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MEG correlates of the recognition of facial expressions of emotion were studied in four healthy volunteers. Subjects performed a facial emotion recognition task and a control task involving recognition of complex objects including faces. Facial emotion recognition activated inferior frontal cortex, amygdala and different parts of temporal cortex in a relatively consistent time sequence. The characteristics of these activations were clearly different from those recorded during the control task. Most interesting was the fact that faces evoked different MEG responses as a function of task demands, i.e., the activations recorded during facial emotion recognition were different from those recorded during simple face recognition in the control task. These findings support the assumption that MEG is able to specifically identify the activation pattern of the brain when recognition of the emotional expression of a face is performed.

In this article we investigate MEG correlates of syntactic violations in continuous speech. An early left anterior negativity (ELAN) has been reported in previous EEG studies and has been related to syntactic processing. We used Magnetic Field Tomography (MFT) to extract a 3D estimate of the current density distribution J, from MEG data recorded while subjects listened to continuous speech. Separate estimates were obtained from the activity associated with the first word of the sentence, and the last words of the sentence which signified syntactic violation, semantic violation or correct sentences. In each case independent 3D MFT estimates of activity were obtained 2 ms apart. After converting the solutions into a PET-like format we perform a statistical analysis on a voxel-by-voxel basis. Visual inspection of the power of J at the time of the ELAN component and the statistical maps overlaid on the individual anatomical MRI suggests generators in the vicinity of the auditory cortex and in left frontal regions. Directional activation curves are computed to show the variation of activity as a function of time, from well circumscribed areas. The activation curve for the auditory cortex has a characteristic pattern consisting of three peaks, seen in the average time-locked to the onset of the first word, and the critical word of the syntactic violation. The left auditory cortex shows a delay of about 30 ms in the syntactic violation condition compared to the first word condition. No such delay is seen in the right auditory cortex.

Recently, magnetoencephalography (MEG)-based real-time brain computing interfaces (BCI) have been developed to enable novel and promising methods of neuroscience research and therapy. Artifact rejection prior to source localization largely enhances the localization accuracy. However, many BCI approaches neglect real-time artifact removal due to its time consuming processing. With cardiac artifact rejection for real-time analysis (CARTA), we introduce a novel algorithm capable of real-time cardiac artifact (CA) rejection. The method is based on constrained independent component analysis (ICA), where a priori information of the underlying source signal is used to optimize and accelerate signal decomposition. In CARTA, this is performed by estimating the subject's individual density distribution of the cardiac activity, which leads to a subject-specific signal decomposition algorithm. We show that the new method is capable of effectively reducing CAs within one iteration and a time delay of 1 ms. In contrast, Infomax and Extended Infomax ICA converged not until seven iterations, while FastICA needs at least ten iterations. CARTA was tested and applied to data from three different but most common MEG systems (4-D-Neuroimaging, VSM MedTech Inc., and Elekta Neuromag). Therefore, the new method contributes to reliable signal analysis utilizing BCI approaches.

“Why should we bother about connectivity in the age of functional imaging, at a time when magnets of ever increasing strength promise to detect the location of even the faintest thought? Isn’t it enough to locate cortical areas engaged in deception, introspection, empathy? Do we really have to worry about their connections? The answer is “yes”. In the case of the nervous system, the unit of relational architecture that allows the whole to exceed the sum of the parts is known as large-scale network. Its elucidation requires an elaborate understanding of connectivity patterns” [1]. Despite considerable advances in experimental techniques and in our understanding of animal anatomy over the last decades, the real connectivity of the human brain has essentially remained a mystery. It is the human brain’s multiscale topology that poses a particular challenge to any neuroimaging technique and prevented the neuroscientists from unraveling the connectome so far.

Frontiers in neuroinformatics 5, 34 (2011). doi:10.3389/fninf.2011.00034, Published by Frontiers Research Foundation, Lausanne

Multichannel recordings of magnetoencephalography (MEG) are usually comprised of repetitive events (e.g. external stimuli) in order to evoke the relatively weak magnetic fields of brain responses to a specific task. The analysis of the underlying electrophysiological brain activity of such unaveraged signals is notoriously challenging. During MEG experiments environmental and other external noise sources derogate the signal of interest. Furthermore, brain activity which is not involved in the task processing and therefore not of prime interest (often termed as “brain noise”) also interfere with the weak brain responses. In order to increase the signal-to-noise ratio (SNR) of the recorded data a widely common strategy is to perform signal averages. Assuming white1 noise that is temporally uncorrelated across trials, the SNR improvement gained by the averaging process over N trials scales theoretically with √N. In practice the noise reduction is a little less than 1/√N since, the evoked activity usually varies in its signal strength over time. An important aspect to bear in mind when performing averages is, that it will reveal the most prominent neuromagnetic correlates of brain responses, only. In this way information about weaker brain activity is largely suppressed, especially when multiple strong and weaker sources acting in a coordinated manner. Additionally, the temporal dynamics of each individual response will not be preserved. In contrast, single-trial analysis retains the temporal dynamics of the neuromagnetic responses, but suffers from poor signal-to-noise ratio (SNR), and is therefore rarely applied. Multichannel MEG recordings are usually comprised of a mixture of the underlying brain activity and field components originated from noise and artifact sources. In MEG, as well as in electroencephalography (EEG), the most prominent biological artifacts originate from eye blinks/movements (ocular artifacts, OA), heart beats (cardiac artifacts, CA) and muscle activity (MA). The signal strength of such biological artifacts may be several orders of magnitude higher than the signal of interest. Therefore, the analysis of MEG/EEG signals

Higher association cortices as well as unisensory areas can support multisensory integration [D. Senkowski et al. (2008) Trends Neurosci., 31, 401-409]. The present study investigated whether audiovisual integration of emotional information emerges early at unisensory or later at higher association cortices. Emotional stimuli were presented in three blocks: audiovisual (AV), auditory (A) and visual (V). Eighteen participants performed a delayed emotional recognition task (happy, angry or neutral prosody and/or facial expression) while whole-brain magnetoencephalography (MEG) data were obtained. Time-frequency evoked and total power analyses were performed on the sensor data, and source localization of the frequencies of interest performed via a synthetic aperture magnetometry beamformer. To examine crossmodal integration between bimodal and unimodal conditions, two contrasts were specified: AVA and AVV. In the AVA contrast, early effects were observed on both the temporal and the occipital evoked responses. However, at the source level, early alpha suppression was limited to the occipital sources without changes in temporal cortices. In the AVV contrast, sensor and source findings revealed increased alpha suppression only in temporal cortices, with no changes in visual cortex. Thus, no crossmodal effect in unisensory areas emerged. Instead, increased frontal alpha activity in both the AVA and AVV contrasts supports the view that affective information from face and prosody converges at higher association cortices.

Polarised Light Imaging (PLI) utilises the birefringence of the myelin sheaths in order to visualise the orientation of nerve fibres in microtome sections of adult human post-mortem brains at ultra-high spatial resolution. The preparation of post-mortem brains for PLI involves fixation, freezing and cutting into 100-micrometer thick sections. Hence, geometrical distortions of histological sections are inevitable and have to be removed for 3D reconstruction and subsequent fibre tracking. We here present a processing pipeline for 3D reconstruction of these sections using PLI derived multimodal images of post-mortem brains. Blockface images of the brains were obtained during cutting; they serve as reference data for alignment and elimination of distortion artefacts. In addition to the spatial image transformation, fibre orientation vectors were reoriented using the transformation fields, which consider both affine and subsequent non-linear registration. The application of this registration and reorientation approach results in a smooth fibre vector field, which reflects brain morphology. PLI combined with 3D reconstruction and fibre tracking is a powerful tool for human brain mapping. It can also serve as an independent method for evaluating in vivo fibre tractography.

In verbal communication, prosodic codes may be phylogenetically older than lexical ones. Little is known, however, about early, automatic encoding of emotional prosody. This study investigated the neuromagnetic analogue of mismatch negativity (MMN) as an index of early stimulus processing of emotional prosody using whole-head magnetoencephalography (MEG). We applied two different paradigms to study MMN; in addition to the traditional oddball paradigm, the so-called optimum design was adapted to emotion detection. In a sequence of randomly changing disyllabic pseudo-words produced by one male speaker in neutral intonation, a traditional oddball design with emotional deviants (10% happy and angry each) and an optimum design with emotional (17% happy and sad each) and nonemotional gender deviants (17% female) elicited the mismatch responses. The emotional category changes demonstrated early responses (

We investigated the brain responses to the transitions from the static to moving audiovisual stimuli using magnetoencephalography. The spatially congruent auditory and visual stimuli moved in the same direction whereas the incongruent stimuli moved in the opposite directions. Using dipole modeling we found that the static-to-moving transitions evoked a neural response in the primary auditory cortex bilaterally. The response started about 100 ms after the motion onset from a negative component (mvN1) and lasted during the entire interval of the stimulus motion. The mvN1 component was similar to the classical auditory N1 response to the static sound, but had smaller amplitude and later latency. The coordinates of the mvN1 and N1 dipoles in the primary auditory cortex were also similar. The amplitude of the auditory response to the moving stimuli appears to be sensitive to spatial congruency of the audiovisual motion; it was larger in the incongruent than congruent condition. This is evidence that the moving visual stimuli modulate the early sensory activity in the primary auditory cortex. Such early audiovisual integration may be specific for motion processing.

The insula has consistently been shown to be involved in processing stimuli that evoke the emotional response of disgust. Recently, its specificity for processing disgust has been challenged and a broader role of the insula in the representation of interoceptive information has been suggested. Studying the temporal dynamics of insula activation during emotional processing can contribute valuable information pertaining to this issue. Few studies have addressed the insula's putative specificity to disgust and the dynamics of its underlying neural processes. In the present study, neuromagnetic responses of 13 subjects performing an emotional continuous performance task (CPT) to faces with disgust, happy, and neutral expressions were obtained. Magnetic field tomography extracted the time course of bilateral insula activities. Right insula activation was stronger to disgust and happy than neutral facial expressions at about 200 ms after stimulus onset. Later only at about 350 ms after stimulus onset the right insula was activated stronger to disgust than happy facial expressions. Thus, the early right insula response reflects activation to emotionally arousing stimuli regardless of valence, and the later right insula response differentiates disgust from happy facial expressions. Behavioral performance but not the insula activity differed between 100 ms and 1000 ms presentation conditions. Present findings support the notion that the insula is involved in the representation of interoceptive information.

The mismatch negativity (MMN) is an event-related potential reflecting automatic information processing and auditory sensory memory. This measure of early cognitive function is well documented to be impaired in schizophrenia. Different paradigms and methods (EEG and magnetoencephalography, MEG), however, are applied to measure MMN and it is unclear whether they reflect one unitary mechanism. We investigated the change of MMN and its MEG counterpart in schizophrenia for a standard oddball design (80% standards, 10% duration and 10% frequency deviants) and a new optimum design (Naatanen et al. 2003; 50% standards and 10% deviants each reflecting change of one of 5 auditory features). Twelve patients with schizophrenia (DSM IV) and 12 healthy controls were investigated with EEG (64-channel) and 148-channel whole-head MEG. Data analysis was performed with fully observer-independent automatized Matlab-routines based on localization from probabilistic cytoarchitectonic maps. For the schizophrenia group, the mismatch response was reduced most significantly and with the highest amplitude difference in the neuromagnetic optimum design. We conclude that optimized MMN designs are most promising for diagnostics of endophenotypes in schizophrenia. The differences in effects of schizophrenia on the different MMN measures suggest (a) that MEG captures more early cortical processes as compared to EEG which are mostly affected in schizophrenia and (b) that adaptation/habituation, feature representation, and auditory memory trace may contribute to MMN depending on its measurement technique and the design parameters. The abstract feature representation as addressed by the optimum design may be the core dysfunction in schizophrenia.

Size and location of activated cortical areas are often identified in relation to their surrounding macro-anatomical landmarks such as gyri and sulci. The sulcal pattern, however, is highly variable. In addition, many cortical areas are not linked to well defined landmarks, which in turn do not have a fixed relationship to functional and cytoarchitectonic boundaries. Therefore, it is difficult to unambiguously attribute localized neuronal activity to the corresponding cortical areas in the living human brain. Here we present new methods that are implemented in a toolbox for the objective anatomical identification of neuromagnetic activity with respect to cortical areas. The toolbox enables the platform independent integration of many types of source analysis obtained from magnetoencephalography (MEG) together with probabilistic cytoarchitectonic maps obtained in postmortem brains. The probability maps provide information about the relative frequency of a given cortical area being located at a given position in the brain. In the new software, the neuromagnetic data are analyzed with respect to cytoarchitectonic maps that have been transformed to the individual subject brain space. A number of measures define the degree of overlap between and distance from the activated areas and the corresponding cytoarchitectonic maps. The implemented algorithms enable the investigator to quantify how much of the reconstructed current density can be attributed to distinct cortical areas. Dynamic correspondence patterns between the millisecond-resolved MEG data and the static cytoarchitectonic maps are obtained. We show examples for auditory and visual activation patterns. However, size and location of the postmortem brain areas as well as the inverse method applied to the neuromagnetic data bias the anatomical classification. Therefore, the adaptation to the respective application and a combination of the objective quantities are discussed.

Pattern reversal stimulation provides an established tool for assessing the integrity of the visual pathway and for studying early visual processing. Numerous magnetoencephalographic (MEG) and electroencephalographic (EEG) studies have revealed a three-phasic waveform of the averaged pattern reversal visual evoked potential/magnetic field, with components N75(m), P100(m), and N145(m). However, the anatomical assignment of these components to distinct cortical generators is still a matter of debate, which has inter alia connected with considerable interindividual variations of the human striate and extrastriate cortex. The anatomical variability can be compensated for by means of probabilistic cytoarchitectonic maps, which are three-dimensional maps obtained by an observer-independent statistical mapping in a sample of ten postmortem brains. Transformed onto a subject's brain under consideration, these maps provide the probability with which a given voxel of the subject's brain belongs to a particular cytoarchitectonic area. We optimize the spatial selectivity of the probability maps for V1 and V2 with a probability threshold which optimizes the self- vs. cross-overlap in the population of postmortem brains used for deriving the probabilistic cytoarchitectonic maps. For the first time, we use probabilistic cytoarchitectonic maps of visual cortical areas in order to anatomically identify active cortical generators underlying pattern reversal visual evoked magnetic fields as revealed by MEG. The generators are determined with magnetic field tomography (MFT), which reconstructs the current source density in each voxel. In all seven subjects, our approach reveals generators in V1/V2 (with a greater overlap with V1) and in V5 unilaterally (right V5 in three subjects, left V5 in four subjects) and consistent time courses of their stimulus-locked activations, with three peak activations in V1/V2 (contributing to C1m/N75m, P100m, and N145m) and two peak activations in V5 (contributing to P100m and N145m). The reverberating V1/V2 and V5 activations demonstrate the effect of recurrent activation mechanisms including V1 and extrastriate areas and/or corticofugal feedback loops. Our results demonstrate that the combined investigation of MEG signals with MFT and probabilistic cytoarchitectonic maps significantly improves the anatomical identification of active brain areas.

Processing of facial information is distributed across several brain regions, as has been shown recently in many neuroimaging studies. Disturbances in accurate face processing have been repeatedly demonstrated in different stages of schizophrenia. Recently, electroencephalography (EEG) and tomographic analysis of average magnetoencephalographic (MEG) data were used to define the latencies of significant regional brain activations in healthy and schizophrenic subjects elicited during the recognition of facial expression of emotions. The current study re-examines these results using tomographic analysis of single trial MEG data. In addition to the areas identified by the analysis of the average MEG data, statistically significant activity is identified in several other areas, including a sustained increase in the right amygdala activity in response to emotional faces in schizophrenic subjects. The single trial analysis demonstrated that the reduced activations identified from the average MEG signal of schizophrenic subjects is due to high variability across single trials rather than reduced activity in each single trial. In control subjects, direct measures of linkage demonstrate distinct stages of processing of emotional faces within well-defined network of brain regions. Activity in each node of the network, confined to 30 to 40 ms latency windows, is linked to earlier and later activations of the other nodes of the network. In schizophrenic subjects, no such well-defined stages of processing were observed. Instead, the activations, although strong were poorly linked to each other, managing only isolated links between pairs of areas.

Recognition of facial expressions of emotions is very important for communication and social cognition. Neuroimaging studies showed that numerous brain regions participate in this complex function. To study spatiotemporal aspects of the neural representation of facial emotion recognition we recorded neuromagnetic activity in 12 healthy individuals by means of a whole head magnetoencephalography system. Source reconstructions revealed that several cortical and subcortical brain regions produced strong neural activity in response to emotional faces at latencies between 100 and 360 ms that were much stronger than those to neutral as well as to blurred faces. Orbitofrontal cortex and amygdala showed affect-related activity at short latencies already within 180 ms after stimulus onset. Some of the emotion-responsive regions were repeatedly activated during the stimulus presentation period pointing to the assumption that these reactivations represent indicators of a distributed interacting circuitry.

Objective: The authors sought to identify brain mechanisms underlying the well-documented facial affect recognition deficit in patients with schizophrenia. Since this deficit is stable over the course of the illness and relatively specific for schizophrenic disorders, it was expected that knowledge about the related brain mechanisms would provide substantial information about the pathophysiology of the illness. Method: Fifteen partly remitted schizophrenic inpatients and 12 healthy volunteers categorized facial expressions of emotion and performed two control tasks while magnetoencephalographic recordings were done by means of a 148-channel whole head system, which revealed foci of high cerebral activity and their evolution in time. Anatomical sites were defined through coregistrated magnetic resonance images. Results: The magnetoencephalography data recorded in response to facial expressions of emotion revealed that patients generated weaker activations (primary current density) in inferior prefrontal, temporal, occipital, and inferior parietal areas at circumscribed latencies. Group differences did not occur in basic visual areas during a first sensory-related activation between 60 and 120 msec. Behavioral performance was associated with strength of activation in inferior prefrontal areas, the right posterior fusiform gyrus region, right anterior temporal cortex, and the right inferior parietal cortex. Conclusions: Disturbed facial affect recognition in schizophrenic patients might be a result of hypoactivity in distributed brain regions, some of them previously related to the pathophysiology of schizophrenic disorders. These regions are probably working within a spatially and temporally defined circuitry.

Sudden Cardiac Death (SCD) is an important public health problem. It is estimated that 350.000 people die suddenly every year in the USA [1]. Main cause of SCD are ventricular tachyarrhythmias [2]. Most patients with SCD suffer from coronary artery disease, but in some patients no organic heart disease can be detected using Standard clinical methods (idiopathic ventricular fibrillation, IVF). In contrast to earlier observations [3], more recent studies have shown a significant recurrence rate of 25% concerning major arrhythmic events and a 1-year mortality of 11% in this patient group [4]. The development of therapeutic strategies for these patients is greatly dependent on the understanding of involved pathophysiological mechanisms.

The BTi MAGNES II twin system was instailed in June 1994 at the Research Centre in Julich and will be exchanged soon for the new MAGNES WH whole head system. Besides Magnetoencephalography (MEG), the research centre also houses functional Magnetic Resonance Imaging (fMRI), Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) neuro-imaging groups. The goal is to provide multi-modality imaging exploiting the strengths of each technique.

A general method for obtaining continuous solutions to the biomagnetic inverse problem was first presented during the 1989 Biomagnetism conference. From the outset, the method was developed for three-dimensional source spaces [1, 2] but, partly to reduce computational demands and partly for ease of presentation, the first major publication of the method [3] used two-dimensional reconstructions. Soon afterwards the algorithms were ported to a transputer, making possible the analysis of large sets of MEG data. The output (estimates of the primary current density in a three-dimensional source space) was displayed by taking slices (tomes) through the source space leading to a series of MFT (Magnetic Field Tomographie) images. Later forms of representation included time integrals and activation curves, describing the evolution of activity within specified Regions of Interest (ROI). Animations run on the transputer array and recorded on video, were by far the most effective presentation tool, showing in colour-coded form the changes in the activity against a background of coregistered MRI slices[4]. Early reconstructions used averaged data but the emphasis has recently shifted to analysis of single trial or continuous data [5, 6]. Each three-dimensional study was underpinned by thorough tests with Computer generated data which, however, have been only superficially reported because of space limitations. We have previously described our philosophy and method [3], the transputer based implementation [7] and the logic in the various algorithmic steps [8]. However, the lack of published material on the background tests must be the cause of misrepresentations of MFT in some recent publications dealing with distributed source analysis, e.g. [9]. The present paper makes good this omission and uses computer-generated data to illustrate the power and limitations of MFT as a 3D imaging method, using realistic sensor configurations and signals that are neurophysiologically realistic in terms of location and temporal characteristics.

We apply a quantitative method for the identification of asymmetric relations between weakly interacting self-sustained oscillators to the study of rhythmic neural electrical activity. We begin by testing the method on biophysically motivated neural oscillator models considering first two diffusively coupled Hindmarsh-Rose oscillators, and then two ensembles of globally coupled neurons interacting through their mean fields. Next, we consider the more complex case of interactions among several oscillatory units. The method is further applied to the analysis of the control of externally vs internally paced movements in humans. A pilot study in one healthy subject reveals that asymmetry of interactions between different brain areas may strongly change with the transition from external to internal pacing, while the degree of synchronization hardly changes. Furthermore, our preliminary results highlight the important role of the secondary auditory cortex in internal rhythm generation.

We present a noninvasive technique which allows the anatomical localization of phase synchronized neuronal populations in the human brain with magnetoencephalography. We study phase synchronization between the reconstructed current source density (CSD) of different brain areas as well as between the CSD and muscular activity. We asked four subjects to tap their fingers in synchrony with a rhythmic tone, and to continue tapping at the same rate after the tone was switched off. The phase synchronization behavior of brain areas relevant for movement coordination, inner voice, and time estimation changes drastically when the transition to internal pacing occurs, while their averaged amplitudes remain unchanged. Information of this kind cannot be derived with standard neuroimaging techniques like functional magnetic resonance imaging or positron emission tomography.