Spontaneous MEG Research Articles

Towards localization of radial traveling waves in the evoked and spontaneous MEG: A solution based on the intra-cortical propagation hypothesis

In animal experiments, radial traveling waves have been recorded on the surface of the cortex. In humans, the recording by microelectrode matrices reveals only fragments of such waves. Our basic assumption is that the source of the EEG/MEG in the alpha and beta bands are radial traveling waves. Similar waves are generated in the networks of recurrently coupled neurons, where excitation is propagated through intracortical connections. We simulated traveling waves on the surface of the human brain and compared the simulation data with the experimental signals of the evoked and spontaneous MEG. Model waves were assigned a number of epicenters in the ROI on the cortical surface, different propagation velocities, and phase. The frequency of the model wave was determined from the spectral and wavelet analyzes. Correlation data allowed us to localize radial waves and to select their parameters in the postcentral sulcus with stimulation of the median nerve and in the cuneus sulcus at rest in healthy human adults. Our approach resulted in a successful reconstruction of the radial waves’ dynamics on individual brain surfaces.

A three domain covariance framework for EEG/MEG data

In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three components that correspond to space, time and epochs/trials, and consider maximum likelihood estimation of the unknown parameter values. An iterative algorithm that finds approximations of the maximum likelihood estimates is proposed. Our covariance model is applicable in a variety of cases where spontaneous EEG or MEG acts as source of noise and realistic noise covariance estimates are needed, such as in evoked activity studies, or where the properties of spontaneous EEG or MEG are themselves the topic of interest, like in combined EEG–fMRI experiments in which the correlation between EEG and fMRI signals is investigated.We use a simulation study to assess the performance of the estimator and investigate the influence of different assumptions about the covariance factors on the estimated covariance matrix and on its components. We apply our method to real EEG and MEG data sets.

3-A-D-1-13. High frequency activities in the frontal cortices during observation of moral or immoral behaviors

We measured MEG in twenty-one healthy subjects when they judged 120 duologue-scenes moral or immoral behaviors using a response of the left index (moral) or middle finger (immoral) movement. Sixty duologue-scenes contained aggressive or egoistic context of either character’s line, and the remainder were the same scenes with neutral or friendly context of both characters’ lines. These scenes were successively presented for 6.5 s in a random order with taking enough breaks. The mean reaction time for the response was approximately 4 s. Spontaneous MEG of 3 s prior to the response was analyzed by a spatial filtering algorithm method. The MEG when watching the duologue-scenes without any lines served as the baseline. As compared with the baseline, the power of high frequency activity (HFA, 22–100 Hz) was increased in the left occipital cortex from −2.5 to −0.5 s, and the right motor area from −1 to 0 s prior to the response for judgment of either moral or immoral behavior. When judging the scenes immoral behaviors, the augmented HFA was observed in the bilateral orbitofrontal and anterior cingulate cortices from −1.7 to 0 s, suggesting that the activations in these areas are related to aversion feeling and decision-making.

Long-range functional interactions in the resting human brain

Event Abstract Back to Event Long-range functional interactions in the resting human brain Dante Mantini1, 2* 1 KU Leuven, Department of Kinesiology, Belgium 2 ETH Zurich, Department of Health Sciences and Technology, Switzerland Perceptions, thoughts, emotions and actions emerge from interactions between neuronal assemblies distributed across the brain rather than from local computations in restricted brain areas. Indeed, the operation of every cognitive act requires the integration of distributed activity, as implemented through long-range neuronal communication via a network of structural connections. Functional interactions in the brain are very often studied in subjects at rest, since the resting state is a privileged condition in which brain activity is unbiased by any specific goal-directed task. Early resting state studies showed that electrophysiological oscillatory activity in specific frequency bands supports synchronization processes related to long-range neuronal communication. In turn, experimental evidence from neuroimaging studies revealed that the human brain is organized into multiple large-scale networks of regions showing correlated hemodynamic activity. Multimodal studies have begun to disclose relationships between functional connectivity, as revealed by hemodynamic signals, and underlying electrophysiological processes. Furthermore, functional connectivity studies directly based on electrophysiological signals have recently revealed fundamental information regarding long-range neuronal communication at behaviorally relevant time-scales. The integration of different lines of evidence from hemodynamic and electrophysiological studies suggests that rapid changes of synchronized oscillatory activity in distributed brain networks is relevant for the ongoing maintenance and modulation of the task representations that form the basis of our cognitive flexibility. Acknowledgements The work was supported by the Swiss National Science Foundation (320030_146531) and the Seventh Framework Programme European Commission (PCIG12-2012-334039). References Lei X, Wang Y, Yuan H, Mantini D. Neuronal oscillations and functional interactions between resting state networks. Hum Brain Mapp. 2014 Jul;35(7):3517-28. Ganzetti M, Mantini D. Functional connectivity and oscillatory neuronal activity in the resting human brain. Neuroscience. 2013 Jun 14;240:297-309. doi: 10.1016/j.neuroscience.2013.02.032. de Pasquale F, Della Penna S, Snyder AZ, Lewis C, Mantini D, Marzetti L, Belardinelli P, Ciancetta L, Pizzella V, Romani GL, Corbetta M. Temporal dynamics of spontaneous MEG activity in brain networks. Proc Natl Acad Sci U S A. 2010 Mar 30;107(13):6040-5. Mantini D, Della Penna S, Marzetti L, de Pasquale F, Pizzella V, Corbetta M, Romani GL. A signal-processing pipeline for magnetoencephalography resting-state networks. Brain Connect. 2011;1(1):49-59. Mantini D, Perrucci MG, Del Gratta C, Romani GL, Corbetta M. Electrophysiological signatures of resting state networks in the human brain. Proc Natl Acad Sci U S A. 2007 Aug 7;104(32):13170-5. Keywords: Electroencephalography, resting state, functional connectivity, Neuronal communication, brain oscillations Conference: Second Belgian Neuroinformatics Congress, Leuven, Belgium, 4 Dec - 4 Dec, 2015. Presentation Type: Invited Lecture Topic: Brain Imaging Citation: Mantini D (2015). Long-range functional interactions in the resting human brain. Front. Neuroinform. Conference Abstract: Second Belgian Neuroinformatics Congress. doi: 10.3389/conf.fninf.2015.19.00001 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 02 Nov 2015; Published Online: 17 Nov 2015. * Correspondence: Dr. Dante Mantini, KU Leuven, Department of Kinesiology, Leuven, --Select State--, 3001, Belgium, dante.mantini@kuleuven.be Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Dante Mantini Google Dante Mantini Google Scholar Dante Mantini PubMed Dante Mantini Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Poster Abstracts for Alcoholism and Stress: A Framework for Future Treatment Strategies

It has been firmly established that opening and closing the eyes strongly modulate the electro- and magnetoencephalography (EEG and MEG) signals acquired during wakeful rest. Certain features of the resting EEG are altered in chronic alcoholics and their offspring, and have been proposed as biomarkers for alcoholism. Spontaneous brain oscillations are also affected by pharmacological manipulations, but the spectral and spatial characteristics of these changes are not clear. This study examined effects of the eyes-open (EO) and eyes-closed (EC) resting paradigm and alcohol challenge on the spatial profile of spontaneous MEG and EEG oscillations. Whole-head MEG and scalp EEG signals were acquired simultaneously from healthy social drinkers (n = 17) who participated in both alcohol (0.6 g/kg ethanol for men, 0.55 g/kg for women) and placebo conditions in a counterbalanced design. Power of the signal was calculated with Fast Fourier Transform and was decomposed into its constituent theta (4–7 Hz), alpha (8–12 Hz), and beta (15–20 Hz) frequency bands. High-resolution structural MRI images were additionally obtained from all participants and used to constrain distributed minimum norm inverse source power estimates. The spatial estimates of the main generator nodes were in agreement with studies using a combined fMRI-EEG approach. Alpha band oscillations dominated the spectral profile and their source was estimated to the medial parieto-occipital area. Power in theta and beta bands was weaker overall and their sources were estimated to a more focal medial prefrontal area. EO and EC manipulation most strongly modulated power in the alpha band, but a wide-band power increase was observed during the EC condition. Alcohol intoxication increased alpha power, particularly during the EC condition. Application of this methodology to cohorts of chronic alcoholics or individuals at risk could potentially provide insight into the neural basis of oscillatory differences that may be predictive of the vulnerability to alcoholism.

Oscillatory spatial profile of alcohol's effects on the resting state: Anatomically-constrained MEG

It has been firmly established that opening and closing the eyes strongly modulate the electro- and magnetoencephalography (EEG and MEG) signals acquired during wakeful rest. Certain features of the resting EEG are altered in chronic alcoholics and their offspring, and have been proposed as biomarkers for alcoholism. Spontaneous brain oscillations are also affected by pharmacological manipulations, but the spectral and spatial characteristics of these changes are not clear. This study examined effects of the eyes-open (EO) and eyes-closed (EC) resting paradigm and alcohol challenge on the spatial profile of spontaneous MEG and EEG oscillations. Whole-head MEG and scalp EEG signals were acquired simultaneously from healthy social drinkers (n = 17) who participated in both alcohol (0.6 g/kg ethanol for men, 0.55 g/kg for women) and placebo conditions in a counterbalanced design. Power of the signal was calculated with Fast Fourier Transform and was decomposed into its constituent theta (4–7 Hz), alpha (8–12 Hz), and beta (15–20 Hz) frequency bands. High-resolution structural MRI images were additionally obtained from all participants and used to constrain distributed minimum norm inverse source power estimates. The spatial estimates of the main generator nodes were in agreement with studies using a combined fMRI-EEG approach. Alpha band oscillations dominated the spectral profile and their source was estimated to the medial parieto-occipital area. Power in theta and beta bands was weaker overall and their sources were estimated to a more focal medial prefrontal area. EO and EC manipulation most strongly modulated power in the alpha band, but a wide-band power increase was observed during the EC condition. Alcohol intoxication increased alpha power, particularly during the EC condition. Application of this methodology to cohorts of chronic alcoholics or individuals at risk could potentially provide insight into the neural basis of oscillatory differences that may be predictive of the vulnerability to alcoholism.

Exploring mechanisms of spontaneous functional connectivity in MEG: How delayed network interactions lead to structured amplitude envelopes of band-pass filtered oscillations

Spontaneous (or resting-state) brain activity has attracted a growing body of neuroimaging research over the last decades. Whole-brain network models have proved helpful to investigate the source of slow (<0.1Hz) correlated hemodynamic fluctuations revealed in fMRI during rest. However, the mechanisms mediating resting-state long-distance correlations and the relationship with the faster neural activity remain unclear. Novel insights coming from MEG studies have shown that the amplitude envelopes of alpha- and beta-frequency oscillations (~8–30Hz) display similar correlation patterns as the fMRI signals.In this work, we combine experimental and theoretical work to investigate the mechanisms of spontaneous MEG functional connectivity. Using a simple model of coupled oscillators adapted to incorporate realistic whole-brain connectivity and conduction delays, we explore how slow and structured amplitude envelopes of band-pass filtered signals – fairly reproducing MEG data collected from 10 healthy subjects at rest – are generated spontaneously in the space-time structure of the brain network.Our simulation results show that the large-scale neuroanatomical connectivity provides an optimal network structure to support a regime with metastable synchronization. In this regime, different subsystems may temporarily synchronize at reduced collective frequencies (falling in the 8–30Hz range due to the delays) while the global system never fully synchronizes. This mechanism modulates the frequency of the oscillators on a slow time-scale (<0.1Hz) leading to structured amplitude fluctuations of band-pass filtered signals. Taken overall, our results reveal that the structured amplitude envelope fluctuations observed in resting-state MEG data may originate from spontaneous synchronization mechanisms naturally occurring in the space-time structure of the brain.

Correlations between development of cognitive/behavioral skills and spontaneous MEG for 3-4-year-old healthy children(Technique and method)

Correlations between development of cognitive/behavioral skills and spontaneous MEG for 3-4-year-old healthy children(Technique and method)

P33-24 Correlations between the development of cognitive functions and spontaneous MEG responses of healthy 3- to 4-year-old infants

P33-24 Correlations between the development of cognitive functions and spontaneous MEG responses of healthy 3- to 4-year-old infants

Temporal dynamics of spontaneous MEG activity in brain networks

Functional MRI (fMRI) studies have shown that low-frequency (<0.1 Hz) spontaneous fluctuations of the blood oxygenation level dependent (BOLD) signal during restful wakefulness are coherent within distributed large-scale cortical and subcortical networks (resting state networks, RSNs). The neuronal mechanisms underlying RSNs remain poorly understood. Here, we describe magnetoencephalographic correspondents of two well-characterized RSNs: the dorsal attention and the default mode networks. Seed-based correlation mapping was performed using time-dependent MEG power reconstructed at each voxel within the brain. The topography of RSNs computed on the basis of extended (5 min) epochs was similar to that observed with fMRI but confined to the same hemisphere as the seed region. Analyses taking into account the nonstationarity of MEG activity showed transient formation of more complete RSNs, including nodes in the contralateral hemisphere. Spectral analysis indicated that RSNs manifest in MEG as synchronous modulation of band-limited power primarily within the theta, alpha, and beta bands-that is, in frequencies slower than those associated with the local electrophysiological correlates of event-related BOLD responses.

MEG of Parkinsonian patients with deep brain stimulation

Event Abstract Back to Event MEG of Parkinsonian patients with deep brain stimulation Katja Airaksinen1, 2*, Jyrki P. Mäkelä1, Samu Taulu3, Antti Ahonen3, Juha Pohjola4, Jussi Nurminen1, Alfons Schnitzler5, 6 and Eero Pekkonen2 1 Helsinki University Central Hospital, BioMag laboratory, Finland 2 Helsinki University Central Hospital, Department of Neurology, Finland 3 Elekta Neuromag, Finland 4 Helsinki University Central Hospital, Department of Neurosurgery, Finland 5 Heinrich-Heine-University, Department of Neurology, Germany 6 Heinrich-Heine-Univeristy, Institute of Clinical Neuroscience and Medical Psychology, Germany Our aim was to clarify the mechanism of action of deep brain stimulation (DBS) of subthalamic nucleus (STN) in patients with Parkinson's disease (PD). We studied 12 advanced PD patients with STN DBS using a 306-channel MEG-system (Elekta Neuromag®) both when the stimulator was on and off. Auditory evoked fields (AEFs) were elicited by 1-kHz tones delivered to each ear separately and somatosensory evoked fields (SEFs) by electrical pulses delivered to the median nerve at both wrists. Spontaneous MEG was recorded in combination with EMG from extended arm of one patient before and after DBS implantation. The magnetic artifacts caused by DBS were suppressed by the spatiotemporal signal space separation (tSSS) -method. Single dipole models for AEFs and SEFs were constructed. The source strengths of AEF N100m and SEF P60m were calculated both with DBS on and off. Coherence spectra between MEG signals and wrist extensor EMG were studied when DBS was on and off both before and after operation. DBS significantly enhanced AEF N100m to ipsilateral stimulation in the right hemisphere (49 ± 17 nAm DBS on, 43 ± 16 nAm DBS off, p=0.02). The mean source strengths of contralateral N100m also increased when DBS was on (n.s.). The mean SEF source strengths of P60m were stronger when stimulator was on than off (n.s.). In one patient the MEG-EMG coherence was abolished 0.5 months after DBS implantation. Four months after implantation the coherence reappeared when DBS was off, whereas it was suppressed when DBS was on. DBS significantly diminished motor symptoms in the patients. MEG with tSSS allows to study DBS effects in PD. DBS appears to modulate auditory processing in PD patients, and have a modest effect on SEFs. Data of one patient suggests that DBS suppresses the MEG-EMG coherence. In line with data from animal models, DBS modulates cortical functions of the human brain. Conference: Biomag 2010 - 17th International Conference on Biomagnetism , Dubrovnik, Croatia, 28 Mar - 1 Apr, 2010. Presentation Type: Poster Presentation Topic: MEG: Clinical applications Citation: Airaksinen K, Mäkelä JP, Taulu S, Ahonen A, Pohjola J, Nurminen J, Schnitzler A and Pekkonen E (2010). MEG of Parkinsonian patients with deep brain stimulation. Front. Neurosci. Conference Abstract: Biomag 2010 - 17th International Conference on Biomagnetism . doi: 10.3389/conf.fnins.2010.06.00285 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 05 Apr 2010; Published Online: 05 Apr 2010. * Correspondence: Katja Airaksinen, Helsinki University Central Hospital, BioMag laboratory, Helsinki, Finland, katja.airaksinen@helsinki.fi Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Katja Airaksinen Jyrki P Mäkelä Samu Taulu Antti Ahonen Juha Pohjola Jussi Nurminen Alfons Schnitzler Eero Pekkonen Google Katja Airaksinen Jyrki P Mäkelä Samu Taulu Antti Ahonen Juha Pohjola Jussi Nurminen Alfons Schnitzler Eero Pekkonen Google Scholar Katja Airaksinen Jyrki P Mäkelä Samu Taulu Antti Ahonen Juha Pohjola Jussi Nurminen Alfons Schnitzler Eero Pekkonen PubMed Katja Airaksinen Jyrki P Mäkelä Samu Taulu Antti Ahonen Juha Pohjola Jussi Nurminen Alfons Schnitzler Eero Pekkonen Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Analyzing statistical dependencies of MEG source envelopes

Event Abstract Back to Event Analyzing statistical dependencies of MEG source envelopes Aapo Hyvarinen1*, Kun Zhang1, Pavan Ramkumar2 and Riitta Hari3 1 University of Helsinki, Finland 2 Helsinki University of Technology, Brain Research Unit, Low Temperature Laboratory, Finland 3 Helsinki University of Technology, Brain Research Unit, Finland We propose a new approach for exploratory analysis of spontaneous MEG activity. The goal is to analyze the correlated modulation of sources of rhythmic activity. The method can be applied to any spontaneous activity, for example signals recorded during rest. To begin with, we localize a number of sources of rhythmic activity using some existing method, for example statistical blind source separation based on independent component analysis [1]. Next, we compute the envelopes of the sources based on generalized autoregressive conditional heteroscedasticity (GARCH) models. We then propose two new methods for analyzing the computed envelopes, based on their statistical dependencies. First, we can simply apply statistical blind separation methods to obtain a decomposition of the envelopes into higher-order components or "modulators", which are approximately independent. Second, we develop a method combining causal analysis with GARCH models in order to discover effective connectivities between the sources, in particular their envelopes. We made preliminary experiments applying these methods on MEG recordings during naturalistic stimulation applied in a previous fMRI study [2]. The first method produces higher-order components that are related to an automatic grouping (clustering) of the sources: sources related to processing the same sense (visual, auditory, or tactile) are typically grouped together. The causal analysis method typically finds connections between sources which process stimuli of the same modality. Our results indicate that many of the sources found by blind source separation are modulated in a correlated fashion. Further analysis of such correlations could provide new information about rhythmic brain activity and connectivity between brain regions.

A multipole beamformer for improved functional imaging of spontaneous MEG signals

Event Abstract Back to Event A multipole beamformer for improved functional imaging of spontaneous MEG signals Stephen Robinson1* and Jiri Vrba2 1 Henry Ford Hospital, United States 2 Elekta, Finland A scalar LCMV beamformer using a 1st order current multipole (dipole plus quadrupole) forward solution constraint has been developed and tested. The current multipole expansion provides a compact parametric representation of MEG signals arising from sources having significant extent over a curved cortical surface. Although the dipole model has been useful for localizing simple focal sources, it is not optimal for beamformer imaging of spontaneous MEG signals. Epileptic activity and background brain rhythms arise from sources with extent comparable to the distance to the MEG sensors. For any specified coordinate the beamformer weights are computed by first determining the moment vector that maximizes signal-to-noise ratio (SNR). This is done using a variant of Sekihara’s method, except that the dipole and quadrupole parts of the moment vector must be normalized independently in order to compute the forward solution for the scalar beamformer. This step accounts for their different physical units. All subsequent calculations of virtual sensor waveforms and functional images are derived from SNR to avoid representing activity in mixed units. We compared the multipole and dipole beamformers using simulated data and acquired MEG signals. The spatial selectivity of the multipole beamformer is nearly identical to that of the dipole beamformer for simulation of a single dipole plus noise. However, the multipole beamformer has been shown to be able to resolve two closely spaced dipole sources under conditions where the dipole beamformer could find only a single spatial peak between the sources. Using acquired MEG data the multipole beamformer is shown to localize activity closely to the cortical mantle whereas the dipole beamformer localized the same activity deeper – sometimes within the white matter. In each case, the multipole beamformer yielded higher SNR as a consequence of the improvement in modeling. This research was supported by NIH/NINDS Grant R01 NS30914. Conference: Biomag 2010 - 17th International Conference on Biomagnetism , Dubrovnik, Croatia, 28 Mar - 1 Apr, 2010. Presentation Type: Poster Presentation Topic: MEG Modeling Citation: Robinson S and Vrba J (2010). A multipole beamformer for improved functional imaging of spontaneous MEG signals. Front. Neurosci. Conference Abstract: Biomag 2010 - 17th International Conference on Biomagnetism . doi: 10.3389/conf.fnins.2010.06.00041 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Mar 2010; Published Online: 19 Mar 2010. * Correspondence: Stephen Robinson, Henry Ford Hospital, Detroit, United States, robinson@neurnis.neuro.hfh.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Stephen Robinson Jiri Vrba Google Stephen Robinson Jiri Vrba Google Scholar Stephen Robinson Jiri Vrba PubMed Stephen Robinson Jiri Vrba Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

MEG EVALUATION OF EPILEPTIC ACTIVITY IN THE TIME AND FREQUENCY DOMAIN

We investigated the localization of current sources in the time and frequency domain from spontaneous MEG data recorded from nine epileptic patients (six females; three males) randomly selected, who had a mean age of 41 years old (range of 17-78 years old), with different types of epilepsy. The MEG data were recorded in a magnetically shielded room with a whole-head 122 channel biomagnetometer. For each MEG spike, we calculated the single Equivalent Current Dipole (ECD) sources at the initial spike peaks with a spherical model. MRI and EEG findings were available in patients' records. Prominent low frequencies can be seen in the majority of channels. For each patient there was an increase of the frequency range after the ECD in comparison with the frequency range before the ECD, in the whole study group due to epileptic discharge which is statistically significant (p=0.02). There was also a statistical significant difference in the increase of the frequency range in four patients with pathologic MRI (p=0.05), in five patients with normal MRI (p=0.02), in five patients with a high incidence of seizures (p=0.04) and in four patients with onset<10 years (p=0.04). The MEG analysis of neuromagnetic data gives information about the modification of the frequency range in the epileptic brains.

Effects of subthalamic nucleus stimulation on spontaneous sensorimotor MEG activity in a Parkinsonian patient

Abstract Abnormal low-frequency entrainment in sensorimotor cortical areas of Parkinson's disease (PD) patients has been observed in MEG recordings. Efficacy of high-frequency stimulation of subthalamic nucleus (STN) in treating PD may result from blocking such abnormal oscillations. Artifacts elicited by stimulation have precluded MEG study of such patients. We recorded spontaneous MEG activity with a 306-channel Elekta Neuromag® instrument from a Parkinsonian patient with an implanted neurostimulator, with electrodes in both subthalamic nuclei when 130-Hz STN stimulation was on and off. Auditory evoked fields (AEFs) were recorded as well. Brain activity was revealed by applying temporally extended signal space separation on the signals strongly contaminated by stimulation-related artifacts. Bipolar STN stimulation decreased spontaneous activity in the 3–20 Hz range over the right sensorimotor cortex both when eyes were open and closed. Less systematic changes were observed over the left hemisphere where monopolar stimulation was associated with an increase of the low-frequency activity. Suppression of occipital alpha activity in eyes open condition as well as AEF source locations corresponded with those in normal subjects. The results suggest that STN stimulation modifies spontaneous activity over the sensorimotor cortices.

Evaluation of neuronal effects of electroconvulsive therapy by MEG

Interictal spontaneous MEG was investigated in five male patients with major depressive disorder (according to DSM IV) treated with right hemispheric ECT over a period of 5 weeks. Spontaneous MEG activity was also recorded in five male patients treated with tricyclic antidepressants during the same time period. The analysis of slow (0–7 Hz) and fast (12.5–30 Hz) MEG activity was done with the dipole density plot, which uses consecutively estimated dipoles across a given analyzing time and delivers quantified dipole concentrations in three dimensions. In the ECT group, the authors found a significant increase in the dipole concentration in the slow activity range (0–7 Hz) after the first and the subsequent treatments, which could not be found in patients treated with tricyclic antidepressants.

The localization of spontaneous brain activity: first results in patients with cerebral tumors

Objective: From EEG studies, it is known that structural brain lesions are accompanied by abnormal rhythmic electric activity. With the better spatial resolution of MEG, MEG dipole analysis can extend the knowledge based on EEG power spectra. This study presents the first results of a completely automatic analysis method applied to spontaneous MEG. Methods: Spontaneous MEG data of 5 patients with cerebral brain tumors and 4 controls were collected using a whole-head MEG system. Signals were bandpass-filtered with cut-off frequencies according to standard EEG bands. A moving dipole model was fitted to samples with at least twice the average sample power. Dipoles explaining 90% or more of the magnetic variance were projected onto a matched MR scan. Results: In controls, dipole distributions are symmetrical with respect to the mid-sagittal plane whereas distributions in patients often are asymmetrical to it. Dipoles describing gamma activity were located contralateral, and dipoles describing delta and theta activity were located ipsilateral to lesions. Conclusions: The automatic method gives plausible 3-dimensional information about generator foci of abnormal slow waves and other rhythms with respect to lesion foci and thereby adds physiological knowledge to that derived from EEG power spectra.

5-07-29 Functional and metabolic analysis of cerebral infarction by spontaneous meg and 1H MR spectroscopy

5-07-29 Functional and metabolic analysis of cerebral infarction by spontaneous meg and 1H MR spectroscopy

Movement-related slow cortical magnetic fields and changes of spontaneous MEG- and EEG-brain rhythms

Cortical activity was recorded from 5 healthy adults with a 122-channel whole-head magnetometer while the subjects performed during unilateral finger movements at self-paced intervals exceeding 6 s. The readiness field (RF) started over the contralateral somatomotor area 0.3–1 s prior to the movement onset in subjects (Ss) 1, 2, and 4, and culminated in the motor field (MF) 30 ms after it (Ss 1–4). These signals were followed by movement evoked fields MEFI (Ss 1–5) and MEFII (Ss 1–4) at 100–150 ms and 200–250 ms after the movement onset, respectively. One subject showed clear RF over the ipsilateral hemisphere as well. The contralateral dominance of the RF contrasted the more symmetric distribution of the simultaneously recorded electric Berreitschaftspotential (BP). The RF onset never preceded the BP onset. We suggest that BP receives contribution from the early bilateral activation of the crown of the precental gyrus, whereas RF reflects later activity of the fissural motor cortex. Spontaneous oscillations in the background activity (spontaneous activity) of approximately 10 Hz started to dampen 2–3 s prior to the movement onset in the somatomotor areas of both hemispheres with contralateral predominance (S1 and S3), and returned to a steady level 0.8–2 s after the movement onset in all subjects. Higher frequency bands in the same area displayed a prominent rebound about 1 s after the movement onset in 4 subjects. Execution of self-paced movements is evidently expressed differently in the slow movement-related fields and in the cortical spontaneous activity.

Movement-related slow cortical magnetic fields and changes of spontaneous MEG- and EEG-brain rhythms

Cortical activity was recorded from 5 healthy adults with a 122-channel whole-head magnetometer while the subjects performed during unilateral finger movements at self-paced intervals exceeding 6 s. The readiness field (RF) started over the contralateral somatomotor area 0.3–1 s prior to the movement onset in subjects (Ss) 1, 2, and 4, and culminated in the motor field (MF) 30 ms after it (Ss 1–4). These signals were followed by movement evoked fields MEFI (Ss 1–5) and MEFII (Ss 1–4) at 100–150 ms and 200–250 ms after the movement onset, respectively. One subject showed clear RF over the ipsilateral hemisphere as well. The contralateral dominance of the RF contrasted the more symmetric distribution of the simultaneously recorded electric Berreitschaftspotential (BP). The RF onset never preceded the BP onset. We suggest that BP receives contribution from the early bilateral activation of the crown of the precental gyrus, whereas RF reflects later activity of the fissural motor cortex. Spontaneous oscillations in the background activity (spontaneous activity) of approximately 10 Hz started to dampen 2–3 s prior to the movement onset in the somatomotor areas of both hemispheres with contralateral predominance (S1 and S3), and returned to a steady level 0.8–2 s after the movement onset in all subjects. Higher frequency bands in the same area displayed a prominent rebound about 1 s after the movement onset in 4 subjects. Execution of self-paced movements is evidently expressed differently in the slow movement-related fields and in the cortical spontaneous activity.