (1995). Magne-toencephalography and magnetic source imaging. Capabili-ties and limitations. In J. Kucharczyk, M. Moseley, T.Roberts & W.J. Orrison (Eds.), Functional neuroimaging.Neuroimaging clinics of North America (pp. 227–249). Phil-adelphia: Saunders.

Hämäläinen, M., Hari, R., Ilmoniemi, R.J., Knuutila, J., &Lounasmaa, O.V. (1993). Magnetoencephalography – theory,instrumentation, and applications to noninvasive studies ofthe working human brain. Reviews of Modern Physics, 65,414–479.

Hari, R. (1998). Magnetoencephalography as a tool of clinicalneurophysiology. In E. Niedermeyer & F. Lopes da Silva(Eds.), Electroencephalography: Basic principles, clinicalapplications, and related fields (pp. 1107–1134). Baltimore:Williams & Wilkins.

Hari, R., Ahonen, A., Forss, N., Granström, M.-L.,Hämäläinen, M., Kajola, M., Knuutila, J., Lounasmaa, O.,Mäkelä, J., Paetau, R., Salmelin, R., & Simola, J. (1993).Parietal mirror focus detected with a whole-head neuro-magnetometer. NeuroReport, 5, 45–48.

Hari, R., Hämäläinen, M., Ilmoniemi, R., Kaukoranta, E.,Reinikainen, K., Salminen, J., Alho, K., Näätänen, R., &Sams, M. (1984). Responses of the primary auditory cortexto pitch changes in a sequence of tone pips: neuromagneticrecordings in man. Neuroscience Letters, 50, 127–132.

Hari, R., & Ilmoniemi, R.J. (1986). Cerebral magnetic fields.Critical Revues in Biomedical Engineering, 14, 93–126.

Heim, S., Eulitz, C., Kaufmann, J., Fuchter, I., Pantev, C.,Lamprecht-Dinnesen, A., Matulat, P., Scheer, P., Borstel, M., &Elbert, T. (2000). Atypical organisation of the auditorycortex in dyslexia as revealed by MEG. Neuropsychologia,38, 1749–1759.

Helenius, P., Salmelin, R., Service, E., & Conolly, J. (1998).Distinct time courses of word and context comprehension inthe left temporal cortex. Brain, 121, 1133–1142.

Kamada, K., Moller, M., Saguer, M., Kassubek, J.,Kaltenhauser, M., Kober, H., Uberall, M., Lauffer, H.,Wenzel, D., & Vieth, J. (1998). Localization analysis of neu-ronal activities in benign rolandic epilepsy using magnetoen-

cephalography. Journal of the Neurological Sciences, 154,164–172.

Karhu, J., Hari, R., Paetau, R., Kajola, M., & Mervaala, E.(1994). Cortical reactivity and mu rhythm in progressivemyoclonus epilepsy Electroencephalography and ClinicalNeurophysiology, 90, 93–102.

Knowlton, R., Laxer, K., Aminoff, M., Roberts, T., Wong, S.,& Rowley, H. (1997). Magnetoencephalography in partialepilepsy: clinical yield and localization accuracy. Annals ofNeurology, 42, 622–631.

Kubota, M., Oka, A., Kin, S., & Sakakihara, Y. (1996). Gen-erators of rolandic discharges identified by magnetoencepha-lography. Electroencephalography and Clinical Neurophysiology,Supplement, 47, 393–401.

Kubota, M., Takeshita, K., Sakakihara, Y., & Yangisawa, M.(2000). Magnetoencephalographic study of giant somatosen-sory evoked responses in patients with rolandic epilepsy.Journal of Child Neurology, 15, 370–379.

Landau, W., & Kleffner, F.R. (1957). Syndrome of acquiredaphasia with convulsive disorder in children. Neurology, 7,523–530.

Lauronen, L. (2001). Neuromagnetic studies on somatosensoryfunctions in CLN3, CLN5 and CLN8 forms of neuronalceroid lipofuschinoses. Doctoral dissertation, University ofHelsinki, Helsinki.

Leahy, R., Mosher, J., Spencer, M., Huang, M., & Lewine, J.(1998). A study for dipole localization accuracy for MEGand EEG using a human skull phantom. Electroencephalo-graphy and Clinical Neurophysiology, 107, 159–173.

Levänen, S., Hari, R., McEvoy, L., & Sams, M. (1993).Responses of the human auditory cortex to changes in oneversus two stimulus features. Experimental Brain Research,97, 177–183.

Lewine, J.D., Andrews, R., Chez, M., Patil, A.A., Devinsky,O., Smith, M., Kanner, A., Davis, J.T., Funke, M., Jones, G.,Chong, B., Provencal, S., Weisend, M., Lee, R.R., &Orrison, W.W.J. (1999). Magnetoencephalographic patternsof epileptiform activity in children with regressive autismspectrum disorders. Pediatrics, 104, 405–418.

Lewine, J.D., & Orrison Jr., W.W. (1995). Magnetoencephalo-graphy and magnetic source imaging. In W.W. Orrison Jr.,J.D. Lewine, J.A. Sanders & M.F. Hartshome (Eds.), Func-tional brain imaging (pp. 369–417). St Louis: Mosby Year-Book.

Mäkelä, J., Kirveskari, E., Seppä, M., Hämäläinen, M., Forss, N.,Avikainen, S., Salonen, O., Salenius, S., Kovala, T., Randell, T.,Jääskeläinen, J., & Hari, R. (2001). Three-dimensional inte-gration of brain anatomy and function to facilitate intra-operative navigation around the sensorimotor strip. HumanBrain Mapping, 12, 180–192.

Minami, T., Gondo, K., Yamamoto, T., Yanai, S., Tasaki, K.,& Ueda, K. (1996). Magnetoencephalographic analysis ofrolandic discharges in benign childhood epilepsy. Annals ofNeurology, 39, 326–334.

Minassian, A., Otsubo, H., Weiss, S., Elliott, I., Rutka, J., &Snead, O. (1999). Magnetoencephalographic localization inpediatric epilepsy surgery: comparison with invasive intra-cranial electroencephalography. Annals of Neurology, 46,627–633.



Morrell, F., Whisler, W., Smith, M., Hoeppner, T., Pierre-Louis, S.,Kanner, A., Buelow, J., Ristanovic, R., Bergen, D., Chez, M.,& Hasegawa, H. (1995). Landau-Kleffner syndrome: treat-ment with subpial intracortical transsection. Brain, 118,1529–1546.

Mosher, J.C., Lewis, P.S., & Leahy, R. (1992). Multiple dipolemodeling and localizing from spatio-temporal MEG data.IEEE Transactions on Biomedical Engineering, 39, 541–557.

Näätänen, R., Lehtokoski, A., Lennes, M., Cheour, M.,Huotilainen, M., Iivonen, A., Vainio, M., Alku, P., Ilmoniemi, R.,Luuk, A., Allik, J., Sinkkonen, J., & Alho, K. (1997).Language-specific phoneme representations revealed byelectric and magnetic brain responses. Nature, 385, 432–434.

Ojemann, G., Ojemann, J., Lettich, E., & Berger, M. (1989).Cortical language localization in left dominant hemisphere –an electrical stimulation mapping investigation in 117patients. Journal of Neurosurgery, 71, 316–326.

Otsubo, H., & Snead, O. III. (2001). Magnetoencephalography(MEG) and magnetic source imaging (MSI) in children.Journal of Child Neurology, 16, 227–235.

Paetau, R. (1994). Sounds trigger spikes in the Landau-Kleffnersyndrome. Journal of Clinical Neurophysiology, 11, 231–241.

Paetau, R., Ahonen, A., Salonen, O., & Sams, M. (1995).Auditory evoked magnetic fields to tones and pseudowordsin healthy children and adults. Journal of Clinical Neuro-physiology, 12, 177–185.

Paetau, R., Granström, M.-L., Blomstedt, G., Jousmäki, V.,Korkman, M., & Liukkonen, E. (1999). Magnetoencepha-lography in presurgical evaluation of children with theLandau-Kleffner syndrome. Epilepsia, 40, 326–335.

Paetau, R., Hämäläinen, M., Hari, R., Kajola, M., Karhu, J.,Larsen, T.A., Lindahl, E., & Salonen, O. (1994). MEGevaluation of children and adolescents with intractableepilepsy. Epilepsia, 35, 275–284.

Paetau, R., Kajola, M., Korkman, M., Hämäläinen, M.,Granström, M.L., & Hari, R. (1991). Landau-Kleffner syn-drome: epileptic activity in the auditory cortex. Neuro-Report, 2, 201–204.

Papanicolaou, A., Simos, P., Breier, J., Zouridakis, G.,Willmore, L., Wheless, J., Constantinou, J., Maggio, W., &Gormley, W. (1999). Magnetoencephalographic mapping of thelanguage-specific cortex. Journal of Neurosurgery, 90, 85–93.

Rojas, D., Walker, J., Sheeder, J., Teale, P., & Reite, M. (1998).Developmental changes in refractoriness of the neuro-magnetic M100 in children. NeuroReport, 9, 1543–1547.

Salenius, S., Portin, K., Kajola, M., Salmelin, R., & Hari, R. (1997).Cortical control of human motorneuron firing during isometriccontraction. Journal of Neurorphysiology, 77, 3401–3405.

Salmelin, R., Hari, R., Lounasmaa, O., & Sams, M. (1994).Dynamics of brain activation during picture naming.Nature, 368, 463–465.

Sams, M., Kaukoranta, E., Hämäläinen, M., & Näätänen, R.(1991). Cortical activity elicited by changes in auditory stim-uli: different sources for the magnetic N100m and mismatchresponses. Psychophysiology, 28, 21–29.

Sarvas, J. (1987). Basic mathematical and electromagnetic con-cepts of the biomagnetic inverse problem. Physics in Medi-cine and Biology, 32, 11–22.

Sato, S., Balish, M., & Muratore, R. (1991). Principles of mag-netoencephalography. Journal of Clinical Neurophysiology, 8,144–156.

Simos, P., Breier, J., Fletcher, J., Bergman, E., & Papanicolaou,A. (2000). Cerebral mechanisms involved in word readingin dyslexic children: a magnetic source imaging approach.Cerebral Cortex, 10, 809–816.

Simos, P., Papanicolaou, A., Breier, J., Wheless, J., Constantinou, J.,Gormley, W., & Maggio, W. (1999). Localization of language-specific cortex by using magnetic source imaging and electricalstimulation mapping. Journal of Neurosurgery, 91, 787–796.

Smith, J., Gallen, C., Orrison, W., Lewine, J., Murro, A., King, D.,& Gallagher, B. (1994). Role of multichannel magneto-encephalography in the evaluation of ablative seizure surgerycandidates. Stereotactic and Functional Neurosurgery, 62,238–244.

Smith, J., Gallen, C., & Schwartz, B. (1994). Multichannelmagnetoencephalographic mapping of sensorimotor cortexfor epilepsy surgery. Stereotactic and Functional Neuro-surgery, 62, 245–251.

Smith, J., Schwartz, B., Gallen, C., Orrison, W., Lewine, J.,Murro, A., King, D., & Park, Y. (1995). Multichannel mag-netoencephalography in ablative seizure surgery outside theanteromesial temporal lobe. Stereotactic and FunctionalNeurosurgery, 65, 81–85.

Sobel, D., Aung, M., Otsubo, H., & Smith, M. (2000). Magne-toencephalography in children with Landau-Kleffner syn-drome and acquired epileptic aphasia. American Journal ofNeuroradiology, 21, 301–307.

Sutherling, W.W., Crandall, P.H., Engel, J.J., Darcey, T.M.,Cahan, L.D., & Barth, D.S. (1988). The magnetic and elec-tric fields agree with intracranial localizations of somatosen-sory cortex. Neurology, 38, 1705–1714.

Tarkiainen, A., Hämäläinen, M., & Salmelin, R. (1996).Comparison of spherical and realistically shaped conductionmodels in magnetoencephalography. 8th World Congress ofInternational Organization of Psychophysiology, Tampere,Finland.

Tassinari, C.A., & DeMarco, P. (1985). Benign partial epilepsywith extreme somato-sensory evoked potentials. In J. Roger,C. Dravet, M. Bureau, F.E. Dreifuss & P. Wolf (Eds.), Epi-leptic syndromes in infancy, childhood, and adolescence(pp. 176–180). London: John Libbey Eurotext.

Uusitalo, M., & Ilmoniemi, R. (1997). Signal-space projectionmethod for separating MEG or EEG into components.Medical and Biological Engineering and Computing, 35, 135–140.

Uutela, K., Hämäläinen, M., & Somersalo, E. (1999). Visual-ization of magnetoencephalographic data using minimumcurrent estimates. Neuroimage, 10, 173–180.

van der Broek, S., Reinders, F., Donderwinkel, M., & Peters, M.(1998). Volume conduction effects in EEG and MEG. Electro-encephalography and Clinical Neurophysiology, 106, 522–534.

Vihla, M., Lounasmaa, O., & Salmelin, R. (2000). Corticalprocessing of change detection: dissociation between naturalvowels and two-frequency complex tones. Proceedings ofNational Academy of Sciences, USA, 97, 10590–10594.

370 Ritva Paetau


Wada, J., & Rasmussen, T.B. (1960). Intracarotid injection ofsodium amytal for the lateralization of cerebral speech dom-inance. Journal of Neurosurgery, 17, 266–282.

Weinberg, H., Stroink, G., & Katila, T. (1985). Biomagnetism:Applications and theory. New York: Pergamon Press.

Wheless, J., Willmore, L., Breier, J., Kataki, M., Smith, J.,King, D., Meador, K., Park, Y., Loring, D., Clifton, G.,Baumgartner, J., Thomas, A., Constantinou, J., & Papanico-lau, A. (1999). A comparison of magnetoencephalography,

MRI, and V-EEG in patients evaluated for epilepsy surgery.Epilepsia, 40, 931–941.

Williamson, S.J., & Kaufman, L. (1981). Biomagnetism. Jour-nal of Magnetism and Magnetic Materials, 22, 129–202.

Zimmermann, J.E., Thiene, P., & Harding, J.T. (1970). Designand operation of stable rf-biased superconducting point-contact quantum devices and a note on the properties ofperfectly clean metal contacts. Journal of Applied Physics,41, 1572–1580.

ritva paetau - biac.duke.edu · ritva paetau department of child neurology, hospital for children...

Documents